Your hospital medicine questions answered

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HM groups should provide informational brochures to admitted patients

I am trying to find out two pieces of information. First, is there a national association of hospitalists that oversees and gives guidance to all of the regional and national hospitalists that are now in practice? If this defines your group, great. On to my second question: Is there an established policy or doctrine that is recommended for hospitals in regard to disclosure to patients that they are indeed a hospitalist type of hospital? If so, could you advise how I might obtain a written copy? Thank you.

C.G. Lemaire, Virginia

Dr. Hospitalist responds: According to the 2008 American Hospital Association survey, about half of the nation’s hospitals have hospitalists. In hospitals with 200 or more beds, 83% have hospitalists. The field has grown rapidly since its inception in the late 1990s. There are an estimated 28,000 hospitalists in the U.S.

ASK Dr. hospitalist


Do you have a problem or concern that you’d like Dr. Hospitalist to address? E-mail your questions to [email protected].

Most hospitalists recognize the Society of Hospital Medicine (SHM) as the professional society that represents their interests. I am not aware of any established SHM policy that mandates or suggests that a hospital disclose to patients the fact that hospitalists work there, nor do I believe that one is necessary. Hospitalists are medical doctors whose interest is the care of hospitalized patients. This is analogous to critical-care physicians, whose interest is care of the patients in hospital intensive-care units, or ED physicians, who care for patients in hospital emergency departments. There is neither a requirement nor expectation for hospitals to notify patients of the availability of these types of physicians working at a hospital.

I understand patient expectations can be different. Most patients expect to see ED physicians when they visit a hospital ED. But this was not always the case. Several decades ago, the field of emergency medicine was in its infancy, and most hospitals did not have ED physicians. I am certain most patients were surprised to see an ED physician instead of their primary-care physician (PCP). But patients came to realize ED physicians were trained specifically to care for ED patients and were available to care for them when their PCP was not available. I think patients will become familiar with hospitalists and expect to see one when they are hospitalized—but until that time arrives, I do think it is reasonable for everyone involved to help set that expectation for patients.

Ideally, HM programs should develop brochures explaining a hospitalist’s role in the care of hospitalized patients, as well as the relationship between hospitalists and PCPs (see “Satisfaction Scorecard,” January 2009, p. 57). These brochures should be distributed not only to hospitalized patients, but to outpatients in PCP offices. The primary-care clinic waiting room is a great place for these brochures.

PCPs should discuss the role of hospitalists when they send a patient to the hospital for admission. It is important for hospitalists and PCPs to know that patients are more likely to be accepting if they understand: 1) the PCP supports this model of care; 2) the hospitalist and PCP are communicating about the patient’s care; and 3) the hospitalist is available to the patient while the PCP is in their clinic.

SHM’s Web site also has a sample brochure, which can be used to introduce and inform patients about the hospitalists’ role in their care. Download the form at www.hospitalmedicine.org/samplebrochure.

Know your contract before signing the dotted line

My contract says that as a hospitalist, I will work 18 shifts a month, each being a nine-hour duration, and on average 2,000 hours per year. It does not add up to 2,000 hours. Does night call count toward the number of hours? Do weekends and holidays count toward the number of hours?

 

 

Anshu Sood, MD

Dr. Hospitalist responds: If I understand you correctly, you are working 1,944 hours annually (18 shifts per month x 12 months x nine hours per shift). You did not tell me whether your compensation is based on the number of hours you work or whether you collect a salary regardless of the number of hours you work. If you collect a salary, sounds like you are scheduled to work fewer hours than expected.

That being said, I also don’t know the other details of your employment agreement. Does your employment agreement include paid vacation and sick time? Perhaps that might explain the difference. Another plausible explanation is that your compensation includes payment for sign-out and sign-in time at the beginning and end of each shift (18 shifts/month x 12 months x 9.25 hours/shift = 1,998 hours). Regardless of the explanation, your question made me wonder: Why are the details of your job description unclear to you, and why are you asking me rather than your employer for clarification? I urge all hospitalists to clearly understand their employment agreements before accepting any job offer. Any differences should be resolved before signing the contract. It is worth the time and money to seek the advice of an attorney familiar with physician employment contracts. The attorney’s job is to review your agreement and explain the terms of the contract, as well as point out what is missing. TH

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HM groups should provide informational brochures to admitted patients

I am trying to find out two pieces of information. First, is there a national association of hospitalists that oversees and gives guidance to all of the regional and national hospitalists that are now in practice? If this defines your group, great. On to my second question: Is there an established policy or doctrine that is recommended for hospitals in regard to disclosure to patients that they are indeed a hospitalist type of hospital? If so, could you advise how I might obtain a written copy? Thank you.

C.G. Lemaire, Virginia

Dr. Hospitalist responds: According to the 2008 American Hospital Association survey, about half of the nation’s hospitals have hospitalists. In hospitals with 200 or more beds, 83% have hospitalists. The field has grown rapidly since its inception in the late 1990s. There are an estimated 28,000 hospitalists in the U.S.

ASK Dr. hospitalist


Do you have a problem or concern that you’d like Dr. Hospitalist to address? E-mail your questions to [email protected].

Most hospitalists recognize the Society of Hospital Medicine (SHM) as the professional society that represents their interests. I am not aware of any established SHM policy that mandates or suggests that a hospital disclose to patients the fact that hospitalists work there, nor do I believe that one is necessary. Hospitalists are medical doctors whose interest is the care of hospitalized patients. This is analogous to critical-care physicians, whose interest is care of the patients in hospital intensive-care units, or ED physicians, who care for patients in hospital emergency departments. There is neither a requirement nor expectation for hospitals to notify patients of the availability of these types of physicians working at a hospital.

I understand patient expectations can be different. Most patients expect to see ED physicians when they visit a hospital ED. But this was not always the case. Several decades ago, the field of emergency medicine was in its infancy, and most hospitals did not have ED physicians. I am certain most patients were surprised to see an ED physician instead of their primary-care physician (PCP). But patients came to realize ED physicians were trained specifically to care for ED patients and were available to care for them when their PCP was not available. I think patients will become familiar with hospitalists and expect to see one when they are hospitalized—but until that time arrives, I do think it is reasonable for everyone involved to help set that expectation for patients.

Ideally, HM programs should develop brochures explaining a hospitalist’s role in the care of hospitalized patients, as well as the relationship between hospitalists and PCPs (see “Satisfaction Scorecard,” January 2009, p. 57). These brochures should be distributed not only to hospitalized patients, but to outpatients in PCP offices. The primary-care clinic waiting room is a great place for these brochures.

PCPs should discuss the role of hospitalists when they send a patient to the hospital for admission. It is important for hospitalists and PCPs to know that patients are more likely to be accepting if they understand: 1) the PCP supports this model of care; 2) the hospitalist and PCP are communicating about the patient’s care; and 3) the hospitalist is available to the patient while the PCP is in their clinic.

SHM’s Web site also has a sample brochure, which can be used to introduce and inform patients about the hospitalists’ role in their care. Download the form at www.hospitalmedicine.org/samplebrochure.

Know your contract before signing the dotted line

My contract says that as a hospitalist, I will work 18 shifts a month, each being a nine-hour duration, and on average 2,000 hours per year. It does not add up to 2,000 hours. Does night call count toward the number of hours? Do weekends and holidays count toward the number of hours?

 

 

Anshu Sood, MD

Dr. Hospitalist responds: If I understand you correctly, you are working 1,944 hours annually (18 shifts per month x 12 months x nine hours per shift). You did not tell me whether your compensation is based on the number of hours you work or whether you collect a salary regardless of the number of hours you work. If you collect a salary, sounds like you are scheduled to work fewer hours than expected.

That being said, I also don’t know the other details of your employment agreement. Does your employment agreement include paid vacation and sick time? Perhaps that might explain the difference. Another plausible explanation is that your compensation includes payment for sign-out and sign-in time at the beginning and end of each shift (18 shifts/month x 12 months x 9.25 hours/shift = 1,998 hours). Regardless of the explanation, your question made me wonder: Why are the details of your job description unclear to you, and why are you asking me rather than your employer for clarification? I urge all hospitalists to clearly understand their employment agreements before accepting any job offer. Any differences should be resolved before signing the contract. It is worth the time and money to seek the advice of an attorney familiar with physician employment contracts. The attorney’s job is to review your agreement and explain the terms of the contract, as well as point out what is missing. TH

HM groups should provide informational brochures to admitted patients

I am trying to find out two pieces of information. First, is there a national association of hospitalists that oversees and gives guidance to all of the regional and national hospitalists that are now in practice? If this defines your group, great. On to my second question: Is there an established policy or doctrine that is recommended for hospitals in regard to disclosure to patients that they are indeed a hospitalist type of hospital? If so, could you advise how I might obtain a written copy? Thank you.

C.G. Lemaire, Virginia

Dr. Hospitalist responds: According to the 2008 American Hospital Association survey, about half of the nation’s hospitals have hospitalists. In hospitals with 200 or more beds, 83% have hospitalists. The field has grown rapidly since its inception in the late 1990s. There are an estimated 28,000 hospitalists in the U.S.

ASK Dr. hospitalist


Do you have a problem or concern that you’d like Dr. Hospitalist to address? E-mail your questions to [email protected].

Most hospitalists recognize the Society of Hospital Medicine (SHM) as the professional society that represents their interests. I am not aware of any established SHM policy that mandates or suggests that a hospital disclose to patients the fact that hospitalists work there, nor do I believe that one is necessary. Hospitalists are medical doctors whose interest is the care of hospitalized patients. This is analogous to critical-care physicians, whose interest is care of the patients in hospital intensive-care units, or ED physicians, who care for patients in hospital emergency departments. There is neither a requirement nor expectation for hospitals to notify patients of the availability of these types of physicians working at a hospital.

I understand patient expectations can be different. Most patients expect to see ED physicians when they visit a hospital ED. But this was not always the case. Several decades ago, the field of emergency medicine was in its infancy, and most hospitals did not have ED physicians. I am certain most patients were surprised to see an ED physician instead of their primary-care physician (PCP). But patients came to realize ED physicians were trained specifically to care for ED patients and were available to care for them when their PCP was not available. I think patients will become familiar with hospitalists and expect to see one when they are hospitalized—but until that time arrives, I do think it is reasonable for everyone involved to help set that expectation for patients.

Ideally, HM programs should develop brochures explaining a hospitalist’s role in the care of hospitalized patients, as well as the relationship between hospitalists and PCPs (see “Satisfaction Scorecard,” January 2009, p. 57). These brochures should be distributed not only to hospitalized patients, but to outpatients in PCP offices. The primary-care clinic waiting room is a great place for these brochures.

PCPs should discuss the role of hospitalists when they send a patient to the hospital for admission. It is important for hospitalists and PCPs to know that patients are more likely to be accepting if they understand: 1) the PCP supports this model of care; 2) the hospitalist and PCP are communicating about the patient’s care; and 3) the hospitalist is available to the patient while the PCP is in their clinic.

SHM’s Web site also has a sample brochure, which can be used to introduce and inform patients about the hospitalists’ role in their care. Download the form at www.hospitalmedicine.org/samplebrochure.

Know your contract before signing the dotted line

My contract says that as a hospitalist, I will work 18 shifts a month, each being a nine-hour duration, and on average 2,000 hours per year. It does not add up to 2,000 hours. Does night call count toward the number of hours? Do weekends and holidays count toward the number of hours?

 

 

Anshu Sood, MD

Dr. Hospitalist responds: If I understand you correctly, you are working 1,944 hours annually (18 shifts per month x 12 months x nine hours per shift). You did not tell me whether your compensation is based on the number of hours you work or whether you collect a salary regardless of the number of hours you work. If you collect a salary, sounds like you are scheduled to work fewer hours than expected.

That being said, I also don’t know the other details of your employment agreement. Does your employment agreement include paid vacation and sick time? Perhaps that might explain the difference. Another plausible explanation is that your compensation includes payment for sign-out and sign-in time at the beginning and end of each shift (18 shifts/month x 12 months x 9.25 hours/shift = 1,998 hours). Regardless of the explanation, your question made me wonder: Why are the details of your job description unclear to you, and why are you asking me rather than your employer for clarification? I urge all hospitalists to clearly understand their employment agreements before accepting any job offer. Any differences should be resolved before signing the contract. It is worth the time and money to seek the advice of an attorney familiar with physician employment contracts. The attorney’s job is to review your agreement and explain the terms of the contract, as well as point out what is missing. TH

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Pregabalin for fibromyalgia: Some relief but no cure

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Pregabalin for fibromyalgia: Some relief but no cure

Pregabalin (Lyrica) is a novel analogue of the neurotransmitter gamma aminobutyric acid (GABA) with analgesic, anticonvulsant, and anxiolytic activity. Its approval by the US Food and Drug Administration (FDA) in 2007 for the treatment of fibromyalgia made it the first drug approved for this indication. Until then, management of fibromyalgia entailed drugs to treat pain, sleep, fatigue, and psychological disorders, and a strong emphasis on exercise and physical therapy.

Those who still question the validity of fibromyalgia as a diagnosis object to drug companies “benefiting” from the sale of such drugs.1 But many hail pregabalin as an important advance in our understanding of the pathogenesis of fibromyalgia and how to treat it. A key question remains: How will pregabalin fit into the treatment of this often-challenging disease?

FROM FIBROSITIS TO FIBROMYALGIA

Fibromyalgia is a syndrome characterized by widespread pain. Chronic muscular pain is a common problem, but fibromyalgia is distinguished from other pain disorders by additional findings, such as consistent areas of tenderness (tender points), nonrestorative sleep, severe fatigue, and frequent psychological comorbidities such as depression and anxiety.

Fibromyalgia was originally termed “fibrositis” in 1904 by Sir William Gowers, who described it as a painful condition of the fibrous tissue, which he believed was due to inflammation in the muscles.2,3 For several decades, research was dedicated to looking for pathology in the muscle tissue, which was thought to be the major source of pain for most patients with fibromyalgia.

In the mid-1970s, Dr. H. Moldofsky, a noted sleep researcher, reported on abnormalities of the alpha-delta component of nonrapid-eye-movement sleep in these patients. He subsequently collaborated with Dr. Hugh A. Smythe, who helped define the fibromyalgia tender points. Fibrositis was subsequently renamed fibromyalgia syndrome, since it was agreed that there was no true inflammation in muscles or fibrous tissue.

In 1990, the American College of Rheumatology published “classification criteria” for the disease.4 The criteria include two main features:

  • A history of widespread pain (“widespread” being defined as in the axial distribution, in both the left and right sides of the body, and above and below the waist), which must be present for 3 months or more, and
  • Tenderness in at least 11 of 18 specified points that is elicited when a pressure of 4 kg (the amount of pressure required to blanch a thumbnail) is applied in steady increments starting at 1 kg.

Although pain is subjective and therefore difficult to assess, the classification criteria did make it easier to study the disease in a uniform way and led to an explosion of research in this field.

FUNCTIONAL ABNORMALITIES NI THE CENTRAL NERVOUS SYSTEM

Research to date points to the pain in fibromyalgia as being mediated by changes in the central nervous system rather than in the musculoskeletal system, as was initially thought.

In the dorsal horn of the spinal cord, nociceptive (pain-sensing) neurons from the periphery synapse with the second-order neurons that carry the pain signal to the brain. In fibromyalgia, several processes seem to amplify the signal.

Central sensitization is defined as enhanced excitability of neurons in the dorsal horn. Its features include augmented spontaneous neuronal activity, enlarged receptive field areas, and enhanced responses generated by large- and small-caliber primary afferent fibers. It can result from prolonged or strong activity in the dorsal horn neurons, and it leads to the spread of hyperactivity across multiple spinal segments.5–7

While much of the evidence for central sensitization in fibromyalgia is from animal studies, the phenomenon has also been studied in humans. Desmeules et al8 found that, compared with people without fibromyalgia, those with fibromyalgia had significantly lower thresholds of pain as assessed subjectively and measured objectively using the nociceptive flexion R-III reflex, which the authors described as “a specific physiologic correlate for the objective evaluation of central nociceptive pathways.”

Wind-up. Prolonged stimulation of C fibers in the dorsal horn can result in the phenomenon of wind-up, which refers to the temporal summation of second pain.

A painful stimulus evokes two pain signals. The first signal is brief and travels rapidly to the spinal cord via myelinated fibers (A fibers). The second signal, which is related to chronic pain and is described as dull, aching, or burning, travels more slowly to the dorsal horn via unmyelinated fibers (C fibers), the synapses of which use the neurotransmitter glutamate. Temporal summation is a phenomenon observed in experiments in which a series of painful stimuli are applied at regular intervals of about 2 seconds; although each stimulus is identical in intensity, subjects perceive them as increasing in intensity. The reason: during this repetitive stimulation, N-methyl-d-aspartate (NMDA) receptors become activated, leading to the removal of a magnesium block within the receptor. This results in an influx of calcium into the neuron and activation of protein kinase C, nitric oxide synthase, and cyclooxygenase. Ultimately, the firing rates of the nociceptive neurons are increased and the peripheral pain signal is strongly amplified.6

Wind-up has been shown to lead to characteristics of central sensitization related to C-fiber activity in animals.7 Staud et al9 studied wind-up in patients with and without fibromyalgia using series of repetitive thermal stimulation to produce temporal summation. Though wind-up was evoked in both groups, differences were observed both in the magnitude of sensory response to the first stimulus within a series and in the amount of temporal summation within a series.

Elevated excitatory neurotransmitters. In 1994, Russell et al10 showed that the concentration of substance P, an excitatory neurotransmitter, was three times higher in the cerebrospinal fluid of people with fibromyalgia than in normal controls.

Harris and colleagues11 reported that glutamate, another excitatory neurotransmitter, is elevated within the brain in people with fibromyalgia. They further showed that the levels of glutamate within the insula of the brain are directly associated with the levels of both experimental pressure-evoked pain thresholds and clinical pain ratings in fibromyalgia patients.

Evidence from imaging studies. Other objective evidence of central sensitization in fibromyalgia patients comes from studies using novel imaging.

Gracely et al12 performed functional magnetic resonance imaging (MRI) in people with and without fibromyalgia while applying pressure to their thumbs with a thumbscrew-type device. At equal levels of pressure, the people with fibromyalgia said the pressure hurt more, and specific areas of their brains lit up more on functional MRI. When the experimenters increased the pressure in the people without fibromyalgia until this group subjectively rated the pain as high as the fibromyalgia patients rated the lower level of pressure, their brains lit up to a similar degree in the same areas. These findings provide objective evidence of significantly lower pain thresholds in patients with fibromyalgia than in healthy controls, and they support the theory of central augmentation of pain sensitivity in fibromyalgia.

Staud et al13 also used functional MRI and found greater brain activity associated with temporal summation in fibromyalgia patients compared with controls. (In this experiment, the painful stimulus consisted of heat pulses to the foot.)

Drugs other than pregabalin that modulate the dorsal horn activity of the pain pathway include opioids, tramadol (Ultram), gabapentin (Neurontin), GABA agonists such as baclofen (Lioresal), antidepressants, alpha-2 adrenergic agonists (phenylephrine), and 5-HT3 antagonists such as ondansetron (Zofran), but none has been consistently effective for fibromyalgia.5,14

 

 

PREGABALIN

Pregabalin is an alpha-2-delta ligand similar to GABA, but it does not act on GABA receptors. Rather, it binds with high affinity to the alpha-2-delta subunit of voltage-gated presynaptic calcium channels, resulting in reduction of calcium flow through the channels, which subsequently inhibits the release of neurotransmitters including glutamate, norepinephrine, and substance P.15–17 Animal studies suggest that the decrease in the levels of these excitatory neurotransmitters is the mechanism of action of pregabalin, resulting in its analgesic, anticonvulsant, and anxiolytic benefit.15 Another potential mechanism of pregabalin is enhancement of slow-wave sleep, demonstrated in one study in healthy human subjects.18

Besides fibromyalgia, pregabalin is also approved for the treatment of diabetic peripheral neuropathy, postherpetic neuralgia, generalized anxiety disorder, and social anxiety disorder, and as adjunctive therapy for partial-onset seizure in adults.

Pharmacokinetics

Pregabalin is quickly absorbed, primarily in the proximal colon (bioavailability > 90%), and has highly predictable and linear pharmacokinetics.15 Food consumption does not affect its absorption or elimination but can delay its peak plasma concentration, which occurs at 1.5 hours. Its elimination half-life is approximately 6 hours.15 Because it does not bind to plasma proteins, it freely crosses the blood-brain barrier. The drug reaches its steady-state concentration within 2 days of starting therapy.

Its clearance is not affected by the sex or race of the patient, but its total clearance may be lower in the elderly because of age-related loss of renal function. Patients on hemodialysis may require a supplemental dose after dialysis because hemodialysis removes the pregabalin.

The drug is not metabolized by the P450 system in the liver, so it interacts only minimally with drugs that do use the P450 system. However, its clearance may be decreased when it is used concomitantly with drugs that can reduce the glomerular filtration rate, such as nonsteroidal anti-inflammatory drugs, aminoglycosides, and cyclosporine.15

Efficacy

The efficacy of pregabalin in fibromyalgia was evaluated in several recent trials.19

Crofford et al16 assessed pregabalin’s effects on pain, sleep, fatigue, and health-related quality of life. Some 529 patients with fibromyalgia were randomized in a double-blind fashion to four treatment groups: placebo, and pregabalin 150 mg/day, 300 mg/day, and 450 mg/day. The baseline mean pain scores (a 0-to-10 scale derived from daily diary ratings) were 6.9 in the placebo group, 6.9 for the pregabalin 150 mg/day group, 7.3 for the pregabalin 300 mg/day group, and 7.0 for the pregabalin 450 mg/day group.

The pain scores declined in all groups, but at 8 weeks, the mean score had declined 0.93 points more in the group receiving pregabalin 450 mg/day than in the placebo group (P ≤ .001). The scores in the groups taking pregabalin 150 mg/day and 300 mg/day were not significantly different from those in the placebo group. Significantly more patients in the 450-mg/day group (29%, vs 13% in the placebo group) had at least 50% improvement in pain at the end of the study. Patients in both the 300-mg/day group and the 450-mg/day had statistically significant improvement in their quality of sleep, in fatigue, and on the Patient Global Impression of Change (PGIC) scale.

Arnold et al20 conducted a trial with 750 patients in which three doses of pregabalin were compared with placebo: 300 mg/day, 450 mg/day, and 600 mg/day. The primary end point was also the change in pain score from baseline (using the 0-to-10 scale derived from a daily pain diary). The mean baseline pain score was 6.7.

At 14 weeks, the mean pain score was lower than at baseline in all the groups, but it had declined 0.71 more in the pregabalin 300-mg/day group than in the placebo group, 0.98 points more in the 450-mg/day group, and 1.0 points more in the 600-mg/day group. All three pregabalin groups also showed significant improvement on the PGIC scale, and patients in the 450-mg/day and 600-mg/day groups showed statistically significant improvement in the Fibromyalgia Impact Questionnaire (FIQ) score. All three pregabalin treatment groups also had significantly better patient-reported sleep outcomes than in the placebo group, both in measures of overall sleep and quality of sleep. With the exception of a significant improvement of anxiety on 600 mg/day, there was no significant difference between the treatment and placebo groups in the secondary outcomes of depression and anxiety symptoms and fatigue.

Duan et al21 presented a pooled analysis of this and a similarly designed double-blind, placebo-controlled trial (the results of which were not available individually) at the 71st annual meeting of the American College of Rheumatology in November 2007. The analysis included 1,493 patients with a mean baseline pain score of 6.9. Compared with the mean pain score in the placebo group, those in the pregabalin groups had declined more by the end of the study: 0.55 points more with 300 mg/day, 0.71 points more with 450 mg/day, and 0.82 points more with 600 mg/day. This pooled analysis also showed significant improvement in PGIC score with all pregabalin doses and in the FIQ score with 450 mg/day and 600 mg/day.

The FREEDOM trial22 (Fibromyalgia Relapse Evaluation and Efficacy for Durability of Meaningful Relief) evaluated the durability of effect of pregabalin in reducing pain and symptoms associated with fibromyalgia in 1,051 patients who initially responded to the drug.

The patients received 6 weeks of open-label treatment with pregabalin and then 26 weeks of double-blind treatment (dose adjustment was allowed based on efficacy and tolerability for the first 3 weeks). The time to loss of therapeutic response was significantly longer with pregabalin than with placebo. Loss of therapeutic response was defined as worsening of pain for two consecutive visits or worsening of fibromyalgia symptoms requiring alternative therapy.

By the end of the double-blind phase, 61% of those in the placebo group had loss of therapeutic response compared with only 32% in the pregabalin group. The time to worsening of the FIQ score was also significantly longer in the pregabalin group than in the placebo group.

 

 

Adverse effects: Dizziness, sleepiness, weight gain

Dizziness and sleepiness were the most common adverse events in these studies.

In the 8-week study by Crofford et al,16 dizziness was dose-related, occurring in 10.7% of those receiving placebo (one patient withdrew because of dizziness), 22.7% of those receiving 150 mg/day (two patients withdrew), 31.3% of those receiving 300 mg/day (four patients withdrew), and 49.2% of those receiving 450 mg/day (five patients withdrew). Somnolence was also dose-related, occurring in 4.6% in the placebo group, 15.9% in the 150-mg/day group (two patients withdrew due to somnolence), 27.6% in the 300-mg/day group (three withdrew), and 28.0% in the 450-mg/day group (five withdrew).

The 14-week study by Arnold et al20 also showed higher frequencies of adverse events with higher doses. The rates of dizziness were 7.6% with placebo, 27.9% with pregabalin 300 mg/day, 37.4% with 450 mg/day, and 42.0% with 600 mg/day. The rates of somnolence were 3.8% with placebo, 12.6% with 300 mg/day of pregabalin, 19.5% with 450 mg/day, and 21.8% with 600 mg/day. Dizziness and somnolence were also the most common adverse effects that led to discontinuation of pregabalin, with rates of 4% and 3%, respectively.

The open-label phase of the FREEDOM trial showed rates of 36% for dizziness and 22% for somnolence among pregabalin-treated patients.

Weight gain and peripheral edema were also common adverse effects in these studies.22 Definitions of weight gain varied, and edema was not accompanied by evidence of cardiac or renal dysfunction.

Less common side effects seen more frequently in the treated groups included dry mouth, blurred vision, and difficulty with concentration and attention. The package insert also warns of angioedema, hypersensitivity reaction, mild asymptomatic creatine kinase elevation, decreased platelet count (without bleeding), and prolongation of the PR interval on electrocardiography.

Pregabalin is a schedule V controlled substance; in clinical studies, abrupt or rapid discontinuation of the drug led to insomnia, nausea, headache, or diarrhea in some patients, suggesting symptoms of dependence. In clinical studies involving a total of more than 5,500 patients, 4% of patients on pregabalin and 1% of patients on placebo reported euphoria as an adverse effect,19 suggesting possible potential for abuse.

Dosing

As a result of the above studies, the recommended starting dose of pregabalin for fibromyalgia is 150 mg/day in two or three divided doses, gradually increased to 300 mg/day within 1 week based on tolerability and efficacy. The dose may be increased to a maximum of 450 mg/day. The 600-mg dose was found to have no significant additional benefit, but it did have more adverse effects and therefore is not recommended. It is important to note that in these studies multiple medications for pain and insomnia were prohibited, so data on drug interactions with pregabalin are limited.

Few achieve complete remission, but most patients feel better

Several studies of the natural history of fibromyalgia have shown that very few patients experience complete remission of the disease, even after many years. Therefore, one should try to set up realistic expectations for patients, with the goal of achieving functional improvement in activities of daily living and a return to one’s predisease state.

In the longest follow-up study, 39 patients in Boston, MA, were prospectively followed for over 10 years. No patient achieved complete remission: all of them reported some fibromyalgia-related symptoms at the end of the study.23 However, 66% of them felt a little to a lot better than when first diagnosed, 55% felt well or very well, and only 7% felt poorly.

Other studies have also shown complete remission to be rare.24,25 A 5-year follow-up study investigating fibromyalgia patients’ perceptions of their symptoms and its impact on everyday life activities demonstrated that the social consequences of fibromyalgia’s symptoms are severe and constant over time.26

Evidence of favorable outcomes was reported in one study in which 47% of patients reported moderate to marked improvement in overall fibromyalgia status upon 3-year follow-up,27 and in another study, in which remission was objectively identified in 24.2% of patients 2 years after diagnosis.28

OTHER THERAPIES

Although there have been many studies of pharmacologic therapies for fibromyalgia to date, the trials had significant limitations, such as short duration, inadequate sample size, nonstandardized measures of efficacy, question of regression to the mean, and inadequate blinding, resulting in insufficient evidence to recommend one drug over another.

Tricyclic antidepressants. Two meta-analyses and a clinical review have supported the efficacy of tricyclic antidepressants in improving symptoms in fibromyalgia patients.29–31

Selective serotonin reuptake inhibitors (SSRIs) have not been well studied, and the small size and methodologic shortcomings of these studies make it difficult to draw conclusions about the efficacy of SSRIs in reducing pain in fibromyalgia patients.30,31

Duloxetine (Cymbalta) and milnacipran (Savella) are serotonin and norepinephrine reuptake inhibitors.32–34 A randomized, double-blind placebo-controlled trial evaluated duloxetine in 520 fibromyalgia patients with and without major depressive disorder. Pain scores improved significantly over 6 months in duloxetine-treated patients at doses of 60 and 120 mg/day.33 Duloxetine became the second drug approved for the treatment of fibromyalgia in 2007, and milnacipran became the third in 2009.

WHAT ROLE FOR PREGABALIN?

Pregabalin may reduce pain in some patients with fibromyalgia. However, the presenting symptoms can vary significantly, and symptoms can vary even in individual patients over time. Therefore, in most patients with fibromyalgia, a multidisciplinary approach is used to treat pain, sleep disturbance, and fatigue, along with comorbidities such as neurally mediated hypotension and psychiatric disorders. Because treatment of fibromyalgia often involves multiple drugs in addition to exercise and behavioral therapies, future studies should examine combinations of drugs and the use of drugs in conjunction with nondrug treatments.

Pregabalin advances our knowledge of fibromyalgia through improving the understanding of central sensitization and how brain neurotransmitters control central pain perceptions. Drug treatment must still be part of the comprehensive management of this disease. Physician and patient education about the current understanding of the disease is paramount in setting realistic goals for treatment.14 Future strategies to manage fibromyalgia will be based on the pathophysiology of this complex condition.

References
  1. Berenson A. Drug approved. Is disease real? New York Times, January 14, 2008. http://www.nytimes.com/2008/01/14/health/14pain.html. Accessed February 2, 2009.
  2. White KP, Harth M. Classification, epidemiology, and natural history of fibromyalgia. Curr Pain Headache Rep 2001; 5:320329.
  3. Bennett RM. Fibromyalgia: present to future. Curr Pain Headache Rep 2004; 8:379384.
  4. Wolfe F, Smythe HA, Yunus MF, et al. The American College of Rheumatolgy 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum 1990; 33:160172.
  5. Bennett RM. The rational management of fibromyalgia patients. Rheum Dis Clin North Am 2002; 28:181199.
  6. Staud R. Evidence of involvement of central neural mechanisms in generating fibromyalgia pain. Curr Rheumatol Rep 2002; 4:299305.
  7. Li J, Simone DA, Larson AA. Windup leads to characteristics of central sensitization. Pain 1999; 79:7582.
  8. Desmeules JA, Cedraschi C, Rapiti E, et al. Neurophysiologic evidence for a central sensitization in patients with fibromyalgia. Arthritis Rheum 2003; 48:14201429.
  9. Staud R, Vierck CJ, Cannon RL, Mauderli AP, Price DD. Abnormal sensitization and temporal summation of pain (wind-up) in patients with fibromyalgia syndrome. Pain 2001; 91:165175.
  10. Russell IJ, Orr MD, Littman B, et al. Elevated cerebrospinal fluid levels of substance P in patients with fibromyalgia syndrome. Arthritis Rheum 1994; 37:15931601.
  11. Harris RE, Sundgren PC, Pang Y, et al. Dynamic levels of glutamate within the insula are associated with improvements in multiple pain domains in fibromyalgia. Arthritis Rheum 2008; 58:903907.
  12. Gracely RH, Petzke F, Wolf JM, Clauw DJ. Functional magnetic resonance imaging evidence of augmented pain processing in fibromyalgia. Arthritis Rheum 2002; 46:13331343.
  13. Staud R, Craggs JG, Perlstein WM, Robinson ME, Price DD. Brain activity associated with slow temporal summation of C-fiber evoked pain in fibromyalgia patients and healthy controls. Eur J Pain 2008; 12:10781089.
  14. Baker K, Barkhuizen A. Pharmacologic treatment of fibromyalgia. Curr Pain Headache Rep 2005; 9:301306.
  15. Tassone DM, Boyce E, Guyer J, Nuzum D. Pregabalin: a novel gamma-aminobutyric acid analogue in the treatment of neuropathic pain, partial-onset seizures, and anxiety disorders. Clin Ther 2007; 29:2648.
  16. Crofford LJ, Rowbotham MC, Mease PJ, et al, and the Pregabalin 1008-105 Study Group. Pregabalin for the treatment of fibromyalgia syndrome. results of a randomized, double-blind, placebo-controlled trial. Arthritis Rheum 2005; 52:12641273.
  17. Stahl SM. Anticonvulsants and the relief of chronic pain: pregabalin and gabapentin as alpha(2)delta ligands at voltage-gated calcium channels. J Clin Psychiatry 2004; 65:596597.
  18. Hindmarch I, Dawson J, Stanley N. A double-blind study in healthy volunteers to assess the effects of sleep on pregabalin compared with alprazolam and placebo. Sleep 2005; 28:187193.
  19. Pfizer Executive Summary. Lyrica (pregabalin) capsules c-v. July 2007. www.fda.gov/OHRMS/DOCKETS/ac/08/briefing/2008-4372b1-02-Pfizer.pdf. Accessed February 2, 2009.
  20. Arnold LM, Russell IJ, Diri EW, et al. A 14-week, randomized, double-blinded, placebo-controlled mono-therapy trial of pregabalin in patients with fibomyalgia. J Pain 2008; 9:792805.
  21. Duan WR, Florian H, Young JP, Martin S, Haig G, Barrett JA. Pregabalin monotherapy for management of fibromyalgia: analysis of two double-blind, randomized, placebo-controlled trials (poster presentation). American College of Rheumatology Annual Scientific Meeting, Boston, MA, November 6–7, 2007.
  22. Crofford LJ, Mease PJ, Simpson SL, et al. Fibromyalgia relapse evaluation and efficacy for durability of meaningful relief (FREEDOM): a 6-month, double-blind, placebo-controlled trial with pregabalin. Pain 2008; 136:419431.
  23. Kennedy M, Felson DT. A prospective long-term study of fibromyalgia syndrome. Arthritis Rheum 1996; 39:682685.
  24. Bengtsson A, Backman E. Long-term follow-up of fibro-myalgia patients [abstract]. Scand J Rheumatolology 1992; 21(suppl 94):9.
  25. Ledingham J, Doherty S, Doherty M. Primary fibromyalgia syndrome—an outcome study. Br J Rheumatol 1993; 32:139142.
  26. Henrikkson CM. Longterm effects of fibromyalgia on everyday life: a study of 56 patients. Scand J Rheumatol 1994; 23:3641.
  27. Fitzcharles MA, Costa DD, Pöyhiä R. A study of standard care in fibromyalgia syndrome: a favorable outcome. J Rheumatol 2003; 30:154159.
  28. Granges G, Zilko P, Littlejohn GO. Fibromyalgia syndrome: assessment of the severity of the condition 2 years after the diagnosis. J Rheumatol 1994; 21:523529.
  29. Goldenberg DL, Burckhardt C, Crofford L. Management of fibromyalgia syndrome. JAMA 2004; 292:23882395.
  30. Arnold LM, Keck PE, Welge JA. Antidepressant treatment of fibromyalgia: a meta-analysis and review. Psychosomatics 2000; 41:104113.
  31. O’Malley PG, Balden E, Tomkins G, Santoro J, Kroenke K, Jackson JL. Treatment of fibromyalgia with anti-depressants: a meta-analysis. J Gen Intern Med 2000; 15:659666.
  32. Arnold LM, Lu Y, Crofford LJ, et al. A double-blind, multicenter trial comparing duloxetine with placebo in the treatment of fibromyalgia patients with or without major depressive disorder. Arthritis Rheum 2004; 50:29742984.
  33. Russell IJ, Mease PJ, Smith TR, et al. Efficacy and safety of duloxetine for treatment of fibromyalgia in patients with or without major depressive disorder: Results from a 6-month, randomized, double-blind, placebo-controlled fixed-dose trial. Pain 2008; 136:432444.
  34. Clauw DJ, Mease P, Palmer RH, Gendreau RM, Wang Y. Milnacipran for the treatment of fibromyalgia in adults: a 15-week, multicenter, randomized, double-blind, placebo-controlled, multiple-dose clinical trial. Clin Ther 2008; 30:19882004.
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Address: Atul Deodhar, MD, Division of Arthritis and Rheumatic Diseases (OP09), Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239; e-mail [email protected]

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Address: Atul Deodhar, MD, Division of Arthritis and Rheumatic Diseases (OP09), Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239; e-mail [email protected]

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Related Articles

Pregabalin (Lyrica) is a novel analogue of the neurotransmitter gamma aminobutyric acid (GABA) with analgesic, anticonvulsant, and anxiolytic activity. Its approval by the US Food and Drug Administration (FDA) in 2007 for the treatment of fibromyalgia made it the first drug approved for this indication. Until then, management of fibromyalgia entailed drugs to treat pain, sleep, fatigue, and psychological disorders, and a strong emphasis on exercise and physical therapy.

Those who still question the validity of fibromyalgia as a diagnosis object to drug companies “benefiting” from the sale of such drugs.1 But many hail pregabalin as an important advance in our understanding of the pathogenesis of fibromyalgia and how to treat it. A key question remains: How will pregabalin fit into the treatment of this often-challenging disease?

FROM FIBROSITIS TO FIBROMYALGIA

Fibromyalgia is a syndrome characterized by widespread pain. Chronic muscular pain is a common problem, but fibromyalgia is distinguished from other pain disorders by additional findings, such as consistent areas of tenderness (tender points), nonrestorative sleep, severe fatigue, and frequent psychological comorbidities such as depression and anxiety.

Fibromyalgia was originally termed “fibrositis” in 1904 by Sir William Gowers, who described it as a painful condition of the fibrous tissue, which he believed was due to inflammation in the muscles.2,3 For several decades, research was dedicated to looking for pathology in the muscle tissue, which was thought to be the major source of pain for most patients with fibromyalgia.

In the mid-1970s, Dr. H. Moldofsky, a noted sleep researcher, reported on abnormalities of the alpha-delta component of nonrapid-eye-movement sleep in these patients. He subsequently collaborated with Dr. Hugh A. Smythe, who helped define the fibromyalgia tender points. Fibrositis was subsequently renamed fibromyalgia syndrome, since it was agreed that there was no true inflammation in muscles or fibrous tissue.

In 1990, the American College of Rheumatology published “classification criteria” for the disease.4 The criteria include two main features:

  • A history of widespread pain (“widespread” being defined as in the axial distribution, in both the left and right sides of the body, and above and below the waist), which must be present for 3 months or more, and
  • Tenderness in at least 11 of 18 specified points that is elicited when a pressure of 4 kg (the amount of pressure required to blanch a thumbnail) is applied in steady increments starting at 1 kg.

Although pain is subjective and therefore difficult to assess, the classification criteria did make it easier to study the disease in a uniform way and led to an explosion of research in this field.

FUNCTIONAL ABNORMALITIES NI THE CENTRAL NERVOUS SYSTEM

Research to date points to the pain in fibromyalgia as being mediated by changes in the central nervous system rather than in the musculoskeletal system, as was initially thought.

In the dorsal horn of the spinal cord, nociceptive (pain-sensing) neurons from the periphery synapse with the second-order neurons that carry the pain signal to the brain. In fibromyalgia, several processes seem to amplify the signal.

Central sensitization is defined as enhanced excitability of neurons in the dorsal horn. Its features include augmented spontaneous neuronal activity, enlarged receptive field areas, and enhanced responses generated by large- and small-caliber primary afferent fibers. It can result from prolonged or strong activity in the dorsal horn neurons, and it leads to the spread of hyperactivity across multiple spinal segments.5–7

While much of the evidence for central sensitization in fibromyalgia is from animal studies, the phenomenon has also been studied in humans. Desmeules et al8 found that, compared with people without fibromyalgia, those with fibromyalgia had significantly lower thresholds of pain as assessed subjectively and measured objectively using the nociceptive flexion R-III reflex, which the authors described as “a specific physiologic correlate for the objective evaluation of central nociceptive pathways.”

Wind-up. Prolonged stimulation of C fibers in the dorsal horn can result in the phenomenon of wind-up, which refers to the temporal summation of second pain.

A painful stimulus evokes two pain signals. The first signal is brief and travels rapidly to the spinal cord via myelinated fibers (A fibers). The second signal, which is related to chronic pain and is described as dull, aching, or burning, travels more slowly to the dorsal horn via unmyelinated fibers (C fibers), the synapses of which use the neurotransmitter glutamate. Temporal summation is a phenomenon observed in experiments in which a series of painful stimuli are applied at regular intervals of about 2 seconds; although each stimulus is identical in intensity, subjects perceive them as increasing in intensity. The reason: during this repetitive stimulation, N-methyl-d-aspartate (NMDA) receptors become activated, leading to the removal of a magnesium block within the receptor. This results in an influx of calcium into the neuron and activation of protein kinase C, nitric oxide synthase, and cyclooxygenase. Ultimately, the firing rates of the nociceptive neurons are increased and the peripheral pain signal is strongly amplified.6

Wind-up has been shown to lead to characteristics of central sensitization related to C-fiber activity in animals.7 Staud et al9 studied wind-up in patients with and without fibromyalgia using series of repetitive thermal stimulation to produce temporal summation. Though wind-up was evoked in both groups, differences were observed both in the magnitude of sensory response to the first stimulus within a series and in the amount of temporal summation within a series.

Elevated excitatory neurotransmitters. In 1994, Russell et al10 showed that the concentration of substance P, an excitatory neurotransmitter, was three times higher in the cerebrospinal fluid of people with fibromyalgia than in normal controls.

Harris and colleagues11 reported that glutamate, another excitatory neurotransmitter, is elevated within the brain in people with fibromyalgia. They further showed that the levels of glutamate within the insula of the brain are directly associated with the levels of both experimental pressure-evoked pain thresholds and clinical pain ratings in fibromyalgia patients.

Evidence from imaging studies. Other objective evidence of central sensitization in fibromyalgia patients comes from studies using novel imaging.

Gracely et al12 performed functional magnetic resonance imaging (MRI) in people with and without fibromyalgia while applying pressure to their thumbs with a thumbscrew-type device. At equal levels of pressure, the people with fibromyalgia said the pressure hurt more, and specific areas of their brains lit up more on functional MRI. When the experimenters increased the pressure in the people without fibromyalgia until this group subjectively rated the pain as high as the fibromyalgia patients rated the lower level of pressure, their brains lit up to a similar degree in the same areas. These findings provide objective evidence of significantly lower pain thresholds in patients with fibromyalgia than in healthy controls, and they support the theory of central augmentation of pain sensitivity in fibromyalgia.

Staud et al13 also used functional MRI and found greater brain activity associated with temporal summation in fibromyalgia patients compared with controls. (In this experiment, the painful stimulus consisted of heat pulses to the foot.)

Drugs other than pregabalin that modulate the dorsal horn activity of the pain pathway include opioids, tramadol (Ultram), gabapentin (Neurontin), GABA agonists such as baclofen (Lioresal), antidepressants, alpha-2 adrenergic agonists (phenylephrine), and 5-HT3 antagonists such as ondansetron (Zofran), but none has been consistently effective for fibromyalgia.5,14

 

 

PREGABALIN

Pregabalin is an alpha-2-delta ligand similar to GABA, but it does not act on GABA receptors. Rather, it binds with high affinity to the alpha-2-delta subunit of voltage-gated presynaptic calcium channels, resulting in reduction of calcium flow through the channels, which subsequently inhibits the release of neurotransmitters including glutamate, norepinephrine, and substance P.15–17 Animal studies suggest that the decrease in the levels of these excitatory neurotransmitters is the mechanism of action of pregabalin, resulting in its analgesic, anticonvulsant, and anxiolytic benefit.15 Another potential mechanism of pregabalin is enhancement of slow-wave sleep, demonstrated in one study in healthy human subjects.18

Besides fibromyalgia, pregabalin is also approved for the treatment of diabetic peripheral neuropathy, postherpetic neuralgia, generalized anxiety disorder, and social anxiety disorder, and as adjunctive therapy for partial-onset seizure in adults.

Pharmacokinetics

Pregabalin is quickly absorbed, primarily in the proximal colon (bioavailability > 90%), and has highly predictable and linear pharmacokinetics.15 Food consumption does not affect its absorption or elimination but can delay its peak plasma concentration, which occurs at 1.5 hours. Its elimination half-life is approximately 6 hours.15 Because it does not bind to plasma proteins, it freely crosses the blood-brain barrier. The drug reaches its steady-state concentration within 2 days of starting therapy.

Its clearance is not affected by the sex or race of the patient, but its total clearance may be lower in the elderly because of age-related loss of renal function. Patients on hemodialysis may require a supplemental dose after dialysis because hemodialysis removes the pregabalin.

The drug is not metabolized by the P450 system in the liver, so it interacts only minimally with drugs that do use the P450 system. However, its clearance may be decreased when it is used concomitantly with drugs that can reduce the glomerular filtration rate, such as nonsteroidal anti-inflammatory drugs, aminoglycosides, and cyclosporine.15

Efficacy

The efficacy of pregabalin in fibromyalgia was evaluated in several recent trials.19

Crofford et al16 assessed pregabalin’s effects on pain, sleep, fatigue, and health-related quality of life. Some 529 patients with fibromyalgia were randomized in a double-blind fashion to four treatment groups: placebo, and pregabalin 150 mg/day, 300 mg/day, and 450 mg/day. The baseline mean pain scores (a 0-to-10 scale derived from daily diary ratings) were 6.9 in the placebo group, 6.9 for the pregabalin 150 mg/day group, 7.3 for the pregabalin 300 mg/day group, and 7.0 for the pregabalin 450 mg/day group.

The pain scores declined in all groups, but at 8 weeks, the mean score had declined 0.93 points more in the group receiving pregabalin 450 mg/day than in the placebo group (P ≤ .001). The scores in the groups taking pregabalin 150 mg/day and 300 mg/day were not significantly different from those in the placebo group. Significantly more patients in the 450-mg/day group (29%, vs 13% in the placebo group) had at least 50% improvement in pain at the end of the study. Patients in both the 300-mg/day group and the 450-mg/day had statistically significant improvement in their quality of sleep, in fatigue, and on the Patient Global Impression of Change (PGIC) scale.

Arnold et al20 conducted a trial with 750 patients in which three doses of pregabalin were compared with placebo: 300 mg/day, 450 mg/day, and 600 mg/day. The primary end point was also the change in pain score from baseline (using the 0-to-10 scale derived from a daily pain diary). The mean baseline pain score was 6.7.

At 14 weeks, the mean pain score was lower than at baseline in all the groups, but it had declined 0.71 more in the pregabalin 300-mg/day group than in the placebo group, 0.98 points more in the 450-mg/day group, and 1.0 points more in the 600-mg/day group. All three pregabalin groups also showed significant improvement on the PGIC scale, and patients in the 450-mg/day and 600-mg/day groups showed statistically significant improvement in the Fibromyalgia Impact Questionnaire (FIQ) score. All three pregabalin treatment groups also had significantly better patient-reported sleep outcomes than in the placebo group, both in measures of overall sleep and quality of sleep. With the exception of a significant improvement of anxiety on 600 mg/day, there was no significant difference between the treatment and placebo groups in the secondary outcomes of depression and anxiety symptoms and fatigue.

Duan et al21 presented a pooled analysis of this and a similarly designed double-blind, placebo-controlled trial (the results of which were not available individually) at the 71st annual meeting of the American College of Rheumatology in November 2007. The analysis included 1,493 patients with a mean baseline pain score of 6.9. Compared with the mean pain score in the placebo group, those in the pregabalin groups had declined more by the end of the study: 0.55 points more with 300 mg/day, 0.71 points more with 450 mg/day, and 0.82 points more with 600 mg/day. This pooled analysis also showed significant improvement in PGIC score with all pregabalin doses and in the FIQ score with 450 mg/day and 600 mg/day.

The FREEDOM trial22 (Fibromyalgia Relapse Evaluation and Efficacy for Durability of Meaningful Relief) evaluated the durability of effect of pregabalin in reducing pain and symptoms associated with fibromyalgia in 1,051 patients who initially responded to the drug.

The patients received 6 weeks of open-label treatment with pregabalin and then 26 weeks of double-blind treatment (dose adjustment was allowed based on efficacy and tolerability for the first 3 weeks). The time to loss of therapeutic response was significantly longer with pregabalin than with placebo. Loss of therapeutic response was defined as worsening of pain for two consecutive visits or worsening of fibromyalgia symptoms requiring alternative therapy.

By the end of the double-blind phase, 61% of those in the placebo group had loss of therapeutic response compared with only 32% in the pregabalin group. The time to worsening of the FIQ score was also significantly longer in the pregabalin group than in the placebo group.

 

 

Adverse effects: Dizziness, sleepiness, weight gain

Dizziness and sleepiness were the most common adverse events in these studies.

In the 8-week study by Crofford et al,16 dizziness was dose-related, occurring in 10.7% of those receiving placebo (one patient withdrew because of dizziness), 22.7% of those receiving 150 mg/day (two patients withdrew), 31.3% of those receiving 300 mg/day (four patients withdrew), and 49.2% of those receiving 450 mg/day (five patients withdrew). Somnolence was also dose-related, occurring in 4.6% in the placebo group, 15.9% in the 150-mg/day group (two patients withdrew due to somnolence), 27.6% in the 300-mg/day group (three withdrew), and 28.0% in the 450-mg/day group (five withdrew).

The 14-week study by Arnold et al20 also showed higher frequencies of adverse events with higher doses. The rates of dizziness were 7.6% with placebo, 27.9% with pregabalin 300 mg/day, 37.4% with 450 mg/day, and 42.0% with 600 mg/day. The rates of somnolence were 3.8% with placebo, 12.6% with 300 mg/day of pregabalin, 19.5% with 450 mg/day, and 21.8% with 600 mg/day. Dizziness and somnolence were also the most common adverse effects that led to discontinuation of pregabalin, with rates of 4% and 3%, respectively.

The open-label phase of the FREEDOM trial showed rates of 36% for dizziness and 22% for somnolence among pregabalin-treated patients.

Weight gain and peripheral edema were also common adverse effects in these studies.22 Definitions of weight gain varied, and edema was not accompanied by evidence of cardiac or renal dysfunction.

Less common side effects seen more frequently in the treated groups included dry mouth, blurred vision, and difficulty with concentration and attention. The package insert also warns of angioedema, hypersensitivity reaction, mild asymptomatic creatine kinase elevation, decreased platelet count (without bleeding), and prolongation of the PR interval on electrocardiography.

Pregabalin is a schedule V controlled substance; in clinical studies, abrupt or rapid discontinuation of the drug led to insomnia, nausea, headache, or diarrhea in some patients, suggesting symptoms of dependence. In clinical studies involving a total of more than 5,500 patients, 4% of patients on pregabalin and 1% of patients on placebo reported euphoria as an adverse effect,19 suggesting possible potential for abuse.

Dosing

As a result of the above studies, the recommended starting dose of pregabalin for fibromyalgia is 150 mg/day in two or three divided doses, gradually increased to 300 mg/day within 1 week based on tolerability and efficacy. The dose may be increased to a maximum of 450 mg/day. The 600-mg dose was found to have no significant additional benefit, but it did have more adverse effects and therefore is not recommended. It is important to note that in these studies multiple medications for pain and insomnia were prohibited, so data on drug interactions with pregabalin are limited.

Few achieve complete remission, but most patients feel better

Several studies of the natural history of fibromyalgia have shown that very few patients experience complete remission of the disease, even after many years. Therefore, one should try to set up realistic expectations for patients, with the goal of achieving functional improvement in activities of daily living and a return to one’s predisease state.

In the longest follow-up study, 39 patients in Boston, MA, were prospectively followed for over 10 years. No patient achieved complete remission: all of them reported some fibromyalgia-related symptoms at the end of the study.23 However, 66% of them felt a little to a lot better than when first diagnosed, 55% felt well or very well, and only 7% felt poorly.

Other studies have also shown complete remission to be rare.24,25 A 5-year follow-up study investigating fibromyalgia patients’ perceptions of their symptoms and its impact on everyday life activities demonstrated that the social consequences of fibromyalgia’s symptoms are severe and constant over time.26

Evidence of favorable outcomes was reported in one study in which 47% of patients reported moderate to marked improvement in overall fibromyalgia status upon 3-year follow-up,27 and in another study, in which remission was objectively identified in 24.2% of patients 2 years after diagnosis.28

OTHER THERAPIES

Although there have been many studies of pharmacologic therapies for fibromyalgia to date, the trials had significant limitations, such as short duration, inadequate sample size, nonstandardized measures of efficacy, question of regression to the mean, and inadequate blinding, resulting in insufficient evidence to recommend one drug over another.

Tricyclic antidepressants. Two meta-analyses and a clinical review have supported the efficacy of tricyclic antidepressants in improving symptoms in fibromyalgia patients.29–31

Selective serotonin reuptake inhibitors (SSRIs) have not been well studied, and the small size and methodologic shortcomings of these studies make it difficult to draw conclusions about the efficacy of SSRIs in reducing pain in fibromyalgia patients.30,31

Duloxetine (Cymbalta) and milnacipran (Savella) are serotonin and norepinephrine reuptake inhibitors.32–34 A randomized, double-blind placebo-controlled trial evaluated duloxetine in 520 fibromyalgia patients with and without major depressive disorder. Pain scores improved significantly over 6 months in duloxetine-treated patients at doses of 60 and 120 mg/day.33 Duloxetine became the second drug approved for the treatment of fibromyalgia in 2007, and milnacipran became the third in 2009.

WHAT ROLE FOR PREGABALIN?

Pregabalin may reduce pain in some patients with fibromyalgia. However, the presenting symptoms can vary significantly, and symptoms can vary even in individual patients over time. Therefore, in most patients with fibromyalgia, a multidisciplinary approach is used to treat pain, sleep disturbance, and fatigue, along with comorbidities such as neurally mediated hypotension and psychiatric disorders. Because treatment of fibromyalgia often involves multiple drugs in addition to exercise and behavioral therapies, future studies should examine combinations of drugs and the use of drugs in conjunction with nondrug treatments.

Pregabalin advances our knowledge of fibromyalgia through improving the understanding of central sensitization and how brain neurotransmitters control central pain perceptions. Drug treatment must still be part of the comprehensive management of this disease. Physician and patient education about the current understanding of the disease is paramount in setting realistic goals for treatment.14 Future strategies to manage fibromyalgia will be based on the pathophysiology of this complex condition.

Pregabalin (Lyrica) is a novel analogue of the neurotransmitter gamma aminobutyric acid (GABA) with analgesic, anticonvulsant, and anxiolytic activity. Its approval by the US Food and Drug Administration (FDA) in 2007 for the treatment of fibromyalgia made it the first drug approved for this indication. Until then, management of fibromyalgia entailed drugs to treat pain, sleep, fatigue, and psychological disorders, and a strong emphasis on exercise and physical therapy.

Those who still question the validity of fibromyalgia as a diagnosis object to drug companies “benefiting” from the sale of such drugs.1 But many hail pregabalin as an important advance in our understanding of the pathogenesis of fibromyalgia and how to treat it. A key question remains: How will pregabalin fit into the treatment of this often-challenging disease?

FROM FIBROSITIS TO FIBROMYALGIA

Fibromyalgia is a syndrome characterized by widespread pain. Chronic muscular pain is a common problem, but fibromyalgia is distinguished from other pain disorders by additional findings, such as consistent areas of tenderness (tender points), nonrestorative sleep, severe fatigue, and frequent psychological comorbidities such as depression and anxiety.

Fibromyalgia was originally termed “fibrositis” in 1904 by Sir William Gowers, who described it as a painful condition of the fibrous tissue, which he believed was due to inflammation in the muscles.2,3 For several decades, research was dedicated to looking for pathology in the muscle tissue, which was thought to be the major source of pain for most patients with fibromyalgia.

In the mid-1970s, Dr. H. Moldofsky, a noted sleep researcher, reported on abnormalities of the alpha-delta component of nonrapid-eye-movement sleep in these patients. He subsequently collaborated with Dr. Hugh A. Smythe, who helped define the fibromyalgia tender points. Fibrositis was subsequently renamed fibromyalgia syndrome, since it was agreed that there was no true inflammation in muscles or fibrous tissue.

In 1990, the American College of Rheumatology published “classification criteria” for the disease.4 The criteria include two main features:

  • A history of widespread pain (“widespread” being defined as in the axial distribution, in both the left and right sides of the body, and above and below the waist), which must be present for 3 months or more, and
  • Tenderness in at least 11 of 18 specified points that is elicited when a pressure of 4 kg (the amount of pressure required to blanch a thumbnail) is applied in steady increments starting at 1 kg.

Although pain is subjective and therefore difficult to assess, the classification criteria did make it easier to study the disease in a uniform way and led to an explosion of research in this field.

FUNCTIONAL ABNORMALITIES NI THE CENTRAL NERVOUS SYSTEM

Research to date points to the pain in fibromyalgia as being mediated by changes in the central nervous system rather than in the musculoskeletal system, as was initially thought.

In the dorsal horn of the spinal cord, nociceptive (pain-sensing) neurons from the periphery synapse with the second-order neurons that carry the pain signal to the brain. In fibromyalgia, several processes seem to amplify the signal.

Central sensitization is defined as enhanced excitability of neurons in the dorsal horn. Its features include augmented spontaneous neuronal activity, enlarged receptive field areas, and enhanced responses generated by large- and small-caliber primary afferent fibers. It can result from prolonged or strong activity in the dorsal horn neurons, and it leads to the spread of hyperactivity across multiple spinal segments.5–7

While much of the evidence for central sensitization in fibromyalgia is from animal studies, the phenomenon has also been studied in humans. Desmeules et al8 found that, compared with people without fibromyalgia, those with fibromyalgia had significantly lower thresholds of pain as assessed subjectively and measured objectively using the nociceptive flexion R-III reflex, which the authors described as “a specific physiologic correlate for the objective evaluation of central nociceptive pathways.”

Wind-up. Prolonged stimulation of C fibers in the dorsal horn can result in the phenomenon of wind-up, which refers to the temporal summation of second pain.

A painful stimulus evokes two pain signals. The first signal is brief and travels rapidly to the spinal cord via myelinated fibers (A fibers). The second signal, which is related to chronic pain and is described as dull, aching, or burning, travels more slowly to the dorsal horn via unmyelinated fibers (C fibers), the synapses of which use the neurotransmitter glutamate. Temporal summation is a phenomenon observed in experiments in which a series of painful stimuli are applied at regular intervals of about 2 seconds; although each stimulus is identical in intensity, subjects perceive them as increasing in intensity. The reason: during this repetitive stimulation, N-methyl-d-aspartate (NMDA) receptors become activated, leading to the removal of a magnesium block within the receptor. This results in an influx of calcium into the neuron and activation of protein kinase C, nitric oxide synthase, and cyclooxygenase. Ultimately, the firing rates of the nociceptive neurons are increased and the peripheral pain signal is strongly amplified.6

Wind-up has been shown to lead to characteristics of central sensitization related to C-fiber activity in animals.7 Staud et al9 studied wind-up in patients with and without fibromyalgia using series of repetitive thermal stimulation to produce temporal summation. Though wind-up was evoked in both groups, differences were observed both in the magnitude of sensory response to the first stimulus within a series and in the amount of temporal summation within a series.

Elevated excitatory neurotransmitters. In 1994, Russell et al10 showed that the concentration of substance P, an excitatory neurotransmitter, was three times higher in the cerebrospinal fluid of people with fibromyalgia than in normal controls.

Harris and colleagues11 reported that glutamate, another excitatory neurotransmitter, is elevated within the brain in people with fibromyalgia. They further showed that the levels of glutamate within the insula of the brain are directly associated with the levels of both experimental pressure-evoked pain thresholds and clinical pain ratings in fibromyalgia patients.

Evidence from imaging studies. Other objective evidence of central sensitization in fibromyalgia patients comes from studies using novel imaging.

Gracely et al12 performed functional magnetic resonance imaging (MRI) in people with and without fibromyalgia while applying pressure to their thumbs with a thumbscrew-type device. At equal levels of pressure, the people with fibromyalgia said the pressure hurt more, and specific areas of their brains lit up more on functional MRI. When the experimenters increased the pressure in the people without fibromyalgia until this group subjectively rated the pain as high as the fibromyalgia patients rated the lower level of pressure, their brains lit up to a similar degree in the same areas. These findings provide objective evidence of significantly lower pain thresholds in patients with fibromyalgia than in healthy controls, and they support the theory of central augmentation of pain sensitivity in fibromyalgia.

Staud et al13 also used functional MRI and found greater brain activity associated with temporal summation in fibromyalgia patients compared with controls. (In this experiment, the painful stimulus consisted of heat pulses to the foot.)

Drugs other than pregabalin that modulate the dorsal horn activity of the pain pathway include opioids, tramadol (Ultram), gabapentin (Neurontin), GABA agonists such as baclofen (Lioresal), antidepressants, alpha-2 adrenergic agonists (phenylephrine), and 5-HT3 antagonists such as ondansetron (Zofran), but none has been consistently effective for fibromyalgia.5,14

 

 

PREGABALIN

Pregabalin is an alpha-2-delta ligand similar to GABA, but it does not act on GABA receptors. Rather, it binds with high affinity to the alpha-2-delta subunit of voltage-gated presynaptic calcium channels, resulting in reduction of calcium flow through the channels, which subsequently inhibits the release of neurotransmitters including glutamate, norepinephrine, and substance P.15–17 Animal studies suggest that the decrease in the levels of these excitatory neurotransmitters is the mechanism of action of pregabalin, resulting in its analgesic, anticonvulsant, and anxiolytic benefit.15 Another potential mechanism of pregabalin is enhancement of slow-wave sleep, demonstrated in one study in healthy human subjects.18

Besides fibromyalgia, pregabalin is also approved for the treatment of diabetic peripheral neuropathy, postherpetic neuralgia, generalized anxiety disorder, and social anxiety disorder, and as adjunctive therapy for partial-onset seizure in adults.

Pharmacokinetics

Pregabalin is quickly absorbed, primarily in the proximal colon (bioavailability > 90%), and has highly predictable and linear pharmacokinetics.15 Food consumption does not affect its absorption or elimination but can delay its peak plasma concentration, which occurs at 1.5 hours. Its elimination half-life is approximately 6 hours.15 Because it does not bind to plasma proteins, it freely crosses the blood-brain barrier. The drug reaches its steady-state concentration within 2 days of starting therapy.

Its clearance is not affected by the sex or race of the patient, but its total clearance may be lower in the elderly because of age-related loss of renal function. Patients on hemodialysis may require a supplemental dose after dialysis because hemodialysis removes the pregabalin.

The drug is not metabolized by the P450 system in the liver, so it interacts only minimally with drugs that do use the P450 system. However, its clearance may be decreased when it is used concomitantly with drugs that can reduce the glomerular filtration rate, such as nonsteroidal anti-inflammatory drugs, aminoglycosides, and cyclosporine.15

Efficacy

The efficacy of pregabalin in fibromyalgia was evaluated in several recent trials.19

Crofford et al16 assessed pregabalin’s effects on pain, sleep, fatigue, and health-related quality of life. Some 529 patients with fibromyalgia were randomized in a double-blind fashion to four treatment groups: placebo, and pregabalin 150 mg/day, 300 mg/day, and 450 mg/day. The baseline mean pain scores (a 0-to-10 scale derived from daily diary ratings) were 6.9 in the placebo group, 6.9 for the pregabalin 150 mg/day group, 7.3 for the pregabalin 300 mg/day group, and 7.0 for the pregabalin 450 mg/day group.

The pain scores declined in all groups, but at 8 weeks, the mean score had declined 0.93 points more in the group receiving pregabalin 450 mg/day than in the placebo group (P ≤ .001). The scores in the groups taking pregabalin 150 mg/day and 300 mg/day were not significantly different from those in the placebo group. Significantly more patients in the 450-mg/day group (29%, vs 13% in the placebo group) had at least 50% improvement in pain at the end of the study. Patients in both the 300-mg/day group and the 450-mg/day had statistically significant improvement in their quality of sleep, in fatigue, and on the Patient Global Impression of Change (PGIC) scale.

Arnold et al20 conducted a trial with 750 patients in which three doses of pregabalin were compared with placebo: 300 mg/day, 450 mg/day, and 600 mg/day. The primary end point was also the change in pain score from baseline (using the 0-to-10 scale derived from a daily pain diary). The mean baseline pain score was 6.7.

At 14 weeks, the mean pain score was lower than at baseline in all the groups, but it had declined 0.71 more in the pregabalin 300-mg/day group than in the placebo group, 0.98 points more in the 450-mg/day group, and 1.0 points more in the 600-mg/day group. All three pregabalin groups also showed significant improvement on the PGIC scale, and patients in the 450-mg/day and 600-mg/day groups showed statistically significant improvement in the Fibromyalgia Impact Questionnaire (FIQ) score. All three pregabalin treatment groups also had significantly better patient-reported sleep outcomes than in the placebo group, both in measures of overall sleep and quality of sleep. With the exception of a significant improvement of anxiety on 600 mg/day, there was no significant difference between the treatment and placebo groups in the secondary outcomes of depression and anxiety symptoms and fatigue.

Duan et al21 presented a pooled analysis of this and a similarly designed double-blind, placebo-controlled trial (the results of which were not available individually) at the 71st annual meeting of the American College of Rheumatology in November 2007. The analysis included 1,493 patients with a mean baseline pain score of 6.9. Compared with the mean pain score in the placebo group, those in the pregabalin groups had declined more by the end of the study: 0.55 points more with 300 mg/day, 0.71 points more with 450 mg/day, and 0.82 points more with 600 mg/day. This pooled analysis also showed significant improvement in PGIC score with all pregabalin doses and in the FIQ score with 450 mg/day and 600 mg/day.

The FREEDOM trial22 (Fibromyalgia Relapse Evaluation and Efficacy for Durability of Meaningful Relief) evaluated the durability of effect of pregabalin in reducing pain and symptoms associated with fibromyalgia in 1,051 patients who initially responded to the drug.

The patients received 6 weeks of open-label treatment with pregabalin and then 26 weeks of double-blind treatment (dose adjustment was allowed based on efficacy and tolerability for the first 3 weeks). The time to loss of therapeutic response was significantly longer with pregabalin than with placebo. Loss of therapeutic response was defined as worsening of pain for two consecutive visits or worsening of fibromyalgia symptoms requiring alternative therapy.

By the end of the double-blind phase, 61% of those in the placebo group had loss of therapeutic response compared with only 32% in the pregabalin group. The time to worsening of the FIQ score was also significantly longer in the pregabalin group than in the placebo group.

 

 

Adverse effects: Dizziness, sleepiness, weight gain

Dizziness and sleepiness were the most common adverse events in these studies.

In the 8-week study by Crofford et al,16 dizziness was dose-related, occurring in 10.7% of those receiving placebo (one patient withdrew because of dizziness), 22.7% of those receiving 150 mg/day (two patients withdrew), 31.3% of those receiving 300 mg/day (four patients withdrew), and 49.2% of those receiving 450 mg/day (five patients withdrew). Somnolence was also dose-related, occurring in 4.6% in the placebo group, 15.9% in the 150-mg/day group (two patients withdrew due to somnolence), 27.6% in the 300-mg/day group (three withdrew), and 28.0% in the 450-mg/day group (five withdrew).

The 14-week study by Arnold et al20 also showed higher frequencies of adverse events with higher doses. The rates of dizziness were 7.6% with placebo, 27.9% with pregabalin 300 mg/day, 37.4% with 450 mg/day, and 42.0% with 600 mg/day. The rates of somnolence were 3.8% with placebo, 12.6% with 300 mg/day of pregabalin, 19.5% with 450 mg/day, and 21.8% with 600 mg/day. Dizziness and somnolence were also the most common adverse effects that led to discontinuation of pregabalin, with rates of 4% and 3%, respectively.

The open-label phase of the FREEDOM trial showed rates of 36% for dizziness and 22% for somnolence among pregabalin-treated patients.

Weight gain and peripheral edema were also common adverse effects in these studies.22 Definitions of weight gain varied, and edema was not accompanied by evidence of cardiac or renal dysfunction.

Less common side effects seen more frequently in the treated groups included dry mouth, blurred vision, and difficulty with concentration and attention. The package insert also warns of angioedema, hypersensitivity reaction, mild asymptomatic creatine kinase elevation, decreased platelet count (without bleeding), and prolongation of the PR interval on electrocardiography.

Pregabalin is a schedule V controlled substance; in clinical studies, abrupt or rapid discontinuation of the drug led to insomnia, nausea, headache, or diarrhea in some patients, suggesting symptoms of dependence. In clinical studies involving a total of more than 5,500 patients, 4% of patients on pregabalin and 1% of patients on placebo reported euphoria as an adverse effect,19 suggesting possible potential for abuse.

Dosing

As a result of the above studies, the recommended starting dose of pregabalin for fibromyalgia is 150 mg/day in two or three divided doses, gradually increased to 300 mg/day within 1 week based on tolerability and efficacy. The dose may be increased to a maximum of 450 mg/day. The 600-mg dose was found to have no significant additional benefit, but it did have more adverse effects and therefore is not recommended. It is important to note that in these studies multiple medications for pain and insomnia were prohibited, so data on drug interactions with pregabalin are limited.

Few achieve complete remission, but most patients feel better

Several studies of the natural history of fibromyalgia have shown that very few patients experience complete remission of the disease, even after many years. Therefore, one should try to set up realistic expectations for patients, with the goal of achieving functional improvement in activities of daily living and a return to one’s predisease state.

In the longest follow-up study, 39 patients in Boston, MA, were prospectively followed for over 10 years. No patient achieved complete remission: all of them reported some fibromyalgia-related symptoms at the end of the study.23 However, 66% of them felt a little to a lot better than when first diagnosed, 55% felt well or very well, and only 7% felt poorly.

Other studies have also shown complete remission to be rare.24,25 A 5-year follow-up study investigating fibromyalgia patients’ perceptions of their symptoms and its impact on everyday life activities demonstrated that the social consequences of fibromyalgia’s symptoms are severe and constant over time.26

Evidence of favorable outcomes was reported in one study in which 47% of patients reported moderate to marked improvement in overall fibromyalgia status upon 3-year follow-up,27 and in another study, in which remission was objectively identified in 24.2% of patients 2 years after diagnosis.28

OTHER THERAPIES

Although there have been many studies of pharmacologic therapies for fibromyalgia to date, the trials had significant limitations, such as short duration, inadequate sample size, nonstandardized measures of efficacy, question of regression to the mean, and inadequate blinding, resulting in insufficient evidence to recommend one drug over another.

Tricyclic antidepressants. Two meta-analyses and a clinical review have supported the efficacy of tricyclic antidepressants in improving symptoms in fibromyalgia patients.29–31

Selective serotonin reuptake inhibitors (SSRIs) have not been well studied, and the small size and methodologic shortcomings of these studies make it difficult to draw conclusions about the efficacy of SSRIs in reducing pain in fibromyalgia patients.30,31

Duloxetine (Cymbalta) and milnacipran (Savella) are serotonin and norepinephrine reuptake inhibitors.32–34 A randomized, double-blind placebo-controlled trial evaluated duloxetine in 520 fibromyalgia patients with and without major depressive disorder. Pain scores improved significantly over 6 months in duloxetine-treated patients at doses of 60 and 120 mg/day.33 Duloxetine became the second drug approved for the treatment of fibromyalgia in 2007, and milnacipran became the third in 2009.

WHAT ROLE FOR PREGABALIN?

Pregabalin may reduce pain in some patients with fibromyalgia. However, the presenting symptoms can vary significantly, and symptoms can vary even in individual patients over time. Therefore, in most patients with fibromyalgia, a multidisciplinary approach is used to treat pain, sleep disturbance, and fatigue, along with comorbidities such as neurally mediated hypotension and psychiatric disorders. Because treatment of fibromyalgia often involves multiple drugs in addition to exercise and behavioral therapies, future studies should examine combinations of drugs and the use of drugs in conjunction with nondrug treatments.

Pregabalin advances our knowledge of fibromyalgia through improving the understanding of central sensitization and how brain neurotransmitters control central pain perceptions. Drug treatment must still be part of the comprehensive management of this disease. Physician and patient education about the current understanding of the disease is paramount in setting realistic goals for treatment.14 Future strategies to manage fibromyalgia will be based on the pathophysiology of this complex condition.

References
  1. Berenson A. Drug approved. Is disease real? New York Times, January 14, 2008. http://www.nytimes.com/2008/01/14/health/14pain.html. Accessed February 2, 2009.
  2. White KP, Harth M. Classification, epidemiology, and natural history of fibromyalgia. Curr Pain Headache Rep 2001; 5:320329.
  3. Bennett RM. Fibromyalgia: present to future. Curr Pain Headache Rep 2004; 8:379384.
  4. Wolfe F, Smythe HA, Yunus MF, et al. The American College of Rheumatolgy 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum 1990; 33:160172.
  5. Bennett RM. The rational management of fibromyalgia patients. Rheum Dis Clin North Am 2002; 28:181199.
  6. Staud R. Evidence of involvement of central neural mechanisms in generating fibromyalgia pain. Curr Rheumatol Rep 2002; 4:299305.
  7. Li J, Simone DA, Larson AA. Windup leads to characteristics of central sensitization. Pain 1999; 79:7582.
  8. Desmeules JA, Cedraschi C, Rapiti E, et al. Neurophysiologic evidence for a central sensitization in patients with fibromyalgia. Arthritis Rheum 2003; 48:14201429.
  9. Staud R, Vierck CJ, Cannon RL, Mauderli AP, Price DD. Abnormal sensitization and temporal summation of pain (wind-up) in patients with fibromyalgia syndrome. Pain 2001; 91:165175.
  10. Russell IJ, Orr MD, Littman B, et al. Elevated cerebrospinal fluid levels of substance P in patients with fibromyalgia syndrome. Arthritis Rheum 1994; 37:15931601.
  11. Harris RE, Sundgren PC, Pang Y, et al. Dynamic levels of glutamate within the insula are associated with improvements in multiple pain domains in fibromyalgia. Arthritis Rheum 2008; 58:903907.
  12. Gracely RH, Petzke F, Wolf JM, Clauw DJ. Functional magnetic resonance imaging evidence of augmented pain processing in fibromyalgia. Arthritis Rheum 2002; 46:13331343.
  13. Staud R, Craggs JG, Perlstein WM, Robinson ME, Price DD. Brain activity associated with slow temporal summation of C-fiber evoked pain in fibromyalgia patients and healthy controls. Eur J Pain 2008; 12:10781089.
  14. Baker K, Barkhuizen A. Pharmacologic treatment of fibromyalgia. Curr Pain Headache Rep 2005; 9:301306.
  15. Tassone DM, Boyce E, Guyer J, Nuzum D. Pregabalin: a novel gamma-aminobutyric acid analogue in the treatment of neuropathic pain, partial-onset seizures, and anxiety disorders. Clin Ther 2007; 29:2648.
  16. Crofford LJ, Rowbotham MC, Mease PJ, et al, and the Pregabalin 1008-105 Study Group. Pregabalin for the treatment of fibromyalgia syndrome. results of a randomized, double-blind, placebo-controlled trial. Arthritis Rheum 2005; 52:12641273.
  17. Stahl SM. Anticonvulsants and the relief of chronic pain: pregabalin and gabapentin as alpha(2)delta ligands at voltage-gated calcium channels. J Clin Psychiatry 2004; 65:596597.
  18. Hindmarch I, Dawson J, Stanley N. A double-blind study in healthy volunteers to assess the effects of sleep on pregabalin compared with alprazolam and placebo. Sleep 2005; 28:187193.
  19. Pfizer Executive Summary. Lyrica (pregabalin) capsules c-v. July 2007. www.fda.gov/OHRMS/DOCKETS/ac/08/briefing/2008-4372b1-02-Pfizer.pdf. Accessed February 2, 2009.
  20. Arnold LM, Russell IJ, Diri EW, et al. A 14-week, randomized, double-blinded, placebo-controlled mono-therapy trial of pregabalin in patients with fibomyalgia. J Pain 2008; 9:792805.
  21. Duan WR, Florian H, Young JP, Martin S, Haig G, Barrett JA. Pregabalin monotherapy for management of fibromyalgia: analysis of two double-blind, randomized, placebo-controlled trials (poster presentation). American College of Rheumatology Annual Scientific Meeting, Boston, MA, November 6–7, 2007.
  22. Crofford LJ, Mease PJ, Simpson SL, et al. Fibromyalgia relapse evaluation and efficacy for durability of meaningful relief (FREEDOM): a 6-month, double-blind, placebo-controlled trial with pregabalin. Pain 2008; 136:419431.
  23. Kennedy M, Felson DT. A prospective long-term study of fibromyalgia syndrome. Arthritis Rheum 1996; 39:682685.
  24. Bengtsson A, Backman E. Long-term follow-up of fibro-myalgia patients [abstract]. Scand J Rheumatolology 1992; 21(suppl 94):9.
  25. Ledingham J, Doherty S, Doherty M. Primary fibromyalgia syndrome—an outcome study. Br J Rheumatol 1993; 32:139142.
  26. Henrikkson CM. Longterm effects of fibromyalgia on everyday life: a study of 56 patients. Scand J Rheumatol 1994; 23:3641.
  27. Fitzcharles MA, Costa DD, Pöyhiä R. A study of standard care in fibromyalgia syndrome: a favorable outcome. J Rheumatol 2003; 30:154159.
  28. Granges G, Zilko P, Littlejohn GO. Fibromyalgia syndrome: assessment of the severity of the condition 2 years after the diagnosis. J Rheumatol 1994; 21:523529.
  29. Goldenberg DL, Burckhardt C, Crofford L. Management of fibromyalgia syndrome. JAMA 2004; 292:23882395.
  30. Arnold LM, Keck PE, Welge JA. Antidepressant treatment of fibromyalgia: a meta-analysis and review. Psychosomatics 2000; 41:104113.
  31. O’Malley PG, Balden E, Tomkins G, Santoro J, Kroenke K, Jackson JL. Treatment of fibromyalgia with anti-depressants: a meta-analysis. J Gen Intern Med 2000; 15:659666.
  32. Arnold LM, Lu Y, Crofford LJ, et al. A double-blind, multicenter trial comparing duloxetine with placebo in the treatment of fibromyalgia patients with or without major depressive disorder. Arthritis Rheum 2004; 50:29742984.
  33. Russell IJ, Mease PJ, Smith TR, et al. Efficacy and safety of duloxetine for treatment of fibromyalgia in patients with or without major depressive disorder: Results from a 6-month, randomized, double-blind, placebo-controlled fixed-dose trial. Pain 2008; 136:432444.
  34. Clauw DJ, Mease P, Palmer RH, Gendreau RM, Wang Y. Milnacipran for the treatment of fibromyalgia in adults: a 15-week, multicenter, randomized, double-blind, placebo-controlled, multiple-dose clinical trial. Clin Ther 2008; 30:19882004.
References
  1. Berenson A. Drug approved. Is disease real? New York Times, January 14, 2008. http://www.nytimes.com/2008/01/14/health/14pain.html. Accessed February 2, 2009.
  2. White KP, Harth M. Classification, epidemiology, and natural history of fibromyalgia. Curr Pain Headache Rep 2001; 5:320329.
  3. Bennett RM. Fibromyalgia: present to future. Curr Pain Headache Rep 2004; 8:379384.
  4. Wolfe F, Smythe HA, Yunus MF, et al. The American College of Rheumatolgy 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum 1990; 33:160172.
  5. Bennett RM. The rational management of fibromyalgia patients. Rheum Dis Clin North Am 2002; 28:181199.
  6. Staud R. Evidence of involvement of central neural mechanisms in generating fibromyalgia pain. Curr Rheumatol Rep 2002; 4:299305.
  7. Li J, Simone DA, Larson AA. Windup leads to characteristics of central sensitization. Pain 1999; 79:7582.
  8. Desmeules JA, Cedraschi C, Rapiti E, et al. Neurophysiologic evidence for a central sensitization in patients with fibromyalgia. Arthritis Rheum 2003; 48:14201429.
  9. Staud R, Vierck CJ, Cannon RL, Mauderli AP, Price DD. Abnormal sensitization and temporal summation of pain (wind-up) in patients with fibromyalgia syndrome. Pain 2001; 91:165175.
  10. Russell IJ, Orr MD, Littman B, et al. Elevated cerebrospinal fluid levels of substance P in patients with fibromyalgia syndrome. Arthritis Rheum 1994; 37:15931601.
  11. Harris RE, Sundgren PC, Pang Y, et al. Dynamic levels of glutamate within the insula are associated with improvements in multiple pain domains in fibromyalgia. Arthritis Rheum 2008; 58:903907.
  12. Gracely RH, Petzke F, Wolf JM, Clauw DJ. Functional magnetic resonance imaging evidence of augmented pain processing in fibromyalgia. Arthritis Rheum 2002; 46:13331343.
  13. Staud R, Craggs JG, Perlstein WM, Robinson ME, Price DD. Brain activity associated with slow temporal summation of C-fiber evoked pain in fibromyalgia patients and healthy controls. Eur J Pain 2008; 12:10781089.
  14. Baker K, Barkhuizen A. Pharmacologic treatment of fibromyalgia. Curr Pain Headache Rep 2005; 9:301306.
  15. Tassone DM, Boyce E, Guyer J, Nuzum D. Pregabalin: a novel gamma-aminobutyric acid analogue in the treatment of neuropathic pain, partial-onset seizures, and anxiety disorders. Clin Ther 2007; 29:2648.
  16. Crofford LJ, Rowbotham MC, Mease PJ, et al, and the Pregabalin 1008-105 Study Group. Pregabalin for the treatment of fibromyalgia syndrome. results of a randomized, double-blind, placebo-controlled trial. Arthritis Rheum 2005; 52:12641273.
  17. Stahl SM. Anticonvulsants and the relief of chronic pain: pregabalin and gabapentin as alpha(2)delta ligands at voltage-gated calcium channels. J Clin Psychiatry 2004; 65:596597.
  18. Hindmarch I, Dawson J, Stanley N. A double-blind study in healthy volunteers to assess the effects of sleep on pregabalin compared with alprazolam and placebo. Sleep 2005; 28:187193.
  19. Pfizer Executive Summary. Lyrica (pregabalin) capsules c-v. July 2007. www.fda.gov/OHRMS/DOCKETS/ac/08/briefing/2008-4372b1-02-Pfizer.pdf. Accessed February 2, 2009.
  20. Arnold LM, Russell IJ, Diri EW, et al. A 14-week, randomized, double-blinded, placebo-controlled mono-therapy trial of pregabalin in patients with fibomyalgia. J Pain 2008; 9:792805.
  21. Duan WR, Florian H, Young JP, Martin S, Haig G, Barrett JA. Pregabalin monotherapy for management of fibromyalgia: analysis of two double-blind, randomized, placebo-controlled trials (poster presentation). American College of Rheumatology Annual Scientific Meeting, Boston, MA, November 6–7, 2007.
  22. Crofford LJ, Mease PJ, Simpson SL, et al. Fibromyalgia relapse evaluation and efficacy for durability of meaningful relief (FREEDOM): a 6-month, double-blind, placebo-controlled trial with pregabalin. Pain 2008; 136:419431.
  23. Kennedy M, Felson DT. A prospective long-term study of fibromyalgia syndrome. Arthritis Rheum 1996; 39:682685.
  24. Bengtsson A, Backman E. Long-term follow-up of fibro-myalgia patients [abstract]. Scand J Rheumatolology 1992; 21(suppl 94):9.
  25. Ledingham J, Doherty S, Doherty M. Primary fibromyalgia syndrome—an outcome study. Br J Rheumatol 1993; 32:139142.
  26. Henrikkson CM. Longterm effects of fibromyalgia on everyday life: a study of 56 patients. Scand J Rheumatol 1994; 23:3641.
  27. Fitzcharles MA, Costa DD, Pöyhiä R. A study of standard care in fibromyalgia syndrome: a favorable outcome. J Rheumatol 2003; 30:154159.
  28. Granges G, Zilko P, Littlejohn GO. Fibromyalgia syndrome: assessment of the severity of the condition 2 years after the diagnosis. J Rheumatol 1994; 21:523529.
  29. Goldenberg DL, Burckhardt C, Crofford L. Management of fibromyalgia syndrome. JAMA 2004; 292:23882395.
  30. Arnold LM, Keck PE, Welge JA. Antidepressant treatment of fibromyalgia: a meta-analysis and review. Psychosomatics 2000; 41:104113.
  31. O’Malley PG, Balden E, Tomkins G, Santoro J, Kroenke K, Jackson JL. Treatment of fibromyalgia with anti-depressants: a meta-analysis. J Gen Intern Med 2000; 15:659666.
  32. Arnold LM, Lu Y, Crofford LJ, et al. A double-blind, multicenter trial comparing duloxetine with placebo in the treatment of fibromyalgia patients with or without major depressive disorder. Arthritis Rheum 2004; 50:29742984.
  33. Russell IJ, Mease PJ, Smith TR, et al. Efficacy and safety of duloxetine for treatment of fibromyalgia in patients with or without major depressive disorder: Results from a 6-month, randomized, double-blind, placebo-controlled fixed-dose trial. Pain 2008; 136:432444.
  34. Clauw DJ, Mease P, Palmer RH, Gendreau RM, Wang Y. Milnacipran for the treatment of fibromyalgia in adults: a 15-week, multicenter, randomized, double-blind, placebo-controlled, multiple-dose clinical trial. Clin Ther 2008; 30:19882004.
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Cleveland Clinic Journal of Medicine - 76(4)
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Cleveland Clinic Journal of Medicine - 76(4)
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Pregabalin for fibromyalgia: Some relief but no cure
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Pregabalin for fibromyalgia: Some relief but no cure
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KEY POINTS

  • Several lines of evidence point to functional abnormalities in the central nervous system as being responsible for fibromyalgia.
  • Clinical trials found pregabalin superior to placebo. Nevertheless, patients need to have reasonable expectations of its possible benefit.
  • In most patients with fibromyalgia, a multidisciplinary approach is used to treat pain, sleep disturbance, and fatigue, along with comorbidities such as neurally mediated hypotension and psychiatric disorders.
  • Research with pregabalin enhances our understanding of fibromyalgia and may point the way to future treatments.
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Multiple huge bullae after renal transplant

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Multiple huge bullae after renal transplant

Figure 1.
A 56-year-old woman presents with multiple huge bullae and crusted erosions in her left sixth to eighth cervical and first thoracic dermatomes (Figure 1), accompanied by severe, sharp, lancinating pain. She underwent renal transplantation 3 months ago for end-stage diabetic kidney disease and is now taking immunosuppressants, including tacrolimus (Prograf) (trough serum level 8–10 ng/dL), mycophenolate mofetil (CellCept) 500 mg twice a day, and prednisolone 5 mg per day.

Q: What is the most likely diagnosis?

  • Contact dermatitis
  • Herpes zoster
  • Herpes simplex
  • Pemphigus
  • Bullous pemphigoid
  • Graft-vs-host disease

A: The correct answer is herpes zoster (shingles), which represents reactivation of varicella-zoster virus.

The diagnosis of herpes zoster is usually based solely on the clinical presentation. It is typically characterized in immunocompetent patients by a unilateral vesicular eruption with a well-defined dermatomal distribution. But occasionally, as in this patient on immunosuppressant drugs, it presents with atypical skin lesions such as multiple huge bullae involving multiple dermatomes.1,2

Patients treated with immunosuppressive agents after organ transplantation are at high risk of herpes zoster. A recent published retrospective study of adult kidney transplant recipients showed an average incidence of approximately 28 per 1,000 person-years.3

Treatment involves analgesics and sometimes antiviral drugs, and the decisions should take into account the patient’s age and immune status.1

Figure 2.
This patient was admitted to the hospital and was put in a private room. The lesions were protected from further breakdown and secondary bacterial infection. We discontinued mycophenolate mofetil and prescribed acyclovir (Zovirax) 250 mg intravenously every 8 hours (dose adjusted according to her renal function) for 7 days. Antibiotics needed to be given later for cellulitis that developed as a complication. She had no sign of ophthalmic involvement, visceral involvement, or other complication. She was discharged with healing skin after 42 days of hospitalization (Figure 2) and is free from postherpetic neuralgia.

References
  1. Nagel MA, Gilden DH. The protean neurologic manifestations of varicella-zoster virus infection. Cleve Clin J Med 2007; 74:489504.
  2. Albrecht MA. Clinical manifestations of varicella-zoster virus infection: Herpes zoster. InRose BD, editor: UpToDate. Waltham, MA: UpToDate, 2008.
  3. Arness T, Pedersen R, Dierkhising R, Kremers W, Patel R. Varicella zoster virus-associated disease in adult kidney transplant recipients: incidence and risk-factor analysis. Transpl Infect Dis 2008; 10:260268.
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Hung-Tien Kuo, MD
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Hung-Chun Chen, MD, PhD
Department of Internal Medicine, Kaohsiung Medical University Hospital and Faculty of Renal Care, Kaohsiung Medical University, Kaohsiung, Taiwan

Address: Hung-Chun Chen, MD, PhD, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, No.100, Tzyou 1st Road, Kaohsiung 807, Taiwan; e-mail [email protected]

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Hung-Chun Chen, MD, PhD
Department of Internal Medicine, Kaohsiung Medical University Hospital and Faculty of Renal Care, Kaohsiung Medical University, Kaohsiung, Taiwan

Address: Hung-Chun Chen, MD, PhD, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, No.100, Tzyou 1st Road, Kaohsiung 807, Taiwan; e-mail [email protected]

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Hung-Chun Chen, MD, PhD
Department of Internal Medicine, Kaohsiung Medical University Hospital and Faculty of Renal Care, Kaohsiung Medical University, Kaohsiung, Taiwan

Address: Hung-Chun Chen, MD, PhD, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, No.100, Tzyou 1st Road, Kaohsiung 807, Taiwan; e-mail [email protected]

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Figure 1.
A 56-year-old woman presents with multiple huge bullae and crusted erosions in her left sixth to eighth cervical and first thoracic dermatomes (Figure 1), accompanied by severe, sharp, lancinating pain. She underwent renal transplantation 3 months ago for end-stage diabetic kidney disease and is now taking immunosuppressants, including tacrolimus (Prograf) (trough serum level 8–10 ng/dL), mycophenolate mofetil (CellCept) 500 mg twice a day, and prednisolone 5 mg per day.

Q: What is the most likely diagnosis?

  • Contact dermatitis
  • Herpes zoster
  • Herpes simplex
  • Pemphigus
  • Bullous pemphigoid
  • Graft-vs-host disease

A: The correct answer is herpes zoster (shingles), which represents reactivation of varicella-zoster virus.

The diagnosis of herpes zoster is usually based solely on the clinical presentation. It is typically characterized in immunocompetent patients by a unilateral vesicular eruption with a well-defined dermatomal distribution. But occasionally, as in this patient on immunosuppressant drugs, it presents with atypical skin lesions such as multiple huge bullae involving multiple dermatomes.1,2

Patients treated with immunosuppressive agents after organ transplantation are at high risk of herpes zoster. A recent published retrospective study of adult kidney transplant recipients showed an average incidence of approximately 28 per 1,000 person-years.3

Treatment involves analgesics and sometimes antiviral drugs, and the decisions should take into account the patient’s age and immune status.1

Figure 2.
This patient was admitted to the hospital and was put in a private room. The lesions were protected from further breakdown and secondary bacterial infection. We discontinued mycophenolate mofetil and prescribed acyclovir (Zovirax) 250 mg intravenously every 8 hours (dose adjusted according to her renal function) for 7 days. Antibiotics needed to be given later for cellulitis that developed as a complication. She had no sign of ophthalmic involvement, visceral involvement, or other complication. She was discharged with healing skin after 42 days of hospitalization (Figure 2) and is free from postherpetic neuralgia.

Figure 1.
A 56-year-old woman presents with multiple huge bullae and crusted erosions in her left sixth to eighth cervical and first thoracic dermatomes (Figure 1), accompanied by severe, sharp, lancinating pain. She underwent renal transplantation 3 months ago for end-stage diabetic kidney disease and is now taking immunosuppressants, including tacrolimus (Prograf) (trough serum level 8–10 ng/dL), mycophenolate mofetil (CellCept) 500 mg twice a day, and prednisolone 5 mg per day.

Q: What is the most likely diagnosis?

  • Contact dermatitis
  • Herpes zoster
  • Herpes simplex
  • Pemphigus
  • Bullous pemphigoid
  • Graft-vs-host disease

A: The correct answer is herpes zoster (shingles), which represents reactivation of varicella-zoster virus.

The diagnosis of herpes zoster is usually based solely on the clinical presentation. It is typically characterized in immunocompetent patients by a unilateral vesicular eruption with a well-defined dermatomal distribution. But occasionally, as in this patient on immunosuppressant drugs, it presents with atypical skin lesions such as multiple huge bullae involving multiple dermatomes.1,2

Patients treated with immunosuppressive agents after organ transplantation are at high risk of herpes zoster. A recent published retrospective study of adult kidney transplant recipients showed an average incidence of approximately 28 per 1,000 person-years.3

Treatment involves analgesics and sometimes antiviral drugs, and the decisions should take into account the patient’s age and immune status.1

Figure 2.
This patient was admitted to the hospital and was put in a private room. The lesions were protected from further breakdown and secondary bacterial infection. We discontinued mycophenolate mofetil and prescribed acyclovir (Zovirax) 250 mg intravenously every 8 hours (dose adjusted according to her renal function) for 7 days. Antibiotics needed to be given later for cellulitis that developed as a complication. She had no sign of ophthalmic involvement, visceral involvement, or other complication. She was discharged with healing skin after 42 days of hospitalization (Figure 2) and is free from postherpetic neuralgia.

References
  1. Nagel MA, Gilden DH. The protean neurologic manifestations of varicella-zoster virus infection. Cleve Clin J Med 2007; 74:489504.
  2. Albrecht MA. Clinical manifestations of varicella-zoster virus infection: Herpes zoster. InRose BD, editor: UpToDate. Waltham, MA: UpToDate, 2008.
  3. Arness T, Pedersen R, Dierkhising R, Kremers W, Patel R. Varicella zoster virus-associated disease in adult kidney transplant recipients: incidence and risk-factor analysis. Transpl Infect Dis 2008; 10:260268.
References
  1. Nagel MA, Gilden DH. The protean neurologic manifestations of varicella-zoster virus infection. Cleve Clin J Med 2007; 74:489504.
  2. Albrecht MA. Clinical manifestations of varicella-zoster virus infection: Herpes zoster. InRose BD, editor: UpToDate. Waltham, MA: UpToDate, 2008.
  3. Arness T, Pedersen R, Dierkhising R, Kremers W, Patel R. Varicella zoster virus-associated disease in adult kidney transplant recipients: incidence and risk-factor analysis. Transpl Infect Dis 2008; 10:260268.
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Abstract

Background To reduce unintended pregnancy, it is necessary to understand why women have unprotected intercourse when they do not desire pregnancy.

Methods We devised a survey of 42 potential reasons why women have unprotected intercourse based on the responses of a focus group we had previously convened. We administered the survey to women between the ages of 18 and 39 years who were visiting primary care clinics and were not trying to get pregnant.

Results Of the 151 respondents, 84 (56%) were having unprotected intercourse. Women gave an average of 9 reasons for having unprotected intercourse. The most common reasons fell into 3 categories: lack of thought/preparation (87% of respondents), being in a long-term or strong relationship (70%), and concerns about side effects of contraception (80%). Eighty-three of the 84 women (99%) chose at least 1 of these categories.

Conclusion Basing survey questions on focus group responses provided important insights into the reasons women risk unintended pregnancy. A deeper understanding of this issue is critical to reducing unintended pregnancy.

What are the reasons women ordinarily give for unintended pregnancy? The results of our study show that some of the more common ones are not included on standard risk-assessment surveys. If we hope to offer patients a meaningful course of intervention, it would help to understand the issues these women contend with.

Despite the availability of effective contraception, many women have unprotected intercourse that puts them at risk for unintended pregnancy. Among women in the United States who are age 18 or older, slightly more than 40% of live births result from unintended conception.1 The reasons women have unprotected intercourse have not been clear. Of the few studies that have addressed this issue,2 some have restricted their investigation to a few potential reasons2-4 or have limited exploration to the reasons associated with a single episode of intercourse.5 The latter type of investigation is too narrow. A more comprehensive approach is needed because risk-taking is likely to be a complex phenomenon, with reasons changing as the context changes or as women try different forms of contraception.

We conducted focus groups with women who were risking unintended pregnancy.6 With results from the focus groups, we developed a survey to determine the relative prevalence of reasons given, and thereby direct future interventions at those that are most common.

Methods

We recruited participants from local primary care clinics serving financially disadvantaged populations. Flyers describing the study were posted, and interested women approached a research assistant stationed in the clinic. We explained the survey and reviewed eligibility criteria with those who inquired. Women who wished to participate gave verbal consent and were taken to a private area, where a research assistant administered the survey. The study was approved by the local institutional review board. We waived written consent because the survey was anonymous and we collected no identifiers.

 

Eligibility required that a woman be between the ages of 18 and 39 years, unmarried, and not be pregnant or trying to get pregnant. Women who reported having had a hysterectomy or tubal ligation or being menopausal were ineligible. We defined unprotected intercourse as vaginal intercourse with a fertile male without using a condom, hormonal method, diaphragm, intrauterine device (IUD), vaginal ring, Lea’s shield (a vaginal barrier contraceptive), emergency contraception, vaginal sponge, or cervical cap. These eligibility requirements were identical to those of the focus groups that had provided input for our survey questions.

Women who reported having unprotected sex in the past year were asked to choose from 42 possible reasons (foils) adapted from responses offered in the focus groups.6 When possible, we used the exact words uttered by focus group participants (eg, “I just went with the flow”). We asked women to select all the reasons that applied to them over the past year. The survey also included questions about previous pregnancies, use of home pregnancy test kits, and medical conditions that could affect an unintended pregnancy or fetus (preconceptual health status).

Analysis

We performed univariate analysis using the chi square test in the Statistical Analysis System package (SAS version 8.0, SAS Institute, Inc., Cary, NC). Age was evaluated as a dichotomous variable compared to the median.

Results

Demographics and health

The 151 respondents had a median age of 24 years, and a median household income of <$20,000 per year. Eighty-four women (56%) had unprotected intercourse in the past year. Of the 151 respondents, 56% were white and 41% were black. Twenty-two percent had not graduated from high school. Ten percent had recently been homeless, 9% had recently been jailed, 7% had a recent sexually transmitted disease, and 4% had traded sex for gain.

 

 

Median body mass index was 26. Fifty-one percent were smokers, 19% were binge drinkers, 11% had hypertension, and 5% had diabetes. Ninety-four (62%) of the respondents had at least 1 previous pregnancy (average of 2 live births), and 39% of them had used a home pregnancy test kit to diagnose their last pregnancy.

Reasons for unprotected intercourse

Of the 84 women who reported having unprotected intercourse in the past year, 1 woman selected all 42 of the reasons on the survey, with a single exception (“I don’t know where to get birth control/contraception”). On average, the women selected 9 reasons each. The most common reasons for having unprotected intercourse appear in the TABLE.

Lack of concern. Seventy-three women (87%) cited at least 1 of the following reasons: “just not thinking about birth control,” “not planning to have sex,” getting caught up in the “heat of the moment,” or “just went with the flow.” We categorized these reasons as lack of thought/preparation.6

Beliefs about relationship. Fifty-nine women (70%) cited relationship-related reasons: their partner would “be there” for them if they did get pregnant, or they were “in a long-term relationship and it was too much of a hassle to keep using birth control/condoms.”

Unacceptable side effects. Sixty-seven women (80%) cited method-related side effects, including weight gain, discomfort with condoms, and reduced pleasure. Of note, the most commonly cited reason was that condoms gave the woman discomfort.

Categories not mutually exclusive. These 3 categories—lack of thought/preparation, relationship-related reasons, and side effects—overlapped significantly, with 72 women (86%) choosing more than 1 of these categories, and 44 (52%) choosing all 3. Eighty-three of the 84 women (99%) chose at least 1 of these categories.

As stated, 55 women (65%) believed their partner would “be there” for them, and 43 of these had a previous pregnancy. Of the 43, 58% said their partner actually “was there” for them during the last pregnancy. The remainder had not had partner support during the last pregnancy, but believed their current partner would support them in the event of a future pregnancy.

 

Additional volunteered reasons. Beyond the reasons given in the TABLE, 23% said they forgot to take their pill, and 20% said they would not really mind that much if they got pregnant.

Between 10% and 18% of women cited each of the following reasons: judgment clouded by alcohol or drugs, thinking they could always get an abortion if they conceived, not wanting to ask their partner to use a condom, being scared of needles, being worried about vaginal bleeding, having a medical condition (smoking, obesity, etc.) that limited their choice of contraception, having a partner who objected to her using contraception, or feeling that contraception was unnatural.

Less than 10% of women cited the following reasons: problems with transportation to get to clinic, insurance that did not cover contraception or a preferred method of contraception, not liking the clinic or clinic personnel, inability to understand explanations by clinic personnel, cost, forced sex, a preference for rhythm method, feeling that a method was messy, family/friends being against her using contraception, religious objections, being embarrassed to buy contraception, or being unsure how to use contraception.

Few age or race differences. There was little difference in response between races, with the exception of being uncomfortable asking a partner to use condoms, which was noted by 23% of blacks and 2% of whites (P=.006). There were no significant differences by age.

Among the women who had unprotected intercourse, 79 (94%) had used some form of birth control at least once during the past year. Of these, 90% had used condoms, 34% had taken the Pill, 22% had used medroxyprogesterone acetate injectable suspension (Depo Provera), and 20% had used the norelgestromin/ethinyl estradiol transdermal system (Ortho Evra/“the patch”). Eighteen percent had used emergency contraception in the past year.

TABLE
Reasons women most commonly cited for unprotected intercourse

 

REASONPERCENT (N=84)
“Heat of the moment”/“just went with the flow”70%
Partner would “be there” if pregnancy occurred65%
Not planning to have sex54%
Not thinking about using birth control at the time52%
Condoms are uncomfortable for woman49%
Weight gain with hormonal methods43%
Partner does not like condoms43%
Ran out of birth control method37%
In a long-term relationship and it was too much of a hassle to keep using contraception37%
Thought pregnancy was unlikely to occur36%
Contraception reduces pleasure36%
Forgot to use birth control method32%
Prefer to use withdrawal30%

Discussion

The most common reasons for having unprotected intercourse reflected lack of thought/preparation, relationship issues, and concerns about side effects. Most women expressed reasons from more than 1 of these categories, suggesting they are interrelated.7

 

 

 

Preparation issues. Most women used contraception inconsistently rather than not at all. At times they were motivated to use contraception; at times they were not.

Relationship issues. Women in our study cited several relationship-related reasons that might explain inconsistent use of contraception. Many women felt that regular contraception became a “hassle” in long-term relationships. This is supported by studies showing that condoms may be reserved for partners who are considered at risk for disease, or that condom use may be thought to imply a lack of trust antithetical to a long-term relationship.8 Others believed their partner would “be there” for them if a pregnancy occurred and gave this as a reason for having unprotected intercourse. Regarding this belief, past experience to the contrary did not appear to dampen optimism about the future.

Side effect issues. Interestingly, the most commonly cited method-related side effect was that male condoms made the woman uncomfortable during intercourse. They cited discomfort for the man less frequently. Female discomfort has also been identified as a reason college women avoid condom use.9 Others have shown that women have difficulties with condom lubrication,10 although it is less of an issue for men.11 This suggests that education about condoms should include informing women about lubrication options. However, education alone may not resolve this issue, and it is important to inform women about alternative contraceptive choices.

Our extensive list of reasons facilitated responses. On average, each woman identified 9 reasons why she had unprotected intercourse. This was likely a result of the large number of foils presented in the survey, which allowed women to give a fuller picture of their reasons than a more limited number of choices might allow.

For example, the Pregnancy Risk Assessment Monitoring System (PRAMS) survey offers just 6 foils, and they do not include the common thought/preparation and relationship issues. Broad surveys like PRAMS are necessarily concise about single issues. Free-text responses to the PRAMS survey show that respondents endorse reasons not reflected in the few foils.4

Moreover, we used the exact phrasing given by focus group participants whenever possible, which could increase selection of appropriate foils. This is why we included reasons such as wanting to “go with the flow.” We also included reasons that were cited by the focus groups, but which have rarely been included in surveys, such as condoms creating discomfort for women.

Implications of our findings. Slightly more than half of the women in the study were having unprotected intercourse and were at risk for unintended pregnancy. Although “unintendedness” is a concept that may not be widely recognized by individual women,7 it is a useful epidemiological construct that serves as a marker for adverse outcomes, such as low birth weight or premature labor.12 In our study, women at risk for unintended pregnancy had a variety of medical conditions and health behaviors that could affect a pregnancy. Moreover, slightly more than one-third of participants thought they were unlikely to get pregnant despite having unprotected intercourse. This argues for improved preconceptional care in this population.13 Education may improve understanding of fertility, contraceptive options, risk reduction strategies, and communication techniques.

 

Limitations. The study is subject to several limitations. All responses were self-reported and subject to recall bias. The population was a convenience sample of financially disadvantaged women visiting outpatient clinics, and is not representative of other populations. Women attending a clinic might reasonably be expected to have access to health care and contraception, which might not be true of other populations. Thus, few women in our study cited cost or access to care as a reason for having unprotected intercourse.

Funding

This study was funded in part by the Michigan Department of Community Health.

Correspondence
Mary D. Nettleman, MD, MS, B 427 Clinical Center, East Lansing, MI 48824; [email protected]

References

 

1. Ahluwalia IB, Whitehead N, Bensyl D. Pregnancy intention and contraceptive use among adult women. Matern Child Health J. 2007;11:347-351.

2. Ayoola A, Brewer J, Nettleman M. Reasons why women have unprotected sex: a review. J Womens Health. 2007;16:302-310.

3. Project Choices Epidemiologic Survey Group. Alcohol-exposed pregnancy: Characteristics associated with risk. Am J Prev Med. 2002;23:166-173.

4. Nettleman MD, Chung H, Brewer J, et al. Reasons for unprotected intercourse: analysis of the PRAMS survey. Contraception. 2007;75:361-366.

5. Centers for Disease Control and Prevention. Monitoring progress toward achieving Maternal and Infant Healthy People 2010 objectives—19 states, Pregnancy Risk Assessment Monitoring System (PRAMS), 2000-2003. MMWR Surveill Summ. 2006;55:1-11.

6. Nettleman M, Brewer J, Ayoola A. Reasons for unprotected intercourse in adult women: a qualitative study. J Midwifery Womens Health. 2007;52:148-152.

7. Santelli J, Rochat R, Hatfield-Timajchy K, et al. Unintended Pregnancy Working Group. The measurement and meaning of unintended pregnancy. Perspect Sex Reprod Health. 2003;35:94-101.

8. Marston C, King E. Factors that shape young people’s sexual behaviour: a systematic review. Lancet. 2000;368:1581-1586.

9. Crosby R, Yarber WL, Sanders SA, et al. Condom discomfort and associated problems with their use among university students. J Am Coll Health. 2005;54:143-147.

10. Sanders SA, Graham CA, Yarber WL, et al. Condom use errors and problems among young women who put condoms on their male partners. J Am Med Womens Assoc. 2003;58:95-98.

11. Crosby RA, Sanders SA, Yarber WL, et al. Condom use errors and problems among college men. Sex Transm Dis. 2002;29:552-557.

12. Centers for Disease Control and prevention. Recommendations to improve preconception health and health care—United States: a report of the CDC/ATSDR Preconception Care Work Group and the Select Panel on Preconception Care. MMWR. 2006;55(RR- 6):1-15.

13. Kost K, Landry DJ, Darroch JE. The effects of pregnancy planning status on birth outcomes and infant care. Fam Plann Perspect. 1998;30:223.

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Adejoke Ayoola, RN, PhD
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Abstract

Background To reduce unintended pregnancy, it is necessary to understand why women have unprotected intercourse when they do not desire pregnancy.

Methods We devised a survey of 42 potential reasons why women have unprotected intercourse based on the responses of a focus group we had previously convened. We administered the survey to women between the ages of 18 and 39 years who were visiting primary care clinics and were not trying to get pregnant.

Results Of the 151 respondents, 84 (56%) were having unprotected intercourse. Women gave an average of 9 reasons for having unprotected intercourse. The most common reasons fell into 3 categories: lack of thought/preparation (87% of respondents), being in a long-term or strong relationship (70%), and concerns about side effects of contraception (80%). Eighty-three of the 84 women (99%) chose at least 1 of these categories.

Conclusion Basing survey questions on focus group responses provided important insights into the reasons women risk unintended pregnancy. A deeper understanding of this issue is critical to reducing unintended pregnancy.

What are the reasons women ordinarily give for unintended pregnancy? The results of our study show that some of the more common ones are not included on standard risk-assessment surveys. If we hope to offer patients a meaningful course of intervention, it would help to understand the issues these women contend with.

Despite the availability of effective contraception, many women have unprotected intercourse that puts them at risk for unintended pregnancy. Among women in the United States who are age 18 or older, slightly more than 40% of live births result from unintended conception.1 The reasons women have unprotected intercourse have not been clear. Of the few studies that have addressed this issue,2 some have restricted their investigation to a few potential reasons2-4 or have limited exploration to the reasons associated with a single episode of intercourse.5 The latter type of investigation is too narrow. A more comprehensive approach is needed because risk-taking is likely to be a complex phenomenon, with reasons changing as the context changes or as women try different forms of contraception.

We conducted focus groups with women who were risking unintended pregnancy.6 With results from the focus groups, we developed a survey to determine the relative prevalence of reasons given, and thereby direct future interventions at those that are most common.

Methods

We recruited participants from local primary care clinics serving financially disadvantaged populations. Flyers describing the study were posted, and interested women approached a research assistant stationed in the clinic. We explained the survey and reviewed eligibility criteria with those who inquired. Women who wished to participate gave verbal consent and were taken to a private area, where a research assistant administered the survey. The study was approved by the local institutional review board. We waived written consent because the survey was anonymous and we collected no identifiers.

 

Eligibility required that a woman be between the ages of 18 and 39 years, unmarried, and not be pregnant or trying to get pregnant. Women who reported having had a hysterectomy or tubal ligation or being menopausal were ineligible. We defined unprotected intercourse as vaginal intercourse with a fertile male without using a condom, hormonal method, diaphragm, intrauterine device (IUD), vaginal ring, Lea’s shield (a vaginal barrier contraceptive), emergency contraception, vaginal sponge, or cervical cap. These eligibility requirements were identical to those of the focus groups that had provided input for our survey questions.

Women who reported having unprotected sex in the past year were asked to choose from 42 possible reasons (foils) adapted from responses offered in the focus groups.6 When possible, we used the exact words uttered by focus group participants (eg, “I just went with the flow”). We asked women to select all the reasons that applied to them over the past year. The survey also included questions about previous pregnancies, use of home pregnancy test kits, and medical conditions that could affect an unintended pregnancy or fetus (preconceptual health status).

Analysis

We performed univariate analysis using the chi square test in the Statistical Analysis System package (SAS version 8.0, SAS Institute, Inc., Cary, NC). Age was evaluated as a dichotomous variable compared to the median.

Results

Demographics and health

The 151 respondents had a median age of 24 years, and a median household income of <$20,000 per year. Eighty-four women (56%) had unprotected intercourse in the past year. Of the 151 respondents, 56% were white and 41% were black. Twenty-two percent had not graduated from high school. Ten percent had recently been homeless, 9% had recently been jailed, 7% had a recent sexually transmitted disease, and 4% had traded sex for gain.

 

 

Median body mass index was 26. Fifty-one percent were smokers, 19% were binge drinkers, 11% had hypertension, and 5% had diabetes. Ninety-four (62%) of the respondents had at least 1 previous pregnancy (average of 2 live births), and 39% of them had used a home pregnancy test kit to diagnose their last pregnancy.

Reasons for unprotected intercourse

Of the 84 women who reported having unprotected intercourse in the past year, 1 woman selected all 42 of the reasons on the survey, with a single exception (“I don’t know where to get birth control/contraception”). On average, the women selected 9 reasons each. The most common reasons for having unprotected intercourse appear in the TABLE.

Lack of concern. Seventy-three women (87%) cited at least 1 of the following reasons: “just not thinking about birth control,” “not planning to have sex,” getting caught up in the “heat of the moment,” or “just went with the flow.” We categorized these reasons as lack of thought/preparation.6

Beliefs about relationship. Fifty-nine women (70%) cited relationship-related reasons: their partner would “be there” for them if they did get pregnant, or they were “in a long-term relationship and it was too much of a hassle to keep using birth control/condoms.”

Unacceptable side effects. Sixty-seven women (80%) cited method-related side effects, including weight gain, discomfort with condoms, and reduced pleasure. Of note, the most commonly cited reason was that condoms gave the woman discomfort.

Categories not mutually exclusive. These 3 categories—lack of thought/preparation, relationship-related reasons, and side effects—overlapped significantly, with 72 women (86%) choosing more than 1 of these categories, and 44 (52%) choosing all 3. Eighty-three of the 84 women (99%) chose at least 1 of these categories.

As stated, 55 women (65%) believed their partner would “be there” for them, and 43 of these had a previous pregnancy. Of the 43, 58% said their partner actually “was there” for them during the last pregnancy. The remainder had not had partner support during the last pregnancy, but believed their current partner would support them in the event of a future pregnancy.

 

Additional volunteered reasons. Beyond the reasons given in the TABLE, 23% said they forgot to take their pill, and 20% said they would not really mind that much if they got pregnant.

Between 10% and 18% of women cited each of the following reasons: judgment clouded by alcohol or drugs, thinking they could always get an abortion if they conceived, not wanting to ask their partner to use a condom, being scared of needles, being worried about vaginal bleeding, having a medical condition (smoking, obesity, etc.) that limited their choice of contraception, having a partner who objected to her using contraception, or feeling that contraception was unnatural.

Less than 10% of women cited the following reasons: problems with transportation to get to clinic, insurance that did not cover contraception or a preferred method of contraception, not liking the clinic or clinic personnel, inability to understand explanations by clinic personnel, cost, forced sex, a preference for rhythm method, feeling that a method was messy, family/friends being against her using contraception, religious objections, being embarrassed to buy contraception, or being unsure how to use contraception.

Few age or race differences. There was little difference in response between races, with the exception of being uncomfortable asking a partner to use condoms, which was noted by 23% of blacks and 2% of whites (P=.006). There were no significant differences by age.

Among the women who had unprotected intercourse, 79 (94%) had used some form of birth control at least once during the past year. Of these, 90% had used condoms, 34% had taken the Pill, 22% had used medroxyprogesterone acetate injectable suspension (Depo Provera), and 20% had used the norelgestromin/ethinyl estradiol transdermal system (Ortho Evra/“the patch”). Eighteen percent had used emergency contraception in the past year.

TABLE
Reasons women most commonly cited for unprotected intercourse

 

REASONPERCENT (N=84)
“Heat of the moment”/“just went with the flow”70%
Partner would “be there” if pregnancy occurred65%
Not planning to have sex54%
Not thinking about using birth control at the time52%
Condoms are uncomfortable for woman49%
Weight gain with hormonal methods43%
Partner does not like condoms43%
Ran out of birth control method37%
In a long-term relationship and it was too much of a hassle to keep using contraception37%
Thought pregnancy was unlikely to occur36%
Contraception reduces pleasure36%
Forgot to use birth control method32%
Prefer to use withdrawal30%

Discussion

The most common reasons for having unprotected intercourse reflected lack of thought/preparation, relationship issues, and concerns about side effects. Most women expressed reasons from more than 1 of these categories, suggesting they are interrelated.7

 

 

 

Preparation issues. Most women used contraception inconsistently rather than not at all. At times they were motivated to use contraception; at times they were not.

Relationship issues. Women in our study cited several relationship-related reasons that might explain inconsistent use of contraception. Many women felt that regular contraception became a “hassle” in long-term relationships. This is supported by studies showing that condoms may be reserved for partners who are considered at risk for disease, or that condom use may be thought to imply a lack of trust antithetical to a long-term relationship.8 Others believed their partner would “be there” for them if a pregnancy occurred and gave this as a reason for having unprotected intercourse. Regarding this belief, past experience to the contrary did not appear to dampen optimism about the future.

Side effect issues. Interestingly, the most commonly cited method-related side effect was that male condoms made the woman uncomfortable during intercourse. They cited discomfort for the man less frequently. Female discomfort has also been identified as a reason college women avoid condom use.9 Others have shown that women have difficulties with condom lubrication,10 although it is less of an issue for men.11 This suggests that education about condoms should include informing women about lubrication options. However, education alone may not resolve this issue, and it is important to inform women about alternative contraceptive choices.

Our extensive list of reasons facilitated responses. On average, each woman identified 9 reasons why she had unprotected intercourse. This was likely a result of the large number of foils presented in the survey, which allowed women to give a fuller picture of their reasons than a more limited number of choices might allow.

For example, the Pregnancy Risk Assessment Monitoring System (PRAMS) survey offers just 6 foils, and they do not include the common thought/preparation and relationship issues. Broad surveys like PRAMS are necessarily concise about single issues. Free-text responses to the PRAMS survey show that respondents endorse reasons not reflected in the few foils.4

Moreover, we used the exact phrasing given by focus group participants whenever possible, which could increase selection of appropriate foils. This is why we included reasons such as wanting to “go with the flow.” We also included reasons that were cited by the focus groups, but which have rarely been included in surveys, such as condoms creating discomfort for women.

Implications of our findings. Slightly more than half of the women in the study were having unprotected intercourse and were at risk for unintended pregnancy. Although “unintendedness” is a concept that may not be widely recognized by individual women,7 it is a useful epidemiological construct that serves as a marker for adverse outcomes, such as low birth weight or premature labor.12 In our study, women at risk for unintended pregnancy had a variety of medical conditions and health behaviors that could affect a pregnancy. Moreover, slightly more than one-third of participants thought they were unlikely to get pregnant despite having unprotected intercourse. This argues for improved preconceptional care in this population.13 Education may improve understanding of fertility, contraceptive options, risk reduction strategies, and communication techniques.

 

Limitations. The study is subject to several limitations. All responses were self-reported and subject to recall bias. The population was a convenience sample of financially disadvantaged women visiting outpatient clinics, and is not representative of other populations. Women attending a clinic might reasonably be expected to have access to health care and contraception, which might not be true of other populations. Thus, few women in our study cited cost or access to care as a reason for having unprotected intercourse.

Funding

This study was funded in part by the Michigan Department of Community Health.

Correspondence
Mary D. Nettleman, MD, MS, B 427 Clinical Center, East Lansing, MI 48824; [email protected]

 

Abstract

Background To reduce unintended pregnancy, it is necessary to understand why women have unprotected intercourse when they do not desire pregnancy.

Methods We devised a survey of 42 potential reasons why women have unprotected intercourse based on the responses of a focus group we had previously convened. We administered the survey to women between the ages of 18 and 39 years who were visiting primary care clinics and were not trying to get pregnant.

Results Of the 151 respondents, 84 (56%) were having unprotected intercourse. Women gave an average of 9 reasons for having unprotected intercourse. The most common reasons fell into 3 categories: lack of thought/preparation (87% of respondents), being in a long-term or strong relationship (70%), and concerns about side effects of contraception (80%). Eighty-three of the 84 women (99%) chose at least 1 of these categories.

Conclusion Basing survey questions on focus group responses provided important insights into the reasons women risk unintended pregnancy. A deeper understanding of this issue is critical to reducing unintended pregnancy.

What are the reasons women ordinarily give for unintended pregnancy? The results of our study show that some of the more common ones are not included on standard risk-assessment surveys. If we hope to offer patients a meaningful course of intervention, it would help to understand the issues these women contend with.

Despite the availability of effective contraception, many women have unprotected intercourse that puts them at risk for unintended pregnancy. Among women in the United States who are age 18 or older, slightly more than 40% of live births result from unintended conception.1 The reasons women have unprotected intercourse have not been clear. Of the few studies that have addressed this issue,2 some have restricted their investigation to a few potential reasons2-4 or have limited exploration to the reasons associated with a single episode of intercourse.5 The latter type of investigation is too narrow. A more comprehensive approach is needed because risk-taking is likely to be a complex phenomenon, with reasons changing as the context changes or as women try different forms of contraception.

We conducted focus groups with women who were risking unintended pregnancy.6 With results from the focus groups, we developed a survey to determine the relative prevalence of reasons given, and thereby direct future interventions at those that are most common.

Methods

We recruited participants from local primary care clinics serving financially disadvantaged populations. Flyers describing the study were posted, and interested women approached a research assistant stationed in the clinic. We explained the survey and reviewed eligibility criteria with those who inquired. Women who wished to participate gave verbal consent and were taken to a private area, where a research assistant administered the survey. The study was approved by the local institutional review board. We waived written consent because the survey was anonymous and we collected no identifiers.

 

Eligibility required that a woman be between the ages of 18 and 39 years, unmarried, and not be pregnant or trying to get pregnant. Women who reported having had a hysterectomy or tubal ligation or being menopausal were ineligible. We defined unprotected intercourse as vaginal intercourse with a fertile male without using a condom, hormonal method, diaphragm, intrauterine device (IUD), vaginal ring, Lea’s shield (a vaginal barrier contraceptive), emergency contraception, vaginal sponge, or cervical cap. These eligibility requirements were identical to those of the focus groups that had provided input for our survey questions.

Women who reported having unprotected sex in the past year were asked to choose from 42 possible reasons (foils) adapted from responses offered in the focus groups.6 When possible, we used the exact words uttered by focus group participants (eg, “I just went with the flow”). We asked women to select all the reasons that applied to them over the past year. The survey also included questions about previous pregnancies, use of home pregnancy test kits, and medical conditions that could affect an unintended pregnancy or fetus (preconceptual health status).

Analysis

We performed univariate analysis using the chi square test in the Statistical Analysis System package (SAS version 8.0, SAS Institute, Inc., Cary, NC). Age was evaluated as a dichotomous variable compared to the median.

Results

Demographics and health

The 151 respondents had a median age of 24 years, and a median household income of <$20,000 per year. Eighty-four women (56%) had unprotected intercourse in the past year. Of the 151 respondents, 56% were white and 41% were black. Twenty-two percent had not graduated from high school. Ten percent had recently been homeless, 9% had recently been jailed, 7% had a recent sexually transmitted disease, and 4% had traded sex for gain.

 

 

Median body mass index was 26. Fifty-one percent were smokers, 19% were binge drinkers, 11% had hypertension, and 5% had diabetes. Ninety-four (62%) of the respondents had at least 1 previous pregnancy (average of 2 live births), and 39% of them had used a home pregnancy test kit to diagnose their last pregnancy.

Reasons for unprotected intercourse

Of the 84 women who reported having unprotected intercourse in the past year, 1 woman selected all 42 of the reasons on the survey, with a single exception (“I don’t know where to get birth control/contraception”). On average, the women selected 9 reasons each. The most common reasons for having unprotected intercourse appear in the TABLE.

Lack of concern. Seventy-three women (87%) cited at least 1 of the following reasons: “just not thinking about birth control,” “not planning to have sex,” getting caught up in the “heat of the moment,” or “just went with the flow.” We categorized these reasons as lack of thought/preparation.6

Beliefs about relationship. Fifty-nine women (70%) cited relationship-related reasons: their partner would “be there” for them if they did get pregnant, or they were “in a long-term relationship and it was too much of a hassle to keep using birth control/condoms.”

Unacceptable side effects. Sixty-seven women (80%) cited method-related side effects, including weight gain, discomfort with condoms, and reduced pleasure. Of note, the most commonly cited reason was that condoms gave the woman discomfort.

Categories not mutually exclusive. These 3 categories—lack of thought/preparation, relationship-related reasons, and side effects—overlapped significantly, with 72 women (86%) choosing more than 1 of these categories, and 44 (52%) choosing all 3. Eighty-three of the 84 women (99%) chose at least 1 of these categories.

As stated, 55 women (65%) believed their partner would “be there” for them, and 43 of these had a previous pregnancy. Of the 43, 58% said their partner actually “was there” for them during the last pregnancy. The remainder had not had partner support during the last pregnancy, but believed their current partner would support them in the event of a future pregnancy.

 

Additional volunteered reasons. Beyond the reasons given in the TABLE, 23% said they forgot to take their pill, and 20% said they would not really mind that much if they got pregnant.

Between 10% and 18% of women cited each of the following reasons: judgment clouded by alcohol or drugs, thinking they could always get an abortion if they conceived, not wanting to ask their partner to use a condom, being scared of needles, being worried about vaginal bleeding, having a medical condition (smoking, obesity, etc.) that limited their choice of contraception, having a partner who objected to her using contraception, or feeling that contraception was unnatural.

Less than 10% of women cited the following reasons: problems with transportation to get to clinic, insurance that did not cover contraception or a preferred method of contraception, not liking the clinic or clinic personnel, inability to understand explanations by clinic personnel, cost, forced sex, a preference for rhythm method, feeling that a method was messy, family/friends being against her using contraception, religious objections, being embarrassed to buy contraception, or being unsure how to use contraception.

Few age or race differences. There was little difference in response between races, with the exception of being uncomfortable asking a partner to use condoms, which was noted by 23% of blacks and 2% of whites (P=.006). There were no significant differences by age.

Among the women who had unprotected intercourse, 79 (94%) had used some form of birth control at least once during the past year. Of these, 90% had used condoms, 34% had taken the Pill, 22% had used medroxyprogesterone acetate injectable suspension (Depo Provera), and 20% had used the norelgestromin/ethinyl estradiol transdermal system (Ortho Evra/“the patch”). Eighteen percent had used emergency contraception in the past year.

TABLE
Reasons women most commonly cited for unprotected intercourse

 

REASONPERCENT (N=84)
“Heat of the moment”/“just went with the flow”70%
Partner would “be there” if pregnancy occurred65%
Not planning to have sex54%
Not thinking about using birth control at the time52%
Condoms are uncomfortable for woman49%
Weight gain with hormonal methods43%
Partner does not like condoms43%
Ran out of birth control method37%
In a long-term relationship and it was too much of a hassle to keep using contraception37%
Thought pregnancy was unlikely to occur36%
Contraception reduces pleasure36%
Forgot to use birth control method32%
Prefer to use withdrawal30%

Discussion

The most common reasons for having unprotected intercourse reflected lack of thought/preparation, relationship issues, and concerns about side effects. Most women expressed reasons from more than 1 of these categories, suggesting they are interrelated.7

 

 

 

Preparation issues. Most women used contraception inconsistently rather than not at all. At times they were motivated to use contraception; at times they were not.

Relationship issues. Women in our study cited several relationship-related reasons that might explain inconsistent use of contraception. Many women felt that regular contraception became a “hassle” in long-term relationships. This is supported by studies showing that condoms may be reserved for partners who are considered at risk for disease, or that condom use may be thought to imply a lack of trust antithetical to a long-term relationship.8 Others believed their partner would “be there” for them if a pregnancy occurred and gave this as a reason for having unprotected intercourse. Regarding this belief, past experience to the contrary did not appear to dampen optimism about the future.

Side effect issues. Interestingly, the most commonly cited method-related side effect was that male condoms made the woman uncomfortable during intercourse. They cited discomfort for the man less frequently. Female discomfort has also been identified as a reason college women avoid condom use.9 Others have shown that women have difficulties with condom lubrication,10 although it is less of an issue for men.11 This suggests that education about condoms should include informing women about lubrication options. However, education alone may not resolve this issue, and it is important to inform women about alternative contraceptive choices.

Our extensive list of reasons facilitated responses. On average, each woman identified 9 reasons why she had unprotected intercourse. This was likely a result of the large number of foils presented in the survey, which allowed women to give a fuller picture of their reasons than a more limited number of choices might allow.

For example, the Pregnancy Risk Assessment Monitoring System (PRAMS) survey offers just 6 foils, and they do not include the common thought/preparation and relationship issues. Broad surveys like PRAMS are necessarily concise about single issues. Free-text responses to the PRAMS survey show that respondents endorse reasons not reflected in the few foils.4

Moreover, we used the exact phrasing given by focus group participants whenever possible, which could increase selection of appropriate foils. This is why we included reasons such as wanting to “go with the flow.” We also included reasons that were cited by the focus groups, but which have rarely been included in surveys, such as condoms creating discomfort for women.

Implications of our findings. Slightly more than half of the women in the study were having unprotected intercourse and were at risk for unintended pregnancy. Although “unintendedness” is a concept that may not be widely recognized by individual women,7 it is a useful epidemiological construct that serves as a marker for adverse outcomes, such as low birth weight or premature labor.12 In our study, women at risk for unintended pregnancy had a variety of medical conditions and health behaviors that could affect a pregnancy. Moreover, slightly more than one-third of participants thought they were unlikely to get pregnant despite having unprotected intercourse. This argues for improved preconceptional care in this population.13 Education may improve understanding of fertility, contraceptive options, risk reduction strategies, and communication techniques.

 

Limitations. The study is subject to several limitations. All responses were self-reported and subject to recall bias. The population was a convenience sample of financially disadvantaged women visiting outpatient clinics, and is not representative of other populations. Women attending a clinic might reasonably be expected to have access to health care and contraception, which might not be true of other populations. Thus, few women in our study cited cost or access to care as a reason for having unprotected intercourse.

Funding

This study was funded in part by the Michigan Department of Community Health.

Correspondence
Mary D. Nettleman, MD, MS, B 427 Clinical Center, East Lansing, MI 48824; [email protected]

References

 

1. Ahluwalia IB, Whitehead N, Bensyl D. Pregnancy intention and contraceptive use among adult women. Matern Child Health J. 2007;11:347-351.

2. Ayoola A, Brewer J, Nettleman M. Reasons why women have unprotected sex: a review. J Womens Health. 2007;16:302-310.

3. Project Choices Epidemiologic Survey Group. Alcohol-exposed pregnancy: Characteristics associated with risk. Am J Prev Med. 2002;23:166-173.

4. Nettleman MD, Chung H, Brewer J, et al. Reasons for unprotected intercourse: analysis of the PRAMS survey. Contraception. 2007;75:361-366.

5. Centers for Disease Control and Prevention. Monitoring progress toward achieving Maternal and Infant Healthy People 2010 objectives—19 states, Pregnancy Risk Assessment Monitoring System (PRAMS), 2000-2003. MMWR Surveill Summ. 2006;55:1-11.

6. Nettleman M, Brewer J, Ayoola A. Reasons for unprotected intercourse in adult women: a qualitative study. J Midwifery Womens Health. 2007;52:148-152.

7. Santelli J, Rochat R, Hatfield-Timajchy K, et al. Unintended Pregnancy Working Group. The measurement and meaning of unintended pregnancy. Perspect Sex Reprod Health. 2003;35:94-101.

8. Marston C, King E. Factors that shape young people’s sexual behaviour: a systematic review. Lancet. 2000;368:1581-1586.

9. Crosby R, Yarber WL, Sanders SA, et al. Condom discomfort and associated problems with their use among university students. J Am Coll Health. 2005;54:143-147.

10. Sanders SA, Graham CA, Yarber WL, et al. Condom use errors and problems among young women who put condoms on their male partners. J Am Med Womens Assoc. 2003;58:95-98.

11. Crosby RA, Sanders SA, Yarber WL, et al. Condom use errors and problems among college men. Sex Transm Dis. 2002;29:552-557.

12. Centers for Disease Control and prevention. Recommendations to improve preconception health and health care—United States: a report of the CDC/ATSDR Preconception Care Work Group and the Select Panel on Preconception Care. MMWR. 2006;55(RR- 6):1-15.

13. Kost K, Landry DJ, Darroch JE. The effects of pregnancy planning status on birth outcomes and infant care. Fam Plann Perspect. 1998;30:223.

References

 

1. Ahluwalia IB, Whitehead N, Bensyl D. Pregnancy intention and contraceptive use among adult women. Matern Child Health J. 2007;11:347-351.

2. Ayoola A, Brewer J, Nettleman M. Reasons why women have unprotected sex: a review. J Womens Health. 2007;16:302-310.

3. Project Choices Epidemiologic Survey Group. Alcohol-exposed pregnancy: Characteristics associated with risk. Am J Prev Med. 2002;23:166-173.

4. Nettleman MD, Chung H, Brewer J, et al. Reasons for unprotected intercourse: analysis of the PRAMS survey. Contraception. 2007;75:361-366.

5. Centers for Disease Control and Prevention. Monitoring progress toward achieving Maternal and Infant Healthy People 2010 objectives—19 states, Pregnancy Risk Assessment Monitoring System (PRAMS), 2000-2003. MMWR Surveill Summ. 2006;55:1-11.

6. Nettleman M, Brewer J, Ayoola A. Reasons for unprotected intercourse in adult women: a qualitative study. J Midwifery Womens Health. 2007;52:148-152.

7. Santelli J, Rochat R, Hatfield-Timajchy K, et al. Unintended Pregnancy Working Group. The measurement and meaning of unintended pregnancy. Perspect Sex Reprod Health. 2003;35:94-101.

8. Marston C, King E. Factors that shape young people’s sexual behaviour: a systematic review. Lancet. 2000;368:1581-1586.

9. Crosby R, Yarber WL, Sanders SA, et al. Condom discomfort and associated problems with their use among university students. J Am Coll Health. 2005;54:143-147.

10. Sanders SA, Graham CA, Yarber WL, et al. Condom use errors and problems among young women who put condoms on their male partners. J Am Med Womens Assoc. 2003;58:95-98.

11. Crosby RA, Sanders SA, Yarber WL, et al. Condom use errors and problems among college men. Sex Transm Dis. 2002;29:552-557.

12. Centers for Disease Control and prevention. Recommendations to improve preconception health and health care—United States: a report of the CDC/ATSDR Preconception Care Work Group and the Select Panel on Preconception Care. MMWR. 2006;55(RR- 6):1-15.

13. Kost K, Landry DJ, Darroch JE. The effects of pregnancy planning status on birth outcomes and infant care. Fam Plann Perspect. 1998;30:223.

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Fine-Tuning the Discharge Process

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The first metrics from SHM's Project BOOST mentorship program won't be ready until later this year, but the recent addition of more intervention sites comes as pilot institutions are reporting success in changing the discharge culture.

SHM recently announced 24 new sites for Project BOOST (Better Outcomes for Older Adults through Safe Transitions), bringing the number of participating institutions to 30. Each site features SHM mentors working with hospitalists to improve transitional care via a discharge planning toolkit.

Emmanuel King, MD, director of the Nurse Practitioner Hospitalist Service at the Hospital of the University of Pennsylvania in Philadelphia, says a major shift is implementing the "7P Risk Scale," a transitional-care checklist. Dr. King says some of his staff initially balked at depression screening and questions about health literacy, but when the tools were introduced and the checklist items were embraced, hospitalists felt "included in and comfortable with the process."

"Tweaking it to meet the needs of the team was a great idea," says Dr. King, assistant professor of clinical at UPenn's School of Medicine. "We've been able to get the team to buy in."

Tina Budnitz, MPH, SHM senior advisor for quality initiatives, says some early responses to Project BOOST have been better than expected, especially in the area of follow-up tasks.

"I was expecting people to say they were incredibly time-intensive," Budnitz says. "Some of the hospitalists got back to us and said, 'We think it's a good idea to call every patient, regardless of their risk status.' "

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The first metrics from SHM's Project BOOST mentorship program won't be ready until later this year, but the recent addition of more intervention sites comes as pilot institutions are reporting success in changing the discharge culture.

SHM recently announced 24 new sites for Project BOOST (Better Outcomes for Older Adults through Safe Transitions), bringing the number of participating institutions to 30. Each site features SHM mentors working with hospitalists to improve transitional care via a discharge planning toolkit.

Emmanuel King, MD, director of the Nurse Practitioner Hospitalist Service at the Hospital of the University of Pennsylvania in Philadelphia, says a major shift is implementing the "7P Risk Scale," a transitional-care checklist. Dr. King says some of his staff initially balked at depression screening and questions about health literacy, but when the tools were introduced and the checklist items were embraced, hospitalists felt "included in and comfortable with the process."

"Tweaking it to meet the needs of the team was a great idea," says Dr. King, assistant professor of clinical at UPenn's School of Medicine. "We've been able to get the team to buy in."

Tina Budnitz, MPH, SHM senior advisor for quality initiatives, says some early responses to Project BOOST have been better than expected, especially in the area of follow-up tasks.

"I was expecting people to say they were incredibly time-intensive," Budnitz says. "Some of the hospitalists got back to us and said, 'We think it's a good idea to call every patient, regardless of their risk status.' "

The first metrics from SHM's Project BOOST mentorship program won't be ready until later this year, but the recent addition of more intervention sites comes as pilot institutions are reporting success in changing the discharge culture.

SHM recently announced 24 new sites for Project BOOST (Better Outcomes for Older Adults through Safe Transitions), bringing the number of participating institutions to 30. Each site features SHM mentors working with hospitalists to improve transitional care via a discharge planning toolkit.

Emmanuel King, MD, director of the Nurse Practitioner Hospitalist Service at the Hospital of the University of Pennsylvania in Philadelphia, says a major shift is implementing the "7P Risk Scale," a transitional-care checklist. Dr. King says some of his staff initially balked at depression screening and questions about health literacy, but when the tools were introduced and the checklist items were embraced, hospitalists felt "included in and comfortable with the process."

"Tweaking it to meet the needs of the team was a great idea," says Dr. King, assistant professor of clinical at UPenn's School of Medicine. "We've been able to get the team to buy in."

Tina Budnitz, MPH, SHM senior advisor for quality initiatives, says some early responses to Project BOOST have been better than expected, especially in the area of follow-up tasks.

"I was expecting people to say they were incredibly time-intensive," Budnitz says. "Some of the hospitalists got back to us and said, 'We think it's a good idea to call every patient, regardless of their risk status.' "

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HM Spreads Its Wings

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HM Spreads Its Wings

Hospitalists are not just general internists anymore, having successfully branched out into such subspecialties as cardiology, pulmonology, and gastroenterology, according to a March 12 study in the New England Journal of Medicine (2009;360:1102-12).

In the first quantitative national review to study hospitalists based on Medicare payment data, a team of researchers at the University of Texas Medical Branch at Galveston calculated that the percentage of internal medicine physicians practicing as hospitalists jumped to 19% in 2006 from 5.9% in 1995.

Perhaps more interesting is the number of cardiologists, pulmonologists, gastroenterologists, family physicians, and general practitioners who work as hospitalists totaled roughly 20% in 2006. The study defined hospitalists as those who generated more than 90% of their E/M claims from hospitalized patients.

HM appears to have even more room to grow, as more physicians move toward the HM model and away from primary care, according to an editorial accompanying the NEJM study. The editorial debated the value-adds and the complications caused by the presence of hospitalists in all phases of the care continuum. The authors also acknowledged the model is widely accepted as beneficial.

"The economic and practical forces that promoted the growth in the care of patients by hospitalists are intensifying, not lessening, and hospitalists are here to stay," according to the editorial, written by a trio of NEJM editors, including editor-in-chief Jeffrey M. Drazen, MD. "It is time to focus on how to enhance the value."

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Hospitalists are not just general internists anymore, having successfully branched out into such subspecialties as cardiology, pulmonology, and gastroenterology, according to a March 12 study in the New England Journal of Medicine (2009;360:1102-12).

In the first quantitative national review to study hospitalists based on Medicare payment data, a team of researchers at the University of Texas Medical Branch at Galveston calculated that the percentage of internal medicine physicians practicing as hospitalists jumped to 19% in 2006 from 5.9% in 1995.

Perhaps more interesting is the number of cardiologists, pulmonologists, gastroenterologists, family physicians, and general practitioners who work as hospitalists totaled roughly 20% in 2006. The study defined hospitalists as those who generated more than 90% of their E/M claims from hospitalized patients.

HM appears to have even more room to grow, as more physicians move toward the HM model and away from primary care, according to an editorial accompanying the NEJM study. The editorial debated the value-adds and the complications caused by the presence of hospitalists in all phases of the care continuum. The authors also acknowledged the model is widely accepted as beneficial.

"The economic and practical forces that promoted the growth in the care of patients by hospitalists are intensifying, not lessening, and hospitalists are here to stay," according to the editorial, written by a trio of NEJM editors, including editor-in-chief Jeffrey M. Drazen, MD. "It is time to focus on how to enhance the value."

Hospitalists are not just general internists anymore, having successfully branched out into such subspecialties as cardiology, pulmonology, and gastroenterology, according to a March 12 study in the New England Journal of Medicine (2009;360:1102-12).

In the first quantitative national review to study hospitalists based on Medicare payment data, a team of researchers at the University of Texas Medical Branch at Galveston calculated that the percentage of internal medicine physicians practicing as hospitalists jumped to 19% in 2006 from 5.9% in 1995.

Perhaps more interesting is the number of cardiologists, pulmonologists, gastroenterologists, family physicians, and general practitioners who work as hospitalists totaled roughly 20% in 2006. The study defined hospitalists as those who generated more than 90% of their E/M claims from hospitalized patients.

HM appears to have even more room to grow, as more physicians move toward the HM model and away from primary care, according to an editorial accompanying the NEJM study. The editorial debated the value-adds and the complications caused by the presence of hospitalists in all phases of the care continuum. The authors also acknowledged the model is widely accepted as beneficial.

"The economic and practical forces that promoted the growth in the care of patients by hospitalists are intensifying, not lessening, and hospitalists are here to stay," according to the editorial, written by a trio of NEJM editors, including editor-in-chief Jeffrey M. Drazen, MD. "It is time to focus on how to enhance the value."

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Interhospital Transfer of Children

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Interhospital transfer of critically ill and injured children: An evaluation of transfer patterns, resource utilization, and clinical outcomes

Interhospital transfer of critically ill and injured children is necessitated by variation in resource availability between hospitals. Critically ill children judged in need of clinical services or expertise not locally available undergo transfer to hospitals with more appropriate resource capabilities and expertise, with the expectation that clinical outcomes of transfer will be better than nontransfer.

Significant variation both in the availability of pediatric critical care services across US hospitals1 and in child mortality among hospitals without pediatric critical care services2 suggests that interhospital transfer will remain an integral part of healthcare delivery for critically ill and injured children. Timely provision of definitive care for acute life‐threatening disease is associated with good clinical outcomes.3, 4 While prior studies have examined clinical outcomes and resource consumption among critically ill adults who underwent interhospital transfer for intensive care,59 there is scarce information regarding clinical characteristics and outcomes of interhospital transfer for critically ill and injured children.

This study was conducted to test the hypothesis that, among critically ill and injured children who undergo interhospital transfer for intensive care, children transferred after an initial hospitalization at the referring facility will have higher mortality, longer length of stay (LOS), and higher resource consumption than children transferred directly from the emergency department (ED) of the referring hospitals.

METHODS

Study Design

We conducted a secondary analysis of administrative claims data from the Michigan Medicaid program for the period January 1, 2002, to December 31, 2004. The data included all paid claims for health services rendered to enrollees in the Medicaid program. The Institutional Review Board of the University of Michigan Medical School approved the study.

Study Sample and Variable Identification

A 3‐step approach was employed to identify interhospital transfer admissions for intensive care of children. Initially, the Medicaid claims were queried to identify all hospitalizations for children 018 years who received intensive care services, using Medicare revenue codes.10 Admissions for neonatal intensive care were excluded from the analysis. The American Hospital Association Guide to the Health Care Field, a compendium of US healthcare facilities, was used to verify the presence of intensive care facilities.11, 12 Subsequently, to identify the subset of children who underwent interhospital transfer, data were queried for the presence of claims from another hospital, and the date of discharge from the referring hospital had to be the same as the date of admission to the receiving hospital intensive care unit (ICU). Finally, to ascertain the source of interhospital transfer, Medicare revenue codes and current procedural terminology (CPT) codes were used to identify claims for receipt of services at specific sites within the referring hospital; namely, the ED, ward, or the ICU. This information was used to categorize admissions into 1 of 3 pathways of interhospital transfer:

  • ED transferFrom the ED of the referring hospital to the ICU of the receiving hospital.

  • Ward transferFrom the wards of the referring hospital to the ICU of the receiving hospital.

  • Inter‐ICU transferFrom the ICU of the referring hospital to the ICU of the receiving hospital.

 

Dependent Variables

Mortality at the Receiving Hospital

This is determined by linkage to vital statistics records maintained by the Michigan Department of Community Health, Division of Vital Records and Health Statistics.

LOS at the Receiving Hospital

This is determined as the count of days of hospitalization at the receiving hospital. Of note, this includes ICU days and non‐ICU days at the receiving hospital.

Independent Variables

Source of Interhospital Transfer

The main (exposure) independent variable. Categorized into ED, ward, or inter‐ICU transfers, as described.

Patient Demographics

Age and gender.

Comorbid Illness

Determined using International Classification of Diseases, ninth revision (ICD‐9) diagnosis codes, applying methodology as described.13

Organ Dysfunction at the Referring and Receiving Hospitals

Determined using ICD‐9 diagnosis codes, applying methodology as described.14

Patient Diagnostic Categories

Eleven diagnostic categories were created based on primary admission diagnoses (Appendix A).

LOS at the Referring Hospital

Determined as the count of days of hospitalization at the referring hospital.

Receipt of Cardiopulmonary Resuscitation (CPR) on the Date of Interhospital Transfer

Determined using procedure codes.

Receipt of Medical‐Surgical Procedures at the Receiving Hospital

Identified through the use of ICD‐9 procedure codes, CPT codes, and Healthcare Common Procedure Coding System codes. The procedures are listed in Appendix B.

Statistical Analysis

Descriptive statistics were used to characterize the study sample. According to the 3 sources of interhospital transfer, patient characteristics (age, gender, presence of organ dysfunction, and comorbid illness), median LOS at the referring hospital, and receipt of CPR on the date of interhospital transfer were compared using chi‐square tests for categorical variables, and Kruskal‐Wallis tests for continuous variables. Similarly, outcome variables of in‐hospital mortality and median LOS at the receiving hospital were compared across the 3 sources of interhospital transfer. Analysis of variance was used to compare mean LOS at the receiving hospital across the 3 sources of interhospital transfer. Median (with interquartile range [IQR]) and mean (with standard deviation [SD]) values are presented to describe LOS, given skew in LOS data.

To account for potential confounding of LOS and mortality at the receiving hospital by the presence of organ dysfunction and comorbid illness1316 at the referring hospital, multivariate logistic regression and multiple linear regression analyses were conducted to estimate the odds of in‐hospital mortality and the incremental LOS, respectively, for ward and inter‐ICU transfers, compared with ED transfers. Statistical analyses were conducted using Stata 8 for windows (Stata Corporation, College Station, TX). A 2‐tailed level of 0.05 was used as the threshold for statistical significance.

RESULTS

Patient Characteristics

Of 1,643 transfer admissions for intensive care during the study period, 1022 (62%) were ED transfers, 512 (31%) were ward transfers, and 109 (7%) were inter‐ICU transfers. The average age was 2 years, with male gender (57%) predominance. Comorbid illness was present in 19% of admissions, while 11% had evidence of organ dysfunction at the referring hospital. Table 1 presents key patient demographic and clinical characteristics at the referring hospitals, by transfer source. Inter‐ICU and ward transfers were younger than ED transfers, and had a higher preponderance of comorbid illness and organ dysfunction. At the time of interhospital transfer, compared with ED transfers, the proportion of admissions with organ dysfunction (a marker of illness severity) was 3‐fold and 8‐fold higher among ward and inter‐ICU transfers, respectively.

Patient Characteristics at the Referring Hospital According to Transfer Source
 Transfer SourceP
CharacteristicsED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)
  • NOTE: Transfer source: ED, transfer admission from the emergency department of the referring hospital to the intensive care unit of the receiving hospital. Ward, transfer admission from the ward of the referring hospital to the intensive care unit of the receiving hospital. Inter‐ICU, transfer admission from the intensive care unit of the referring hospital to the intensive care unit of the receiving hospital.

  • Abbreviations: ED, emergency department; ICU, intensive care unit; IQR, interquartile range; SD, standard deviation.

Median age in years (IQR)2 (09)1 (07)1 (010)<0.01
Male (%)57.856.247.60.13
Comorbid illness (% )13.125.050.5<0.01
Pretransfer hospital length of stay (days)    
Median (IQR)01 (02)3 (18)<0.01
Mean (SD)0.2 (5.2)1.6 (4.8)9.7 (18.0)<0.01
Pretransfer organ dysfunction (%)5.514.540.4<0.01

Patterns of Transfer

The leading diagnoses among all children were respiratory disease, trauma, and neurological disease (Table 2), with some variation in diagnoses by source of interhospital transfer. For example, cardiovascular disease was the second leading diagnosis after respiratory disease among the inter‐ICU transfers, while more children with endocrine disease (predominantly diabetic ketoacidosis), traumatic injury, or drug poisoning were transferred directly from the ED, than from the ward or the ICU settings. For burn care, 80% (45/56) of all transfer admissions were direct from the ED (Table 3). The majority (78%) of children with traumatic injuries were directly transferred from the ED to the ICU, while the remainder were transferred after initial care delivered on the ward (18%) or ICU (4%) settings prior to interhospital transfer for definitive intensive trauma care. Importantly, among the inter‐ICU transfers, 104 (95%) were transferred to pediatric ICUs from referring hospitals with adult and pediatric ICU facilities, suggesting uptransfer for specialized care. Five children were transferred between hospitals with adult ICU facilities.

Primary Diagnostic Categories According to Transfer Source
  Transfer Source
Diagnostic Category (%)Overall* (n = 1639)ED* (n = 1018)Ward (n = 512)Inter‐ICU (n = 109)
  • Diagnoses were missing in 4 admissions.

Respiratory disease35.132.841.028.4
Trauma16.220.59.29.1
Neurological disease12.412.512.311.9
Gastrointestinal disease6.75.47.411.9
Infectious disease5.84.08.410.0
Endocrine disease5.57.91.80
Drug overdose/poisoning5.06.42.91.8
Cardiovascular disease4.82.86.316.5
Hematologic/oncologic disease2.01.62.91.8
Cardiac arrest0.200.60.9
Other diagnoses6.25.47.27.7
Ten Leading Medical‐Surgical Procedures and Services Rendered at the Receiving Hospital According to Transfer Source
  Transfer Source 
Characteristics (%)Overall (n = 1643)ED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)P
Respiratory26.819.036.754.1<0.01
Radiological21.219.520.541.3<0.01
Vascular access20.015.227.033.0<0.01
Gastrointestinal3.93.03.712.8<0.01
Neurological3.83.23.710.1<0.01
Cardiovascular3.61.84.118.4<0.01
Burn care3.44.52.00<0.01
General surgery3.22.14.38.3<0.01
Dialysis2.62.02.58.3<0.01
ECMO2.11.32.29.2<0.01

CPR was performed on the date of interhospital transfer for 23 patients (1.4% of the sample), of whom 13 (56.5%) were ward transfers, 8 (34.8%) were inter‐ICU transfers, and 2 (8.7%) were ED transfers (P < 0.02). Two‐thirds of these children did not survive subsequent hospitalization at the receiving hospitals.

Clinical Outcomes and Resource Utilization at the Receiving Hospitals

At the receiving hospitals, other than burn care, medical‐surgical procedures were performed most often among the inter‐ICU transfers. Ward transfers also had higher receipt of procedures compared with ED transfers (Table 3). The inter‐ICU and ward transfers had a higher preponderance of organ dysfunction at the receiving hospitals, compared to the ED transfers (38.5% and 29.3% versus 20.8%, P < 0.01).

Clinical outcomes at the receiving hospitals varied significantly according to the source of interhospital transfer (Table 4). Sixty‐six (4%) of patients died at the receiving hospitals. In comparison with ED transfers, unadjusted in‐hospital mortality was 2‐fold and 3‐fold higher among the ward and inter‐ICU transfers, respectively. Also, hospital LOS was significantly longer among the ward and inter‐ICU transfers than for the ED transfers.

Patient Unadjusted Outcomes at the Receiving Hospital According to Transfer Source
 Transfer Source 
CharacteristicsED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)P
  • Abbreviations: IQR, interquartile range; SD, standard deviation.

Mortality (%)2.85.58.3<0.01
Length of stay (days)    
Median (IQR)3 (27)5 (312)13 (724)<0.01
Mean (SD)6.7 (10.4)8.5 (9.2)21.4 (22.9)<0.01

In multivariate analyses adjusting for patient age, and the presence of comorbid illness and organ dysfunction at the referring hospital, compared with ED transfers, odds of mortality were significantly higher (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.023.03) for ward transfers. Inter‐ICU transfers also had higher odds of mortality (OR, 2.07; 95% CI, 0.884.86), without achieving statistical significance. Similarly, compared with ED transfers, LOS at the receiving hospital was longer by 1.5 days (95% CI, 0.32.7 days) for ward transfers, and by 13.5 days (95% CI, 11.115.8 days) for inter‐ICU transfers.

DISCUSSION

This study is the first to highlight significant variation in clinical outcomes and resource consumption after interhospital transfer of critically ill and injured children, depending on the source of transfer. In comparison with children transferred directly from the referring hospitals' ED settings, children transferred from the referring hospitals' wards had higher mortality, while those who underwent inter‐ICU transfer had significantly higher resource consumption. In addition, ward transfers had the highest proportion of children who underwent CPR on the date of interhospital transfer, highlighting elevated severity of disease prior to transfer and an urgent need for improved understanding of pretransfer clinical care and medical decision‐making. The findings raise the possibility that more timely transfer of some patients directly from community hospital EDs to regional ICUs might improve survival and reduce resource consumption.

Although interhospital transfers are common in everyday clinical practice, there has been a knowledge gap in pediatric acute and critical care medicine regarding the clinical outcomes and resource consumption among children who undergo such transfers. Findings from the current study narrow this gap by relating triage at the referring hospitals to clinical outcomes and resource utilization at the receiving hospitals.

Certain distinct transfer patterns were observed. Most children with burn injury underwent direct transfer from the ED to the ICU; this transfer pattern may be related both to the limited availability of ICUs with burn care capability in Michigan and to the acuity of burn injuries, which often mandates immediate triage to hospitals with intensive burn care facilities. Conversely, while the majority of children with traumatic injuries were directly transferred from emergency to intensive care, over one‐fifth were transferred after initial care delivered on the ward or ICU settings prior to interhospital transfer for definitive intensive trauma care. Such imperfect regionalization of trauma care suggests further study of clinical outcomes and resource utilization among injured children is warranted. Likewise, cardiovascular disease was prominent among the inter‐ICU transfers, suggesting a clinical practice pattern of stabilization and resuscitation at the initial ICU prior to interhospital vertical or uptransfer for definitive cardiac care at the receiving hospitals.

It remains unknown whether the timing of interhospital transfer of critically ill children is a determinant of clinical outcomes. Prior studies among adults have reported higher mortality with prolonged duration of pre‐ICU care on the ward.4, 17 In the current study, ward and inter‐ICU transfers were initially hospitalized for a median of 1 and 3 days, respectively, prior to transfer. While we could not determine from administrative data what the precise triggers for interhospital transfer in this study were, it is instructive to note that ward transfers comprised more than one‐half of all children who received CPR on the date of transfer. For children who received CPR, severe clinical deterioration likely triggered transfer to hospitals with ICU facilities, but because only a minority of children received CPR overall, other triggers of transfer warrant investigation. For most of the children transferred, it seems plausible that the precipitant of transfer was likely a mismatch of their clinical status with the clinical capacities of the facilities where they were initially hospitalized. Future work should investigate if there is an association between clinical outcomes at the receiving hospitals, and both the timing of interhospital transfer and the clinical status of patients at transfer.

Importantly, compared with ED transfers, ward transfers demonstrated elevated odds of mortality after adjustment for coexisting comorbid illness, patient age, and pretransfer organ dysfunction at the referring hospital. Some possible explanations for this finding include the progression of disease while receiving care on the ward, or suboptimal access to ICU facilities due to barriers to transfer at either the referring or receiving hospitals. Importantly, progression of disease in ward settings may be detected by early identification of children at high risk of clinical deterioration on the wards of hospitals without ICU facilities, prior to cardiopulmonary arrest, because death after CPR may not be averted with subsequent ICU care.18

Various approaches to facilitate rapid and appropriate triage and reassessment of children in hospitals without ICU facilities, prior to severe clinical deterioration or need for CPR, must be investigated. These approaches might include in‐hospital measures such as the establishment of medical emergency teams to respond to clinical deterioration on the wards19 or collaborative interhospital measures such as the use of telemedicine20 or similar remote communication/triage systems to enhance communication between clinical caregivers at hospitals with ICU facilities and those in hospitals without ICU facilities. Furthermore, interhospital transfer agreements may facilitate expeditious and appropriate transfer of severely ill patients to hospitals with ICU facilities.

Access to hospitals with ICU facilities might also influence outcomes for critically ill children admitted initially to wards of hospitals without ICU facilities. Kanter2 reported significant variation in mortality among children who received care at New York hospitals without ICU facilities. Of note, 27% of statewide pediatric inpatient deaths occurred in those hospitals without ICU facilities. It appeared that, while some pediatric deaths in hospitals without ICU facilities were expected, regional variation in such mortality might have been associated with reduced access to, or poor utilization of, hospitals with ICU facilities. Barriers to interhospital transfers might include underrecognition of mismatch between patient illness severity and hospital capability at referring hospitals, or lack of capacity to accept transfers at the receiving hospitals. Further study is warranted to investigate clinical decision‐making underlying the initiation of the interhospital transfer processes, and procedural or institutional barriers that might hinder the transfer of critically ill children from hospitals without ICU facilities.

Resource consumption at the receiving hospitals, measured by hospital LOS and receipt of medical‐surgical procedures, was highest among the inter‐ICU transfers. This was an expected finding, given the high frequency of organ dysfunction among the inter‐ICU transfers, before and after interhospital transfer. These patients had the highest use of advanced and resource‐intensive technology, including continuous renal replacement therapy, extracorporeal membrane oxygenation, and cardiovascular procedures such as open‐heart surgery. In addition, the duration of hospitalization at the receiving hospital was 2 weeks longer among the inter‐ICU transfers when compared with the ED transfers. Such prolonged hospitalization has been previously associated with significantly increased resource consumption.4, 6 In the absence of physiologic data pertaining to illness severity, however, it is unknown whether this observed differential LOS by source of interhospital transfer might be attributable to both unobserved illness severity and/or extensive in‐hospital post‐ICU multidisciplinary rehabilitative care for inter‐ICU transfer patients, compared with ED transfer patients.

Our study findings need to be interpreted in light of certain limitations. Administrative claims data do not allow for assessment of the quality of hospital care, a factor that might play an important role in patient clinical outcomes. The data lacked any physiologic information that might enhance the ability to estimate patient severity of illness; the analysis used the presence of organ dysfunction at the referring hospitals as a proxy for illness severity. The use of diagnosis codebased measures of severity adjustment, as employed in the current study, however, has been reported to be comparable with clinical severity measures because of the relatively complete capture of diagnosis codes for life‐threatening conditions occurring late in the hospitalization, such as prior to interhospital transfer in the current study.2123

The absence of clinical information prevented assessment of the likelihood of in‐hospital morbidity, transport complications, and need for various therapeutic interventions after ICU care, which are also highly relevant outcomes of interhospital transfers. It is unknown if the small sample size among inter‐ICU transfers limited the ability to demonstrate a statistically significant difference in odds of mortality among inter‐ICU transfers compared with ED transfers.

Also, the identification of diagnoses and procedures was made using multiple coding instruments and is therefore susceptible to inaccuracies of detection and attribution that may have biased the findings. Study findings did not include cost, because cost data were not available for children enrolled in Medicaid managed care plans under capitated arrangements. Finally, it is unknown how generalizable the current study findings might be to children with private insurance, or to children who are uninsured.

The study findings highlight potential opportunities for future research. Further studies are warranted to identify key characteristics that differentiate children admitted to nonpediatric hospitals who are subsequently transferred to pediatric hospitals with ICU facilities versus the children who are not transferred. Also, in‐depth study of the decision‐making that underlies interhospital transfer of critically ill or injured children to hospitals with ICU facilities for advanced care after initial hospitalization is vital to improved understanding of factors that might contribute to the extensive resource consumption and mortality burden borne by these children. The existence and effectiveness of interhospital transfer agreements at the state level needs to be examined specifically as it relates to patterns and clinical outcomes of interhospital transfer of critically ill and injured children in the US.

In conclusion, in this multiyear, statewide sample among critically ill and injured children enrolled by a statewide public payer, clinical outcomes were worse and resource consumption higher, among children who underwent interhospital transfer after initial hospitalization compared with those transferred directly from referring EDs. The findings raise the possibility that more timely transfer of some patients directly from community hospital EDs to regional ICUs might improve survival and reduce resource consumption.

Efforts to improve the care of critically ill and injured children may be enhanced by improved understanding of the medical decision‐making underlying interhospital transfer; application of innovative methods to identify and ensure rapid access to clinical expertise for children initially admitted to hospitals without pediatric intensive care facilities who might subsequently require intensive care; and routine reassessment of hospitalized children to ensure effective and efficient triage and re‐triage at the ED, ward, and ICU levels of referring hospitals.

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References
  1. Odetola FO,Clark SJ,Freed GL,Bratton SL,Davis MM.A national survey of pediatric critical care resources in the United States.Pediatrics.2005;115:e382386.
  2. Kanter RK.Regional variation in child mortality at hospitals lacking a pediatric intensive care unit.Crit Care Med.2002;30:9499.
  3. Sampalis JS,Denis R,Frechette P,Brown R,Fleiszer D,Mulder D.Direct transport to tertiary trauma centers versus transfer from lower level facilities: impact on mortality and morbidity among patients with major trauma.J Trauma.1997;43:288296.
  4. Rapoport J,Teres D,Lemeshow S,Harris D.Timing of intensive care unit admission in relation to ICU outcome.Crit Care Med.1990;18:12311235.
  5. Escarce JJ,Kelley MA:Admission source to the medical intensive care unit predicts hospital death independent of APACHE II score.JAMA.1990;264:23892394.
  6. Rosenberg AL,Hofer TP,Strachan C,Watts CM,Hayward RA.Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures.Ann Intern Med.2003;138:882890.
  7. Borlase BC,Baxter JK,Kenney PR,Forse RA,Benotti PN,Blackburn GL.Elective intrahospital admissions versus acute interhospital transfers to a surgical intensive care unit: cost and outcome prediction.J Trauma.1991;31:915918.
  8. Combes A,Luyt CE,Trouillet JL,Chastre J,Gibert C.Adverse effect on a referral intensive care unit's performance of accepting patients transferred from another intensive care unit.Crit Care Med.2005;33:705710.
  9. Durairaj L,Will JG,Torner JC,Doebbeling BN.Prognostic factors for mortality following interhospital transfers to the medical intensive care unit of a tertiary referral center.Crit Care Med.2003;31:19811986.
  10. National Government Services. Medicare UB‐04 Revenue Codes. Available at http://www.ngsmedicare.com/NGSMedicare/PartA/EducationandSupport/ToolsandMaterials/0908ub‐04.pdf. Accessed April 7,2008.
  11. American Hospital Association.AHA Guide to the Health Care Field.2002 ed.Chicago:American Hospital Association;2002.
  12. American Hospital Association.AHA Guide to the Health Care Field.2003 ed.Chicago:American Hospital Association;2003.
  13. Feudtner C,Christakis DA,Connell FA.Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997.Pediatrics.2000;106:205209.
  14. Johnston JA,Yi MS,Britto MT,Mrus JM.Importance of organ dysfunction in determining hospital outcomes in children.J Pediatr.2004;144:595601.
  15. Leclerc F,Leteurtre S,Duhamel A, et al.Cumulative influence of organ dysfunctions and septic state on mortality of critically ill children.Am J Respir Crit Care Med.2005;171:348353.
  16. Watson RS,Carcillo JA,Linde‐Zwirble WT,Clermont G,Lidicker J,Angus DC.The epidemiology of severe sepsis in children in the United States.Am J Respir Crit Care Med.2003;167:695701.
  17. Goldhill DR,McNarry AF,Hadjianastassiou VG,Tekkis PP.The longer patients are in hospital before intensive care admission the higher their mortality.Intensive Care Med.2004;30:19081913.
  18. Tibballs J,Kinney S.A prospective study of outcome of in‐patient pediatric cardiopulmonary arrest.Resuscitation.2006;71:310318.
  19. Sharek PJ,Parast LM,Leong K, et al.Effect of a rapid response team on hospital‐wide mortality and code rates outside the ICU in a children's hospital.JAMA.2007;298:22672274.
  20. Marcin JP,Nesbitt TS,Kallas HJ,Struve SN,Traugott CA,Dimand RJ.Use of telemedicine to provide pediatric critical care consultations to underserved rural northern California.J Pediatr.2004;144:375380.
  21. Romano PS,Chan BK.Risk‐adjusting acute myocardial infarction mortality: are APR‐DRGs the right tool?Health Serv Res.2000;34:14691489.
  22. Iezzoni LI,Ash AS,Shwartz M,Landon BE,Mackiernan YD.Predicting in‐hospital deaths from coronary artery bypass graft surgery: do different severity measures give different predictions?Med Care.1998;36:2839.
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Journal of Hospital Medicine - 4(3)
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164-170
Legacy Keywords
health resources, hospitalized children, length of stay, mortality, triage
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Interhospital transfer of critically ill and injured children is necessitated by variation in resource availability between hospitals. Critically ill children judged in need of clinical services or expertise not locally available undergo transfer to hospitals with more appropriate resource capabilities and expertise, with the expectation that clinical outcomes of transfer will be better than nontransfer.

Significant variation both in the availability of pediatric critical care services across US hospitals1 and in child mortality among hospitals without pediatric critical care services2 suggests that interhospital transfer will remain an integral part of healthcare delivery for critically ill and injured children. Timely provision of definitive care for acute life‐threatening disease is associated with good clinical outcomes.3, 4 While prior studies have examined clinical outcomes and resource consumption among critically ill adults who underwent interhospital transfer for intensive care,59 there is scarce information regarding clinical characteristics and outcomes of interhospital transfer for critically ill and injured children.

This study was conducted to test the hypothesis that, among critically ill and injured children who undergo interhospital transfer for intensive care, children transferred after an initial hospitalization at the referring facility will have higher mortality, longer length of stay (LOS), and higher resource consumption than children transferred directly from the emergency department (ED) of the referring hospitals.

METHODS

Study Design

We conducted a secondary analysis of administrative claims data from the Michigan Medicaid program for the period January 1, 2002, to December 31, 2004. The data included all paid claims for health services rendered to enrollees in the Medicaid program. The Institutional Review Board of the University of Michigan Medical School approved the study.

Study Sample and Variable Identification

A 3‐step approach was employed to identify interhospital transfer admissions for intensive care of children. Initially, the Medicaid claims were queried to identify all hospitalizations for children 018 years who received intensive care services, using Medicare revenue codes.10 Admissions for neonatal intensive care were excluded from the analysis. The American Hospital Association Guide to the Health Care Field, a compendium of US healthcare facilities, was used to verify the presence of intensive care facilities.11, 12 Subsequently, to identify the subset of children who underwent interhospital transfer, data were queried for the presence of claims from another hospital, and the date of discharge from the referring hospital had to be the same as the date of admission to the receiving hospital intensive care unit (ICU). Finally, to ascertain the source of interhospital transfer, Medicare revenue codes and current procedural terminology (CPT) codes were used to identify claims for receipt of services at specific sites within the referring hospital; namely, the ED, ward, or the ICU. This information was used to categorize admissions into 1 of 3 pathways of interhospital transfer:

  • ED transferFrom the ED of the referring hospital to the ICU of the receiving hospital.

  • Ward transferFrom the wards of the referring hospital to the ICU of the receiving hospital.

  • Inter‐ICU transferFrom the ICU of the referring hospital to the ICU of the receiving hospital.

 

Dependent Variables

Mortality at the Receiving Hospital

This is determined by linkage to vital statistics records maintained by the Michigan Department of Community Health, Division of Vital Records and Health Statistics.

LOS at the Receiving Hospital

This is determined as the count of days of hospitalization at the receiving hospital. Of note, this includes ICU days and non‐ICU days at the receiving hospital.

Independent Variables

Source of Interhospital Transfer

The main (exposure) independent variable. Categorized into ED, ward, or inter‐ICU transfers, as described.

Patient Demographics

Age and gender.

Comorbid Illness

Determined using International Classification of Diseases, ninth revision (ICD‐9) diagnosis codes, applying methodology as described.13

Organ Dysfunction at the Referring and Receiving Hospitals

Determined using ICD‐9 diagnosis codes, applying methodology as described.14

Patient Diagnostic Categories

Eleven diagnostic categories were created based on primary admission diagnoses (Appendix A).

LOS at the Referring Hospital

Determined as the count of days of hospitalization at the referring hospital.

Receipt of Cardiopulmonary Resuscitation (CPR) on the Date of Interhospital Transfer

Determined using procedure codes.

Receipt of Medical‐Surgical Procedures at the Receiving Hospital

Identified through the use of ICD‐9 procedure codes, CPT codes, and Healthcare Common Procedure Coding System codes. The procedures are listed in Appendix B.

Statistical Analysis

Descriptive statistics were used to characterize the study sample. According to the 3 sources of interhospital transfer, patient characteristics (age, gender, presence of organ dysfunction, and comorbid illness), median LOS at the referring hospital, and receipt of CPR on the date of interhospital transfer were compared using chi‐square tests for categorical variables, and Kruskal‐Wallis tests for continuous variables. Similarly, outcome variables of in‐hospital mortality and median LOS at the receiving hospital were compared across the 3 sources of interhospital transfer. Analysis of variance was used to compare mean LOS at the receiving hospital across the 3 sources of interhospital transfer. Median (with interquartile range [IQR]) and mean (with standard deviation [SD]) values are presented to describe LOS, given skew in LOS data.

To account for potential confounding of LOS and mortality at the receiving hospital by the presence of organ dysfunction and comorbid illness1316 at the referring hospital, multivariate logistic regression and multiple linear regression analyses were conducted to estimate the odds of in‐hospital mortality and the incremental LOS, respectively, for ward and inter‐ICU transfers, compared with ED transfers. Statistical analyses were conducted using Stata 8 for windows (Stata Corporation, College Station, TX). A 2‐tailed level of 0.05 was used as the threshold for statistical significance.

RESULTS

Patient Characteristics

Of 1,643 transfer admissions for intensive care during the study period, 1022 (62%) were ED transfers, 512 (31%) were ward transfers, and 109 (7%) were inter‐ICU transfers. The average age was 2 years, with male gender (57%) predominance. Comorbid illness was present in 19% of admissions, while 11% had evidence of organ dysfunction at the referring hospital. Table 1 presents key patient demographic and clinical characteristics at the referring hospitals, by transfer source. Inter‐ICU and ward transfers were younger than ED transfers, and had a higher preponderance of comorbid illness and organ dysfunction. At the time of interhospital transfer, compared with ED transfers, the proportion of admissions with organ dysfunction (a marker of illness severity) was 3‐fold and 8‐fold higher among ward and inter‐ICU transfers, respectively.

Patient Characteristics at the Referring Hospital According to Transfer Source
 Transfer SourceP
CharacteristicsED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)
  • NOTE: Transfer source: ED, transfer admission from the emergency department of the referring hospital to the intensive care unit of the receiving hospital. Ward, transfer admission from the ward of the referring hospital to the intensive care unit of the receiving hospital. Inter‐ICU, transfer admission from the intensive care unit of the referring hospital to the intensive care unit of the receiving hospital.

  • Abbreviations: ED, emergency department; ICU, intensive care unit; IQR, interquartile range; SD, standard deviation.

Median age in years (IQR)2 (09)1 (07)1 (010)<0.01
Male (%)57.856.247.60.13
Comorbid illness (% )13.125.050.5<0.01
Pretransfer hospital length of stay (days)    
Median (IQR)01 (02)3 (18)<0.01
Mean (SD)0.2 (5.2)1.6 (4.8)9.7 (18.0)<0.01
Pretransfer organ dysfunction (%)5.514.540.4<0.01

Patterns of Transfer

The leading diagnoses among all children were respiratory disease, trauma, and neurological disease (Table 2), with some variation in diagnoses by source of interhospital transfer. For example, cardiovascular disease was the second leading diagnosis after respiratory disease among the inter‐ICU transfers, while more children with endocrine disease (predominantly diabetic ketoacidosis), traumatic injury, or drug poisoning were transferred directly from the ED, than from the ward or the ICU settings. For burn care, 80% (45/56) of all transfer admissions were direct from the ED (Table 3). The majority (78%) of children with traumatic injuries were directly transferred from the ED to the ICU, while the remainder were transferred after initial care delivered on the ward (18%) or ICU (4%) settings prior to interhospital transfer for definitive intensive trauma care. Importantly, among the inter‐ICU transfers, 104 (95%) were transferred to pediatric ICUs from referring hospitals with adult and pediatric ICU facilities, suggesting uptransfer for specialized care. Five children were transferred between hospitals with adult ICU facilities.

Primary Diagnostic Categories According to Transfer Source
  Transfer Source
Diagnostic Category (%)Overall* (n = 1639)ED* (n = 1018)Ward (n = 512)Inter‐ICU (n = 109)
  • Diagnoses were missing in 4 admissions.

Respiratory disease35.132.841.028.4
Trauma16.220.59.29.1
Neurological disease12.412.512.311.9
Gastrointestinal disease6.75.47.411.9
Infectious disease5.84.08.410.0
Endocrine disease5.57.91.80
Drug overdose/poisoning5.06.42.91.8
Cardiovascular disease4.82.86.316.5
Hematologic/oncologic disease2.01.62.91.8
Cardiac arrest0.200.60.9
Other diagnoses6.25.47.27.7
Ten Leading Medical‐Surgical Procedures and Services Rendered at the Receiving Hospital According to Transfer Source
  Transfer Source 
Characteristics (%)Overall (n = 1643)ED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)P
Respiratory26.819.036.754.1<0.01
Radiological21.219.520.541.3<0.01
Vascular access20.015.227.033.0<0.01
Gastrointestinal3.93.03.712.8<0.01
Neurological3.83.23.710.1<0.01
Cardiovascular3.61.84.118.4<0.01
Burn care3.44.52.00<0.01
General surgery3.22.14.38.3<0.01
Dialysis2.62.02.58.3<0.01
ECMO2.11.32.29.2<0.01

CPR was performed on the date of interhospital transfer for 23 patients (1.4% of the sample), of whom 13 (56.5%) were ward transfers, 8 (34.8%) were inter‐ICU transfers, and 2 (8.7%) were ED transfers (P < 0.02). Two‐thirds of these children did not survive subsequent hospitalization at the receiving hospitals.

Clinical Outcomes and Resource Utilization at the Receiving Hospitals

At the receiving hospitals, other than burn care, medical‐surgical procedures were performed most often among the inter‐ICU transfers. Ward transfers also had higher receipt of procedures compared with ED transfers (Table 3). The inter‐ICU and ward transfers had a higher preponderance of organ dysfunction at the receiving hospitals, compared to the ED transfers (38.5% and 29.3% versus 20.8%, P < 0.01).

Clinical outcomes at the receiving hospitals varied significantly according to the source of interhospital transfer (Table 4). Sixty‐six (4%) of patients died at the receiving hospitals. In comparison with ED transfers, unadjusted in‐hospital mortality was 2‐fold and 3‐fold higher among the ward and inter‐ICU transfers, respectively. Also, hospital LOS was significantly longer among the ward and inter‐ICU transfers than for the ED transfers.

Patient Unadjusted Outcomes at the Receiving Hospital According to Transfer Source
 Transfer Source 
CharacteristicsED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)P
  • Abbreviations: IQR, interquartile range; SD, standard deviation.

Mortality (%)2.85.58.3<0.01
Length of stay (days)    
Median (IQR)3 (27)5 (312)13 (724)<0.01
Mean (SD)6.7 (10.4)8.5 (9.2)21.4 (22.9)<0.01

In multivariate analyses adjusting for patient age, and the presence of comorbid illness and organ dysfunction at the referring hospital, compared with ED transfers, odds of mortality were significantly higher (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.023.03) for ward transfers. Inter‐ICU transfers also had higher odds of mortality (OR, 2.07; 95% CI, 0.884.86), without achieving statistical significance. Similarly, compared with ED transfers, LOS at the receiving hospital was longer by 1.5 days (95% CI, 0.32.7 days) for ward transfers, and by 13.5 days (95% CI, 11.115.8 days) for inter‐ICU transfers.

DISCUSSION

This study is the first to highlight significant variation in clinical outcomes and resource consumption after interhospital transfer of critically ill and injured children, depending on the source of transfer. In comparison with children transferred directly from the referring hospitals' ED settings, children transferred from the referring hospitals' wards had higher mortality, while those who underwent inter‐ICU transfer had significantly higher resource consumption. In addition, ward transfers had the highest proportion of children who underwent CPR on the date of interhospital transfer, highlighting elevated severity of disease prior to transfer and an urgent need for improved understanding of pretransfer clinical care and medical decision‐making. The findings raise the possibility that more timely transfer of some patients directly from community hospital EDs to regional ICUs might improve survival and reduce resource consumption.

Although interhospital transfers are common in everyday clinical practice, there has been a knowledge gap in pediatric acute and critical care medicine regarding the clinical outcomes and resource consumption among children who undergo such transfers. Findings from the current study narrow this gap by relating triage at the referring hospitals to clinical outcomes and resource utilization at the receiving hospitals.

Certain distinct transfer patterns were observed. Most children with burn injury underwent direct transfer from the ED to the ICU; this transfer pattern may be related both to the limited availability of ICUs with burn care capability in Michigan and to the acuity of burn injuries, which often mandates immediate triage to hospitals with intensive burn care facilities. Conversely, while the majority of children with traumatic injuries were directly transferred from emergency to intensive care, over one‐fifth were transferred after initial care delivered on the ward or ICU settings prior to interhospital transfer for definitive intensive trauma care. Such imperfect regionalization of trauma care suggests further study of clinical outcomes and resource utilization among injured children is warranted. Likewise, cardiovascular disease was prominent among the inter‐ICU transfers, suggesting a clinical practice pattern of stabilization and resuscitation at the initial ICU prior to interhospital vertical or uptransfer for definitive cardiac care at the receiving hospitals.

It remains unknown whether the timing of interhospital transfer of critically ill children is a determinant of clinical outcomes. Prior studies among adults have reported higher mortality with prolonged duration of pre‐ICU care on the ward.4, 17 In the current study, ward and inter‐ICU transfers were initially hospitalized for a median of 1 and 3 days, respectively, prior to transfer. While we could not determine from administrative data what the precise triggers for interhospital transfer in this study were, it is instructive to note that ward transfers comprised more than one‐half of all children who received CPR on the date of transfer. For children who received CPR, severe clinical deterioration likely triggered transfer to hospitals with ICU facilities, but because only a minority of children received CPR overall, other triggers of transfer warrant investigation. For most of the children transferred, it seems plausible that the precipitant of transfer was likely a mismatch of their clinical status with the clinical capacities of the facilities where they were initially hospitalized. Future work should investigate if there is an association between clinical outcomes at the receiving hospitals, and both the timing of interhospital transfer and the clinical status of patients at transfer.

Importantly, compared with ED transfers, ward transfers demonstrated elevated odds of mortality after adjustment for coexisting comorbid illness, patient age, and pretransfer organ dysfunction at the referring hospital. Some possible explanations for this finding include the progression of disease while receiving care on the ward, or suboptimal access to ICU facilities due to barriers to transfer at either the referring or receiving hospitals. Importantly, progression of disease in ward settings may be detected by early identification of children at high risk of clinical deterioration on the wards of hospitals without ICU facilities, prior to cardiopulmonary arrest, because death after CPR may not be averted with subsequent ICU care.18

Various approaches to facilitate rapid and appropriate triage and reassessment of children in hospitals without ICU facilities, prior to severe clinical deterioration or need for CPR, must be investigated. These approaches might include in‐hospital measures such as the establishment of medical emergency teams to respond to clinical deterioration on the wards19 or collaborative interhospital measures such as the use of telemedicine20 or similar remote communication/triage systems to enhance communication between clinical caregivers at hospitals with ICU facilities and those in hospitals without ICU facilities. Furthermore, interhospital transfer agreements may facilitate expeditious and appropriate transfer of severely ill patients to hospitals with ICU facilities.

Access to hospitals with ICU facilities might also influence outcomes for critically ill children admitted initially to wards of hospitals without ICU facilities. Kanter2 reported significant variation in mortality among children who received care at New York hospitals without ICU facilities. Of note, 27% of statewide pediatric inpatient deaths occurred in those hospitals without ICU facilities. It appeared that, while some pediatric deaths in hospitals without ICU facilities were expected, regional variation in such mortality might have been associated with reduced access to, or poor utilization of, hospitals with ICU facilities. Barriers to interhospital transfers might include underrecognition of mismatch between patient illness severity and hospital capability at referring hospitals, or lack of capacity to accept transfers at the receiving hospitals. Further study is warranted to investigate clinical decision‐making underlying the initiation of the interhospital transfer processes, and procedural or institutional barriers that might hinder the transfer of critically ill children from hospitals without ICU facilities.

Resource consumption at the receiving hospitals, measured by hospital LOS and receipt of medical‐surgical procedures, was highest among the inter‐ICU transfers. This was an expected finding, given the high frequency of organ dysfunction among the inter‐ICU transfers, before and after interhospital transfer. These patients had the highest use of advanced and resource‐intensive technology, including continuous renal replacement therapy, extracorporeal membrane oxygenation, and cardiovascular procedures such as open‐heart surgery. In addition, the duration of hospitalization at the receiving hospital was 2 weeks longer among the inter‐ICU transfers when compared with the ED transfers. Such prolonged hospitalization has been previously associated with significantly increased resource consumption.4, 6 In the absence of physiologic data pertaining to illness severity, however, it is unknown whether this observed differential LOS by source of interhospital transfer might be attributable to both unobserved illness severity and/or extensive in‐hospital post‐ICU multidisciplinary rehabilitative care for inter‐ICU transfer patients, compared with ED transfer patients.

Our study findings need to be interpreted in light of certain limitations. Administrative claims data do not allow for assessment of the quality of hospital care, a factor that might play an important role in patient clinical outcomes. The data lacked any physiologic information that might enhance the ability to estimate patient severity of illness; the analysis used the presence of organ dysfunction at the referring hospitals as a proxy for illness severity. The use of diagnosis codebased measures of severity adjustment, as employed in the current study, however, has been reported to be comparable with clinical severity measures because of the relatively complete capture of diagnosis codes for life‐threatening conditions occurring late in the hospitalization, such as prior to interhospital transfer in the current study.2123

The absence of clinical information prevented assessment of the likelihood of in‐hospital morbidity, transport complications, and need for various therapeutic interventions after ICU care, which are also highly relevant outcomes of interhospital transfers. It is unknown if the small sample size among inter‐ICU transfers limited the ability to demonstrate a statistically significant difference in odds of mortality among inter‐ICU transfers compared with ED transfers.

Also, the identification of diagnoses and procedures was made using multiple coding instruments and is therefore susceptible to inaccuracies of detection and attribution that may have biased the findings. Study findings did not include cost, because cost data were not available for children enrolled in Medicaid managed care plans under capitated arrangements. Finally, it is unknown how generalizable the current study findings might be to children with private insurance, or to children who are uninsured.

The study findings highlight potential opportunities for future research. Further studies are warranted to identify key characteristics that differentiate children admitted to nonpediatric hospitals who are subsequently transferred to pediatric hospitals with ICU facilities versus the children who are not transferred. Also, in‐depth study of the decision‐making that underlies interhospital transfer of critically ill or injured children to hospitals with ICU facilities for advanced care after initial hospitalization is vital to improved understanding of factors that might contribute to the extensive resource consumption and mortality burden borne by these children. The existence and effectiveness of interhospital transfer agreements at the state level needs to be examined specifically as it relates to patterns and clinical outcomes of interhospital transfer of critically ill and injured children in the US.

In conclusion, in this multiyear, statewide sample among critically ill and injured children enrolled by a statewide public payer, clinical outcomes were worse and resource consumption higher, among children who underwent interhospital transfer after initial hospitalization compared with those transferred directly from referring EDs. The findings raise the possibility that more timely transfer of some patients directly from community hospital EDs to regional ICUs might improve survival and reduce resource consumption.

Efforts to improve the care of critically ill and injured children may be enhanced by improved understanding of the medical decision‐making underlying interhospital transfer; application of innovative methods to identify and ensure rapid access to clinical expertise for children initially admitted to hospitals without pediatric intensive care facilities who might subsequently require intensive care; and routine reassessment of hospitalized children to ensure effective and efficient triage and re‐triage at the ED, ward, and ICU levels of referring hospitals.

Interhospital transfer of critically ill and injured children is necessitated by variation in resource availability between hospitals. Critically ill children judged in need of clinical services or expertise not locally available undergo transfer to hospitals with more appropriate resource capabilities and expertise, with the expectation that clinical outcomes of transfer will be better than nontransfer.

Significant variation both in the availability of pediatric critical care services across US hospitals1 and in child mortality among hospitals without pediatric critical care services2 suggests that interhospital transfer will remain an integral part of healthcare delivery for critically ill and injured children. Timely provision of definitive care for acute life‐threatening disease is associated with good clinical outcomes.3, 4 While prior studies have examined clinical outcomes and resource consumption among critically ill adults who underwent interhospital transfer for intensive care,59 there is scarce information regarding clinical characteristics and outcomes of interhospital transfer for critically ill and injured children.

This study was conducted to test the hypothesis that, among critically ill and injured children who undergo interhospital transfer for intensive care, children transferred after an initial hospitalization at the referring facility will have higher mortality, longer length of stay (LOS), and higher resource consumption than children transferred directly from the emergency department (ED) of the referring hospitals.

METHODS

Study Design

We conducted a secondary analysis of administrative claims data from the Michigan Medicaid program for the period January 1, 2002, to December 31, 2004. The data included all paid claims for health services rendered to enrollees in the Medicaid program. The Institutional Review Board of the University of Michigan Medical School approved the study.

Study Sample and Variable Identification

A 3‐step approach was employed to identify interhospital transfer admissions for intensive care of children. Initially, the Medicaid claims were queried to identify all hospitalizations for children 018 years who received intensive care services, using Medicare revenue codes.10 Admissions for neonatal intensive care were excluded from the analysis. The American Hospital Association Guide to the Health Care Field, a compendium of US healthcare facilities, was used to verify the presence of intensive care facilities.11, 12 Subsequently, to identify the subset of children who underwent interhospital transfer, data were queried for the presence of claims from another hospital, and the date of discharge from the referring hospital had to be the same as the date of admission to the receiving hospital intensive care unit (ICU). Finally, to ascertain the source of interhospital transfer, Medicare revenue codes and current procedural terminology (CPT) codes were used to identify claims for receipt of services at specific sites within the referring hospital; namely, the ED, ward, or the ICU. This information was used to categorize admissions into 1 of 3 pathways of interhospital transfer:

  • ED transferFrom the ED of the referring hospital to the ICU of the receiving hospital.

  • Ward transferFrom the wards of the referring hospital to the ICU of the receiving hospital.

  • Inter‐ICU transferFrom the ICU of the referring hospital to the ICU of the receiving hospital.

 

Dependent Variables

Mortality at the Receiving Hospital

This is determined by linkage to vital statistics records maintained by the Michigan Department of Community Health, Division of Vital Records and Health Statistics.

LOS at the Receiving Hospital

This is determined as the count of days of hospitalization at the receiving hospital. Of note, this includes ICU days and non‐ICU days at the receiving hospital.

Independent Variables

Source of Interhospital Transfer

The main (exposure) independent variable. Categorized into ED, ward, or inter‐ICU transfers, as described.

Patient Demographics

Age and gender.

Comorbid Illness

Determined using International Classification of Diseases, ninth revision (ICD‐9) diagnosis codes, applying methodology as described.13

Organ Dysfunction at the Referring and Receiving Hospitals

Determined using ICD‐9 diagnosis codes, applying methodology as described.14

Patient Diagnostic Categories

Eleven diagnostic categories were created based on primary admission diagnoses (Appendix A).

LOS at the Referring Hospital

Determined as the count of days of hospitalization at the referring hospital.

Receipt of Cardiopulmonary Resuscitation (CPR) on the Date of Interhospital Transfer

Determined using procedure codes.

Receipt of Medical‐Surgical Procedures at the Receiving Hospital

Identified through the use of ICD‐9 procedure codes, CPT codes, and Healthcare Common Procedure Coding System codes. The procedures are listed in Appendix B.

Statistical Analysis

Descriptive statistics were used to characterize the study sample. According to the 3 sources of interhospital transfer, patient characteristics (age, gender, presence of organ dysfunction, and comorbid illness), median LOS at the referring hospital, and receipt of CPR on the date of interhospital transfer were compared using chi‐square tests for categorical variables, and Kruskal‐Wallis tests for continuous variables. Similarly, outcome variables of in‐hospital mortality and median LOS at the receiving hospital were compared across the 3 sources of interhospital transfer. Analysis of variance was used to compare mean LOS at the receiving hospital across the 3 sources of interhospital transfer. Median (with interquartile range [IQR]) and mean (with standard deviation [SD]) values are presented to describe LOS, given skew in LOS data.

To account for potential confounding of LOS and mortality at the receiving hospital by the presence of organ dysfunction and comorbid illness1316 at the referring hospital, multivariate logistic regression and multiple linear regression analyses were conducted to estimate the odds of in‐hospital mortality and the incremental LOS, respectively, for ward and inter‐ICU transfers, compared with ED transfers. Statistical analyses were conducted using Stata 8 for windows (Stata Corporation, College Station, TX). A 2‐tailed level of 0.05 was used as the threshold for statistical significance.

RESULTS

Patient Characteristics

Of 1,643 transfer admissions for intensive care during the study period, 1022 (62%) were ED transfers, 512 (31%) were ward transfers, and 109 (7%) were inter‐ICU transfers. The average age was 2 years, with male gender (57%) predominance. Comorbid illness was present in 19% of admissions, while 11% had evidence of organ dysfunction at the referring hospital. Table 1 presents key patient demographic and clinical characteristics at the referring hospitals, by transfer source. Inter‐ICU and ward transfers were younger than ED transfers, and had a higher preponderance of comorbid illness and organ dysfunction. At the time of interhospital transfer, compared with ED transfers, the proportion of admissions with organ dysfunction (a marker of illness severity) was 3‐fold and 8‐fold higher among ward and inter‐ICU transfers, respectively.

Patient Characteristics at the Referring Hospital According to Transfer Source
 Transfer SourceP
CharacteristicsED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)
  • NOTE: Transfer source: ED, transfer admission from the emergency department of the referring hospital to the intensive care unit of the receiving hospital. Ward, transfer admission from the ward of the referring hospital to the intensive care unit of the receiving hospital. Inter‐ICU, transfer admission from the intensive care unit of the referring hospital to the intensive care unit of the receiving hospital.

  • Abbreviations: ED, emergency department; ICU, intensive care unit; IQR, interquartile range; SD, standard deviation.

Median age in years (IQR)2 (09)1 (07)1 (010)<0.01
Male (%)57.856.247.60.13
Comorbid illness (% )13.125.050.5<0.01
Pretransfer hospital length of stay (days)    
Median (IQR)01 (02)3 (18)<0.01
Mean (SD)0.2 (5.2)1.6 (4.8)9.7 (18.0)<0.01
Pretransfer organ dysfunction (%)5.514.540.4<0.01

Patterns of Transfer

The leading diagnoses among all children were respiratory disease, trauma, and neurological disease (Table 2), with some variation in diagnoses by source of interhospital transfer. For example, cardiovascular disease was the second leading diagnosis after respiratory disease among the inter‐ICU transfers, while more children with endocrine disease (predominantly diabetic ketoacidosis), traumatic injury, or drug poisoning were transferred directly from the ED, than from the ward or the ICU settings. For burn care, 80% (45/56) of all transfer admissions were direct from the ED (Table 3). The majority (78%) of children with traumatic injuries were directly transferred from the ED to the ICU, while the remainder were transferred after initial care delivered on the ward (18%) or ICU (4%) settings prior to interhospital transfer for definitive intensive trauma care. Importantly, among the inter‐ICU transfers, 104 (95%) were transferred to pediatric ICUs from referring hospitals with adult and pediatric ICU facilities, suggesting uptransfer for specialized care. Five children were transferred between hospitals with adult ICU facilities.

Primary Diagnostic Categories According to Transfer Source
  Transfer Source
Diagnostic Category (%)Overall* (n = 1639)ED* (n = 1018)Ward (n = 512)Inter‐ICU (n = 109)
  • Diagnoses were missing in 4 admissions.

Respiratory disease35.132.841.028.4
Trauma16.220.59.29.1
Neurological disease12.412.512.311.9
Gastrointestinal disease6.75.47.411.9
Infectious disease5.84.08.410.0
Endocrine disease5.57.91.80
Drug overdose/poisoning5.06.42.91.8
Cardiovascular disease4.82.86.316.5
Hematologic/oncologic disease2.01.62.91.8
Cardiac arrest0.200.60.9
Other diagnoses6.25.47.27.7
Ten Leading Medical‐Surgical Procedures and Services Rendered at the Receiving Hospital According to Transfer Source
  Transfer Source 
Characteristics (%)Overall (n = 1643)ED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)P
Respiratory26.819.036.754.1<0.01
Radiological21.219.520.541.3<0.01
Vascular access20.015.227.033.0<0.01
Gastrointestinal3.93.03.712.8<0.01
Neurological3.83.23.710.1<0.01
Cardiovascular3.61.84.118.4<0.01
Burn care3.44.52.00<0.01
General surgery3.22.14.38.3<0.01
Dialysis2.62.02.58.3<0.01
ECMO2.11.32.29.2<0.01

CPR was performed on the date of interhospital transfer for 23 patients (1.4% of the sample), of whom 13 (56.5%) were ward transfers, 8 (34.8%) were inter‐ICU transfers, and 2 (8.7%) were ED transfers (P < 0.02). Two‐thirds of these children did not survive subsequent hospitalization at the receiving hospitals.

Clinical Outcomes and Resource Utilization at the Receiving Hospitals

At the receiving hospitals, other than burn care, medical‐surgical procedures were performed most often among the inter‐ICU transfers. Ward transfers also had higher receipt of procedures compared with ED transfers (Table 3). The inter‐ICU and ward transfers had a higher preponderance of organ dysfunction at the receiving hospitals, compared to the ED transfers (38.5% and 29.3% versus 20.8%, P < 0.01).

Clinical outcomes at the receiving hospitals varied significantly according to the source of interhospital transfer (Table 4). Sixty‐six (4%) of patients died at the receiving hospitals. In comparison with ED transfers, unadjusted in‐hospital mortality was 2‐fold and 3‐fold higher among the ward and inter‐ICU transfers, respectively. Also, hospital LOS was significantly longer among the ward and inter‐ICU transfers than for the ED transfers.

Patient Unadjusted Outcomes at the Receiving Hospital According to Transfer Source
 Transfer Source 
CharacteristicsED (n = 1022)Ward (n = 512)Inter‐ICU (n = 109)P
  • Abbreviations: IQR, interquartile range; SD, standard deviation.

Mortality (%)2.85.58.3<0.01
Length of stay (days)    
Median (IQR)3 (27)5 (312)13 (724)<0.01
Mean (SD)6.7 (10.4)8.5 (9.2)21.4 (22.9)<0.01

In multivariate analyses adjusting for patient age, and the presence of comorbid illness and organ dysfunction at the referring hospital, compared with ED transfers, odds of mortality were significantly higher (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.023.03) for ward transfers. Inter‐ICU transfers also had higher odds of mortality (OR, 2.07; 95% CI, 0.884.86), without achieving statistical significance. Similarly, compared with ED transfers, LOS at the receiving hospital was longer by 1.5 days (95% CI, 0.32.7 days) for ward transfers, and by 13.5 days (95% CI, 11.115.8 days) for inter‐ICU transfers.

DISCUSSION

This study is the first to highlight significant variation in clinical outcomes and resource consumption after interhospital transfer of critically ill and injured children, depending on the source of transfer. In comparison with children transferred directly from the referring hospitals' ED settings, children transferred from the referring hospitals' wards had higher mortality, while those who underwent inter‐ICU transfer had significantly higher resource consumption. In addition, ward transfers had the highest proportion of children who underwent CPR on the date of interhospital transfer, highlighting elevated severity of disease prior to transfer and an urgent need for improved understanding of pretransfer clinical care and medical decision‐making. The findings raise the possibility that more timely transfer of some patients directly from community hospital EDs to regional ICUs might improve survival and reduce resource consumption.

Although interhospital transfers are common in everyday clinical practice, there has been a knowledge gap in pediatric acute and critical care medicine regarding the clinical outcomes and resource consumption among children who undergo such transfers. Findings from the current study narrow this gap by relating triage at the referring hospitals to clinical outcomes and resource utilization at the receiving hospitals.

Certain distinct transfer patterns were observed. Most children with burn injury underwent direct transfer from the ED to the ICU; this transfer pattern may be related both to the limited availability of ICUs with burn care capability in Michigan and to the acuity of burn injuries, which often mandates immediate triage to hospitals with intensive burn care facilities. Conversely, while the majority of children with traumatic injuries were directly transferred from emergency to intensive care, over one‐fifth were transferred after initial care delivered on the ward or ICU settings prior to interhospital transfer for definitive intensive trauma care. Such imperfect regionalization of trauma care suggests further study of clinical outcomes and resource utilization among injured children is warranted. Likewise, cardiovascular disease was prominent among the inter‐ICU transfers, suggesting a clinical practice pattern of stabilization and resuscitation at the initial ICU prior to interhospital vertical or uptransfer for definitive cardiac care at the receiving hospitals.

It remains unknown whether the timing of interhospital transfer of critically ill children is a determinant of clinical outcomes. Prior studies among adults have reported higher mortality with prolonged duration of pre‐ICU care on the ward.4, 17 In the current study, ward and inter‐ICU transfers were initially hospitalized for a median of 1 and 3 days, respectively, prior to transfer. While we could not determine from administrative data what the precise triggers for interhospital transfer in this study were, it is instructive to note that ward transfers comprised more than one‐half of all children who received CPR on the date of transfer. For children who received CPR, severe clinical deterioration likely triggered transfer to hospitals with ICU facilities, but because only a minority of children received CPR overall, other triggers of transfer warrant investigation. For most of the children transferred, it seems plausible that the precipitant of transfer was likely a mismatch of their clinical status with the clinical capacities of the facilities where they were initially hospitalized. Future work should investigate if there is an association between clinical outcomes at the receiving hospitals, and both the timing of interhospital transfer and the clinical status of patients at transfer.

Importantly, compared with ED transfers, ward transfers demonstrated elevated odds of mortality after adjustment for coexisting comorbid illness, patient age, and pretransfer organ dysfunction at the referring hospital. Some possible explanations for this finding include the progression of disease while receiving care on the ward, or suboptimal access to ICU facilities due to barriers to transfer at either the referring or receiving hospitals. Importantly, progression of disease in ward settings may be detected by early identification of children at high risk of clinical deterioration on the wards of hospitals without ICU facilities, prior to cardiopulmonary arrest, because death after CPR may not be averted with subsequent ICU care.18

Various approaches to facilitate rapid and appropriate triage and reassessment of children in hospitals without ICU facilities, prior to severe clinical deterioration or need for CPR, must be investigated. These approaches might include in‐hospital measures such as the establishment of medical emergency teams to respond to clinical deterioration on the wards19 or collaborative interhospital measures such as the use of telemedicine20 or similar remote communication/triage systems to enhance communication between clinical caregivers at hospitals with ICU facilities and those in hospitals without ICU facilities. Furthermore, interhospital transfer agreements may facilitate expeditious and appropriate transfer of severely ill patients to hospitals with ICU facilities.

Access to hospitals with ICU facilities might also influence outcomes for critically ill children admitted initially to wards of hospitals without ICU facilities. Kanter2 reported significant variation in mortality among children who received care at New York hospitals without ICU facilities. Of note, 27% of statewide pediatric inpatient deaths occurred in those hospitals without ICU facilities. It appeared that, while some pediatric deaths in hospitals without ICU facilities were expected, regional variation in such mortality might have been associated with reduced access to, or poor utilization of, hospitals with ICU facilities. Barriers to interhospital transfers might include underrecognition of mismatch between patient illness severity and hospital capability at referring hospitals, or lack of capacity to accept transfers at the receiving hospitals. Further study is warranted to investigate clinical decision‐making underlying the initiation of the interhospital transfer processes, and procedural or institutional barriers that might hinder the transfer of critically ill children from hospitals without ICU facilities.

Resource consumption at the receiving hospitals, measured by hospital LOS and receipt of medical‐surgical procedures, was highest among the inter‐ICU transfers. This was an expected finding, given the high frequency of organ dysfunction among the inter‐ICU transfers, before and after interhospital transfer. These patients had the highest use of advanced and resource‐intensive technology, including continuous renal replacement therapy, extracorporeal membrane oxygenation, and cardiovascular procedures such as open‐heart surgery. In addition, the duration of hospitalization at the receiving hospital was 2 weeks longer among the inter‐ICU transfers when compared with the ED transfers. Such prolonged hospitalization has been previously associated with significantly increased resource consumption.4, 6 In the absence of physiologic data pertaining to illness severity, however, it is unknown whether this observed differential LOS by source of interhospital transfer might be attributable to both unobserved illness severity and/or extensive in‐hospital post‐ICU multidisciplinary rehabilitative care for inter‐ICU transfer patients, compared with ED transfer patients.

Our study findings need to be interpreted in light of certain limitations. Administrative claims data do not allow for assessment of the quality of hospital care, a factor that might play an important role in patient clinical outcomes. The data lacked any physiologic information that might enhance the ability to estimate patient severity of illness; the analysis used the presence of organ dysfunction at the referring hospitals as a proxy for illness severity. The use of diagnosis codebased measures of severity adjustment, as employed in the current study, however, has been reported to be comparable with clinical severity measures because of the relatively complete capture of diagnosis codes for life‐threatening conditions occurring late in the hospitalization, such as prior to interhospital transfer in the current study.2123

The absence of clinical information prevented assessment of the likelihood of in‐hospital morbidity, transport complications, and need for various therapeutic interventions after ICU care, which are also highly relevant outcomes of interhospital transfers. It is unknown if the small sample size among inter‐ICU transfers limited the ability to demonstrate a statistically significant difference in odds of mortality among inter‐ICU transfers compared with ED transfers.

Also, the identification of diagnoses and procedures was made using multiple coding instruments and is therefore susceptible to inaccuracies of detection and attribution that may have biased the findings. Study findings did not include cost, because cost data were not available for children enrolled in Medicaid managed care plans under capitated arrangements. Finally, it is unknown how generalizable the current study findings might be to children with private insurance, or to children who are uninsured.

The study findings highlight potential opportunities for future research. Further studies are warranted to identify key characteristics that differentiate children admitted to nonpediatric hospitals who are subsequently transferred to pediatric hospitals with ICU facilities versus the children who are not transferred. Also, in‐depth study of the decision‐making that underlies interhospital transfer of critically ill or injured children to hospitals with ICU facilities for advanced care after initial hospitalization is vital to improved understanding of factors that might contribute to the extensive resource consumption and mortality burden borne by these children. The existence and effectiveness of interhospital transfer agreements at the state level needs to be examined specifically as it relates to patterns and clinical outcomes of interhospital transfer of critically ill and injured children in the US.

In conclusion, in this multiyear, statewide sample among critically ill and injured children enrolled by a statewide public payer, clinical outcomes were worse and resource consumption higher, among children who underwent interhospital transfer after initial hospitalization compared with those transferred directly from referring EDs. The findings raise the possibility that more timely transfer of some patients directly from community hospital EDs to regional ICUs might improve survival and reduce resource consumption.

Efforts to improve the care of critically ill and injured children may be enhanced by improved understanding of the medical decision‐making underlying interhospital transfer; application of innovative methods to identify and ensure rapid access to clinical expertise for children initially admitted to hospitals without pediatric intensive care facilities who might subsequently require intensive care; and routine reassessment of hospitalized children to ensure effective and efficient triage and re‐triage at the ED, ward, and ICU levels of referring hospitals.

References
  1. Odetola FO,Clark SJ,Freed GL,Bratton SL,Davis MM.A national survey of pediatric critical care resources in the United States.Pediatrics.2005;115:e382386.
  2. Kanter RK.Regional variation in child mortality at hospitals lacking a pediatric intensive care unit.Crit Care Med.2002;30:9499.
  3. Sampalis JS,Denis R,Frechette P,Brown R,Fleiszer D,Mulder D.Direct transport to tertiary trauma centers versus transfer from lower level facilities: impact on mortality and morbidity among patients with major trauma.J Trauma.1997;43:288296.
  4. Rapoport J,Teres D,Lemeshow S,Harris D.Timing of intensive care unit admission in relation to ICU outcome.Crit Care Med.1990;18:12311235.
  5. Escarce JJ,Kelley MA:Admission source to the medical intensive care unit predicts hospital death independent of APACHE II score.JAMA.1990;264:23892394.
  6. Rosenberg AL,Hofer TP,Strachan C,Watts CM,Hayward RA.Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures.Ann Intern Med.2003;138:882890.
  7. Borlase BC,Baxter JK,Kenney PR,Forse RA,Benotti PN,Blackburn GL.Elective intrahospital admissions versus acute interhospital transfers to a surgical intensive care unit: cost and outcome prediction.J Trauma.1991;31:915918.
  8. Combes A,Luyt CE,Trouillet JL,Chastre J,Gibert C.Adverse effect on a referral intensive care unit's performance of accepting patients transferred from another intensive care unit.Crit Care Med.2005;33:705710.
  9. Durairaj L,Will JG,Torner JC,Doebbeling BN.Prognostic factors for mortality following interhospital transfers to the medical intensive care unit of a tertiary referral center.Crit Care Med.2003;31:19811986.
  10. National Government Services. Medicare UB‐04 Revenue Codes. Available at http://www.ngsmedicare.com/NGSMedicare/PartA/EducationandSupport/ToolsandMaterials/0908ub‐04.pdf. Accessed April 7,2008.
  11. American Hospital Association.AHA Guide to the Health Care Field.2002 ed.Chicago:American Hospital Association;2002.
  12. American Hospital Association.AHA Guide to the Health Care Field.2003 ed.Chicago:American Hospital Association;2003.
  13. Feudtner C,Christakis DA,Connell FA.Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997.Pediatrics.2000;106:205209.
  14. Johnston JA,Yi MS,Britto MT,Mrus JM.Importance of organ dysfunction in determining hospital outcomes in children.J Pediatr.2004;144:595601.
  15. Leclerc F,Leteurtre S,Duhamel A, et al.Cumulative influence of organ dysfunctions and septic state on mortality of critically ill children.Am J Respir Crit Care Med.2005;171:348353.
  16. Watson RS,Carcillo JA,Linde‐Zwirble WT,Clermont G,Lidicker J,Angus DC.The epidemiology of severe sepsis in children in the United States.Am J Respir Crit Care Med.2003;167:695701.
  17. Goldhill DR,McNarry AF,Hadjianastassiou VG,Tekkis PP.The longer patients are in hospital before intensive care admission the higher their mortality.Intensive Care Med.2004;30:19081913.
  18. Tibballs J,Kinney S.A prospective study of outcome of in‐patient pediatric cardiopulmonary arrest.Resuscitation.2006;71:310318.
  19. Sharek PJ,Parast LM,Leong K, et al.Effect of a rapid response team on hospital‐wide mortality and code rates outside the ICU in a children's hospital.JAMA.2007;298:22672274.
  20. Marcin JP,Nesbitt TS,Kallas HJ,Struve SN,Traugott CA,Dimand RJ.Use of telemedicine to provide pediatric critical care consultations to underserved rural northern California.J Pediatr.2004;144:375380.
  21. Romano PS,Chan BK.Risk‐adjusting acute myocardial infarction mortality: are APR‐DRGs the right tool?Health Serv Res.2000;34:14691489.
  22. Iezzoni LI,Ash AS,Shwartz M,Landon BE,Mackiernan YD.Predicting in‐hospital deaths from coronary artery bypass graft surgery: do different severity measures give different predictions?Med Care.1998;36:2839.
  23. Odetola FO,Gebremariam A,Freed GL.Patient and hospital correlates of clinical outcomes and resource‐utilization in severe pediatric sepsis.Pediatrics.2007;119:487494.
References
  1. Odetola FO,Clark SJ,Freed GL,Bratton SL,Davis MM.A national survey of pediatric critical care resources in the United States.Pediatrics.2005;115:e382386.
  2. Kanter RK.Regional variation in child mortality at hospitals lacking a pediatric intensive care unit.Crit Care Med.2002;30:9499.
  3. Sampalis JS,Denis R,Frechette P,Brown R,Fleiszer D,Mulder D.Direct transport to tertiary trauma centers versus transfer from lower level facilities: impact on mortality and morbidity among patients with major trauma.J Trauma.1997;43:288296.
  4. Rapoport J,Teres D,Lemeshow S,Harris D.Timing of intensive care unit admission in relation to ICU outcome.Crit Care Med.1990;18:12311235.
  5. Escarce JJ,Kelley MA:Admission source to the medical intensive care unit predicts hospital death independent of APACHE II score.JAMA.1990;264:23892394.
  6. Rosenberg AL,Hofer TP,Strachan C,Watts CM,Hayward RA.Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures.Ann Intern Med.2003;138:882890.
  7. Borlase BC,Baxter JK,Kenney PR,Forse RA,Benotti PN,Blackburn GL.Elective intrahospital admissions versus acute interhospital transfers to a surgical intensive care unit: cost and outcome prediction.J Trauma.1991;31:915918.
  8. Combes A,Luyt CE,Trouillet JL,Chastre J,Gibert C.Adverse effect on a referral intensive care unit's performance of accepting patients transferred from another intensive care unit.Crit Care Med.2005;33:705710.
  9. Durairaj L,Will JG,Torner JC,Doebbeling BN.Prognostic factors for mortality following interhospital transfers to the medical intensive care unit of a tertiary referral center.Crit Care Med.2003;31:19811986.
  10. National Government Services. Medicare UB‐04 Revenue Codes. Available at http://www.ngsmedicare.com/NGSMedicare/PartA/EducationandSupport/ToolsandMaterials/0908ub‐04.pdf. Accessed April 7,2008.
  11. American Hospital Association.AHA Guide to the Health Care Field.2002 ed.Chicago:American Hospital Association;2002.
  12. American Hospital Association.AHA Guide to the Health Care Field.2003 ed.Chicago:American Hospital Association;2003.
  13. Feudtner C,Christakis DA,Connell FA.Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997.Pediatrics.2000;106:205209.
  14. Johnston JA,Yi MS,Britto MT,Mrus JM.Importance of organ dysfunction in determining hospital outcomes in children.J Pediatr.2004;144:595601.
  15. Leclerc F,Leteurtre S,Duhamel A, et al.Cumulative influence of organ dysfunctions and septic state on mortality of critically ill children.Am J Respir Crit Care Med.2005;171:348353.
  16. Watson RS,Carcillo JA,Linde‐Zwirble WT,Clermont G,Lidicker J,Angus DC.The epidemiology of severe sepsis in children in the United States.Am J Respir Crit Care Med.2003;167:695701.
  17. Goldhill DR,McNarry AF,Hadjianastassiou VG,Tekkis PP.The longer patients are in hospital before intensive care admission the higher their mortality.Intensive Care Med.2004;30:19081913.
  18. Tibballs J,Kinney S.A prospective study of outcome of in‐patient pediatric cardiopulmonary arrest.Resuscitation.2006;71:310318.
  19. Sharek PJ,Parast LM,Leong K, et al.Effect of a rapid response team on hospital‐wide mortality and code rates outside the ICU in a children's hospital.JAMA.2007;298:22672274.
  20. Marcin JP,Nesbitt TS,Kallas HJ,Struve SN,Traugott CA,Dimand RJ.Use of telemedicine to provide pediatric critical care consultations to underserved rural northern California.J Pediatr.2004;144:375380.
  21. Romano PS,Chan BK.Risk‐adjusting acute myocardial infarction mortality: are APR‐DRGs the right tool?Health Serv Res.2000;34:14691489.
  22. Iezzoni LI,Ash AS,Shwartz M,Landon BE,Mackiernan YD.Predicting in‐hospital deaths from coronary artery bypass graft surgery: do different severity measures give different predictions?Med Care.1998;36:2839.
  23. Odetola FO,Gebremariam A,Freed GL.Patient and hospital correlates of clinical outcomes and resource‐utilization in severe pediatric sepsis.Pediatrics.2007;119:487494.
Issue
Journal of Hospital Medicine - 4(3)
Issue
Journal of Hospital Medicine - 4(3)
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164-170
Page Number
164-170
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Interhospital transfer of critically ill and injured children: An evaluation of transfer patterns, resource utilization, and clinical outcomes
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Interhospital transfer of critically ill and injured children: An evaluation of transfer patterns, resource utilization, and clinical outcomes
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health resources, hospitalized children, length of stay, mortality, triage
Legacy Keywords
health resources, hospitalized children, length of stay, mortality, triage
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