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Bipolar disorder diagnoses higher than referrals

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Bipolar disorder diagnoses higher than referrals

Fewer patients were referred to psychiatrists for suspected bipolar disorder than the number of patients diagnosed with the illness, Canadian researchers reported in the Journal of Affective Disorders.

Dr. Andrée Daigneault and her colleagues found that, over a 10-year period, the number of patients referred for suspicion of bipolar disorder (n = 583) was lower than the number of bipolar disorder diagnoses (n = 640).

To conduct the study, the investigators looked at records from Hôpital du Sacré-Coeur de Montréal’s Module Evaluation/Liaison (MEL) division. The hospital’s psychiatrists examined 18,111 patients from 1998 to 2010 and carried out 10,492 (58%) assessments, reported Dr. Daigneault of the hospital and the Douglas Mental Health University Institute, Montreal, and her associates.

Of all patients assessed by the MEL, 583 patients were referred for a suspicion of bipolar disorder, while 640 patients received the diagnosis from a MEL psychiatrist (40.3% type I, 40.5% type II). The proportion of patients referred to the MEL for suspicion of bipolar disorder remained stable over the 10 years of the study and held between 2.2% and 4.6% annually. Both bipolar I and II disorders were more commonly diagnosed in secondary care than in primary, the authors noted. They also found no increase in the proportion of bipolar disorder referrals over the 10 years of the study.

“If the psychiatric and medical communities seem to become increasing familiar with [bipolar disorder], our study fails to demonstrate that [bipolar disorder] is overly suspected or identified in primary care,” the authors wrote. They said their data suggest that general practitioners “have not been influenced by the popularity of [bipolar disorder], as could have been suggested if rates of [bipolar] suspicions increased over time or surpassed that of [bipolar] diagnoses.”

Read the full article here: (J. Affect. Disord. 2015;174:225-32 [doi:10.1016/j.jad.2014.10.057]).

[email protected]

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Fewer patients were referred to psychiatrists for suspected bipolar disorder than the number of patients diagnosed with the illness, Canadian researchers reported in the Journal of Affective Disorders.

Dr. Andrée Daigneault and her colleagues found that, over a 10-year period, the number of patients referred for suspicion of bipolar disorder (n = 583) was lower than the number of bipolar disorder diagnoses (n = 640).

To conduct the study, the investigators looked at records from Hôpital du Sacré-Coeur de Montréal’s Module Evaluation/Liaison (MEL) division. The hospital’s psychiatrists examined 18,111 patients from 1998 to 2010 and carried out 10,492 (58%) assessments, reported Dr. Daigneault of the hospital and the Douglas Mental Health University Institute, Montreal, and her associates.

Of all patients assessed by the MEL, 583 patients were referred for a suspicion of bipolar disorder, while 640 patients received the diagnosis from a MEL psychiatrist (40.3% type I, 40.5% type II). The proportion of patients referred to the MEL for suspicion of bipolar disorder remained stable over the 10 years of the study and held between 2.2% and 4.6% annually. Both bipolar I and II disorders were more commonly diagnosed in secondary care than in primary, the authors noted. They also found no increase in the proportion of bipolar disorder referrals over the 10 years of the study.

“If the psychiatric and medical communities seem to become increasing familiar with [bipolar disorder], our study fails to demonstrate that [bipolar disorder] is overly suspected or identified in primary care,” the authors wrote. They said their data suggest that general practitioners “have not been influenced by the popularity of [bipolar disorder], as could have been suggested if rates of [bipolar] suspicions increased over time or surpassed that of [bipolar] diagnoses.”

Read the full article here: (J. Affect. Disord. 2015;174:225-32 [doi:10.1016/j.jad.2014.10.057]).

[email protected]

Fewer patients were referred to psychiatrists for suspected bipolar disorder than the number of patients diagnosed with the illness, Canadian researchers reported in the Journal of Affective Disorders.

Dr. Andrée Daigneault and her colleagues found that, over a 10-year period, the number of patients referred for suspicion of bipolar disorder (n = 583) was lower than the number of bipolar disorder diagnoses (n = 640).

To conduct the study, the investigators looked at records from Hôpital du Sacré-Coeur de Montréal’s Module Evaluation/Liaison (MEL) division. The hospital’s psychiatrists examined 18,111 patients from 1998 to 2010 and carried out 10,492 (58%) assessments, reported Dr. Daigneault of the hospital and the Douglas Mental Health University Institute, Montreal, and her associates.

Of all patients assessed by the MEL, 583 patients were referred for a suspicion of bipolar disorder, while 640 patients received the diagnosis from a MEL psychiatrist (40.3% type I, 40.5% type II). The proportion of patients referred to the MEL for suspicion of bipolar disorder remained stable over the 10 years of the study and held between 2.2% and 4.6% annually. Both bipolar I and II disorders were more commonly diagnosed in secondary care than in primary, the authors noted. They also found no increase in the proportion of bipolar disorder referrals over the 10 years of the study.

“If the psychiatric and medical communities seem to become increasing familiar with [bipolar disorder], our study fails to demonstrate that [bipolar disorder] is overly suspected or identified in primary care,” the authors wrote. They said their data suggest that general practitioners “have not been influenced by the popularity of [bipolar disorder], as could have been suggested if rates of [bipolar] suspicions increased over time or surpassed that of [bipolar] diagnoses.”

Read the full article here: (J. Affect. Disord. 2015;174:225-32 [doi:10.1016/j.jad.2014.10.057]).

[email protected]

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Asenapine for pediatric bipolar disorder: New indication

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Asenapine for pediatric bipolar disorder: New indication

Asenapine an atypical antipsychotic sold under the brand name Saphris, was granted a second, pediatric indi­cation by the FDA in March 2015 as mono­therapy for acute treatment of manic or mixed episodes of bipolar I disorder in chil­dren and adolescents age 10 to 17 (Table 1).1 (Asenapine was first approved in August 2009 as monotherapy or adjunctive therapy to lithium or valproate in adults for schizo­phrenia and bipolar I disorder.1,2)



Dosage and administration
Asenapine is available as 2.5-, 5-, and 10-mg sublingual tablets, the only atypical anti­psychotic with this formulation.1 The rec­ommended dosage for the new indication is 2.5 mg twice daily for 3 days, titrated to 5 mg twice daily, titrated again to 10 mg twice daily after 3 days.3 In a phase I study, pedi­atric patients appeared to be more sensitive to dystonia when the recommended dosage escalation schedule was not followed.3

In clinical trials, drinking water 2 to 5 minutes after taking asenapine decreased exposure to the drug. Instruct patients not to swallow the tablet and to avoid eating and drinking for 10 minutes after administration.3

For full prescribing information for pediat­ric and adult patients, see Reference 3.


Safety and efficacy
In a 3-week, placebo-controlled, double-blind trial of 403 patients, 302 children and adolescents age 10 to 17 received asenap­ine at fixed dosages of 2.5 to 10 mg twice daily; the remainder were given placebo. The Young Mania Rating Scale (YMRS) total score and Clinical Global Impressions Severity of Illness scores of patients who received asenapine improved significantly compared with those who received placebo, as measured by change from baseline to week 3 (Table 2).1



The safety and efficacy of asenapine has not been evaluated in pediatric bipolar dis­order patients age ≤10 or pediatric schizo­phrenia patients age ≤12, or as an adjunctive therapy in pediatric bipolar disorder patients.

Asenapine was not shown to be effective in pediatric patients with schizophrenia in an 8-week, placebo-controlled, double-blind trial.

The pharmacokinetics of asenapine in pediatric patients are similar to those seen in adults.


Adverse effects
In pediatric patients, the most common reported adverse effects of asenapine are:
   • dizziness
   • dysgeusia
   • fatigue
   • increased appetite
   • increased weight
   • nausea
   • oral paresthesia
   • somnolence.

Similar adverse effects were reported in the pediatric bipolar disorder and adult bipolar disorder clinical trials (Table 3).3 A complete list of reported adverse effects is given in the package insert.3


When treating pediatric patients, moni­tor the child’s weight gain against expected normal weight gain.

Asenapine is contraindicated in patients with hepatic impairment and those who have a hypersensitivity to asenapine or any components in its formulation.3

References


1. Actavis receives FDA approval of Saphris for pediatric patients with bipolar I disorder. Drugs.com. http://www.drugs.com/newdrugs/actavis-receivesfda-
approval-saphris-pediatric-patients-bipolardisorder-4188.html. Published March 2015. Accessed June 19, 2015.
2. Lincoln J, Preskon S. Asenapine for schizophrenia and bipolar I disorder. Current Psychiatry. 2009;12(8):75-76,83-85.
3. Saphris [package insert]. St. Louis, MO: Forest Pharmaceuticals; 2015.

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Asenapine an atypical antipsychotic sold under the brand name Saphris, was granted a second, pediatric indi­cation by the FDA in March 2015 as mono­therapy for acute treatment of manic or mixed episodes of bipolar I disorder in chil­dren and adolescents age 10 to 17 (Table 1).1 (Asenapine was first approved in August 2009 as monotherapy or adjunctive therapy to lithium or valproate in adults for schizo­phrenia and bipolar I disorder.1,2)



Dosage and administration
Asenapine is available as 2.5-, 5-, and 10-mg sublingual tablets, the only atypical anti­psychotic with this formulation.1 The rec­ommended dosage for the new indication is 2.5 mg twice daily for 3 days, titrated to 5 mg twice daily, titrated again to 10 mg twice daily after 3 days.3 In a phase I study, pedi­atric patients appeared to be more sensitive to dystonia when the recommended dosage escalation schedule was not followed.3

In clinical trials, drinking water 2 to 5 minutes after taking asenapine decreased exposure to the drug. Instruct patients not to swallow the tablet and to avoid eating and drinking for 10 minutes after administration.3

For full prescribing information for pediat­ric and adult patients, see Reference 3.


Safety and efficacy
In a 3-week, placebo-controlled, double-blind trial of 403 patients, 302 children and adolescents age 10 to 17 received asenap­ine at fixed dosages of 2.5 to 10 mg twice daily; the remainder were given placebo. The Young Mania Rating Scale (YMRS) total score and Clinical Global Impressions Severity of Illness scores of patients who received asenapine improved significantly compared with those who received placebo, as measured by change from baseline to week 3 (Table 2).1



The safety and efficacy of asenapine has not been evaluated in pediatric bipolar dis­order patients age ≤10 or pediatric schizo­phrenia patients age ≤12, or as an adjunctive therapy in pediatric bipolar disorder patients.

Asenapine was not shown to be effective in pediatric patients with schizophrenia in an 8-week, placebo-controlled, double-blind trial.

The pharmacokinetics of asenapine in pediatric patients are similar to those seen in adults.


Adverse effects
In pediatric patients, the most common reported adverse effects of asenapine are:
   • dizziness
   • dysgeusia
   • fatigue
   • increased appetite
   • increased weight
   • nausea
   • oral paresthesia
   • somnolence.

Similar adverse effects were reported in the pediatric bipolar disorder and adult bipolar disorder clinical trials (Table 3).3 A complete list of reported adverse effects is given in the package insert.3


When treating pediatric patients, moni­tor the child’s weight gain against expected normal weight gain.

Asenapine is contraindicated in patients with hepatic impairment and those who have a hypersensitivity to asenapine or any components in its formulation.3

Asenapine an atypical antipsychotic sold under the brand name Saphris, was granted a second, pediatric indi­cation by the FDA in March 2015 as mono­therapy for acute treatment of manic or mixed episodes of bipolar I disorder in chil­dren and adolescents age 10 to 17 (Table 1).1 (Asenapine was first approved in August 2009 as monotherapy or adjunctive therapy to lithium or valproate in adults for schizo­phrenia and bipolar I disorder.1,2)



Dosage and administration
Asenapine is available as 2.5-, 5-, and 10-mg sublingual tablets, the only atypical anti­psychotic with this formulation.1 The rec­ommended dosage for the new indication is 2.5 mg twice daily for 3 days, titrated to 5 mg twice daily, titrated again to 10 mg twice daily after 3 days.3 In a phase I study, pedi­atric patients appeared to be more sensitive to dystonia when the recommended dosage escalation schedule was not followed.3

In clinical trials, drinking water 2 to 5 minutes after taking asenapine decreased exposure to the drug. Instruct patients not to swallow the tablet and to avoid eating and drinking for 10 minutes after administration.3

For full prescribing information for pediat­ric and adult patients, see Reference 3.


Safety and efficacy
In a 3-week, placebo-controlled, double-blind trial of 403 patients, 302 children and adolescents age 10 to 17 received asenap­ine at fixed dosages of 2.5 to 10 mg twice daily; the remainder were given placebo. The Young Mania Rating Scale (YMRS) total score and Clinical Global Impressions Severity of Illness scores of patients who received asenapine improved significantly compared with those who received placebo, as measured by change from baseline to week 3 (Table 2).1



The safety and efficacy of asenapine has not been evaluated in pediatric bipolar dis­order patients age ≤10 or pediatric schizo­phrenia patients age ≤12, or as an adjunctive therapy in pediatric bipolar disorder patients.

Asenapine was not shown to be effective in pediatric patients with schizophrenia in an 8-week, placebo-controlled, double-blind trial.

The pharmacokinetics of asenapine in pediatric patients are similar to those seen in adults.


Adverse effects
In pediatric patients, the most common reported adverse effects of asenapine are:
   • dizziness
   • dysgeusia
   • fatigue
   • increased appetite
   • increased weight
   • nausea
   • oral paresthesia
   • somnolence.

Similar adverse effects were reported in the pediatric bipolar disorder and adult bipolar disorder clinical trials (Table 3).3 A complete list of reported adverse effects is given in the package insert.3


When treating pediatric patients, moni­tor the child’s weight gain against expected normal weight gain.

Asenapine is contraindicated in patients with hepatic impairment and those who have a hypersensitivity to asenapine or any components in its formulation.3

References


1. Actavis receives FDA approval of Saphris for pediatric patients with bipolar I disorder. Drugs.com. http://www.drugs.com/newdrugs/actavis-receivesfda-
approval-saphris-pediatric-patients-bipolardisorder-4188.html. Published March 2015. Accessed June 19, 2015.
2. Lincoln J, Preskon S. Asenapine for schizophrenia and bipolar I disorder. Current Psychiatry. 2009;12(8):75-76,83-85.
3. Saphris [package insert]. St. Louis, MO: Forest Pharmaceuticals; 2015.

References


1. Actavis receives FDA approval of Saphris for pediatric patients with bipolar I disorder. Drugs.com. http://www.drugs.com/newdrugs/actavis-receivesfda-
approval-saphris-pediatric-patients-bipolardisorder-4188.html. Published March 2015. Accessed June 19, 2015.
2. Lincoln J, Preskon S. Asenapine for schizophrenia and bipolar I disorder. Current Psychiatry. 2009;12(8):75-76,83-85.
3. Saphris [package insert]. St. Louis, MO: Forest Pharmaceuticals; 2015.

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Knowledge lacking on auditory hallucinations in bipolar, depressed patients

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Knowledge lacking on auditory hallucinations in bipolar, depressed patients

Research into auditory verbal hallucinations (AVH) in patients with bipolar disorder (BD) and major depressive disorder (MDD) is lacking in several important ways, according to a systematic review by Dr. Wei Lin Toh and associates.

While previous research indicates that a significant number of people with BD and MDD experience AVH, estimates vary widely, from 11.3% to 62.8% of BD patients, and 5.4% to 40.6% of MDD patients. One neuroimaging study found potential frontotemporal connectivity relating to AVH in bipolar patients.

No study has systematically investigated phenomenological characteristics of AVH in BD and MDD, a significant gap in knowledge relating to AVH in the two disorders. In addition, the investigators recommend research into links between AVH and delusions, as many BD patients and MDD patients experience both delusions and hallucinations of any sort.

“The topic of AVH remains a central but largely understudied symptom in BD, and more so, MDD. Further progress can only be achieved when phenomenological, cognitive, and neuroimaging research efforts go hand-in-hand,” concluded Dr. Toh of Swinburne University of Technology, Melbourne, and colleagues.

Find the full review in the Journal of Affective Disorders (May 28, 2015 [doi: 10.1016/j.jad.2015.05.040]).

[email protected]

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Research into auditory verbal hallucinations (AVH) in patients with bipolar disorder (BD) and major depressive disorder (MDD) is lacking in several important ways, according to a systematic review by Dr. Wei Lin Toh and associates.

While previous research indicates that a significant number of people with BD and MDD experience AVH, estimates vary widely, from 11.3% to 62.8% of BD patients, and 5.4% to 40.6% of MDD patients. One neuroimaging study found potential frontotemporal connectivity relating to AVH in bipolar patients.

No study has systematically investigated phenomenological characteristics of AVH in BD and MDD, a significant gap in knowledge relating to AVH in the two disorders. In addition, the investigators recommend research into links between AVH and delusions, as many BD patients and MDD patients experience both delusions and hallucinations of any sort.

“The topic of AVH remains a central but largely understudied symptom in BD, and more so, MDD. Further progress can only be achieved when phenomenological, cognitive, and neuroimaging research efforts go hand-in-hand,” concluded Dr. Toh of Swinburne University of Technology, Melbourne, and colleagues.

Find the full review in the Journal of Affective Disorders (May 28, 2015 [doi: 10.1016/j.jad.2015.05.040]).

[email protected]

Research into auditory verbal hallucinations (AVH) in patients with bipolar disorder (BD) and major depressive disorder (MDD) is lacking in several important ways, according to a systematic review by Dr. Wei Lin Toh and associates.

While previous research indicates that a significant number of people with BD and MDD experience AVH, estimates vary widely, from 11.3% to 62.8% of BD patients, and 5.4% to 40.6% of MDD patients. One neuroimaging study found potential frontotemporal connectivity relating to AVH in bipolar patients.

No study has systematically investigated phenomenological characteristics of AVH in BD and MDD, a significant gap in knowledge relating to AVH in the two disorders. In addition, the investigators recommend research into links between AVH and delusions, as many BD patients and MDD patients experience both delusions and hallucinations of any sort.

“The topic of AVH remains a central but largely understudied symptom in BD, and more so, MDD. Further progress can only be achieved when phenomenological, cognitive, and neuroimaging research efforts go hand-in-hand,” concluded Dr. Toh of Swinburne University of Technology, Melbourne, and colleagues.

Find the full review in the Journal of Affective Disorders (May 28, 2015 [doi: 10.1016/j.jad.2015.05.040]).

[email protected]

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Bipolar disorder patients may underestimate their sleep quality

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Bipolar disorder patients may underestimate their sleep quality

MIAMI BEACH – Patients with active bipolar disorder significantly underestimated the quality of their sleep, despite having sleep quality comparable to that of healthy controls.

Sleep complaints are common among individuals with bipolar disorder, and addressing disruptive and troubling sleep problems can be an important component of treating bipolar disorder, noted Dr. Venkatesh Krishnamurthy and his collaborators at Penn State University (Hershey, Pa.).

“Mood state may affect perception of sleep, and the impact of mood state on subjective-objective differences of sleep parameters needs to be further explored,” the researchers noted.

They reported their comparison of subjective and objective measures of sleep for symptomatic patients with bipolar disorder in a poster presentation at a meeting of the American Society for Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting.

The study researchers evaluated 30 individuals with symptomatic bipolar disorder, compared with 31 healthy controls, reported Dr. Krishnamurthy, assistant professor at the department of psychiatry’s Sleep Research and Treatment Center at Penn State’s Milton S. Hershey Medical Center. Patients with bipolar disorder were inpatients or in a partial hospitalization program; 11 patients had bipolar depression, 18 had mixed-state bipolar disorder, and 1 had bipolar disorder with a manic episode, Dr. Krishnamurthy said in an interview.

To compare subjective and objective measures of sleep in the two groups, the researchers administered a sleep-quality questionnaire and used actigraphy to document sleep objectively.

The Pittsburgh Sleep Quality Index (PSQI), the instrument used for subjective assessment, is a self-reporting tool that asks patients to report on aspects of sleep quality, usual sleep duration, daytime sleepiness, and sleep medication use over the past month.

The actigraphs used in the study used accelerometers to measure patient movement at a per-second level, and were worn around the clock for the week of the study. These devices, said Dr. Krishnamurthy, give sleep data that correlate well with polysomnography, the gold standard for sleep assessment.

For both patient groups, Dr. Krishnamurthy and his colleagues reported sleep latency, sleep duration, sleep dysfunction, sleep efficiency in percentage, sleep quality, and medication need as assessed by the PSQI, as well as the overall PSQI score.

The group with bipolar disorder reported a mean time to falling asleep of 61 minutes, compared with 14 minutes for the control group (P = 0.00064). Total sleep duration from the PSQI was 6.2 hours in the bipolar disorder patients, compared with 7.4 hours in the control group (P = 0.017). All other subjective measures of sleep quality were significantly worse for the patients with bipolar disorder, and the overall score on the PSQI was also much higher (worse), compared with the control group (11.7 vs 3.3, P = 1 x 10-11).

Actigraphy was used for a 1-week period to measure sleep latency, total sleep time, sleep efficiency, and number and length of awakenings for both groups. When measured objectively, there was no significant difference in the time it took to fall asleep between the patients with bipolar disorder and the healthy controls (14.64 minutes vs. 13.15 minutes), nor was there a significant difference in total sleep time (400.7 minutes vs. 413 minutes). Overall sleep efficiency was similar between groups.

The absolute difference in sleep duration, latency, and efficiency between subjective and objective measures was compared between groups. There was significantly less difference between objective and subjective ratings of all three sleep measures in the healthy subjects than in those with bipolar disorder.

Overall, the patients with bipolar disorder exhibited a strong perception of poor sleep quality, daytime impairment, and insufficient sleep, as shown by the PSQI scores for this group in comparison with the healthy controls. However, these perceptions did not correlate with objective sleep measures for sleep latency, total sleep duration, or sleep efficiency.

Patients with bipolar disorder were significantly more likely to lack employment and to be smokers or use illicit substances; their body mass index was also significantly higher on average than their healthy counterparts.

The bipolar disorder patients may have altered circadian rhythms, cognitive dysfunction because of the illness, and dysfunctional sleep beliefs, which may have independent effects on subjective perceptions of sleep that were not accounted for in the study, said Dr. Krishnamurthy.

The study’s findings mean that clinicians may wish to consider incorporating objective assessments of sleep, such as actigraphy, into care of individuals with bipolar disorder and sleep disturbances, Dr. Krishnamurthy said in an interview. In addition, “behavioral methods to address sleep misperception may be helpful in bipolar subjects.”

The Penn State Hershey College of Medicine funded the study. The authors reported no relevant disclosures.

 

 

[email protected]

On Twitter @karioakes

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MIAMI BEACH – Patients with active bipolar disorder significantly underestimated the quality of their sleep, despite having sleep quality comparable to that of healthy controls.

Sleep complaints are common among individuals with bipolar disorder, and addressing disruptive and troubling sleep problems can be an important component of treating bipolar disorder, noted Dr. Venkatesh Krishnamurthy and his collaborators at Penn State University (Hershey, Pa.).

“Mood state may affect perception of sleep, and the impact of mood state on subjective-objective differences of sleep parameters needs to be further explored,” the researchers noted.

They reported their comparison of subjective and objective measures of sleep for symptomatic patients with bipolar disorder in a poster presentation at a meeting of the American Society for Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting.

The study researchers evaluated 30 individuals with symptomatic bipolar disorder, compared with 31 healthy controls, reported Dr. Krishnamurthy, assistant professor at the department of psychiatry’s Sleep Research and Treatment Center at Penn State’s Milton S. Hershey Medical Center. Patients with bipolar disorder were inpatients or in a partial hospitalization program; 11 patients had bipolar depression, 18 had mixed-state bipolar disorder, and 1 had bipolar disorder with a manic episode, Dr. Krishnamurthy said in an interview.

To compare subjective and objective measures of sleep in the two groups, the researchers administered a sleep-quality questionnaire and used actigraphy to document sleep objectively.

The Pittsburgh Sleep Quality Index (PSQI), the instrument used for subjective assessment, is a self-reporting tool that asks patients to report on aspects of sleep quality, usual sleep duration, daytime sleepiness, and sleep medication use over the past month.

The actigraphs used in the study used accelerometers to measure patient movement at a per-second level, and were worn around the clock for the week of the study. These devices, said Dr. Krishnamurthy, give sleep data that correlate well with polysomnography, the gold standard for sleep assessment.

For both patient groups, Dr. Krishnamurthy and his colleagues reported sleep latency, sleep duration, sleep dysfunction, sleep efficiency in percentage, sleep quality, and medication need as assessed by the PSQI, as well as the overall PSQI score.

The group with bipolar disorder reported a mean time to falling asleep of 61 minutes, compared with 14 minutes for the control group (P = 0.00064). Total sleep duration from the PSQI was 6.2 hours in the bipolar disorder patients, compared with 7.4 hours in the control group (P = 0.017). All other subjective measures of sleep quality were significantly worse for the patients with bipolar disorder, and the overall score on the PSQI was also much higher (worse), compared with the control group (11.7 vs 3.3, P = 1 x 10-11).

Actigraphy was used for a 1-week period to measure sleep latency, total sleep time, sleep efficiency, and number and length of awakenings for both groups. When measured objectively, there was no significant difference in the time it took to fall asleep between the patients with bipolar disorder and the healthy controls (14.64 minutes vs. 13.15 minutes), nor was there a significant difference in total sleep time (400.7 minutes vs. 413 minutes). Overall sleep efficiency was similar between groups.

The absolute difference in sleep duration, latency, and efficiency between subjective and objective measures was compared between groups. There was significantly less difference between objective and subjective ratings of all three sleep measures in the healthy subjects than in those with bipolar disorder.

Overall, the patients with bipolar disorder exhibited a strong perception of poor sleep quality, daytime impairment, and insufficient sleep, as shown by the PSQI scores for this group in comparison with the healthy controls. However, these perceptions did not correlate with objective sleep measures for sleep latency, total sleep duration, or sleep efficiency.

Patients with bipolar disorder were significantly more likely to lack employment and to be smokers or use illicit substances; their body mass index was also significantly higher on average than their healthy counterparts.

The bipolar disorder patients may have altered circadian rhythms, cognitive dysfunction because of the illness, and dysfunctional sleep beliefs, which may have independent effects on subjective perceptions of sleep that were not accounted for in the study, said Dr. Krishnamurthy.

The study’s findings mean that clinicians may wish to consider incorporating objective assessments of sleep, such as actigraphy, into care of individuals with bipolar disorder and sleep disturbances, Dr. Krishnamurthy said in an interview. In addition, “behavioral methods to address sleep misperception may be helpful in bipolar subjects.”

The Penn State Hershey College of Medicine funded the study. The authors reported no relevant disclosures.

 

 

[email protected]

On Twitter @karioakes

MIAMI BEACH – Patients with active bipolar disorder significantly underestimated the quality of their sleep, despite having sleep quality comparable to that of healthy controls.

Sleep complaints are common among individuals with bipolar disorder, and addressing disruptive and troubling sleep problems can be an important component of treating bipolar disorder, noted Dr. Venkatesh Krishnamurthy and his collaborators at Penn State University (Hershey, Pa.).

“Mood state may affect perception of sleep, and the impact of mood state on subjective-objective differences of sleep parameters needs to be further explored,” the researchers noted.

They reported their comparison of subjective and objective measures of sleep for symptomatic patients with bipolar disorder in a poster presentation at a meeting of the American Society for Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting.

The study researchers evaluated 30 individuals with symptomatic bipolar disorder, compared with 31 healthy controls, reported Dr. Krishnamurthy, assistant professor at the department of psychiatry’s Sleep Research and Treatment Center at Penn State’s Milton S. Hershey Medical Center. Patients with bipolar disorder were inpatients or in a partial hospitalization program; 11 patients had bipolar depression, 18 had mixed-state bipolar disorder, and 1 had bipolar disorder with a manic episode, Dr. Krishnamurthy said in an interview.

To compare subjective and objective measures of sleep in the two groups, the researchers administered a sleep-quality questionnaire and used actigraphy to document sleep objectively.

The Pittsburgh Sleep Quality Index (PSQI), the instrument used for subjective assessment, is a self-reporting tool that asks patients to report on aspects of sleep quality, usual sleep duration, daytime sleepiness, and sleep medication use over the past month.

The actigraphs used in the study used accelerometers to measure patient movement at a per-second level, and were worn around the clock for the week of the study. These devices, said Dr. Krishnamurthy, give sleep data that correlate well with polysomnography, the gold standard for sleep assessment.

For both patient groups, Dr. Krishnamurthy and his colleagues reported sleep latency, sleep duration, sleep dysfunction, sleep efficiency in percentage, sleep quality, and medication need as assessed by the PSQI, as well as the overall PSQI score.

The group with bipolar disorder reported a mean time to falling asleep of 61 minutes, compared with 14 minutes for the control group (P = 0.00064). Total sleep duration from the PSQI was 6.2 hours in the bipolar disorder patients, compared with 7.4 hours in the control group (P = 0.017). All other subjective measures of sleep quality were significantly worse for the patients with bipolar disorder, and the overall score on the PSQI was also much higher (worse), compared with the control group (11.7 vs 3.3, P = 1 x 10-11).

Actigraphy was used for a 1-week period to measure sleep latency, total sleep time, sleep efficiency, and number and length of awakenings for both groups. When measured objectively, there was no significant difference in the time it took to fall asleep between the patients with bipolar disorder and the healthy controls (14.64 minutes vs. 13.15 minutes), nor was there a significant difference in total sleep time (400.7 minutes vs. 413 minutes). Overall sleep efficiency was similar between groups.

The absolute difference in sleep duration, latency, and efficiency between subjective and objective measures was compared between groups. There was significantly less difference between objective and subjective ratings of all three sleep measures in the healthy subjects than in those with bipolar disorder.

Overall, the patients with bipolar disorder exhibited a strong perception of poor sleep quality, daytime impairment, and insufficient sleep, as shown by the PSQI scores for this group in comparison with the healthy controls. However, these perceptions did not correlate with objective sleep measures for sleep latency, total sleep duration, or sleep efficiency.

Patients with bipolar disorder were significantly more likely to lack employment and to be smokers or use illicit substances; their body mass index was also significantly higher on average than their healthy counterparts.

The bipolar disorder patients may have altered circadian rhythms, cognitive dysfunction because of the illness, and dysfunctional sleep beliefs, which may have independent effects on subjective perceptions of sleep that were not accounted for in the study, said Dr. Krishnamurthy.

The study’s findings mean that clinicians may wish to consider incorporating objective assessments of sleep, such as actigraphy, into care of individuals with bipolar disorder and sleep disturbances, Dr. Krishnamurthy said in an interview. In addition, “behavioral methods to address sleep misperception may be helpful in bipolar subjects.”

The Penn State Hershey College of Medicine funded the study. The authors reported no relevant disclosures.

 

 

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Key clinical point: Subjective assessment of sleep efficiency and duration varied significantly from actigraphy in active bipolar disorder.

Major finding: Individuals with active bipolar disorder greatly overestimated sleep latency and underestimated sleep duration, reporting significantly worse sleep than healthy subjects, who were more accurate in subjective sleep assessment.

Data source: Subjective assessment via Pittsburgh Sleep Quality Index and objective measurement via actigraphy of 1 week of sleep for 30 individuals with active bipolar disorder (inpatients or partial hospitalization patients), compared with 31 healthy controls.

Disclosures: The Penn State Hershey College of Medicine funded the study. The authors reported no relevant disclosures.

ASCP: Variable pattern of inflammation markers found in serious mental illness

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MIAMI BEACH – Elevated levels of the same cytokine* were seen in three serious mental illnesses, but each illness had separate and distinct patterns of inflammatory markers, according to a study of immune function and mental illness.

Dr. David R. Goldsmith and colleagues conducted a meta-analysis that pooled results of three dozen studies of outpatients with bipolar disorder, schizophrenia, and major depression, to search for commonalities and differences in immune system activation.

The results were presented in a poster session at a meeting of the American Society of Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting.

Dr. David R. Goldsmith

Dr. Goldsmith, chief resident for the research track at Emory University’s department of psychiatry and behavioral sciences, Atlanta, and his collaborators looked at 36 studies examining individuals with major depressive disorder (MDD) (12 studies), euthymic bipolar disorder (14 studies), and chronic schizophrenia (10 studies). It is the first meta-analysis to pool results from studies of blood cytokine levels in outpatients with three serious mental illnesses, he said.

Serious mental illness is associated with immune activation, and previous studies have found activation of various cytokines in many mental illnesses. In the acute phase of mental illness, elevations have been found in both interleukin-6 (IL-6) and the cytokine receptor SIL-2R; for MDD and schizophrenia, cytokine levels are acutely increased, tend to decrease with treatment, and eventually rise again, he said.

However, Dr. Goldsmith and his collaborators found that only the cytokine* IL-6 was significantly elevated, compared with healthy controls, for all three illnesses included in the meta-analysis (P < .01 for all). IL-6 is associated with acute and chronic inflammation. For MDD and schizophrenia, two other cytokines were significantly elevated in the meta-analysis: the soluble IL-2 receptor (SIL–2R), a cytokine receptor associated with T-cell activation; and IL-1 beta, a cytokine produced by activated macrophages (P < .01 for all interactions, except P = .01 for IL-1 beta in bipolar disorder.)

For all three disorders, several inflammatory cytokines were significantly elevated, compared with healthy subjects.

Dr. Goldsmith noted some limitations of the meta-analysis. For example, there was a high degree of variability across studies in collection and storage techniques. In addition, no consistent set of tests exists to assess inflammation in mental illness, so the measures obtained varied from study to study. Potential confounders such as smoking and substance abuse were difficult to account for as well. The study limitations highlight the need for “a common set of inflammatory markers that must carefully be studied in order to understand the role of the cytokines in chronic psychiatric disorders and inform novel treatment decisions that may only be relevant to a subset of patients,” he noted.

Going forward, more uniform data collection and larger datasets should help delineate the association between inflammation and serious mental illness. “Despite the heterogeneity of the data, we do see some signal for the role of persistent immune activation, which we think will be important for some people with mental illness,” Dr. Goldsmith said in an interview.Dr. Goldsmith received the Janssen Pharmaceuticals Academic Research Mentoring Award in 2014. He reported no other conflicts of interest.

*Correction, 7/10/2015: An earlier version of this story mischaracterized an inflammatory marker. IL-6 is a cytokine.

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MIAMI BEACH – Elevated levels of the same cytokine* were seen in three serious mental illnesses, but each illness had separate and distinct patterns of inflammatory markers, according to a study of immune function and mental illness.

Dr. David R. Goldsmith and colleagues conducted a meta-analysis that pooled results of three dozen studies of outpatients with bipolar disorder, schizophrenia, and major depression, to search for commonalities and differences in immune system activation.

The results were presented in a poster session at a meeting of the American Society of Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting.

Dr. David R. Goldsmith

Dr. Goldsmith, chief resident for the research track at Emory University’s department of psychiatry and behavioral sciences, Atlanta, and his collaborators looked at 36 studies examining individuals with major depressive disorder (MDD) (12 studies), euthymic bipolar disorder (14 studies), and chronic schizophrenia (10 studies). It is the first meta-analysis to pool results from studies of blood cytokine levels in outpatients with three serious mental illnesses, he said.

Serious mental illness is associated with immune activation, and previous studies have found activation of various cytokines in many mental illnesses. In the acute phase of mental illness, elevations have been found in both interleukin-6 (IL-6) and the cytokine receptor SIL-2R; for MDD and schizophrenia, cytokine levels are acutely increased, tend to decrease with treatment, and eventually rise again, he said.

However, Dr. Goldsmith and his collaborators found that only the cytokine* IL-6 was significantly elevated, compared with healthy controls, for all three illnesses included in the meta-analysis (P < .01 for all). IL-6 is associated with acute and chronic inflammation. For MDD and schizophrenia, two other cytokines were significantly elevated in the meta-analysis: the soluble IL-2 receptor (SIL–2R), a cytokine receptor associated with T-cell activation; and IL-1 beta, a cytokine produced by activated macrophages (P < .01 for all interactions, except P = .01 for IL-1 beta in bipolar disorder.)

For all three disorders, several inflammatory cytokines were significantly elevated, compared with healthy subjects.

Dr. Goldsmith noted some limitations of the meta-analysis. For example, there was a high degree of variability across studies in collection and storage techniques. In addition, no consistent set of tests exists to assess inflammation in mental illness, so the measures obtained varied from study to study. Potential confounders such as smoking and substance abuse were difficult to account for as well. The study limitations highlight the need for “a common set of inflammatory markers that must carefully be studied in order to understand the role of the cytokines in chronic psychiatric disorders and inform novel treatment decisions that may only be relevant to a subset of patients,” he noted.

Going forward, more uniform data collection and larger datasets should help delineate the association between inflammation and serious mental illness. “Despite the heterogeneity of the data, we do see some signal for the role of persistent immune activation, which we think will be important for some people with mental illness,” Dr. Goldsmith said in an interview.Dr. Goldsmith received the Janssen Pharmaceuticals Academic Research Mentoring Award in 2014. He reported no other conflicts of interest.

*Correction, 7/10/2015: An earlier version of this story mischaracterized an inflammatory marker. IL-6 is a cytokine.

[email protected]

On Twitter @karioakes

MIAMI BEACH – Elevated levels of the same cytokine* were seen in three serious mental illnesses, but each illness had separate and distinct patterns of inflammatory markers, according to a study of immune function and mental illness.

Dr. David R. Goldsmith and colleagues conducted a meta-analysis that pooled results of three dozen studies of outpatients with bipolar disorder, schizophrenia, and major depression, to search for commonalities and differences in immune system activation.

The results were presented in a poster session at a meeting of the American Society of Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting.

Dr. David R. Goldsmith

Dr. Goldsmith, chief resident for the research track at Emory University’s department of psychiatry and behavioral sciences, Atlanta, and his collaborators looked at 36 studies examining individuals with major depressive disorder (MDD) (12 studies), euthymic bipolar disorder (14 studies), and chronic schizophrenia (10 studies). It is the first meta-analysis to pool results from studies of blood cytokine levels in outpatients with three serious mental illnesses, he said.

Serious mental illness is associated with immune activation, and previous studies have found activation of various cytokines in many mental illnesses. In the acute phase of mental illness, elevations have been found in both interleukin-6 (IL-6) and the cytokine receptor SIL-2R; for MDD and schizophrenia, cytokine levels are acutely increased, tend to decrease with treatment, and eventually rise again, he said.

However, Dr. Goldsmith and his collaborators found that only the cytokine* IL-6 was significantly elevated, compared with healthy controls, for all three illnesses included in the meta-analysis (P < .01 for all). IL-6 is associated with acute and chronic inflammation. For MDD and schizophrenia, two other cytokines were significantly elevated in the meta-analysis: the soluble IL-2 receptor (SIL–2R), a cytokine receptor associated with T-cell activation; and IL-1 beta, a cytokine produced by activated macrophages (P < .01 for all interactions, except P = .01 for IL-1 beta in bipolar disorder.)

For all three disorders, several inflammatory cytokines were significantly elevated, compared with healthy subjects.

Dr. Goldsmith noted some limitations of the meta-analysis. For example, there was a high degree of variability across studies in collection and storage techniques. In addition, no consistent set of tests exists to assess inflammation in mental illness, so the measures obtained varied from study to study. Potential confounders such as smoking and substance abuse were difficult to account for as well. The study limitations highlight the need for “a common set of inflammatory markers that must carefully be studied in order to understand the role of the cytokines in chronic psychiatric disorders and inform novel treatment decisions that may only be relevant to a subset of patients,” he noted.

Going forward, more uniform data collection and larger datasets should help delineate the association between inflammation and serious mental illness. “Despite the heterogeneity of the data, we do see some signal for the role of persistent immune activation, which we think will be important for some people with mental illness,” Dr. Goldsmith said in an interview.Dr. Goldsmith received the Janssen Pharmaceuticals Academic Research Mentoring Award in 2014. He reported no other conflicts of interest.

*Correction, 7/10/2015: An earlier version of this story mischaracterized an inflammatory marker. IL-6 is a cytokine.

[email protected]

On Twitter @karioakes

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Key clinical point: A meta-analysis found elevations in the cytokine receptor interleukin-6 (IL-6) in outpatients with three serious mental illnesses.

Major finding: The cytokine* IL-6 was significantly elevated in major depressive disorder, chronic schizophrenia, and euthymic bipolar disorder (P < .01); variable patterns of inflammation were seen in the individual disorders.

Data source: Meta-analysis of 36 studies of blood cytokine levels in chronically ill patients with bipolar disorder, schizophrenia, and major depression.

Disclosures: Dr. Goldsmith received the Janssen Pharmaceuticals Academic Research Mentoring Award in 2014. He reported no other conflicts of interest.

Iowa Gambling Task differentiates bipolar patients from controls

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A significant difference in oxygenated hemoglobin (oxy-Hb) rates was found between bipolar disorder patients and a control group during the Iowa Gambling Task, Dr. Yasuki Ono and associates reported.

While performing the Iowa Gambling Task (IGT), patients with bipolar disorder had significantly lower oxy-Hb levels in the bilateral orbitofrontal cortex and left prefrontal cortex than did those in the control group. Changes in oxy-Hb levels in the orbitofrontal cortex and profrontal cortex during the IGT were negatively correlated with total scores on the Hamilton Rating Scale for Depression. Oxy-Hb levels, however, were similar in both the bipolar disorder group and control group while taking a verbal fluency task.

“Although the IGT was useful for differentiating patients with [bipolar disorder] from control subjects, no significant differences in autonomic activity were observed,” noted Dr. Ono of the department of psychiatry and neurobiology at Kanazawa (Japan) University and associates.

Find the full study in Psychiatry Research: Neuroimaging (2015;233:1-8 [doi:10.1016/j.pscychresns.2015.04.003]).

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A significant difference in oxygenated hemoglobin (oxy-Hb) rates was found between bipolar disorder patients and a control group during the Iowa Gambling Task, Dr. Yasuki Ono and associates reported.

While performing the Iowa Gambling Task (IGT), patients with bipolar disorder had significantly lower oxy-Hb levels in the bilateral orbitofrontal cortex and left prefrontal cortex than did those in the control group. Changes in oxy-Hb levels in the orbitofrontal cortex and profrontal cortex during the IGT were negatively correlated with total scores on the Hamilton Rating Scale for Depression. Oxy-Hb levels, however, were similar in both the bipolar disorder group and control group while taking a verbal fluency task.

“Although the IGT was useful for differentiating patients with [bipolar disorder] from control subjects, no significant differences in autonomic activity were observed,” noted Dr. Ono of the department of psychiatry and neurobiology at Kanazawa (Japan) University and associates.

Find the full study in Psychiatry Research: Neuroimaging (2015;233:1-8 [doi:10.1016/j.pscychresns.2015.04.003]).

[email protected]

A significant difference in oxygenated hemoglobin (oxy-Hb) rates was found between bipolar disorder patients and a control group during the Iowa Gambling Task, Dr. Yasuki Ono and associates reported.

While performing the Iowa Gambling Task (IGT), patients with bipolar disorder had significantly lower oxy-Hb levels in the bilateral orbitofrontal cortex and left prefrontal cortex than did those in the control group. Changes in oxy-Hb levels in the orbitofrontal cortex and profrontal cortex during the IGT were negatively correlated with total scores on the Hamilton Rating Scale for Depression. Oxy-Hb levels, however, were similar in both the bipolar disorder group and control group while taking a verbal fluency task.

“Although the IGT was useful for differentiating patients with [bipolar disorder] from control subjects, no significant differences in autonomic activity were observed,” noted Dr. Ono of the department of psychiatry and neurobiology at Kanazawa (Japan) University and associates.

Find the full study in Psychiatry Research: Neuroimaging (2015;233:1-8 [doi:10.1016/j.pscychresns.2015.04.003]).

[email protected]

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ASCP: Brain imaging findings provide new guidance for neural outcomes research

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MIAMI BEACH – Different brain regions appear to be responsible for processing emotional and cognitive stimuli during a common cognitive task used in psychiatric research, a new medical imaging study shows. Further, the activation of subcortical structures changed over time with repeated exposure to the task. The work has implications for researchers and clinicians involved with identifying new targets to treat mood disorders.

Functional magnetic resonance imaging (fMRI) gives detailed anatomic and physiologic data about the brain and has increasing importance for neural outcomes research, according to David Fleck, Ph.D., research associate professor with the Center for Imaging Research at the University of Cincinnati. His work, presented in a poster session, built on previous imaging research that showed differential activation of brain structures when emotional distraction interrupts a cognitive task.

Dr. David Fleck

Imaging offers investigators a “completely objective” measure of changes in brain function, and thus is an important tool in clinical trials for medications and treatments for mood disorders, Dr. Fleck said at a meeting of the American Society of Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting. He noted that there can be variability in clinician assessments, and patients can both under- and overreport symptoms. Neuroimaging provides a means to measure absolute change in brain activity or structure, or both, over time.

Forty-one healthy subjects were recruited for the study, which obtained baseline, 1 week, and 8 week fMRI brain scans. During the scans, participants completed the Continuous Performance Task with Emotional and Neutral Distractor (CPT-END). This is a “visual oddball” task where participants are asked to differentiate a target – an image of a circle – from images of a square, and also from distracting images. Seventy percent of the time, subjects were shown a square. They saw the target circle 10% of the time and were presented either a neutral or an emotionally laden image, at a 10% rate for each image type, the remainder of the time.

Dr. Fleck and his colleagues at the University of Cincinnati identified the amygdala and the interior prefrontal gyrus as areas that showed more activation with both the neutral and the emotional distractors at baseline than with either the target circle or the square. However, at weeks 1 and 8, the emotional distractors elicited significantly more activation, particularly in the inferior frontal gyrus.

Deeper brain structures also showed differences between attentional and emotional stimuli, and activation changed over time: “Finally, targets elicited more caudate activation at baseline but not week 8 relative to both distractor types, while emotional distractors elicited more thalamic activation at week 8 but not baseline relative to neutrals and targets,” said Dr. Fleck and coinvestigators.

The study partly replicated and extended a study done more than a decade ago that looked at differential brain activation in cognitive attention versus emotional processes. This is important in mood disorder research, Dr. Fleck said in an interview. Bipolar disorder, for example, has significant cognitive and emotional components that contribute to the disease process. “It is hoped that this work will form the basis for a cognitive/emotional fMRI probe of pharmacological targets in mood disorders,” said Dr. Fleck and coinvestigators.

Dr. Fleck noted that advances in imaging technology since 2002 mean that the image analysis in this study could be much more fine-tuned in its identification of regions of interest, saying, “These findings will form the basis for further work characterizing the neurofunctional signature of mood-disordered patients over time.”

Dr. Fleck reported no conflicts of interest.

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MIAMI BEACH – Different brain regions appear to be responsible for processing emotional and cognitive stimuli during a common cognitive task used in psychiatric research, a new medical imaging study shows. Further, the activation of subcortical structures changed over time with repeated exposure to the task. The work has implications for researchers and clinicians involved with identifying new targets to treat mood disorders.

Functional magnetic resonance imaging (fMRI) gives detailed anatomic and physiologic data about the brain and has increasing importance for neural outcomes research, according to David Fleck, Ph.D., research associate professor with the Center for Imaging Research at the University of Cincinnati. His work, presented in a poster session, built on previous imaging research that showed differential activation of brain structures when emotional distraction interrupts a cognitive task.

Dr. David Fleck

Imaging offers investigators a “completely objective” measure of changes in brain function, and thus is an important tool in clinical trials for medications and treatments for mood disorders, Dr. Fleck said at a meeting of the American Society of Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting. He noted that there can be variability in clinician assessments, and patients can both under- and overreport symptoms. Neuroimaging provides a means to measure absolute change in brain activity or structure, or both, over time.

Forty-one healthy subjects were recruited for the study, which obtained baseline, 1 week, and 8 week fMRI brain scans. During the scans, participants completed the Continuous Performance Task with Emotional and Neutral Distractor (CPT-END). This is a “visual oddball” task where participants are asked to differentiate a target – an image of a circle – from images of a square, and also from distracting images. Seventy percent of the time, subjects were shown a square. They saw the target circle 10% of the time and were presented either a neutral or an emotionally laden image, at a 10% rate for each image type, the remainder of the time.

Dr. Fleck and his colleagues at the University of Cincinnati identified the amygdala and the interior prefrontal gyrus as areas that showed more activation with both the neutral and the emotional distractors at baseline than with either the target circle or the square. However, at weeks 1 and 8, the emotional distractors elicited significantly more activation, particularly in the inferior frontal gyrus.

Deeper brain structures also showed differences between attentional and emotional stimuli, and activation changed over time: “Finally, targets elicited more caudate activation at baseline but not week 8 relative to both distractor types, while emotional distractors elicited more thalamic activation at week 8 but not baseline relative to neutrals and targets,” said Dr. Fleck and coinvestigators.

The study partly replicated and extended a study done more than a decade ago that looked at differential brain activation in cognitive attention versus emotional processes. This is important in mood disorder research, Dr. Fleck said in an interview. Bipolar disorder, for example, has significant cognitive and emotional components that contribute to the disease process. “It is hoped that this work will form the basis for a cognitive/emotional fMRI probe of pharmacological targets in mood disorders,” said Dr. Fleck and coinvestigators.

Dr. Fleck noted that advances in imaging technology since 2002 mean that the image analysis in this study could be much more fine-tuned in its identification of regions of interest, saying, “These findings will form the basis for further work characterizing the neurofunctional signature of mood-disordered patients over time.”

Dr. Fleck reported no conflicts of interest.

[email protected]

On Twitter @karioakes

MIAMI BEACH – Different brain regions appear to be responsible for processing emotional and cognitive stimuli during a common cognitive task used in psychiatric research, a new medical imaging study shows. Further, the activation of subcortical structures changed over time with repeated exposure to the task. The work has implications for researchers and clinicians involved with identifying new targets to treat mood disorders.

Functional magnetic resonance imaging (fMRI) gives detailed anatomic and physiologic data about the brain and has increasing importance for neural outcomes research, according to David Fleck, Ph.D., research associate professor with the Center for Imaging Research at the University of Cincinnati. His work, presented in a poster session, built on previous imaging research that showed differential activation of brain structures when emotional distraction interrupts a cognitive task.

Dr. David Fleck

Imaging offers investigators a “completely objective” measure of changes in brain function, and thus is an important tool in clinical trials for medications and treatments for mood disorders, Dr. Fleck said at a meeting of the American Society of Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting. He noted that there can be variability in clinician assessments, and patients can both under- and overreport symptoms. Neuroimaging provides a means to measure absolute change in brain activity or structure, or both, over time.

Forty-one healthy subjects were recruited for the study, which obtained baseline, 1 week, and 8 week fMRI brain scans. During the scans, participants completed the Continuous Performance Task with Emotional and Neutral Distractor (CPT-END). This is a “visual oddball” task where participants are asked to differentiate a target – an image of a circle – from images of a square, and also from distracting images. Seventy percent of the time, subjects were shown a square. They saw the target circle 10% of the time and were presented either a neutral or an emotionally laden image, at a 10% rate for each image type, the remainder of the time.

Dr. Fleck and his colleagues at the University of Cincinnati identified the amygdala and the interior prefrontal gyrus as areas that showed more activation with both the neutral and the emotional distractors at baseline than with either the target circle or the square. However, at weeks 1 and 8, the emotional distractors elicited significantly more activation, particularly in the inferior frontal gyrus.

Deeper brain structures also showed differences between attentional and emotional stimuli, and activation changed over time: “Finally, targets elicited more caudate activation at baseline but not week 8 relative to both distractor types, while emotional distractors elicited more thalamic activation at week 8 but not baseline relative to neutrals and targets,” said Dr. Fleck and coinvestigators.

The study partly replicated and extended a study done more than a decade ago that looked at differential brain activation in cognitive attention versus emotional processes. This is important in mood disorder research, Dr. Fleck said in an interview. Bipolar disorder, for example, has significant cognitive and emotional components that contribute to the disease process. “It is hoped that this work will form the basis for a cognitive/emotional fMRI probe of pharmacological targets in mood disorders,” said Dr. Fleck and coinvestigators.

Dr. Fleck noted that advances in imaging technology since 2002 mean that the image analysis in this study could be much more fine-tuned in its identification of regions of interest, saying, “These findings will form the basis for further work characterizing the neurofunctional signature of mood-disordered patients over time.”

Dr. Fleck reported no conflicts of interest.

[email protected]

On Twitter @karioakes

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Key clinical point: Emotional disruptors to a cognitive attention task activated different brain regions, and emotional activation increased with time.

Major finding: The amygdala and the inferior prefrontal gyrus showed more activation over time with exposure to emotional stimuli during a cognitive attention task.

Data source: fMRI study of 41 healthy subjects given a cognitive/emotional task at baseline, 1, and 8 weeks.

Disclosures: Dr. Fleck reported no relevant financial disclosures.

Avoiding common drug−drug interactions

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Avoiding common drug−drug interactions

Mr. T,  age 23, was given a diagnosis of bipolar disorder 1 year ago. After he experienced inadequate symp­tom relief with valproate, you switched him to extended-release lithium, 1,200 mg/d. Mr. T reported improved mood and stability with this medication adjustment. These posi­tive changes led him to resume activities he enjoyed before onset of bipolar disorder, such as running, reading, and going out to dinner with friends.

Now, Mr. T’s mother calls your office to express concern about her son’s slight

 

hand tremor, which appeared after 2 days of gas­trointestinal distress. She tells you that Mr. T sprained his ankle while running 1 week ago and has been taking over-the-counter ibu­profen for pain relief, which he did often in the past.

You suspect that Mr. T is experiencing lith­ium toxicity as a result of ibuprofen use.

 

 
 

Although mental health providers can eas­ily recognize the drug−drug interaction between lithium and nonsteroidal anti-inflammatory drugs (NSAIDs) that Mr. T experienced, interpreting the safety of a medication regimen with respect to drug− drug interactions before prescribing often is more daunting. This article reviews the basics of drug−drug interactions, while briefly highlighting common examples in psychiatric medicine (Table 11-5). We also provide an outline of additional points to consider when reviewing your patients’ medication regimens and encoun­tering unfamiliar drug−drug interactions.


Types of drug−drug interactions
Drug−drug interactions fall into 2 catego­ries: pharmacodynamic (PD) and pharmaco­kinetic (PK):
   • PD interactions are a result of the com­bined impact of medications on the body when there is no direct effect on absorp­tion, distribution, metabolism, or excretion characteristics, such as 2 medications that act at the same receptor or lead to similar or opposing pharmacologic effects.
   • PK interactions occur when a drug affects the absorption, distribution, metabo­lism, or excretion characteristics of another drug.

Although it is possible that drug−drug interactions will have no clinical effect, when the impact of a PD or PK drug−drug interaction is evident, it likely is the result of additive, synergistic, or antago­nistic consequences on the medications’ intended impact or side-effect profile.


Pharmacodynamic interactions
Serotonin syndrome. The potential for serotonin syndrome occurs when medica­tions that increase synaptic serotonin con­centration are used concomitantly.1 This can occur through several mechanisms, including increased serotonin release, decreased reuptake, or decreased sero­tonin metabolism. A high serotonin con­centration in the CNS and in the periphery overstimulates serotonin receptors, lead­ing to signs and symptoms that can include diarrhea, fever, delirium, coma, and poten­tially death.

QT prolongation and anticholinergic toxicity are further examples of additive PD drug−drug interactions. Anticholinergic toxicity is possible when multiple medica­tions contribute to inhibition of the neuro-transmitter acetylcholine at muscarinic receptors. This leads to adverse effects such as dry mouth, constipation, confusion, and urinary retention.

QT prolongation, which can lead to arrhythmia, occurs when a patient is taking several medications that can increase the QT interval. Consider close monitoring and using alternative agents with less poten­tial to increase the QT interval in patients at risk of arrhythmias (geriatric patients, those with an increased QT interval at base­line, etc.).

Decreased seizure threshold. The increased risk of seizures with bupropion and other medications that lower the sei­zure threshold is another example of an additive PD drug interaction. Bupropion can increase the risk of seizures in a dose-dependent manner, which increases when bupropion is taken with other drugs that lower the seizure threshold.6 Seizure risk associated with alcohol or benzodiazepine withdrawal also may increase the risk for this interaction.

Of note, the increased risk of seizures with the combination of bupropion and alcohol in the absence of withdrawal is not well studied in humans, but positive corre­lation has been seen in an animal study.6

Decreased platelet function. Another example of a PD drug−drug interaction is increased risk of bleeding when a selec­tive serotonin reuptake inhibitor is used with a NSAID or oral anticoagulant. The proposed mechanism for this interaction is that blocking serotonin reuptake on platelets leads to decreased platelet func­tion and an increased risk for prolonged bleeding.7 This is somewhat controversial because, first, it has been noted that drugs with the highest degree of serotonin reup­take inhibition do not always cause the highest risk of bleeding and, second, most of the evidence for this interaction is from observational studies.7

This potential interaction could be most important for patients who need an anti­depressant, are on chronic NSAID or anti­coagulant therapy, and are at high risk of bleeding.


Pharmacokinetic interactions
PK interactions in psychiatry often are caused by interference of drug metabo­lizing enzymes. The cytochrome P450 (CYP450) family of metabolizing enzymes in particular is important to the break­down of medications in the body. Many drug−drug interactions involve medica­tions that can inhibit or induce metabolism of other drugs through their effect on the CYP450 system.

Inhibition interactions. When a drug’s metabolism is inhibited, the result is usu­ally increased serum concentration of that medication (because of less break­down) and a more potent impact on the primary mechanism of action or adverse effects. Sometimes, inhibiting metabo­lism can lead to decreased clinical effect. Tamoxifen (an oral agent used to treat breast cancer) and certain analgesics when used in combination with moderate or strong inhibitors of the CYP2D6 subfam­ily of CYP450 metabolizing enzymes are 2 examples of metabolism inhibition lead­ing to decreased efficacy.8 Both tamoxi­fen and the analgesics listed in Table 11-5 are prodrugs; that is, they must be metabolized to be active. When the enzymes that metabolize these drugs into their active form are inhibited, the concen­tration of active drug decreases.

 

 

Induction interactions. Alternatively, there is an increased rate of drug break­down and resulting decrease in effect when drugs that induce the activity of metabolizing enzymes are used with med­ications that are substrates of the same enzyme. Carbamazepine is commonly involved in this type of drug interaction because it is a strong inducer of CYP 1A2, 2B6, 2C19, 2C9, and 3A4, and the p-glyco­protein drug efflux pump.9 As a result of this rampant induction, carbamazepine can decrease the serum concentration of oral contraceptives below a reliably effec­tive level. Therefore, it is recommended that women of childbearing potential use other contraceptive methods, such as a progestin implant or an intrauterine device.10

In addition, the polycyclic aromatic hydrocarbons found in cigarettes induce activity of CYP1A2. Patients who smoke and use medications metabolized by this enzyme, such as clozapine and olanzap­ine, may need a higher dosage.


Drug elimination interactions
The last drug−drug interaction discussed here returns the discussion to Mr. T and involves drug elimination.2 The NSAIDs Mr. T was using for pain likely caused decreased renal excretion of lithium. Because lithium is primarily excreted through the kidneys, Mr. T’s NSAID use, possibly in com­bination with dehydration caused by gastro­intestinal distress, resulted in lithium toxicity. This class of analgesics should be avoided or used cautiously in patients taking lithium.


Clinical applications
The relatively common drug−drug interac­tions discussed here are just a fraction of the potential interactions mental health practi­tioners see on a daily basis. Understanding the basics of PD and PK interactions in the setting of patient-specific factors can help to clarify the information found in drug−drug interaction databases, such as Micromedex, Lexicomp, Facts and Comparisons, and Epocrates. Table 2 lists additional insights into drug interactions.

 

 

Related Resources
• CredibleMeds. Online resource on QT prolonging drugs. http://crediblemeds.org.
• Madhusoodanan S, Velama U, Parmar J, et al. A current review of cytochrome P450 interactions of psychotropic drugs. Ann Clin Psychiatry. 2014;26(2):120-138.

Drug Brand Names
Benztropine • Cogentin                            Olanzapine • Zyprexa
Bupropion • Wellbutrin                             Oxycodone • Oxycontin
Carbamazepine • Tegretol                        Paroxetine • Paxil
Clozapine • Clozaril                                  Quetiapine • Seroquel
Diphenhydramine • Benadryl                     Sertraline • Zoloft
 Duloxetine • Cymbalta                             Tamoxifen • Soltamox
Fluoxetine • Prozac                                   Trazodone • Desyrel
Lithium • Eskalith, Lithobid                        Valproate • Divalproex
Haloperidol • Haldol                                  Ziprasidone • Geodon
Hydrocodone • Vicodin

 

Disclosure
The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

References


1. Buckley NA, Dawson AH, Isbister GK. Serotonin syndrome. BMJ. 2014;348:g1626. doi: 10.1136/bmj.g1626.
2. Eskalith [package insert]. Research Triangle Park, NC: GlaxoSmithKline; 2003.
3. Handler J. Lithium and antihypertensive medication: a potentially dangerous interaction. J Clin Hypertens (Greenwich). 2009;11(12):738-742.
4. Blanche P, Raynaud E, Kerob D, et al. Lithium intoxication in an elderly patient after combined treatment with losartan. Eur J Clin Pharmacol. 1997;52(6):501.
5. Atacand [package insert]. Wilmington, DE: AstraZeneca LP; 2013.
6. Silverstone PH, Williams R, McMahon L, et al. Alcohol significantly lowers the seizure threshold in mice when co-administered with bupropion hydrochloride. Ann Gen Psychiatry. 2008;7:11.
7. Spina E, Trifirò G, Caraci F. Clinically significant drug interactions with newer antidepressants. CNS Drugs. 2012;26(1):39-67.
8. Ereshefsky L, Sloan DM. Drug-drug interactions with the use of psychotropic medications. CNS Spectr. 2009;14(suppl Q and A forum 8):1-8.
9. Carbamazepine. Drug facts and comparisons database. St. Louis, MO: Wolters Kluwer Health Inc; November 2014.
10. Pennell PB. Pregnancy, epilepsy, and women’s issues. Continuum (Minneap Minn). 2013;19(3 Epilepsy):697-714.

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Kristen Wiese, PharmD
Research Fellow
University of Michigan College of Pharmacy
Ann Arbor, Michigan


Vicki L. Ellingrod, PharmD, FCCP
John Gideon Searle Professor of Clinical and Translational Pharmacy
University of Michigan College of Pharmacy and School of Medicine
Ann Arbor, Michigan

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Research Fellow
University of Michigan College of Pharmacy
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Vicki L. Ellingrod, PharmD, FCCP
John Gideon Searle Professor of Clinical and Translational Pharmacy
University of Michigan College of Pharmacy and School of Medicine
Ann Arbor, Michigan

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Research Fellow
University of Michigan College of Pharmacy
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Vicki L. Ellingrod, PharmD, FCCP
John Gideon Searle Professor of Clinical and Translational Pharmacy
University of Michigan College of Pharmacy and School of Medicine
Ann Arbor, Michigan

Article PDF
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Mr. T,  age 23, was given a diagnosis of bipolar disorder 1 year ago. After he experienced inadequate symp­tom relief with valproate, you switched him to extended-release lithium, 1,200 mg/d. Mr. T reported improved mood and stability with this medication adjustment. These posi­tive changes led him to resume activities he enjoyed before onset of bipolar disorder, such as running, reading, and going out to dinner with friends.

Now, Mr. T’s mother calls your office to express concern about her son’s slight

 

hand tremor, which appeared after 2 days of gas­trointestinal distress. She tells you that Mr. T sprained his ankle while running 1 week ago and has been taking over-the-counter ibu­profen for pain relief, which he did often in the past.

You suspect that Mr. T is experiencing lith­ium toxicity as a result of ibuprofen use.

 

 
 

Although mental health providers can eas­ily recognize the drug−drug interaction between lithium and nonsteroidal anti-inflammatory drugs (NSAIDs) that Mr. T experienced, interpreting the safety of a medication regimen with respect to drug− drug interactions before prescribing often is more daunting. This article reviews the basics of drug−drug interactions, while briefly highlighting common examples in psychiatric medicine (Table 11-5). We also provide an outline of additional points to consider when reviewing your patients’ medication regimens and encoun­tering unfamiliar drug−drug interactions.


Types of drug−drug interactions
Drug−drug interactions fall into 2 catego­ries: pharmacodynamic (PD) and pharmaco­kinetic (PK):
   • PD interactions are a result of the com­bined impact of medications on the body when there is no direct effect on absorp­tion, distribution, metabolism, or excretion characteristics, such as 2 medications that act at the same receptor or lead to similar or opposing pharmacologic effects.
   • PK interactions occur when a drug affects the absorption, distribution, metabo­lism, or excretion characteristics of another drug.

Although it is possible that drug−drug interactions will have no clinical effect, when the impact of a PD or PK drug−drug interaction is evident, it likely is the result of additive, synergistic, or antago­nistic consequences on the medications’ intended impact or side-effect profile.


Pharmacodynamic interactions
Serotonin syndrome. The potential for serotonin syndrome occurs when medica­tions that increase synaptic serotonin con­centration are used concomitantly.1 This can occur through several mechanisms, including increased serotonin release, decreased reuptake, or decreased sero­tonin metabolism. A high serotonin con­centration in the CNS and in the periphery overstimulates serotonin receptors, lead­ing to signs and symptoms that can include diarrhea, fever, delirium, coma, and poten­tially death.

QT prolongation and anticholinergic toxicity are further examples of additive PD drug−drug interactions. Anticholinergic toxicity is possible when multiple medica­tions contribute to inhibition of the neuro-transmitter acetylcholine at muscarinic receptors. This leads to adverse effects such as dry mouth, constipation, confusion, and urinary retention.

QT prolongation, which can lead to arrhythmia, occurs when a patient is taking several medications that can increase the QT interval. Consider close monitoring and using alternative agents with less poten­tial to increase the QT interval in patients at risk of arrhythmias (geriatric patients, those with an increased QT interval at base­line, etc.).

Decreased seizure threshold. The increased risk of seizures with bupropion and other medications that lower the sei­zure threshold is another example of an additive PD drug interaction. Bupropion can increase the risk of seizures in a dose-dependent manner, which increases when bupropion is taken with other drugs that lower the seizure threshold.6 Seizure risk associated with alcohol or benzodiazepine withdrawal also may increase the risk for this interaction.

Of note, the increased risk of seizures with the combination of bupropion and alcohol in the absence of withdrawal is not well studied in humans, but positive corre­lation has been seen in an animal study.6

Decreased platelet function. Another example of a PD drug−drug interaction is increased risk of bleeding when a selec­tive serotonin reuptake inhibitor is used with a NSAID or oral anticoagulant. The proposed mechanism for this interaction is that blocking serotonin reuptake on platelets leads to decreased platelet func­tion and an increased risk for prolonged bleeding.7 This is somewhat controversial because, first, it has been noted that drugs with the highest degree of serotonin reup­take inhibition do not always cause the highest risk of bleeding and, second, most of the evidence for this interaction is from observational studies.7

This potential interaction could be most important for patients who need an anti­depressant, are on chronic NSAID or anti­coagulant therapy, and are at high risk of bleeding.


Pharmacokinetic interactions
PK interactions in psychiatry often are caused by interference of drug metabo­lizing enzymes. The cytochrome P450 (CYP450) family of metabolizing enzymes in particular is important to the break­down of medications in the body. Many drug−drug interactions involve medica­tions that can inhibit or induce metabolism of other drugs through their effect on the CYP450 system.

Inhibition interactions. When a drug’s metabolism is inhibited, the result is usu­ally increased serum concentration of that medication (because of less break­down) and a more potent impact on the primary mechanism of action or adverse effects. Sometimes, inhibiting metabo­lism can lead to decreased clinical effect. Tamoxifen (an oral agent used to treat breast cancer) and certain analgesics when used in combination with moderate or strong inhibitors of the CYP2D6 subfam­ily of CYP450 metabolizing enzymes are 2 examples of metabolism inhibition lead­ing to decreased efficacy.8 Both tamoxi­fen and the analgesics listed in Table 11-5 are prodrugs; that is, they must be metabolized to be active. When the enzymes that metabolize these drugs into their active form are inhibited, the concen­tration of active drug decreases.

 

 

Induction interactions. Alternatively, there is an increased rate of drug break­down and resulting decrease in effect when drugs that induce the activity of metabolizing enzymes are used with med­ications that are substrates of the same enzyme. Carbamazepine is commonly involved in this type of drug interaction because it is a strong inducer of CYP 1A2, 2B6, 2C19, 2C9, and 3A4, and the p-glyco­protein drug efflux pump.9 As a result of this rampant induction, carbamazepine can decrease the serum concentration of oral contraceptives below a reliably effec­tive level. Therefore, it is recommended that women of childbearing potential use other contraceptive methods, such as a progestin implant or an intrauterine device.10

In addition, the polycyclic aromatic hydrocarbons found in cigarettes induce activity of CYP1A2. Patients who smoke and use medications metabolized by this enzyme, such as clozapine and olanzap­ine, may need a higher dosage.


Drug elimination interactions
The last drug−drug interaction discussed here returns the discussion to Mr. T and involves drug elimination.2 The NSAIDs Mr. T was using for pain likely caused decreased renal excretion of lithium. Because lithium is primarily excreted through the kidneys, Mr. T’s NSAID use, possibly in com­bination with dehydration caused by gastro­intestinal distress, resulted in lithium toxicity. This class of analgesics should be avoided or used cautiously in patients taking lithium.


Clinical applications
The relatively common drug−drug interac­tions discussed here are just a fraction of the potential interactions mental health practi­tioners see on a daily basis. Understanding the basics of PD and PK interactions in the setting of patient-specific factors can help to clarify the information found in drug−drug interaction databases, such as Micromedex, Lexicomp, Facts and Comparisons, and Epocrates. Table 2 lists additional insights into drug interactions.

 

 

Related Resources
• CredibleMeds. Online resource on QT prolonging drugs. http://crediblemeds.org.
• Madhusoodanan S, Velama U, Parmar J, et al. A current review of cytochrome P450 interactions of psychotropic drugs. Ann Clin Psychiatry. 2014;26(2):120-138.

Drug Brand Names
Benztropine • Cogentin                            Olanzapine • Zyprexa
Bupropion • Wellbutrin                             Oxycodone • Oxycontin
Carbamazepine • Tegretol                        Paroxetine • Paxil
Clozapine • Clozaril                                  Quetiapine • Seroquel
Diphenhydramine • Benadryl                     Sertraline • Zoloft
 Duloxetine • Cymbalta                             Tamoxifen • Soltamox
Fluoxetine • Prozac                                   Trazodone • Desyrel
Lithium • Eskalith, Lithobid                        Valproate • Divalproex
Haloperidol • Haldol                                  Ziprasidone • Geodon
Hydrocodone • Vicodin

 

Disclosure
The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

Mr. T,  age 23, was given a diagnosis of bipolar disorder 1 year ago. After he experienced inadequate symp­tom relief with valproate, you switched him to extended-release lithium, 1,200 mg/d. Mr. T reported improved mood and stability with this medication adjustment. These posi­tive changes led him to resume activities he enjoyed before onset of bipolar disorder, such as running, reading, and going out to dinner with friends.

Now, Mr. T’s mother calls your office to express concern about her son’s slight

 

hand tremor, which appeared after 2 days of gas­trointestinal distress. She tells you that Mr. T sprained his ankle while running 1 week ago and has been taking over-the-counter ibu­profen for pain relief, which he did often in the past.

You suspect that Mr. T is experiencing lith­ium toxicity as a result of ibuprofen use.

 

 
 

Although mental health providers can eas­ily recognize the drug−drug interaction between lithium and nonsteroidal anti-inflammatory drugs (NSAIDs) that Mr. T experienced, interpreting the safety of a medication regimen with respect to drug− drug interactions before prescribing often is more daunting. This article reviews the basics of drug−drug interactions, while briefly highlighting common examples in psychiatric medicine (Table 11-5). We also provide an outline of additional points to consider when reviewing your patients’ medication regimens and encoun­tering unfamiliar drug−drug interactions.


Types of drug−drug interactions
Drug−drug interactions fall into 2 catego­ries: pharmacodynamic (PD) and pharmaco­kinetic (PK):
   • PD interactions are a result of the com­bined impact of medications on the body when there is no direct effect on absorp­tion, distribution, metabolism, or excretion characteristics, such as 2 medications that act at the same receptor or lead to similar or opposing pharmacologic effects.
   • PK interactions occur when a drug affects the absorption, distribution, metabo­lism, or excretion characteristics of another drug.

Although it is possible that drug−drug interactions will have no clinical effect, when the impact of a PD or PK drug−drug interaction is evident, it likely is the result of additive, synergistic, or antago­nistic consequences on the medications’ intended impact or side-effect profile.


Pharmacodynamic interactions
Serotonin syndrome. The potential for serotonin syndrome occurs when medica­tions that increase synaptic serotonin con­centration are used concomitantly.1 This can occur through several mechanisms, including increased serotonin release, decreased reuptake, or decreased sero­tonin metabolism. A high serotonin con­centration in the CNS and in the periphery overstimulates serotonin receptors, lead­ing to signs and symptoms that can include diarrhea, fever, delirium, coma, and poten­tially death.

QT prolongation and anticholinergic toxicity are further examples of additive PD drug−drug interactions. Anticholinergic toxicity is possible when multiple medica­tions contribute to inhibition of the neuro-transmitter acetylcholine at muscarinic receptors. This leads to adverse effects such as dry mouth, constipation, confusion, and urinary retention.

QT prolongation, which can lead to arrhythmia, occurs when a patient is taking several medications that can increase the QT interval. Consider close monitoring and using alternative agents with less poten­tial to increase the QT interval in patients at risk of arrhythmias (geriatric patients, those with an increased QT interval at base­line, etc.).

Decreased seizure threshold. The increased risk of seizures with bupropion and other medications that lower the sei­zure threshold is another example of an additive PD drug interaction. Bupropion can increase the risk of seizures in a dose-dependent manner, which increases when bupropion is taken with other drugs that lower the seizure threshold.6 Seizure risk associated with alcohol or benzodiazepine withdrawal also may increase the risk for this interaction.

Of note, the increased risk of seizures with the combination of bupropion and alcohol in the absence of withdrawal is not well studied in humans, but positive corre­lation has been seen in an animal study.6

Decreased platelet function. Another example of a PD drug−drug interaction is increased risk of bleeding when a selec­tive serotonin reuptake inhibitor is used with a NSAID or oral anticoagulant. The proposed mechanism for this interaction is that blocking serotonin reuptake on platelets leads to decreased platelet func­tion and an increased risk for prolonged bleeding.7 This is somewhat controversial because, first, it has been noted that drugs with the highest degree of serotonin reup­take inhibition do not always cause the highest risk of bleeding and, second, most of the evidence for this interaction is from observational studies.7

This potential interaction could be most important for patients who need an anti­depressant, are on chronic NSAID or anti­coagulant therapy, and are at high risk of bleeding.


Pharmacokinetic interactions
PK interactions in psychiatry often are caused by interference of drug metabo­lizing enzymes. The cytochrome P450 (CYP450) family of metabolizing enzymes in particular is important to the break­down of medications in the body. Many drug−drug interactions involve medica­tions that can inhibit or induce metabolism of other drugs through their effect on the CYP450 system.

Inhibition interactions. When a drug’s metabolism is inhibited, the result is usu­ally increased serum concentration of that medication (because of less break­down) and a more potent impact on the primary mechanism of action or adverse effects. Sometimes, inhibiting metabo­lism can lead to decreased clinical effect. Tamoxifen (an oral agent used to treat breast cancer) and certain analgesics when used in combination with moderate or strong inhibitors of the CYP2D6 subfam­ily of CYP450 metabolizing enzymes are 2 examples of metabolism inhibition lead­ing to decreased efficacy.8 Both tamoxi­fen and the analgesics listed in Table 11-5 are prodrugs; that is, they must be metabolized to be active. When the enzymes that metabolize these drugs into their active form are inhibited, the concen­tration of active drug decreases.

 

 

Induction interactions. Alternatively, there is an increased rate of drug break­down and resulting decrease in effect when drugs that induce the activity of metabolizing enzymes are used with med­ications that are substrates of the same enzyme. Carbamazepine is commonly involved in this type of drug interaction because it is a strong inducer of CYP 1A2, 2B6, 2C19, 2C9, and 3A4, and the p-glyco­protein drug efflux pump.9 As a result of this rampant induction, carbamazepine can decrease the serum concentration of oral contraceptives below a reliably effec­tive level. Therefore, it is recommended that women of childbearing potential use other contraceptive methods, such as a progestin implant or an intrauterine device.10

In addition, the polycyclic aromatic hydrocarbons found in cigarettes induce activity of CYP1A2. Patients who smoke and use medications metabolized by this enzyme, such as clozapine and olanzap­ine, may need a higher dosage.


Drug elimination interactions
The last drug−drug interaction discussed here returns the discussion to Mr. T and involves drug elimination.2 The NSAIDs Mr. T was using for pain likely caused decreased renal excretion of lithium. Because lithium is primarily excreted through the kidneys, Mr. T’s NSAID use, possibly in com­bination with dehydration caused by gastro­intestinal distress, resulted in lithium toxicity. This class of analgesics should be avoided or used cautiously in patients taking lithium.


Clinical applications
The relatively common drug−drug interac­tions discussed here are just a fraction of the potential interactions mental health practi­tioners see on a daily basis. Understanding the basics of PD and PK interactions in the setting of patient-specific factors can help to clarify the information found in drug−drug interaction databases, such as Micromedex, Lexicomp, Facts and Comparisons, and Epocrates. Table 2 lists additional insights into drug interactions.

 

 

Related Resources
• CredibleMeds. Online resource on QT prolonging drugs. http://crediblemeds.org.
• Madhusoodanan S, Velama U, Parmar J, et al. A current review of cytochrome P450 interactions of psychotropic drugs. Ann Clin Psychiatry. 2014;26(2):120-138.

Drug Brand Names
Benztropine • Cogentin                            Olanzapine • Zyprexa
Bupropion • Wellbutrin                             Oxycodone • Oxycontin
Carbamazepine • Tegretol                        Paroxetine • Paxil
Clozapine • Clozaril                                  Quetiapine • Seroquel
Diphenhydramine • Benadryl                     Sertraline • Zoloft
 Duloxetine • Cymbalta                             Tamoxifen • Soltamox
Fluoxetine • Prozac                                   Trazodone • Desyrel
Lithium • Eskalith, Lithobid                        Valproate • Divalproex
Haloperidol • Haldol                                  Ziprasidone • Geodon
Hydrocodone • Vicodin

 

Disclosure
The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

References


1. Buckley NA, Dawson AH, Isbister GK. Serotonin syndrome. BMJ. 2014;348:g1626. doi: 10.1136/bmj.g1626.
2. Eskalith [package insert]. Research Triangle Park, NC: GlaxoSmithKline; 2003.
3. Handler J. Lithium and antihypertensive medication: a potentially dangerous interaction. J Clin Hypertens (Greenwich). 2009;11(12):738-742.
4. Blanche P, Raynaud E, Kerob D, et al. Lithium intoxication in an elderly patient after combined treatment with losartan. Eur J Clin Pharmacol. 1997;52(6):501.
5. Atacand [package insert]. Wilmington, DE: AstraZeneca LP; 2013.
6. Silverstone PH, Williams R, McMahon L, et al. Alcohol significantly lowers the seizure threshold in mice when co-administered with bupropion hydrochloride. Ann Gen Psychiatry. 2008;7:11.
7. Spina E, Trifirò G, Caraci F. Clinically significant drug interactions with newer antidepressants. CNS Drugs. 2012;26(1):39-67.
8. Ereshefsky L, Sloan DM. Drug-drug interactions with the use of psychotropic medications. CNS Spectr. 2009;14(suppl Q and A forum 8):1-8.
9. Carbamazepine. Drug facts and comparisons database. St. Louis, MO: Wolters Kluwer Health Inc; November 2014.
10. Pennell PB. Pregnancy, epilepsy, and women’s issues. Continuum (Minneap Minn). 2013;19(3 Epilepsy):697-714.

References


1. Buckley NA, Dawson AH, Isbister GK. Serotonin syndrome. BMJ. 2014;348:g1626. doi: 10.1136/bmj.g1626.
2. Eskalith [package insert]. Research Triangle Park, NC: GlaxoSmithKline; 2003.
3. Handler J. Lithium and antihypertensive medication: a potentially dangerous interaction. J Clin Hypertens (Greenwich). 2009;11(12):738-742.
4. Blanche P, Raynaud E, Kerob D, et al. Lithium intoxication in an elderly patient after combined treatment with losartan. Eur J Clin Pharmacol. 1997;52(6):501.
5. Atacand [package insert]. Wilmington, DE: AstraZeneca LP; 2013.
6. Silverstone PH, Williams R, McMahon L, et al. Alcohol significantly lowers the seizure threshold in mice when co-administered with bupropion hydrochloride. Ann Gen Psychiatry. 2008;7:11.
7. Spina E, Trifirò G, Caraci F. Clinically significant drug interactions with newer antidepressants. CNS Drugs. 2012;26(1):39-67.
8. Ereshefsky L, Sloan DM. Drug-drug interactions with the use of psychotropic medications. CNS Spectr. 2009;14(suppl Q and A forum 8):1-8.
9. Carbamazepine. Drug facts and comparisons database. St. Louis, MO: Wolters Kluwer Health Inc; November 2014.
10. Pennell PB. Pregnancy, epilepsy, and women’s issues. Continuum (Minneap Minn). 2013;19(3 Epilepsy):697-714.

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ASCP: Moving from treatment to prevention in mental illness – an achievable goal?

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ASCP: Moving from treatment to prevention in mental illness – an achievable goal?

MIAMI BEACH – Researchers reporting early work in three areas of chronic mental illness or disability – autism spectrum disorder, schizophrenia, and bipolar disorder – shared the promising results of early detection and intervention programs during a plenary session at a meeting of the American Society for Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting. Common themes across research in these disparate illnesses included the benefit of early identification of at-risk individuals and the hope that early intervention might modify the disease course of lifelong illnesses.

Geraldine Dawson, Ph.D., of Duke University in Durham, N.C., shared the results of her early detection and intervention programs. Since siblings of individuals with autism spectrum disorders are at increased risk for autism spectrum disorder (ASD), researchers began using eye-tracking exercises in very young infants. Some studies have reported differences in attention and gaze in infants as young as 4 months old; infants who went on to develop ASD spent less time focusing on the eyes of faces. Infants who later developed ASD also showed less differential in EEG tracings to direct versus averted gaze than normally developing infants. Dr. Dawson’s work found that toddlers with ASD showed distinctly more EEG reactivity to familiar versus unfamiliar objects, but not faces, indicating a lack of ability to differentiate faces.

Courtesy Duke University
Geraldine Dawson, Ph.D.

Those changes, said Dr. Dawson, might indicate a fundamental biologic underpinning to ASD. Further, the lack of interaction with the social environment that’s seen so early might result in overall reduced input and stimulation for the developing prefrontal cortex, influencing development. “We have a double whammy going on here,” said Dr. Dawson, professor in the department of psychiatry and behavioral sciences at Duke.

Dr. Dawson found that early intensive behavioral intervention that started before age 2 and lasted for 2 years resulted in improved cognitive, language, and social behavior. In addition, brain activity of these children in response to social stimuli by the age of 4 was indistinguishable from that of a typical 4-year-old, said Dr. Dawson, also a professor in the departments of psychology and neuroscience, and pediatrics at the university.

She also shared the results of a small pilot study with parents of infants at risk for ASD who were coached in strategies that promote interaction with the social environment. She found that among at-risk infants, by 12 months of age, they showed more normal EEG responses to social stimuli.

Dr. Dawson emphasized that it is not yet known whether the early stimulation reduces later symptoms of autism. She said she hopes that a combination of pharmacologic and behavioral interventions will emerge that will enhance synaptic plasticity and improve outcomes for greater numbers of children.

Dr. John M. Kane spoke to the effectiveness of the NAVIGATE structured team-based assessment and treatment program for individuals newly diagnosed with schizophrenia. The program also incorporated COMPASS, a web-based documentation, shared decision making, and decision support tool. Using a cluster-randomized protocol comparing NAVIGATE to community care for first-episode schizophrenia, Dr. Kane and his colleagues assessed 404 patients at 34 sites in 21 states over a 2-year-year period.

In early results, NAVIGATE enrollees were strikingly more likely to be asked regularly about medication use, side effects, and symptoms; to receive counseling about work or school options; and to have family counseling and support than those receiving usual treatment in the community-based centers participating in the program over the 2 years of the study period.

Early and standardized delivery of the coordinated specialty care model, said Dr. Kane, was associated with patients staying in treatment significantly longer, being more likely to be working or in school, and experiencing symptom improvement. Patients receiving the NAVIGATE intervention had significant improvement in the study’s primary outcome measure, quality of life, said Dr. Kane, professor of psychiatry, neurology, and neuroscience at the Albert Einstein College of Medicine, New York.

Ellen Frank, Ph.D., of the University of Pittsburgh, began her presentation by expressing frank envy for her colleagues’ relatively advanced understanding of the pathophysiology of autism and schizophrenia. By contrast, she said, very little is known about the bipolar disorders.

One thing that is known, however, is the high degree of heritability of bipolar disorder. Her work, she said, begins to assess whether prediagnosis behavioral interventions among children of parents with bipolar disorder might impact the course of the disorder or even prevent its development.

Building on the knowledge that anxiety, depression, and emotional ability in adolescence are predictors for the development of bipolar disorder, Dr. Frank developed and implemented an intervention that focused on regularizing sleep and social rhythms for these at-risk adolescents.

 

 

The open pilot study of 42 evenly split adolescents compared those who received the usual appropriate referrals alone with those who received these referrals, plus sleep and social rhythm–targeted education and support for families and the teens themselves. These interventions, dubbed interpersonal and social rhythm therapy (IPRST), have been shown to reduce illness recurrence in adults with bipolar disorder, said Dr. Frank, also director of the depression and manic-depression prevention program at the Western Psychiatric Institute and Clinic in Pittsburgh.

Over the 6-month follow-up period, Dr. Frank said, IPRST recipients had significantly fewer subclinical symptoms of depression and hypomania (P <.05 for both) than their controls, according to assessors who were blinded as to intervention. Participants and their families were satisfied overall with the IPRST therapy, and Dr. Frank noted that the adolescents were “remarkably willing to be open” during the sessions.

Dr. Frank reiterated the less mature state of knowledge about the etiology and natural history of bipolar disorders. Even so, she said, this small pilot study showed an encouraging improvement in sleep patterns and a global improvement in mood and functioning among teens at significantly increased risk for bipolar disorder.

Dr. Dawson serves on the scientific advisory boards of several entities, including Janssen Research and Development and Roche Pharmaceuticals. She also receives royalties from Guilford Press and Oxford University Press. Dr. Kane has served as a consultant to several companies, including Forest Pharmaceuticals. Dr. Frank’s disclosures include Guilford Press and Servier International.

[email protected]

On Twitter @karioakes

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MIAMI BEACH – Researchers reporting early work in three areas of chronic mental illness or disability – autism spectrum disorder, schizophrenia, and bipolar disorder – shared the promising results of early detection and intervention programs during a plenary session at a meeting of the American Society for Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting. Common themes across research in these disparate illnesses included the benefit of early identification of at-risk individuals and the hope that early intervention might modify the disease course of lifelong illnesses.

Geraldine Dawson, Ph.D., of Duke University in Durham, N.C., shared the results of her early detection and intervention programs. Since siblings of individuals with autism spectrum disorders are at increased risk for autism spectrum disorder (ASD), researchers began using eye-tracking exercises in very young infants. Some studies have reported differences in attention and gaze in infants as young as 4 months old; infants who went on to develop ASD spent less time focusing on the eyes of faces. Infants who later developed ASD also showed less differential in EEG tracings to direct versus averted gaze than normally developing infants. Dr. Dawson’s work found that toddlers with ASD showed distinctly more EEG reactivity to familiar versus unfamiliar objects, but not faces, indicating a lack of ability to differentiate faces.

Courtesy Duke University
Geraldine Dawson, Ph.D.

Those changes, said Dr. Dawson, might indicate a fundamental biologic underpinning to ASD. Further, the lack of interaction with the social environment that’s seen so early might result in overall reduced input and stimulation for the developing prefrontal cortex, influencing development. “We have a double whammy going on here,” said Dr. Dawson, professor in the department of psychiatry and behavioral sciences at Duke.

Dr. Dawson found that early intensive behavioral intervention that started before age 2 and lasted for 2 years resulted in improved cognitive, language, and social behavior. In addition, brain activity of these children in response to social stimuli by the age of 4 was indistinguishable from that of a typical 4-year-old, said Dr. Dawson, also a professor in the departments of psychology and neuroscience, and pediatrics at the university.

She also shared the results of a small pilot study with parents of infants at risk for ASD who were coached in strategies that promote interaction with the social environment. She found that among at-risk infants, by 12 months of age, they showed more normal EEG responses to social stimuli.

Dr. Dawson emphasized that it is not yet known whether the early stimulation reduces later symptoms of autism. She said she hopes that a combination of pharmacologic and behavioral interventions will emerge that will enhance synaptic plasticity and improve outcomes for greater numbers of children.

Dr. John M. Kane spoke to the effectiveness of the NAVIGATE structured team-based assessment and treatment program for individuals newly diagnosed with schizophrenia. The program also incorporated COMPASS, a web-based documentation, shared decision making, and decision support tool. Using a cluster-randomized protocol comparing NAVIGATE to community care for first-episode schizophrenia, Dr. Kane and his colleagues assessed 404 patients at 34 sites in 21 states over a 2-year-year period.

In early results, NAVIGATE enrollees were strikingly more likely to be asked regularly about medication use, side effects, and symptoms; to receive counseling about work or school options; and to have family counseling and support than those receiving usual treatment in the community-based centers participating in the program over the 2 years of the study period.

Early and standardized delivery of the coordinated specialty care model, said Dr. Kane, was associated with patients staying in treatment significantly longer, being more likely to be working or in school, and experiencing symptom improvement. Patients receiving the NAVIGATE intervention had significant improvement in the study’s primary outcome measure, quality of life, said Dr. Kane, professor of psychiatry, neurology, and neuroscience at the Albert Einstein College of Medicine, New York.

Ellen Frank, Ph.D., of the University of Pittsburgh, began her presentation by expressing frank envy for her colleagues’ relatively advanced understanding of the pathophysiology of autism and schizophrenia. By contrast, she said, very little is known about the bipolar disorders.

One thing that is known, however, is the high degree of heritability of bipolar disorder. Her work, she said, begins to assess whether prediagnosis behavioral interventions among children of parents with bipolar disorder might impact the course of the disorder or even prevent its development.

Building on the knowledge that anxiety, depression, and emotional ability in adolescence are predictors for the development of bipolar disorder, Dr. Frank developed and implemented an intervention that focused on regularizing sleep and social rhythms for these at-risk adolescents.

 

 

The open pilot study of 42 evenly split adolescents compared those who received the usual appropriate referrals alone with those who received these referrals, plus sleep and social rhythm–targeted education and support for families and the teens themselves. These interventions, dubbed interpersonal and social rhythm therapy (IPRST), have been shown to reduce illness recurrence in adults with bipolar disorder, said Dr. Frank, also director of the depression and manic-depression prevention program at the Western Psychiatric Institute and Clinic in Pittsburgh.

Over the 6-month follow-up period, Dr. Frank said, IPRST recipients had significantly fewer subclinical symptoms of depression and hypomania (P <.05 for both) than their controls, according to assessors who were blinded as to intervention. Participants and their families were satisfied overall with the IPRST therapy, and Dr. Frank noted that the adolescents were “remarkably willing to be open” during the sessions.

Dr. Frank reiterated the less mature state of knowledge about the etiology and natural history of bipolar disorders. Even so, she said, this small pilot study showed an encouraging improvement in sleep patterns and a global improvement in mood and functioning among teens at significantly increased risk for bipolar disorder.

Dr. Dawson serves on the scientific advisory boards of several entities, including Janssen Research and Development and Roche Pharmaceuticals. She also receives royalties from Guilford Press and Oxford University Press. Dr. Kane has served as a consultant to several companies, including Forest Pharmaceuticals. Dr. Frank’s disclosures include Guilford Press and Servier International.

[email protected]

On Twitter @karioakes

MIAMI BEACH – Researchers reporting early work in three areas of chronic mental illness or disability – autism spectrum disorder, schizophrenia, and bipolar disorder – shared the promising results of early detection and intervention programs during a plenary session at a meeting of the American Society for Clinical Psychopharmacology, formerly known as the New Clinical Drug Evaluation Unit meeting. Common themes across research in these disparate illnesses included the benefit of early identification of at-risk individuals and the hope that early intervention might modify the disease course of lifelong illnesses.

Geraldine Dawson, Ph.D., of Duke University in Durham, N.C., shared the results of her early detection and intervention programs. Since siblings of individuals with autism spectrum disorders are at increased risk for autism spectrum disorder (ASD), researchers began using eye-tracking exercises in very young infants. Some studies have reported differences in attention and gaze in infants as young as 4 months old; infants who went on to develop ASD spent less time focusing on the eyes of faces. Infants who later developed ASD also showed less differential in EEG tracings to direct versus averted gaze than normally developing infants. Dr. Dawson’s work found that toddlers with ASD showed distinctly more EEG reactivity to familiar versus unfamiliar objects, but not faces, indicating a lack of ability to differentiate faces.

Courtesy Duke University
Geraldine Dawson, Ph.D.

Those changes, said Dr. Dawson, might indicate a fundamental biologic underpinning to ASD. Further, the lack of interaction with the social environment that’s seen so early might result in overall reduced input and stimulation for the developing prefrontal cortex, influencing development. “We have a double whammy going on here,” said Dr. Dawson, professor in the department of psychiatry and behavioral sciences at Duke.

Dr. Dawson found that early intensive behavioral intervention that started before age 2 and lasted for 2 years resulted in improved cognitive, language, and social behavior. In addition, brain activity of these children in response to social stimuli by the age of 4 was indistinguishable from that of a typical 4-year-old, said Dr. Dawson, also a professor in the departments of psychology and neuroscience, and pediatrics at the university.

She also shared the results of a small pilot study with parents of infants at risk for ASD who were coached in strategies that promote interaction with the social environment. She found that among at-risk infants, by 12 months of age, they showed more normal EEG responses to social stimuli.

Dr. Dawson emphasized that it is not yet known whether the early stimulation reduces later symptoms of autism. She said she hopes that a combination of pharmacologic and behavioral interventions will emerge that will enhance synaptic plasticity and improve outcomes for greater numbers of children.

Dr. John M. Kane spoke to the effectiveness of the NAVIGATE structured team-based assessment and treatment program for individuals newly diagnosed with schizophrenia. The program also incorporated COMPASS, a web-based documentation, shared decision making, and decision support tool. Using a cluster-randomized protocol comparing NAVIGATE to community care for first-episode schizophrenia, Dr. Kane and his colleagues assessed 404 patients at 34 sites in 21 states over a 2-year-year period.

In early results, NAVIGATE enrollees were strikingly more likely to be asked regularly about medication use, side effects, and symptoms; to receive counseling about work or school options; and to have family counseling and support than those receiving usual treatment in the community-based centers participating in the program over the 2 years of the study period.

Early and standardized delivery of the coordinated specialty care model, said Dr. Kane, was associated with patients staying in treatment significantly longer, being more likely to be working or in school, and experiencing symptom improvement. Patients receiving the NAVIGATE intervention had significant improvement in the study’s primary outcome measure, quality of life, said Dr. Kane, professor of psychiatry, neurology, and neuroscience at the Albert Einstein College of Medicine, New York.

Ellen Frank, Ph.D., of the University of Pittsburgh, began her presentation by expressing frank envy for her colleagues’ relatively advanced understanding of the pathophysiology of autism and schizophrenia. By contrast, she said, very little is known about the bipolar disorders.

One thing that is known, however, is the high degree of heritability of bipolar disorder. Her work, she said, begins to assess whether prediagnosis behavioral interventions among children of parents with bipolar disorder might impact the course of the disorder or even prevent its development.

Building on the knowledge that anxiety, depression, and emotional ability in adolescence are predictors for the development of bipolar disorder, Dr. Frank developed and implemented an intervention that focused on regularizing sleep and social rhythms for these at-risk adolescents.

 

 

The open pilot study of 42 evenly split adolescents compared those who received the usual appropriate referrals alone with those who received these referrals, plus sleep and social rhythm–targeted education and support for families and the teens themselves. These interventions, dubbed interpersonal and social rhythm therapy (IPRST), have been shown to reduce illness recurrence in adults with bipolar disorder, said Dr. Frank, also director of the depression and manic-depression prevention program at the Western Psychiatric Institute and Clinic in Pittsburgh.

Over the 6-month follow-up period, Dr. Frank said, IPRST recipients had significantly fewer subclinical symptoms of depression and hypomania (P <.05 for both) than their controls, according to assessors who were blinded as to intervention. Participants and their families were satisfied overall with the IPRST therapy, and Dr. Frank noted that the adolescents were “remarkably willing to be open” during the sessions.

Dr. Frank reiterated the less mature state of knowledge about the etiology and natural history of bipolar disorders. Even so, she said, this small pilot study showed an encouraging improvement in sleep patterns and a global improvement in mood and functioning among teens at significantly increased risk for bipolar disorder.

Dr. Dawson serves on the scientific advisory boards of several entities, including Janssen Research and Development and Roche Pharmaceuticals. She also receives royalties from Guilford Press and Oxford University Press. Dr. Kane has served as a consultant to several companies, including Forest Pharmaceuticals. Dr. Frank’s disclosures include Guilford Press and Servier International.

[email protected]

On Twitter @karioakes

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Initial symptoms, BMI among factors may predict bipolar mania outcomes

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Doctors looking for treatment options for bipolar mania would be wise to keep the following in mind: The presence of psychotic symptoms during the manic index episode, the number of past depressive episodes, and body mass index may be the best predictors of functional outcome at 6 months’ follow-up after a manic episode.

A team of researchers led by Dr. C. Mar Bonn<scaps>í</scaps>n of the University of Barcelona examined 169 patients with bipolar disorder I who suffered an acute manic episode and were treated clinically and followed up at 6 months. Bipolar severity was assessed using scores from the Functioning Assessment Short Test (FAST) scale. The researchers then used a multivariate analysis to identify six variables that best predicted functional outcome at 6-month follow-up after a manic episode. Only three of the variables were found to be statistically significant: the number of previous depressive episodes (P = .002), the presence of psychotic symptoms during the index manic episode (P = .031), and body mass index (P = .041).

“The effective prevention of depressive episodes may be crucial to prevent further disability. Moreover, early treatment of psychotic symptoms may be of importance to avoid the progression and further worsening of the manic episode. Finally, educating patients in healthy lifestyle, including exercise and eating habits, may also help to avoid long-term treatment side effects of those drugs often associated with weight increase or other comorbidities associated to weight gain,” wrote the investigators.

Read the full article here: Journal of Affective Disorders 2015;182:121-5 (http://dx.doi.org/10.1016/j.jad.2015.04.043).

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Doctors looking for treatment options for bipolar mania would be wise to keep the following in mind: The presence of psychotic symptoms during the manic index episode, the number of past depressive episodes, and body mass index may be the best predictors of functional outcome at 6 months’ follow-up after a manic episode.

A team of researchers led by Dr. C. Mar Bonn<scaps>í</scaps>n of the University of Barcelona examined 169 patients with bipolar disorder I who suffered an acute manic episode and were treated clinically and followed up at 6 months. Bipolar severity was assessed using scores from the Functioning Assessment Short Test (FAST) scale. The researchers then used a multivariate analysis to identify six variables that best predicted functional outcome at 6-month follow-up after a manic episode. Only three of the variables were found to be statistically significant: the number of previous depressive episodes (P = .002), the presence of psychotic symptoms during the index manic episode (P = .031), and body mass index (P = .041).

“The effective prevention of depressive episodes may be crucial to prevent further disability. Moreover, early treatment of psychotic symptoms may be of importance to avoid the progression and further worsening of the manic episode. Finally, educating patients in healthy lifestyle, including exercise and eating habits, may also help to avoid long-term treatment side effects of those drugs often associated with weight increase or other comorbidities associated to weight gain,” wrote the investigators.

Read the full article here: Journal of Affective Disorders 2015;182:121-5 (http://dx.doi.org/10.1016/j.jad.2015.04.043).

[email protected]

Doctors looking for treatment options for bipolar mania would be wise to keep the following in mind: The presence of psychotic symptoms during the manic index episode, the number of past depressive episodes, and body mass index may be the best predictors of functional outcome at 6 months’ follow-up after a manic episode.

A team of researchers led by Dr. C. Mar Bonn<scaps>í</scaps>n of the University of Barcelona examined 169 patients with bipolar disorder I who suffered an acute manic episode and were treated clinically and followed up at 6 months. Bipolar severity was assessed using scores from the Functioning Assessment Short Test (FAST) scale. The researchers then used a multivariate analysis to identify six variables that best predicted functional outcome at 6-month follow-up after a manic episode. Only three of the variables were found to be statistically significant: the number of previous depressive episodes (P = .002), the presence of psychotic symptoms during the index manic episode (P = .031), and body mass index (P = .041).

“The effective prevention of depressive episodes may be crucial to prevent further disability. Moreover, early treatment of psychotic symptoms may be of importance to avoid the progression and further worsening of the manic episode. Finally, educating patients in healthy lifestyle, including exercise and eating habits, may also help to avoid long-term treatment side effects of those drugs often associated with weight increase or other comorbidities associated to weight gain,” wrote the investigators.

Read the full article here: Journal of Affective Disorders 2015;182:121-5 (http://dx.doi.org/10.1016/j.jad.2015.04.043).

[email protected]

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Initial symptoms, BMI among factors may predict bipolar mania outcomes
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