Bipolar Disorder

A smartphone-based self-management intervention developed for patients with bipolar disorder (BD) can help decrease depressive symptoms and improve quality of life, new research suggests.

In a randomized clinical trial of usual care plus the experimental smartphone-based intervention known as LiveWell vs. usual care alone, participants in the smartphone group who were categorized as low-risk or in asymptomatic recovery at baseline also showed reduced manic symptom severity.

The results suggest that “apps for individuals with bipolar disorder will likely be useful for some people in managing medication use, sleep duration, routine, and monitoring for and managing signs and symptoms” of the disorder, coinvestigator Evan H. Goulding, MD, PhD, assistant professor of psychiatry and behavioral sciences, Northwestern University, Chicago, told this news organization.

Use of the app may also “lead to decreased recurrence of mood episodes, impact overall depressive and manic symptom levels, and improve some aspects of quality of life,” Dr. Goulding added.

The findings were published online in JAMA Psychiatry.
 

Daily check-ins

The researchers randomly assigned 205 patients with BD to receive either usual care (n = 81; 56% women; mean age, 39 years) or usual care plus the smartphone-based self-management intervention LiveWell (n = 124; 65% women; mean age, 43 years) between March 2017 and April 2020. To be included, participants could not be experiencing a current mood episode or suicidal ideation.

The smartphone intervention included a daily check-in to monitor medication adherence, sleep, and wellness levels; coach visits to support adherence to the app; six phone calls over 16 weeks; and support from mental health professionals whenever needed. Participants in this group were asked to engage their mental health providers in the intervention as well.

Each participant in the control group had a visit with a coach who facilitated self-management support.

Investigators assessed all participants every 8 weeks until week 48 to gather information on mood symptoms and severity over the past 2 weeks and on quality of life.

The patients were also stratified into high- and low-risk relapse groups. The low-risk group was in asymptomatic recovery, meaning that they experienced two or fewer moderate symptoms of mania or depression in the previous 8 weeks. In addition, they had no moderate symptoms of mania or depression at study enrollment.

Patients in the high-risk group were recovering from an episode of mania or depression. They also had two or fewer moderate symptoms, but for 8 weeks or less.
 

Low-risk group fares better

Results showed that the smartphone intervention was significantly associated with a reduction in depressive symptoms vs. usual care (P = .02), as well as improvement in one aspect of the World Health Organization Quality of Life Assessment that measures social relationships (P = .02).

When the investigators stratified participants into risk groups, they found that for those in the low-risk group the smartphone-based intervention was associated with lower episode-relapse rates, lower mean percentage time symptomatic, and decreased manic symptom severity.

Mean estimated relapse rates by 48 weeks for the low-risk group were 12% for those in the intervention group and 37.2% for those in the control group. No differences were noted for the high-risk group.

Low-risk patients in the intervention group also had lower mean percentage-time symptomatic (17.9%) than those in the control group (26.1%) (Cohen d = .31).

“Our results are consistent with literature emphasizing the identification and facilitation of management plans for early warning signs of mood episodes and using these plans as an important self-management technique for avoiding relapse,” Dr. Goulding said.

Study limitations included low engagement by mental health professionals and low data generalizability to other populations, as the sample was mostly White (84% of the app group and 81% of the control group).

“There is a fairly large literature on risk factors, longitudinal trajectories, and stages of diseases that suggest we should already be able to predict relapse risk for individuals,” Dr. Goulding said.

“However, moving from overall risk to individual risk is trickier and will require larger datasets with longer follow-up to better understand what types of help should be delivered when and to whom,” he added.
 

‘Requires commitment’

John Torous, MD, director of the division of digital psychiatry at Beth Israel Deaconess Medical Center, Boston, noted that mental health apps such as LiveWell require “time and energy devoted by both the patient and their clinician for maximal efficacy, which requires commitment from and training for both parties as well.

“But with such an investment in people, there is good evidence apps can help people with bipolar disorder even during the more severe periods of the illness,” added Dr. Torous, who was not involved with the research.

The study was funded by the National Institute of Mental Health.

Dr. Goulding reports having received honoraria from Otsuka. Dr. Torous has reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

A smartphone-based self-management intervention developed for patients with bipolar disorder (BD) can help decrease depressive symptoms and improve quality of life, new research suggests.

In a randomized clinical trial of usual care plus the experimental smartphone-based intervention known as LiveWell vs. usual care alone, participants in the smartphone group who were categorized as low-risk or in asymptomatic recovery at baseline also showed reduced manic symptom severity.

The results suggest that “apps for individuals with bipolar disorder will likely be useful for some people in managing medication use, sleep duration, routine, and monitoring for and managing signs and symptoms” of the disorder, coinvestigator Evan H. Goulding, MD, PhD, assistant professor of psychiatry and behavioral sciences, Northwestern University, Chicago, told this news organization.

Use of the app may also “lead to decreased recurrence of mood episodes, impact overall depressive and manic symptom levels, and improve some aspects of quality of life,” Dr. Goulding added.

The findings were published online in JAMA Psychiatry.
 

Daily check-ins

The researchers randomly assigned 205 patients with BD to receive either usual care (n = 81; 56% women; mean age, 39 years) or usual care plus the smartphone-based self-management intervention LiveWell (n = 124; 65% women; mean age, 43 years) between March 2017 and April 2020. To be included, participants could not be experiencing a current mood episode or suicidal ideation.

The smartphone intervention included a daily check-in to monitor medication adherence, sleep, and wellness levels; coach visits to support adherence to the app; six phone calls over 16 weeks; and support from mental health professionals whenever needed. Participants in this group were asked to engage their mental health providers in the intervention as well.

Each participant in the control group had a visit with a coach who facilitated self-management support.

Investigators assessed all participants every 8 weeks until week 48 to gather information on mood symptoms and severity over the past 2 weeks and on quality of life.

The patients were also stratified into high- and low-risk relapse groups. The low-risk group was in asymptomatic recovery, meaning that they experienced two or fewer moderate symptoms of mania or depression in the previous 8 weeks. In addition, they had no moderate symptoms of mania or depression at study enrollment.

Patients in the high-risk group were recovering from an episode of mania or depression. They also had two or fewer moderate symptoms, but for 8 weeks or less.
 

Low-risk group fares better

Results showed that the smartphone intervention was significantly associated with a reduction in depressive symptoms vs. usual care (P = .02), as well as improvement in one aspect of the World Health Organization Quality of Life Assessment that measures social relationships (P = .02).

When the investigators stratified participants into risk groups, they found that for those in the low-risk group the smartphone-based intervention was associated with lower episode-relapse rates, lower mean percentage time symptomatic, and decreased manic symptom severity.

Mean estimated relapse rates by 48 weeks for the low-risk group were 12% for those in the intervention group and 37.2% for those in the control group. No differences were noted for the high-risk group.

Low-risk patients in the intervention group also had lower mean percentage-time symptomatic (17.9%) than those in the control group (26.1%) (Cohen d = .31).

“Our results are consistent with literature emphasizing the identification and facilitation of management plans for early warning signs of mood episodes and using these plans as an important self-management technique for avoiding relapse,” Dr. Goulding said.

Study limitations included low engagement by mental health professionals and low data generalizability to other populations, as the sample was mostly White (84% of the app group and 81% of the control group).

“There is a fairly large literature on risk factors, longitudinal trajectories, and stages of diseases that suggest we should already be able to predict relapse risk for individuals,” Dr. Goulding said.

“However, moving from overall risk to individual risk is trickier and will require larger datasets with longer follow-up to better understand what types of help should be delivered when and to whom,” he added.
 

‘Requires commitment’

John Torous, MD, director of the division of digital psychiatry at Beth Israel Deaconess Medical Center, Boston, noted that mental health apps such as LiveWell require “time and energy devoted by both the patient and their clinician for maximal efficacy, which requires commitment from and training for both parties as well.

“But with such an investment in people, there is good evidence apps can help people with bipolar disorder even during the more severe periods of the illness,” added Dr. Torous, who was not involved with the research.

The study was funded by the National Institute of Mental Health.

Dr. Goulding reports having received honoraria from Otsuka. Dr. Torous has reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

A smartphone-based self-management intervention developed for patients with bipolar disorder (BD) can help decrease depressive symptoms and improve quality of life, new research suggests.

In a randomized clinical trial of usual care plus the experimental smartphone-based intervention known as LiveWell vs. usual care alone, participants in the smartphone group who were categorized as low-risk or in asymptomatic recovery at baseline also showed reduced manic symptom severity.

The results suggest that “apps for individuals with bipolar disorder will likely be useful for some people in managing medication use, sleep duration, routine, and monitoring for and managing signs and symptoms” of the disorder, coinvestigator Evan H. Goulding, MD, PhD, assistant professor of psychiatry and behavioral sciences, Northwestern University, Chicago, told this news organization.

Use of the app may also “lead to decreased recurrence of mood episodes, impact overall depressive and manic symptom levels, and improve some aspects of quality of life,” Dr. Goulding added.

The findings were published online in JAMA Psychiatry.
 

Daily check-ins

The researchers randomly assigned 205 patients with BD to receive either usual care (n = 81; 56% women; mean age, 39 years) or usual care plus the smartphone-based self-management intervention LiveWell (n = 124; 65% women; mean age, 43 years) between March 2017 and April 2020. To be included, participants could not be experiencing a current mood episode or suicidal ideation.

The smartphone intervention included a daily check-in to monitor medication adherence, sleep, and wellness levels; coach visits to support adherence to the app; six phone calls over 16 weeks; and support from mental health professionals whenever needed. Participants in this group were asked to engage their mental health providers in the intervention as well.

Each participant in the control group had a visit with a coach who facilitated self-management support.

Investigators assessed all participants every 8 weeks until week 48 to gather information on mood symptoms and severity over the past 2 weeks and on quality of life.

The patients were also stratified into high- and low-risk relapse groups. The low-risk group was in asymptomatic recovery, meaning that they experienced two or fewer moderate symptoms of mania or depression in the previous 8 weeks. In addition, they had no moderate symptoms of mania or depression at study enrollment.

Patients in the high-risk group were recovering from an episode of mania or depression. They also had two or fewer moderate symptoms, but for 8 weeks or less.
 

Low-risk group fares better

Results showed that the smartphone intervention was significantly associated with a reduction in depressive symptoms vs. usual care (P = .02), as well as improvement in one aspect of the World Health Organization Quality of Life Assessment that measures social relationships (P = .02).

When the investigators stratified participants into risk groups, they found that for those in the low-risk group the smartphone-based intervention was associated with lower episode-relapse rates, lower mean percentage time symptomatic, and decreased manic symptom severity.

Mean estimated relapse rates by 48 weeks for the low-risk group were 12% for those in the intervention group and 37.2% for those in the control group. No differences were noted for the high-risk group.

Low-risk patients in the intervention group also had lower mean percentage-time symptomatic (17.9%) than those in the control group (26.1%) (Cohen d = .31).

“Our results are consistent with literature emphasizing the identification and facilitation of management plans for early warning signs of mood episodes and using these plans as an important self-management technique for avoiding relapse,” Dr. Goulding said.

Study limitations included low engagement by mental health professionals and low data generalizability to other populations, as the sample was mostly White (84% of the app group and 81% of the control group).

“There is a fairly large literature on risk factors, longitudinal trajectories, and stages of diseases that suggest we should already be able to predict relapse risk for individuals,” Dr. Goulding said.

“However, moving from overall risk to individual risk is trickier and will require larger datasets with longer follow-up to better understand what types of help should be delivered when and to whom,” he added.
 

‘Requires commitment’

John Torous, MD, director of the division of digital psychiatry at Beth Israel Deaconess Medical Center, Boston, noted that mental health apps such as LiveWell require “time and energy devoted by both the patient and their clinician for maximal efficacy, which requires commitment from and training for both parties as well.

“But with such an investment in people, there is good evidence apps can help people with bipolar disorder even during the more severe periods of the illness,” added Dr. Torous, who was not involved with the research.

The study was funded by the National Institute of Mental Health.

Dr. Goulding reports having received honoraria from Otsuka. Dr. Torous has reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

In the treatment of depression, clinicians are commonly dealing with a mix of comorbidities that are more complex than just depression, and as such, effective treatment options may likewise require thinking outside of the box – and beyond the definitions of the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision).

“The DSM-5 isn’t handed to us on tablets from Mount Sinai,” said Charles B. Nemeroff, MD, PhD, professor and chair in the department of psychiatry and behavioral sciences at the Mulva Clinic for the Neurosciences at the University of Texas at Austin. He spoke at the 21st Annual Psychopharmacology Update presented by Current Psychiatry and the American Academy of Clinical Psychiatrists.

“Our patients don’t fall into these very convenient buckets,” Dr. Nemeroff said. “The problem with depression is patients have very high rates of morbidity and comorbidity.”

The array of potential psychiatric comorbidities that are common in depression is somewhat staggering: As many as 70% of patients also have social anxiety disorder; 67% of patients have obsessive-compulsive disorder (OCD); up to 65% of patients have panic disorder; 48% of patients have posttraumatic stress disorder (PTSD); and 42% have generalized anxiety disorder, Dr. Nemeroff said.

And while the DSM-5 may have all those bases covered, in real world clinical practice, cracking the code of each patient’s unique and often more complicated psychiatric profile – and how to best manage it – can be a challenge. But Dr. Nemeroff said important clues can guide the clinician’s path.

A key starting point is making sure to gauge the severity of the patient’s core depression with one of the validated depression scales – whether it’s the self-reported Beck Depression Inventory, the clinician-rated Hamilton Rating Scale for Depression, the clinician-rated Montgomery Asberg Depression Rating Scale, or the Inventory of Depressive Symptoms, clinicians should pick one and track the score with each visit, Dr. Nemeroff advised.

“It doesn’t matter which tool you prefer – most tend to like the Beck Depression Scale, but the bottom line is that you have to get a measure of severity at every visit,” he said.

Among the most important comorbidities to identify as soon as possible is bipolar disorder, due to the potential worsening of the condition that can occur among those patients if treated with antidepressants, Dr. Nemeroff said.

“The question of whether the patient is bipolar should always be in the back of your mind,” he cautioned. “And if patients have been started on antidepressants, the clues may become evident very quickly.”

The most important indicator that the patient has bipolar disorder “is if they tell you that they were prescribed an antidepressant and it resulted in an increase in what we know to be hypomania – they may describe it as agitation or an inability to sleep,” Dr. Nemeroff said.

Of note, the effect is much more common with SNRIs [serotonin norepinephrine reuptake inhibitors] than SSRIs [selective serotonin reuptake inhibitors], he said.

“The effect is particularly notable with venlafaxine,” he said. “But SNRIs all have the propensity to switch people with depression into hypomania, but only patients who have bipolar disorder.”

“If you give a patient 150 mg of venlafaxine and they switch to developing hypomania, you now have the diagnosis of bipolar disorder, and you can treat them appropriately.”

Other important clues of bipolarity in depressed patients include:

• Family history: Most cases are genetically driven.
• Earlier age of onset (younger than age 25): “If the patient tells you they were depressed prepuberty, you should be thinking about the possibility of bipolar disorder, as it often presents as depression in childhood.”
• Psychotic features: As many as 80% of patients with psychotic depression end up being bipolar, Dr. Nemeroff said.
• Atypical depression: For example, depression with hypersomnia, or having an increased appetite instead of decreased, or a high amount of anxiety.

Remission should be the goal of treatment, and Dr. Nemeroff said that in efforts to accomplish that with the help of medications, psychiatrists may need to think “outside of the box” – or beyond the label.

“Many practitioners become slaves to the PDR [Physicians’ Desk Reference],” he said. “It is only a guide to what the clinical trials show, and not a mandate in terms of dosing.”

“There’s often strong data in the literature that supports going to a higher dose, if necessary, and I have [plenty] of patients, for instance, on 450 or 600 mg of venlafaxine who had not responded to 150 or even 300 mg.”
 

Treatment resistance

When patients continue to fail to respond, regardless of dosing or medication adjustments, Dr. Nemeroff suggested that clinicians should consider the potential important reasons. For instance, in addition to comorbid psychiatric conditions, practitioners should determine if there are medical conditions that they are not aware of.

“Does the patient have an underlying medical condition, such as thyroid dysfunction, early Parkinson’s disease, or even something like cancer?” he said.

There is also the inevitable question of whether the patient is indeed taking the medication. “We know that 30% of our patients do not follow their prescriptions, so of course that’s an important question to ask,” Dr. Nemeroff said.

Finally, while some pharmacogenomic tests are emerging with the suggestion of identifying which patients may or may not respond to certain drugs, Dr. Nemeroff says he’s seen little convincing evidence of their benefits.

“We have a problem in this field in that we don’t have the kinds of markers that they do in oncology, so we’re left with having to generally play trial and error,” he said.

“But when it comes to these pharmacogenomic tests, there’s just no ‘there there’,” he asserted. “From what I’ve seen so far, it’s frankly neuro-mythology.”

Dr. Nemeroff disclosed that he receives grant/research support from the National Institutes of Health and serves as a consultant for and/or on the advisory boards of multiple pharmaceutical companies.

The Psychopharmacology Update was sponsored by Medscape Live. Medscape Live and this news organization are owned by the same parent company.

In the treatment of depression, clinicians are commonly dealing with a mix of comorbidities that are more complex than just depression, and as such, effective treatment options may likewise require thinking outside of the box – and beyond the definitions of the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision).

“The DSM-5 isn’t handed to us on tablets from Mount Sinai,” said Charles B. Nemeroff, MD, PhD, professor and chair in the department of psychiatry and behavioral sciences at the Mulva Clinic for the Neurosciences at the University of Texas at Austin. He spoke at the 21st Annual Psychopharmacology Update presented by Current Psychiatry and the American Academy of Clinical Psychiatrists.

“Our patients don’t fall into these very convenient buckets,” Dr. Nemeroff said. “The problem with depression is patients have very high rates of morbidity and comorbidity.”

The array of potential psychiatric comorbidities that are common in depression is somewhat staggering: As many as 70% of patients also have social anxiety disorder; 67% of patients have obsessive-compulsive disorder (OCD); up to 65% of patients have panic disorder; 48% of patients have posttraumatic stress disorder (PTSD); and 42% have generalized anxiety disorder, Dr. Nemeroff said.

And while the DSM-5 may have all those bases covered, in real world clinical practice, cracking the code of each patient’s unique and often more complicated psychiatric profile – and how to best manage it – can be a challenge. But Dr. Nemeroff said important clues can guide the clinician’s path.

A key starting point is making sure to gauge the severity of the patient’s core depression with one of the validated depression scales – whether it’s the self-reported Beck Depression Inventory, the clinician-rated Hamilton Rating Scale for Depression, the clinician-rated Montgomery Asberg Depression Rating Scale, or the Inventory of Depressive Symptoms, clinicians should pick one and track the score with each visit, Dr. Nemeroff advised.

“It doesn’t matter which tool you prefer – most tend to like the Beck Depression Scale, but the bottom line is that you have to get a measure of severity at every visit,” he said.

Among the most important comorbidities to identify as soon as possible is bipolar disorder, due to the potential worsening of the condition that can occur among those patients if treated with antidepressants, Dr. Nemeroff said.

“The question of whether the patient is bipolar should always be in the back of your mind,” he cautioned. “And if patients have been started on antidepressants, the clues may become evident very quickly.”

The most important indicator that the patient has bipolar disorder “is if they tell you that they were prescribed an antidepressant and it resulted in an increase in what we know to be hypomania – they may describe it as agitation or an inability to sleep,” Dr. Nemeroff said.

Of note, the effect is much more common with SNRIs [serotonin norepinephrine reuptake inhibitors] than SSRIs [selective serotonin reuptake inhibitors], he said.

“The effect is particularly notable with venlafaxine,” he said. “But SNRIs all have the propensity to switch people with depression into hypomania, but only patients who have bipolar disorder.”

“If you give a patient 150 mg of venlafaxine and they switch to developing hypomania, you now have the diagnosis of bipolar disorder, and you can treat them appropriately.”

Other important clues of bipolarity in depressed patients include:

• Family history: Most cases are genetically driven.
• Earlier age of onset (younger than age 25): “If the patient tells you they were depressed prepuberty, you should be thinking about the possibility of bipolar disorder, as it often presents as depression in childhood.”
• Psychotic features: As many as 80% of patients with psychotic depression end up being bipolar, Dr. Nemeroff said.
• Atypical depression: For example, depression with hypersomnia, or having an increased appetite instead of decreased, or a high amount of anxiety.

Remission should be the goal of treatment, and Dr. Nemeroff said that in efforts to accomplish that with the help of medications, psychiatrists may need to think “outside of the box” – or beyond the label.

“Many practitioners become slaves to the PDR [Physicians’ Desk Reference],” he said. “It is only a guide to what the clinical trials show, and not a mandate in terms of dosing.”

“There’s often strong data in the literature that supports going to a higher dose, if necessary, and I have [plenty] of patients, for instance, on 450 or 600 mg of venlafaxine who had not responded to 150 or even 300 mg.”
 

Treatment resistance

When patients continue to fail to respond, regardless of dosing or medication adjustments, Dr. Nemeroff suggested that clinicians should consider the potential important reasons. For instance, in addition to comorbid psychiatric conditions, practitioners should determine if there are medical conditions that they are not aware of.

“Does the patient have an underlying medical condition, such as thyroid dysfunction, early Parkinson’s disease, or even something like cancer?” he said.

There is also the inevitable question of whether the patient is indeed taking the medication. “We know that 30% of our patients do not follow their prescriptions, so of course that’s an important question to ask,” Dr. Nemeroff said.

Finally, while some pharmacogenomic tests are emerging with the suggestion of identifying which patients may or may not respond to certain drugs, Dr. Nemeroff says he’s seen little convincing evidence of their benefits.

“We have a problem in this field in that we don’t have the kinds of markers that they do in oncology, so we’re left with having to generally play trial and error,” he said.

“But when it comes to these pharmacogenomic tests, there’s just no ‘there there’,” he asserted. “From what I’ve seen so far, it’s frankly neuro-mythology.”

Dr. Nemeroff disclosed that he receives grant/research support from the National Institutes of Health and serves as a consultant for and/or on the advisory boards of multiple pharmaceutical companies.

The Psychopharmacology Update was sponsored by Medscape Live. Medscape Live and this news organization are owned by the same parent company.

In the treatment of depression, clinicians are commonly dealing with a mix of comorbidities that are more complex than just depression, and as such, effective treatment options may likewise require thinking outside of the box – and beyond the definitions of the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision).

“The DSM-5 isn’t handed to us on tablets from Mount Sinai,” said Charles B. Nemeroff, MD, PhD, professor and chair in the department of psychiatry and behavioral sciences at the Mulva Clinic for the Neurosciences at the University of Texas at Austin. He spoke at the 21st Annual Psychopharmacology Update presented by Current Psychiatry and the American Academy of Clinical Psychiatrists.

“Our patients don’t fall into these very convenient buckets,” Dr. Nemeroff said. “The problem with depression is patients have very high rates of morbidity and comorbidity.”

The array of potential psychiatric comorbidities that are common in depression is somewhat staggering: As many as 70% of patients also have social anxiety disorder; 67% of patients have obsessive-compulsive disorder (OCD); up to 65% of patients have panic disorder; 48% of patients have posttraumatic stress disorder (PTSD); and 42% have generalized anxiety disorder, Dr. Nemeroff said.

And while the DSM-5 may have all those bases covered, in real world clinical practice, cracking the code of each patient’s unique and often more complicated psychiatric profile – and how to best manage it – can be a challenge. But Dr. Nemeroff said important clues can guide the clinician’s path.

A key starting point is making sure to gauge the severity of the patient’s core depression with one of the validated depression scales – whether it’s the self-reported Beck Depression Inventory, the clinician-rated Hamilton Rating Scale for Depression, the clinician-rated Montgomery Asberg Depression Rating Scale, or the Inventory of Depressive Symptoms, clinicians should pick one and track the score with each visit, Dr. Nemeroff advised.

“It doesn’t matter which tool you prefer – most tend to like the Beck Depression Scale, but the bottom line is that you have to get a measure of severity at every visit,” he said.

Among the most important comorbidities to identify as soon as possible is bipolar disorder, due to the potential worsening of the condition that can occur among those patients if treated with antidepressants, Dr. Nemeroff said.

“The question of whether the patient is bipolar should always be in the back of your mind,” he cautioned. “And if patients have been started on antidepressants, the clues may become evident very quickly.”

The most important indicator that the patient has bipolar disorder “is if they tell you that they were prescribed an antidepressant and it resulted in an increase in what we know to be hypomania – they may describe it as agitation or an inability to sleep,” Dr. Nemeroff said.

Of note, the effect is much more common with SNRIs [serotonin norepinephrine reuptake inhibitors] than SSRIs [selective serotonin reuptake inhibitors], he said.

“The effect is particularly notable with venlafaxine,” he said. “But SNRIs all have the propensity to switch people with depression into hypomania, but only patients who have bipolar disorder.”

“If you give a patient 150 mg of venlafaxine and they switch to developing hypomania, you now have the diagnosis of bipolar disorder, and you can treat them appropriately.”

Other important clues of bipolarity in depressed patients include:

• Family history: Most cases are genetically driven.
• Earlier age of onset (younger than age 25): “If the patient tells you they were depressed prepuberty, you should be thinking about the possibility of bipolar disorder, as it often presents as depression in childhood.”
• Psychotic features: As many as 80% of patients with psychotic depression end up being bipolar, Dr. Nemeroff said.
• Atypical depression: For example, depression with hypersomnia, or having an increased appetite instead of decreased, or a high amount of anxiety.

Remission should be the goal of treatment, and Dr. Nemeroff said that in efforts to accomplish that with the help of medications, psychiatrists may need to think “outside of the box” – or beyond the label.

“Many practitioners become slaves to the PDR [Physicians’ Desk Reference],” he said. “It is only a guide to what the clinical trials show, and not a mandate in terms of dosing.”

“There’s often strong data in the literature that supports going to a higher dose, if necessary, and I have [plenty] of patients, for instance, on 450 or 600 mg of venlafaxine who had not responded to 150 or even 300 mg.”
 

Treatment resistance

When patients continue to fail to respond, regardless of dosing or medication adjustments, Dr. Nemeroff suggested that clinicians should consider the potential important reasons. For instance, in addition to comorbid psychiatric conditions, practitioners should determine if there are medical conditions that they are not aware of.

“Does the patient have an underlying medical condition, such as thyroid dysfunction, early Parkinson’s disease, or even something like cancer?” he said.

There is also the inevitable question of whether the patient is indeed taking the medication. “We know that 30% of our patients do not follow their prescriptions, so of course that’s an important question to ask,” Dr. Nemeroff said.

Finally, while some pharmacogenomic tests are emerging with the suggestion of identifying which patients may or may not respond to certain drugs, Dr. Nemeroff says he’s seen little convincing evidence of their benefits.

“We have a problem in this field in that we don’t have the kinds of markers that they do in oncology, so we’re left with having to generally play trial and error,” he said.

“But when it comes to these pharmacogenomic tests, there’s just no ‘there there’,” he asserted. “From what I’ve seen so far, it’s frankly neuro-mythology.”

Dr. Nemeroff disclosed that he receives grant/research support from the National Institutes of Health and serves as a consultant for and/or on the advisory boards of multiple pharmaceutical companies.

The Psychopharmacology Update was sponsored by Medscape Live. Medscape Live and this news organization are owned by the same parent company.

Editor’s note: Readers’ Forum is a department for correspondence from readers that is not in response to articles published in Current Psychiatry . All submissions to Readers’ Forum undergo peer review and are subject to editing for length and style. For more informa tion, contact [email protected].

Lithium carbonate is a mood stabilizer that is effective in the treatment of bipolar disorder, particularly in controlling mania.¹ Lithium can reduce the risk of suicide,² treat aggression and self-mutilating behavior,³ and prevent steroid-induced psychosis.⁴ It also can raise the white cell count in patients with clozapine-induced leukopenia.⁵

To prevent or lower the risk of relapse, the therapeutic plasma level of lithium should be regularly monitored to ensure an optimal concentration in the CNS. The highest tolerable level of lithium in the plasma is 0.6 to 0.8 mmol/L, with the optimal level ranging up to 1.2 mmol/L.⁶ Regular monitoring of renal function is also required to prevent renal toxicity, particularly if the plasma level exceeds 0.8 mmol/L.⁷ Because of lithium’s relatively narrow therapeutic index, its interaction with other medications, such as angiotensin-converting enzyme inhibitors, diuretics, nonsteroidal anti-inflammatory drugs (NSAIDs), and carbamazepine, can also precipitate lithium toxicity.⁸ We describe a lesson learned from a case of lithium toxicity in an otherwise healthy patient with bipolar disorder.

Case report

An otherwise healthy 39-year-old woman diagnosed with bipolar type I disorder was receiving valproate sodium 600 mg/d and olanzapine 10 mg/d. Despite improvement in her mood, she gained 11.6 kg following 6 months of treatment. As a result, olanzapine was switched to aripiprazole 10 mg/d that was later increased to 15 mg/d, and sodium valproate was gradually optimized up to 1,000 mg/d. She later complained of hair thinning and hair loss so she self-adjusted her medication dosages, which resulted in frequent relapses. Her mood stabilizer was changed from sodium valproate to lithium 600 mg/d.

Unfortunately, after taking lithium for 15 days, she returned to us with fever associated with reduced oral intake, poor sleep, bilateral upper limb rigidity, and bilateral hand tremor. She also complained of extreme thirst and fatigue but no vomiting or diarrhea. She had difficulty falling asleep and slept for only 1 to 2 hours a day. Her symptoms worsened when a general practitioner prescribed NSAIDs for her fever and body ache. Her tremors were later generalized, which made it difficult for her to take her oral medications and disturbed her speech and movement.

On evaluation, our patient appeared comfortable and not agitated. She was orientated to time, place, and person. Her blood pressure was 139/89 mmHg, heart rate was 104 bpm, and she was afebrile. She was dehydrated with minimal urine output. She had coarse tremor in her upper and lower limbs, which were hypertonic but did not display hyperreflexia or clonus. There was no nystagmus or ataxia. A mental state examination showed no signs of manic, hypomanic, or depressive symptoms. She had slurred speech, and her affect was restricted.

Blood investigation revealed a suprathreshold lithium level of 1.70 mmol/L (normal: 0.8 to 1.2 mmol/L). Biochemical parameters showed evidence of acute kidney injury (urea: 6.1 mmol/L; creatinine: 0.140 mmol/L), with no electrolyte imbalance. There was no evidence of hypothyroidism (thyroid-stimulating hormone: 14.9 mIU/L; free thyroxine: 9.9 pmol/L), hyperparathyroidism, or hypercalcemia. Autoimmune markers were positive for antinuclear antibody (titre 1:320) and anti-double stranded DNA (76.8 IU/mL). Apart from hair loss, she denied other symptoms associated with autoimmune disease, such as joint pain, butterfly rash, or persistent fatigue. Other routine blood investigations were within normal limits. Her urine protein throughout admission had shown persistent proteinuria ranging from 3+ to 4+. Electrocardiogram (ECG) showed normal sinus rhythm with no T wave inversion or QT prolongation.

Continue to: A detailed family history...

A detailed family history later confirmed a strong family history of renal disease: her mother had lupus nephritis with nephrotic syndrome, and her brother had died from complications of a rapidly progressive glomerulonephritis. Her renal function prior to lithium initiation was within normal limits (urea: 4.0 mmol/L; serum creatinine: 78 µmol/L).

In the ward, lithium and aripiprazole were discontinued, and she was hydrated. Combined care with the psychiatric and medical teams was established early to safeguard against potential CNS deterioration. She showed marked clinical improvement by Day 3, with the resolution of coarse tremor and rigidity as well as normalization of blood parameters. Her lithium level returned to a therapeutic level by Day 4 after lithium discontinuation, and her renal profile gradually normalized. She was restarted on aripiprazole 10 mg/d for her bipolar illness and responded well. She was discharged on Day 5 with a referral to the nephrology team for further intervention.

Lessons learned

This case highlights the issue of lithium safety in susceptible individuals and the importance of risk stratification in this group of patients. Lithium is an effective treatment for bipolar I disorder and has also been used as adjunctive treatment for major depressive disorder, schizoaffective disorder, treatment-resistant schizophrenia, anorexia nervosa and bulimia nervosa, and the control of chronic aggression.⁹ Lithium is completely absorbed by the gastrointestinal tract following ingestion, is not metabolized, and is eliminated almost entirely by the kidneys (though trace amounts may be found in feces and perspiration).

In our case, a detailed family history of renal disease was not adequately explored until our patient presented with signs suggestive of lithium toxicity. Our patient had been prescribed lithium 600 mg/d as a maintenance therapy. Upon starting lithium, her baseline biochemical parameters were within normal limits, and renal issues were not suspected. The hair thinning and hair loss she experienced could have been an adverse effect of valproate sodium or a manifestation of an underlying autoimmune disease. Coupled with the use of NSAIDs that could have precipitated acute kidney injury, her poor oral intake and dehydration during the acute illness further impaired lithium excretion, leading to a suprathreshold plasma level despite a low dose of lithium. Therefore, before prescribing lithium, a thorough medical and family history is needed, supplemented by an evaluation of renal function, serum electrolytes, and thyroid function to determine the starting dosage of lithium. Routine vital sign assessment and ECG should also be conducted, and concurrent medications and pregnancy status should be confirmed before prescribing lithium. Regular lithium level monitoring is essential.

Measuring a patient’s estimated glomerular filtration rate (eGFR) is recommended to validate renal status¹⁰ and classify and stage kidney disease.¹¹ Combining eGFR with blood urea nitrogen, serum creatinine, and urine microscopic analysis further improves the prediction of renal disease in early stages. We recommend considering a blood test for autoimmune markers in patients with clinical suspicion of autoimmune disease, in the presence of suggestive signs and symptoms, and/or in patients with a positive family history (Table).

Before starting lithium, in addition to conducting a detailed clinical evaluation, information about symptoms and the risk of lithium toxicity should be discussed with patients.¹² Our case serves as a timely reminder that the lack of suggestive biochemical parameters of renal disease should not rule out an underlying renal disease, and a strong family history of renal disease should warrant suspicion of a possible autoimmune origin.

We suggest that future studies evaluate the risks of lithium toxicity in susceptible groups of patients, such as those with family history of renal disease.

Editor’s note: Readers’ Forum is a department for correspondence from readers that is not in response to articles published in Current Psychiatry . All submissions to Readers’ Forum undergo peer review and are subject to editing for length and style. For more informa tion, contact [email protected].

Lithium carbonate is a mood stabilizer that is effective in the treatment of bipolar disorder, particularly in controlling mania.¹ Lithium can reduce the risk of suicide,² treat aggression and self-mutilating behavior,³ and prevent steroid-induced psychosis.⁴ It also can raise the white cell count in patients with clozapine-induced leukopenia.⁵

To prevent or lower the risk of relapse, the therapeutic plasma level of lithium should be regularly monitored to ensure an optimal concentration in the CNS. The highest tolerable level of lithium in the plasma is 0.6 to 0.8 mmol/L, with the optimal level ranging up to 1.2 mmol/L.⁶ Regular monitoring of renal function is also required to prevent renal toxicity, particularly if the plasma level exceeds 0.8 mmol/L.⁷ Because of lithium’s relatively narrow therapeutic index, its interaction with other medications, such as angiotensin-converting enzyme inhibitors, diuretics, nonsteroidal anti-inflammatory drugs (NSAIDs), and carbamazepine, can also precipitate lithium toxicity.⁸ We describe a lesson learned from a case of lithium toxicity in an otherwise healthy patient with bipolar disorder.

Case report

An otherwise healthy 39-year-old woman diagnosed with bipolar type I disorder was receiving valproate sodium 600 mg/d and olanzapine 10 mg/d. Despite improvement in her mood, she gained 11.6 kg following 6 months of treatment. As a result, olanzapine was switched to aripiprazole 10 mg/d that was later increased to 15 mg/d, and sodium valproate was gradually optimized up to 1,000 mg/d. She later complained of hair thinning and hair loss so she self-adjusted her medication dosages, which resulted in frequent relapses. Her mood stabilizer was changed from sodium valproate to lithium 600 mg/d.

Unfortunately, after taking lithium for 15 days, she returned to us with fever associated with reduced oral intake, poor sleep, bilateral upper limb rigidity, and bilateral hand tremor. She also complained of extreme thirst and fatigue but no vomiting or diarrhea. She had difficulty falling asleep and slept for only 1 to 2 hours a day. Her symptoms worsened when a general practitioner prescribed NSAIDs for her fever and body ache. Her tremors were later generalized, which made it difficult for her to take her oral medications and disturbed her speech and movement.

On evaluation, our patient appeared comfortable and not agitated. She was orientated to time, place, and person. Her blood pressure was 139/89 mmHg, heart rate was 104 bpm, and she was afebrile. She was dehydrated with minimal urine output. She had coarse tremor in her upper and lower limbs, which were hypertonic but did not display hyperreflexia or clonus. There was no nystagmus or ataxia. A mental state examination showed no signs of manic, hypomanic, or depressive symptoms. She had slurred speech, and her affect was restricted.

Blood investigation revealed a suprathreshold lithium level of 1.70 mmol/L (normal: 0.8 to 1.2 mmol/L). Biochemical parameters showed evidence of acute kidney injury (urea: 6.1 mmol/L; creatinine: 0.140 mmol/L), with no electrolyte imbalance. There was no evidence of hypothyroidism (thyroid-stimulating hormone: 14.9 mIU/L; free thyroxine: 9.9 pmol/L), hyperparathyroidism, or hypercalcemia. Autoimmune markers were positive for antinuclear antibody (titre 1:320) and anti-double stranded DNA (76.8 IU/mL). Apart from hair loss, she denied other symptoms associated with autoimmune disease, such as joint pain, butterfly rash, or persistent fatigue. Other routine blood investigations were within normal limits. Her urine protein throughout admission had shown persistent proteinuria ranging from 3+ to 4+. Electrocardiogram (ECG) showed normal sinus rhythm with no T wave inversion or QT prolongation.

Continue to: A detailed family history...

A detailed family history later confirmed a strong family history of renal disease: her mother had lupus nephritis with nephrotic syndrome, and her brother had died from complications of a rapidly progressive glomerulonephritis. Her renal function prior to lithium initiation was within normal limits (urea: 4.0 mmol/L; serum creatinine: 78 µmol/L).

In the ward, lithium and aripiprazole were discontinued, and she was hydrated. Combined care with the psychiatric and medical teams was established early to safeguard against potential CNS deterioration. She showed marked clinical improvement by Day 3, with the resolution of coarse tremor and rigidity as well as normalization of blood parameters. Her lithium level returned to a therapeutic level by Day 4 after lithium discontinuation, and her renal profile gradually normalized. She was restarted on aripiprazole 10 mg/d for her bipolar illness and responded well. She was discharged on Day 5 with a referral to the nephrology team for further intervention.

Lessons learned

This case highlights the issue of lithium safety in susceptible individuals and the importance of risk stratification in this group of patients. Lithium is an effective treatment for bipolar I disorder and has also been used as adjunctive treatment for major depressive disorder, schizoaffective disorder, treatment-resistant schizophrenia, anorexia nervosa and bulimia nervosa, and the control of chronic aggression.⁹ Lithium is completely absorbed by the gastrointestinal tract following ingestion, is not metabolized, and is eliminated almost entirely by the kidneys (though trace amounts may be found in feces and perspiration).

In our case, a detailed family history of renal disease was not adequately explored until our patient presented with signs suggestive of lithium toxicity. Our patient had been prescribed lithium 600 mg/d as a maintenance therapy. Upon starting lithium, her baseline biochemical parameters were within normal limits, and renal issues were not suspected. The hair thinning and hair loss she experienced could have been an adverse effect of valproate sodium or a manifestation of an underlying autoimmune disease. Coupled with the use of NSAIDs that could have precipitated acute kidney injury, her poor oral intake and dehydration during the acute illness further impaired lithium excretion, leading to a suprathreshold plasma level despite a low dose of lithium. Therefore, before prescribing lithium, a thorough medical and family history is needed, supplemented by an evaluation of renal function, serum electrolytes, and thyroid function to determine the starting dosage of lithium. Routine vital sign assessment and ECG should also be conducted, and concurrent medications and pregnancy status should be confirmed before prescribing lithium. Regular lithium level monitoring is essential.

Measuring a patient’s estimated glomerular filtration rate (eGFR) is recommended to validate renal status¹⁰ and classify and stage kidney disease.¹¹ Combining eGFR with blood urea nitrogen, serum creatinine, and urine microscopic analysis further improves the prediction of renal disease in early stages. We recommend considering a blood test for autoimmune markers in patients with clinical suspicion of autoimmune disease, in the presence of suggestive signs and symptoms, and/or in patients with a positive family history (Table).

Before starting lithium, in addition to conducting a detailed clinical evaluation, information about symptoms and the risk of lithium toxicity should be discussed with patients.¹² Our case serves as a timely reminder that the lack of suggestive biochemical parameters of renal disease should not rule out an underlying renal disease, and a strong family history of renal disease should warrant suspicion of a possible autoimmune origin.

We suggest that future studies evaluate the risks of lithium toxicity in susceptible groups of patients, such as those with family history of renal disease.

Editor’s note: Readers’ Forum is a department for correspondence from readers that is not in response to articles published in Current Psychiatry . All submissions to Readers’ Forum undergo peer review and are subject to editing for length and style. For more informa tion, contact [email protected].

Lithium carbonate is a mood stabilizer that is effective in the treatment of bipolar disorder, particularly in controlling mania.¹ Lithium can reduce the risk of suicide,² treat aggression and self-mutilating behavior,³ and prevent steroid-induced psychosis.⁴ It also can raise the white cell count in patients with clozapine-induced leukopenia.⁵

To prevent or lower the risk of relapse, the therapeutic plasma level of lithium should be regularly monitored to ensure an optimal concentration in the CNS. The highest tolerable level of lithium in the plasma is 0.6 to 0.8 mmol/L, with the optimal level ranging up to 1.2 mmol/L.⁶ Regular monitoring of renal function is also required to prevent renal toxicity, particularly if the plasma level exceeds 0.8 mmol/L.⁷ Because of lithium’s relatively narrow therapeutic index, its interaction with other medications, such as angiotensin-converting enzyme inhibitors, diuretics, nonsteroidal anti-inflammatory drugs (NSAIDs), and carbamazepine, can also precipitate lithium toxicity.⁸ We describe a lesson learned from a case of lithium toxicity in an otherwise healthy patient with bipolar disorder.

Case report

An otherwise healthy 39-year-old woman diagnosed with bipolar type I disorder was receiving valproate sodium 600 mg/d and olanzapine 10 mg/d. Despite improvement in her mood, she gained 11.6 kg following 6 months of treatment. As a result, olanzapine was switched to aripiprazole 10 mg/d that was later increased to 15 mg/d, and sodium valproate was gradually optimized up to 1,000 mg/d. She later complained of hair thinning and hair loss so she self-adjusted her medication dosages, which resulted in frequent relapses. Her mood stabilizer was changed from sodium valproate to lithium 600 mg/d.

Unfortunately, after taking lithium for 15 days, she returned to us with fever associated with reduced oral intake, poor sleep, bilateral upper limb rigidity, and bilateral hand tremor. She also complained of extreme thirst and fatigue but no vomiting or diarrhea. She had difficulty falling asleep and slept for only 1 to 2 hours a day. Her symptoms worsened when a general practitioner prescribed NSAIDs for her fever and body ache. Her tremors were later generalized, which made it difficult for her to take her oral medications and disturbed her speech and movement.

On evaluation, our patient appeared comfortable and not agitated. She was orientated to time, place, and person. Her blood pressure was 139/89 mmHg, heart rate was 104 bpm, and she was afebrile. She was dehydrated with minimal urine output. She had coarse tremor in her upper and lower limbs, which were hypertonic but did not display hyperreflexia or clonus. There was no nystagmus or ataxia. A mental state examination showed no signs of manic, hypomanic, or depressive symptoms. She had slurred speech, and her affect was restricted.

Blood investigation revealed a suprathreshold lithium level of 1.70 mmol/L (normal: 0.8 to 1.2 mmol/L). Biochemical parameters showed evidence of acute kidney injury (urea: 6.1 mmol/L; creatinine: 0.140 mmol/L), with no electrolyte imbalance. There was no evidence of hypothyroidism (thyroid-stimulating hormone: 14.9 mIU/L; free thyroxine: 9.9 pmol/L), hyperparathyroidism, or hypercalcemia. Autoimmune markers were positive for antinuclear antibody (titre 1:320) and anti-double stranded DNA (76.8 IU/mL). Apart from hair loss, she denied other symptoms associated with autoimmune disease, such as joint pain, butterfly rash, or persistent fatigue. Other routine blood investigations were within normal limits. Her urine protein throughout admission had shown persistent proteinuria ranging from 3+ to 4+. Electrocardiogram (ECG) showed normal sinus rhythm with no T wave inversion or QT prolongation.

Continue to: A detailed family history...

A detailed family history later confirmed a strong family history of renal disease: her mother had lupus nephritis with nephrotic syndrome, and her brother had died from complications of a rapidly progressive glomerulonephritis. Her renal function prior to lithium initiation was within normal limits (urea: 4.0 mmol/L; serum creatinine: 78 µmol/L).

In the ward, lithium and aripiprazole were discontinued, and she was hydrated. Combined care with the psychiatric and medical teams was established early to safeguard against potential CNS deterioration. She showed marked clinical improvement by Day 3, with the resolution of coarse tremor and rigidity as well as normalization of blood parameters. Her lithium level returned to a therapeutic level by Day 4 after lithium discontinuation, and her renal profile gradually normalized. She was restarted on aripiprazole 10 mg/d for her bipolar illness and responded well. She was discharged on Day 5 with a referral to the nephrology team for further intervention.

Lessons learned

This case highlights the issue of lithium safety in susceptible individuals and the importance of risk stratification in this group of patients. Lithium is an effective treatment for bipolar I disorder and has also been used as adjunctive treatment for major depressive disorder, schizoaffective disorder, treatment-resistant schizophrenia, anorexia nervosa and bulimia nervosa, and the control of chronic aggression.⁹ Lithium is completely absorbed by the gastrointestinal tract following ingestion, is not metabolized, and is eliminated almost entirely by the kidneys (though trace amounts may be found in feces and perspiration).

In our case, a detailed family history of renal disease was not adequately explored until our patient presented with signs suggestive of lithium toxicity. Our patient had been prescribed lithium 600 mg/d as a maintenance therapy. Upon starting lithium, her baseline biochemical parameters were within normal limits, and renal issues were not suspected. The hair thinning and hair loss she experienced could have been an adverse effect of valproate sodium or a manifestation of an underlying autoimmune disease. Coupled with the use of NSAIDs that could have precipitated acute kidney injury, her poor oral intake and dehydration during the acute illness further impaired lithium excretion, leading to a suprathreshold plasma level despite a low dose of lithium. Therefore, before prescribing lithium, a thorough medical and family history is needed, supplemented by an evaluation of renal function, serum electrolytes, and thyroid function to determine the starting dosage of lithium. Routine vital sign assessment and ECG should also be conducted, and concurrent medications and pregnancy status should be confirmed before prescribing lithium. Regular lithium level monitoring is essential.

Measuring a patient’s estimated glomerular filtration rate (eGFR) is recommended to validate renal status¹⁰ and classify and stage kidney disease.¹¹ Combining eGFR with blood urea nitrogen, serum creatinine, and urine microscopic analysis further improves the prediction of renal disease in early stages. We recommend considering a blood test for autoimmune markers in patients with clinical suspicion of autoimmune disease, in the presence of suggestive signs and symptoms, and/or in patients with a positive family history (Table).

Before starting lithium, in addition to conducting a detailed clinical evaluation, information about symptoms and the risk of lithium toxicity should be discussed with patients.¹² Our case serves as a timely reminder that the lack of suggestive biochemical parameters of renal disease should not rule out an underlying renal disease, and a strong family history of renal disease should warrant suspicion of a possible autoimmune origin.

We suggest that future studies evaluate the risks of lithium toxicity in susceptible groups of patients, such as those with family history of renal disease.

Catatonia is often difficult to identify and treat. The excited catatonia subtype can be particularly challenging to diagnose because it can present with symptoms similar to those seen in mania or psychosis. In this article, we present 3 cases of excited catatonia that illustrate how to identify it, how to treat the catatonia as well as the underlying pathology, and factors to consider during this process to mitigate the risk of adverse outcomes. We also outline a treatment algorithm we used for the 3 cases. Although we describe using this approach for patients with excited catatonia, it is generalizable to other types of catatonia.

Many causes, varying presentations

Catatonia is a psychomotor syndrome characterized by mutism, negativism, stereotypy, waxy flexibility, and other symptoms.¹ It is defined by the presence of ≥3 of the 12 symptoms listed in the Table.² Causes of catatonia include metabolic abnormalities, endocrine disorders, drug intoxication, neurodevelopmental disorders, medication adverse effects, psychosis, and mood disorders.^1,3

A subtype of this syndrome, excited catatonia, can present with restlessness, agitation, emotional lability, poor sleep, and altered mental status in addition to the more typical symptoms.^1,4 Because excited catatonia can resemble mania or psychosis, it is particularly challenging to identify the underlying disorder causing it and appropriate treatment. Fink et al⁴ discussed how clinicians have interpreted the different presentations of excited catatonia to gain insight into the underlying diagnosis. If the patient’s thought process appears disorganized, psychosis may be suspected.⁴ If the patient is delusional and grandiose, they may be manic, and when altered mental status dominates the presentation, delirium may be the culprit.⁴

Regardless of the underlying cause, the first step is to treat the catatonia. Benzodiazepines and electroconvulsive therapy (ECT) are the most well validated treatments for catatonia and have been used to treat excited catatonia.¹ Excited catatonia is often misdiagnosed and subsequently mistreated. In the following 3 cases, excited catatonia was successfully identified and treated using the same approach (Figure).

Case 1

Mr. A, age 27, has a history of bipolar I disorder. He was brought to the hospital by ambulance after being found to be yelling and acting belligerently, and he was admitted to the inpatient psychiatry unit for manic decompensation due to medication nonadherence. He was started on divalproex sodium 500 mg twice a day for mood stabilization, risperidone 1 mg twice a day for adjunct mood stabilization and psychosis, and lorazepam 1 mg 3 times a day for agitation. Mr. A exhibited odd behavior; he would take off his clothes in the hallway, run around the unit, and randomly yell at staff or to himself. At other times, he would stay silent, repeat the same statements, or oddly posture in the hallway for minutes at a time. These behaviors were seen primarily in the hour or 2 preceding lorazepam administration and improved after he received lorazepam.

Mr. A’s treating team completed the Bush-Francis Catatonia Rating Scale (BFCRS), which yielded a positive catatonia screen of 7/14. As a result, divalproex sodium and risperidone were held, and lorazepam was increased to 2 mg twice a day.

After several days, Mr. A was no longer acting oddly and was able to speak more spontaneously; however, he began to exhibit overt signs of mania. He would speak rapidly and make grandiose claims about managing millions of dollars as the CEO of a famous company. Divalproex sodium was restarted at 500 mg twice a day and increased to 500 mg 3 times a day for mood stabilization. Mr. A continued to receive lorazepam 2 mg 3 times a day for catatonia, and risperidone was restarted at 1 mg twice a day to more effectively target his manic symptoms. Risperidone was increased to 2 mg twice a day. After this change, Mr. A’s grandiosity dissipated, his speech normalized, and his thought process became organized. He was discharged on lorazepam 2 mg 3 times a day, divalproex sodium 500 mg 3 times a day, and risperidone 2 mg twice a day. Mr. A’s length of stay (LOS) for this admission was 11 days.

Continue to: Case 2

Case 2

Mr. B, age 49, presented with irritability and odd posturing. He has a history of schizoaffective disorder, bipolar type for which he was receiving a maintenance regimen of lithium 600 mg/d at bedtime and risperidone 2 mg/d at bedtime. He had multiple previous psychiatric admissions for catatonia. On this admission, Mr. B was irritable and difficult to redirect. He yelled at staff members and had a stiff gait. The BFCRS yielded a positive screening score of 3/14 and a severity score of 8/23. As a result, the treatment team conducted a lorazepam challenge.

After Mr. B received lorazepam 1 mg IM, his thought organization and irritability improved, which allowed him to have a coherent conversation with the interviewer. His gait stiffness also improved. His risperidone and lithium were held, and oral lorazepam 1 mg 3 times a day was started for catatonia. Lorazepam was gradually increased to 4 mg 3 times a day. Mr. B became euthymic and redirectable, and had an improved gait. However, he was also tangential and hyperverbal; these symptoms were indicative of the underlying mania that precipitated his catatonia.

Divalproex sodium extended release (ER) was started and increased to 1,500 mg/d at bedtime for mood stabilization. Lithium was restarted and increased to 300 mg twice a day for adjunct mood stabilization. Risperidone was not restarted. Toward the end of his admission, Mr. B was noted to be overly sedated, so the lorazepam dosage was decreased. He was discharged on lorazepam 2 mg 3 times a day, divalproex sodium ER 1,500 mg/d at bedtime, and lithium 300 mg twice a day. At discharge, Mr. B was calm and euthymic, with a linear thought process. His LOS was 25 days.

Case 3

Mr. C, age 62, presented to the emergency department (ED) because he had exhibited erratic behavior and had not slept for the past week. He has a history of bipolar I disorder, hypothyroidism, diabetes, and hypertension. For many years, he had been stable on divalproex sodium ER 2,500 mg/d at bedtime for mood stabilization and clozapine 100 mg/d at bedtime for adjunct mood stabilization and psychosis. In the ED, Mr. C was irritable, distractible, and tangential. On admission, he was speaking slowly with increased speech latency in response to questions, exhibiting stereotypy, repeating statements over and over, and walking very slowly.

The BFCRS yielded a positive screening score of 5/14 and a severity score of 10/23. Lorazepam 1 mg IM was administered. After 15 minutes, Mr. C’s speech, gait, and distractibility improved. As a result, clozapine and divalproex sodium were held, and he was started on oral lorazepam 1 mg 3 times a day. After several days, Mr. C was speaking fluently and no longer exhibiting stereotypy or having outbursts where he would make repetitive statements. However, he was tangential and irritable at times, which were signs of his underlying mania. Divalproex sodium ER was restarted at 250 mg/d at bedtime for mood stabilization and gradually increased to 2,500 mg/d at bedtime. Clozapine was also restarted at 25 mg/d at bedtime and gradually increased to 200 mg/d at bedtime. The lorazepam was gradually tapered and discontinued over the course of 3 weeks due to oversedation.

Continue to: At discharge...

At discharge, Mr. C was euthymic, calm, linear, and goal-directed. He was discharged on divalproex sodium ER 2,500 mg/d at bedtime and clozapine 200 mg/d at bedtime. His LOS for this admission was 22 days.

A stepwise approach can improve outcomes

The Figure outlines the method we used to manage excited catatonia in these 3 cases. Each of these patients exhibited signs of excited catatonia, but because those symptoms were nearly identical to those of mania, it was initially difficult to identify catatonia. Excited catatonia was suspected after more typical catatonic symptoms—such as a stiff gait, slowed speech, and stereotypy—were observed. The BFCRS was completed to get an objective measure of the likelihood that the patient was catatonic. In all 3 cases, the BFCRS resulted in a positive screen for catatonia. Following this, the patients described in Case 2 and Case 3 received a lorazepam challenge, which confirmed their catatonia. No lorazepam challenge was performed in Case 1 because the patient was already receiving lorazepam when the BFCRS was completed. Although most catatonic patients will respond to a lorazepam challenge, not all will. Therefore, clinicians should maintain some degree of suspicion for catatonia if a patient has a positive screen on the BFCRS but a negative lorazepam challenge.

In all 3 cases, after catatonia was confirmed, the patient’s psychotropic medications were discontinued. In all 3 cases, the antipsychotic was held to prevent progression to neuroleptic malignant syndrome (NMS) or malignant catatonia. Rasmussen et al³ found that 3.6% of the catatonic patients in their sample who were treated with antipsychotics developed NMS. A review of prospective studies looking at patients treated with antipsychotics found the incidence of NMS was .07% to 1.8%.⁵ Because NMS is often clinically indistinguishable from malignant catatonia,^4,6 this incidence of NMS may have represented an increased incidence in malignant catatonia.

In all 3 cases, the mood stabilizer was held to prevent it from complicating the clinical picture. Discontinuing the mood stabilizer and focusing on treating the catatonia before targeting the underlying mania increased the likelihood of differentiating the patient’s catatonic symptoms from manic symptoms. This resulted in more precise medication selection and titration by allowing us to identify the specific symptoms that were being targeted by each medication.

Oral lorazepam was prescribed to target catatonia in all 3 cases, and the dosage was gradually increased until symptoms began to resolve. As the catatonia resolved, the manic symptoms became more easily identifiable, and at this point a mood stabilizer was started and titrated to a therapeutic dose to target the mania. In Case 1 and Case 3, the antipsychotic was restarted to treat the mania more effectively. It was not restarted in Case 2 because the patient’s mania was effectively being managed by 2 mood stabilizers. The risks and benefits of starting an antipsychotic in a catatonic or recently catatonic patient should be carefully considered. In the 2 cases where the antipsychotic was restarted, the patients were closely monitored, and there were no signs of NMS or malignant catatonia.

Continue to: As discharge approached...

As discharge approached, the dosages of oral lorazepam were reevaluated. Catatonic patients can typically tolerate high doses of benzodiazepines without becoming overly sedated, but each patient has a different threshold at which the dosage causes oversedation. In all 3 patients, lorazepam was initially titrated to a dose that treated their catatonic symptoms without causing intolerable sedation. In Case 2 and Case 3, as the catatonia began to resolve, the patients became increasingly sedated on their existing lorazepam dosage, so it was decreased. Because the patient in Case 1 did not become overly sedated, his lorazepam dosage did not need to be reduced.

For 2 of these patients, our approach resulted in a shorter LOS compared to their previous hospitalizations. The LOS in Case 2 was 25 days; 5 years earlier, he had a 49-day LOS for mania and catatonia. During the past admission, the identification and treatment of the catatonia was delayed, which resulted in the patient requiring multiple transfers to the medical unit for unstable vital signs. The LOS in Case 3 was 22 days; 6 months prior to this admission, the patient had 2 psychiatric admissions that totaled 37 days. Although the patient’s presentation in the 2 previous admissions was similar to his presentation as described in Case 3, catatonia had not been identified or treated in either admission. Since his catatonia and mania were treated in Case 3, he has not required a readmission. The patient in Case 1 was previously hospitalized, but information about the LOS of these admissions was not available. These results suggest that early identification and treatment of catatonia via the approach we used can improve patient outcomes.

Bottom Line

Excited catatonia can be challenging to diagnose and treat because it can present with symptoms similar to those seen in mania or psychosis. We describe 3 cases in which we used a stepwise approach to optimize treatment and improve outcomes for patients with excited catatonia. This approach may work equally well for other catatonia subtypes.

Related Resources

• Dubovsky SL, Dubovsky AN. Catatonia: how to identify and treat it. Current Psychiatry. 2018;17(8):16-26.
• Crouse EL, Joel B. Moran JB. Catatonia: recognition, management, and prevention of complications. Current Psychiatry. 2018;17(12):45-49.

Drug Brand Names

Clozapine • Clozaril
Lithium • Eskalith, Lithobid
Lorazepam • Ativan
Risperidone • Risperdal
Divalproex sodium • Depakote

Catatonia is often difficult to identify and treat. The excited catatonia subtype can be particularly challenging to diagnose because it can present with symptoms similar to those seen in mania or psychosis. In this article, we present 3 cases of excited catatonia that illustrate how to identify it, how to treat the catatonia as well as the underlying pathology, and factors to consider during this process to mitigate the risk of adverse outcomes. We also outline a treatment algorithm we used for the 3 cases. Although we describe using this approach for patients with excited catatonia, it is generalizable to other types of catatonia.

Many causes, varying presentations

Catatonia is a psychomotor syndrome characterized by mutism, negativism, stereotypy, waxy flexibility, and other symptoms.¹ It is defined by the presence of ≥3 of the 12 symptoms listed in the Table.² Causes of catatonia include metabolic abnormalities, endocrine disorders, drug intoxication, neurodevelopmental disorders, medication adverse effects, psychosis, and mood disorders.^1,3

A subtype of this syndrome, excited catatonia, can present with restlessness, agitation, emotional lability, poor sleep, and altered mental status in addition to the more typical symptoms.^1,4 Because excited catatonia can resemble mania or psychosis, it is particularly challenging to identify the underlying disorder causing it and appropriate treatment. Fink et al⁴ discussed how clinicians have interpreted the different presentations of excited catatonia to gain insight into the underlying diagnosis. If the patient’s thought process appears disorganized, psychosis may be suspected.⁴ If the patient is delusional and grandiose, they may be manic, and when altered mental status dominates the presentation, delirium may be the culprit.⁴

Regardless of the underlying cause, the first step is to treat the catatonia. Benzodiazepines and electroconvulsive therapy (ECT) are the most well validated treatments for catatonia and have been used to treat excited catatonia.¹ Excited catatonia is often misdiagnosed and subsequently mistreated. In the following 3 cases, excited catatonia was successfully identified and treated using the same approach (Figure).

Case 1

Mr. A, age 27, has a history of bipolar I disorder. He was brought to the hospital by ambulance after being found to be yelling and acting belligerently, and he was admitted to the inpatient psychiatry unit for manic decompensation due to medication nonadherence. He was started on divalproex sodium 500 mg twice a day for mood stabilization, risperidone 1 mg twice a day for adjunct mood stabilization and psychosis, and lorazepam 1 mg 3 times a day for agitation. Mr. A exhibited odd behavior; he would take off his clothes in the hallway, run around the unit, and randomly yell at staff or to himself. At other times, he would stay silent, repeat the same statements, or oddly posture in the hallway for minutes at a time. These behaviors were seen primarily in the hour or 2 preceding lorazepam administration and improved after he received lorazepam.

Mr. A’s treating team completed the Bush-Francis Catatonia Rating Scale (BFCRS), which yielded a positive catatonia screen of 7/14. As a result, divalproex sodium and risperidone were held, and lorazepam was increased to 2 mg twice a day.

After several days, Mr. A was no longer acting oddly and was able to speak more spontaneously; however, he began to exhibit overt signs of mania. He would speak rapidly and make grandiose claims about managing millions of dollars as the CEO of a famous company. Divalproex sodium was restarted at 500 mg twice a day and increased to 500 mg 3 times a day for mood stabilization. Mr. A continued to receive lorazepam 2 mg 3 times a day for catatonia, and risperidone was restarted at 1 mg twice a day to more effectively target his manic symptoms. Risperidone was increased to 2 mg twice a day. After this change, Mr. A’s grandiosity dissipated, his speech normalized, and his thought process became organized. He was discharged on lorazepam 2 mg 3 times a day, divalproex sodium 500 mg 3 times a day, and risperidone 2 mg twice a day. Mr. A’s length of stay (LOS) for this admission was 11 days.

Continue to: Case 2

Case 2

Mr. B, age 49, presented with irritability and odd posturing. He has a history of schizoaffective disorder, bipolar type for which he was receiving a maintenance regimen of lithium 600 mg/d at bedtime and risperidone 2 mg/d at bedtime. He had multiple previous psychiatric admissions for catatonia. On this admission, Mr. B was irritable and difficult to redirect. He yelled at staff members and had a stiff gait. The BFCRS yielded a positive screening score of 3/14 and a severity score of 8/23. As a result, the treatment team conducted a lorazepam challenge.

After Mr. B received lorazepam 1 mg IM, his thought organization and irritability improved, which allowed him to have a coherent conversation with the interviewer. His gait stiffness also improved. His risperidone and lithium were held, and oral lorazepam 1 mg 3 times a day was started for catatonia. Lorazepam was gradually increased to 4 mg 3 times a day. Mr. B became euthymic and redirectable, and had an improved gait. However, he was also tangential and hyperverbal; these symptoms were indicative of the underlying mania that precipitated his catatonia.

Divalproex sodium extended release (ER) was started and increased to 1,500 mg/d at bedtime for mood stabilization. Lithium was restarted and increased to 300 mg twice a day for adjunct mood stabilization. Risperidone was not restarted. Toward the end of his admission, Mr. B was noted to be overly sedated, so the lorazepam dosage was decreased. He was discharged on lorazepam 2 mg 3 times a day, divalproex sodium ER 1,500 mg/d at bedtime, and lithium 300 mg twice a day. At discharge, Mr. B was calm and euthymic, with a linear thought process. His LOS was 25 days.

Case 3

Mr. C, age 62, presented to the emergency department (ED) because he had exhibited erratic behavior and had not slept for the past week. He has a history of bipolar I disorder, hypothyroidism, diabetes, and hypertension. For many years, he had been stable on divalproex sodium ER 2,500 mg/d at bedtime for mood stabilization and clozapine 100 mg/d at bedtime for adjunct mood stabilization and psychosis. In the ED, Mr. C was irritable, distractible, and tangential. On admission, he was speaking slowly with increased speech latency in response to questions, exhibiting stereotypy, repeating statements over and over, and walking very slowly.

The BFCRS yielded a positive screening score of 5/14 and a severity score of 10/23. Lorazepam 1 mg IM was administered. After 15 minutes, Mr. C’s speech, gait, and distractibility improved. As a result, clozapine and divalproex sodium were held, and he was started on oral lorazepam 1 mg 3 times a day. After several days, Mr. C was speaking fluently and no longer exhibiting stereotypy or having outbursts where he would make repetitive statements. However, he was tangential and irritable at times, which were signs of his underlying mania. Divalproex sodium ER was restarted at 250 mg/d at bedtime for mood stabilization and gradually increased to 2,500 mg/d at bedtime. Clozapine was also restarted at 25 mg/d at bedtime and gradually increased to 200 mg/d at bedtime. The lorazepam was gradually tapered and discontinued over the course of 3 weeks due to oversedation.

Continue to: At discharge...

At discharge, Mr. C was euthymic, calm, linear, and goal-directed. He was discharged on divalproex sodium ER 2,500 mg/d at bedtime and clozapine 200 mg/d at bedtime. His LOS for this admission was 22 days.

A stepwise approach can improve outcomes

The Figure outlines the method we used to manage excited catatonia in these 3 cases. Each of these patients exhibited signs of excited catatonia, but because those symptoms were nearly identical to those of mania, it was initially difficult to identify catatonia. Excited catatonia was suspected after more typical catatonic symptoms—such as a stiff gait, slowed speech, and stereotypy—were observed. The BFCRS was completed to get an objective measure of the likelihood that the patient was catatonic. In all 3 cases, the BFCRS resulted in a positive screen for catatonia. Following this, the patients described in Case 2 and Case 3 received a lorazepam challenge, which confirmed their catatonia. No lorazepam challenge was performed in Case 1 because the patient was already receiving lorazepam when the BFCRS was completed. Although most catatonic patients will respond to a lorazepam challenge, not all will. Therefore, clinicians should maintain some degree of suspicion for catatonia if a patient has a positive screen on the BFCRS but a negative lorazepam challenge.

In all 3 cases, after catatonia was confirmed, the patient’s psychotropic medications were discontinued. In all 3 cases, the antipsychotic was held to prevent progression to neuroleptic malignant syndrome (NMS) or malignant catatonia. Rasmussen et al³ found that 3.6% of the catatonic patients in their sample who were treated with antipsychotics developed NMS. A review of prospective studies looking at patients treated with antipsychotics found the incidence of NMS was .07% to 1.8%.⁵ Because NMS is often clinically indistinguishable from malignant catatonia,^4,6 this incidence of NMS may have represented an increased incidence in malignant catatonia.

In all 3 cases, the mood stabilizer was held to prevent it from complicating the clinical picture. Discontinuing the mood stabilizer and focusing on treating the catatonia before targeting the underlying mania increased the likelihood of differentiating the patient’s catatonic symptoms from manic symptoms. This resulted in more precise medication selection and titration by allowing us to identify the specific symptoms that were being targeted by each medication.

Oral lorazepam was prescribed to target catatonia in all 3 cases, and the dosage was gradually increased until symptoms began to resolve. As the catatonia resolved, the manic symptoms became more easily identifiable, and at this point a mood stabilizer was started and titrated to a therapeutic dose to target the mania. In Case 1 and Case 3, the antipsychotic was restarted to treat the mania more effectively. It was not restarted in Case 2 because the patient’s mania was effectively being managed by 2 mood stabilizers. The risks and benefits of starting an antipsychotic in a catatonic or recently catatonic patient should be carefully considered. In the 2 cases where the antipsychotic was restarted, the patients were closely monitored, and there were no signs of NMS or malignant catatonia.

Continue to: As discharge approached...

As discharge approached, the dosages of oral lorazepam were reevaluated. Catatonic patients can typically tolerate high doses of benzodiazepines without becoming overly sedated, but each patient has a different threshold at which the dosage causes oversedation. In all 3 patients, lorazepam was initially titrated to a dose that treated their catatonic symptoms without causing intolerable sedation. In Case 2 and Case 3, as the catatonia began to resolve, the patients became increasingly sedated on their existing lorazepam dosage, so it was decreased. Because the patient in Case 1 did not become overly sedated, his lorazepam dosage did not need to be reduced.

For 2 of these patients, our approach resulted in a shorter LOS compared to their previous hospitalizations. The LOS in Case 2 was 25 days; 5 years earlier, he had a 49-day LOS for mania and catatonia. During the past admission, the identification and treatment of the catatonia was delayed, which resulted in the patient requiring multiple transfers to the medical unit for unstable vital signs. The LOS in Case 3 was 22 days; 6 months prior to this admission, the patient had 2 psychiatric admissions that totaled 37 days. Although the patient’s presentation in the 2 previous admissions was similar to his presentation as described in Case 3, catatonia had not been identified or treated in either admission. Since his catatonia and mania were treated in Case 3, he has not required a readmission. The patient in Case 1 was previously hospitalized, but information about the LOS of these admissions was not available. These results suggest that early identification and treatment of catatonia via the approach we used can improve patient outcomes.

Bottom Line

Excited catatonia can be challenging to diagnose and treat because it can present with symptoms similar to those seen in mania or psychosis. We describe 3 cases in which we used a stepwise approach to optimize treatment and improve outcomes for patients with excited catatonia. This approach may work equally well for other catatonia subtypes.

Related Resources

• Dubovsky SL, Dubovsky AN. Catatonia: how to identify and treat it. Current Psychiatry. 2018;17(8):16-26.
• Crouse EL, Joel B. Moran JB. Catatonia: recognition, management, and prevention of complications. Current Psychiatry. 2018;17(12):45-49.

Drug Brand Names

Clozapine • Clozaril
Lithium • Eskalith, Lithobid
Lorazepam • Ativan
Risperidone • Risperdal
Divalproex sodium • Depakote

Catatonia is often difficult to identify and treat. The excited catatonia subtype can be particularly challenging to diagnose because it can present with symptoms similar to those seen in mania or psychosis. In this article, we present 3 cases of excited catatonia that illustrate how to identify it, how to treat the catatonia as well as the underlying pathology, and factors to consider during this process to mitigate the risk of adverse outcomes. We also outline a treatment algorithm we used for the 3 cases. Although we describe using this approach for patients with excited catatonia, it is generalizable to other types of catatonia.

Many causes, varying presentations

Catatonia is a psychomotor syndrome characterized by mutism, negativism, stereotypy, waxy flexibility, and other symptoms.¹ It is defined by the presence of ≥3 of the 12 symptoms listed in the Table.² Causes of catatonia include metabolic abnormalities, endocrine disorders, drug intoxication, neurodevelopmental disorders, medication adverse effects, psychosis, and mood disorders.^1,3

A subtype of this syndrome, excited catatonia, can present with restlessness, agitation, emotional lability, poor sleep, and altered mental status in addition to the more typical symptoms.^1,4 Because excited catatonia can resemble mania or psychosis, it is particularly challenging to identify the underlying disorder causing it and appropriate treatment. Fink et al⁴ discussed how clinicians have interpreted the different presentations of excited catatonia to gain insight into the underlying diagnosis. If the patient’s thought process appears disorganized, psychosis may be suspected.⁴ If the patient is delusional and grandiose, they may be manic, and when altered mental status dominates the presentation, delirium may be the culprit.⁴

Regardless of the underlying cause, the first step is to treat the catatonia. Benzodiazepines and electroconvulsive therapy (ECT) are the most well validated treatments for catatonia and have been used to treat excited catatonia.¹ Excited catatonia is often misdiagnosed and subsequently mistreated. In the following 3 cases, excited catatonia was successfully identified and treated using the same approach (Figure).

Case 1

Mr. A, age 27, has a history of bipolar I disorder. He was brought to the hospital by ambulance after being found to be yelling and acting belligerently, and he was admitted to the inpatient psychiatry unit for manic decompensation due to medication nonadherence. He was started on divalproex sodium 500 mg twice a day for mood stabilization, risperidone 1 mg twice a day for adjunct mood stabilization and psychosis, and lorazepam 1 mg 3 times a day for agitation. Mr. A exhibited odd behavior; he would take off his clothes in the hallway, run around the unit, and randomly yell at staff or to himself. At other times, he would stay silent, repeat the same statements, or oddly posture in the hallway for minutes at a time. These behaviors were seen primarily in the hour or 2 preceding lorazepam administration and improved after he received lorazepam.

Mr. A’s treating team completed the Bush-Francis Catatonia Rating Scale (BFCRS), which yielded a positive catatonia screen of 7/14. As a result, divalproex sodium and risperidone were held, and lorazepam was increased to 2 mg twice a day.

After several days, Mr. A was no longer acting oddly and was able to speak more spontaneously; however, he began to exhibit overt signs of mania. He would speak rapidly and make grandiose claims about managing millions of dollars as the CEO of a famous company. Divalproex sodium was restarted at 500 mg twice a day and increased to 500 mg 3 times a day for mood stabilization. Mr. A continued to receive lorazepam 2 mg 3 times a day for catatonia, and risperidone was restarted at 1 mg twice a day to more effectively target his manic symptoms. Risperidone was increased to 2 mg twice a day. After this change, Mr. A’s grandiosity dissipated, his speech normalized, and his thought process became organized. He was discharged on lorazepam 2 mg 3 times a day, divalproex sodium 500 mg 3 times a day, and risperidone 2 mg twice a day. Mr. A’s length of stay (LOS) for this admission was 11 days.

Continue to: Case 2

Case 2

Mr. B, age 49, presented with irritability and odd posturing. He has a history of schizoaffective disorder, bipolar type for which he was receiving a maintenance regimen of lithium 600 mg/d at bedtime and risperidone 2 mg/d at bedtime. He had multiple previous psychiatric admissions for catatonia. On this admission, Mr. B was irritable and difficult to redirect. He yelled at staff members and had a stiff gait. The BFCRS yielded a positive screening score of 3/14 and a severity score of 8/23. As a result, the treatment team conducted a lorazepam challenge.

After Mr. B received lorazepam 1 mg IM, his thought organization and irritability improved, which allowed him to have a coherent conversation with the interviewer. His gait stiffness also improved. His risperidone and lithium were held, and oral lorazepam 1 mg 3 times a day was started for catatonia. Lorazepam was gradually increased to 4 mg 3 times a day. Mr. B became euthymic and redirectable, and had an improved gait. However, he was also tangential and hyperverbal; these symptoms were indicative of the underlying mania that precipitated his catatonia.

Divalproex sodium extended release (ER) was started and increased to 1,500 mg/d at bedtime for mood stabilization. Lithium was restarted and increased to 300 mg twice a day for adjunct mood stabilization. Risperidone was not restarted. Toward the end of his admission, Mr. B was noted to be overly sedated, so the lorazepam dosage was decreased. He was discharged on lorazepam 2 mg 3 times a day, divalproex sodium ER 1,500 mg/d at bedtime, and lithium 300 mg twice a day. At discharge, Mr. B was calm and euthymic, with a linear thought process. His LOS was 25 days.

Case 3

Mr. C, age 62, presented to the emergency department (ED) because he had exhibited erratic behavior and had not slept for the past week. He has a history of bipolar I disorder, hypothyroidism, diabetes, and hypertension. For many years, he had been stable on divalproex sodium ER 2,500 mg/d at bedtime for mood stabilization and clozapine 100 mg/d at bedtime for adjunct mood stabilization and psychosis. In the ED, Mr. C was irritable, distractible, and tangential. On admission, he was speaking slowly with increased speech latency in response to questions, exhibiting stereotypy, repeating statements over and over, and walking very slowly.

The BFCRS yielded a positive screening score of 5/14 and a severity score of 10/23. Lorazepam 1 mg IM was administered. After 15 minutes, Mr. C’s speech, gait, and distractibility improved. As a result, clozapine and divalproex sodium were held, and he was started on oral lorazepam 1 mg 3 times a day. After several days, Mr. C was speaking fluently and no longer exhibiting stereotypy or having outbursts where he would make repetitive statements. However, he was tangential and irritable at times, which were signs of his underlying mania. Divalproex sodium ER was restarted at 250 mg/d at bedtime for mood stabilization and gradually increased to 2,500 mg/d at bedtime. Clozapine was also restarted at 25 mg/d at bedtime and gradually increased to 200 mg/d at bedtime. The lorazepam was gradually tapered and discontinued over the course of 3 weeks due to oversedation.

Continue to: At discharge...

At discharge, Mr. C was euthymic, calm, linear, and goal-directed. He was discharged on divalproex sodium ER 2,500 mg/d at bedtime and clozapine 200 mg/d at bedtime. His LOS for this admission was 22 days.

A stepwise approach can improve outcomes

The Figure outlines the method we used to manage excited catatonia in these 3 cases. Each of these patients exhibited signs of excited catatonia, but because those symptoms were nearly identical to those of mania, it was initially difficult to identify catatonia. Excited catatonia was suspected after more typical catatonic symptoms—such as a stiff gait, slowed speech, and stereotypy—were observed. The BFCRS was completed to get an objective measure of the likelihood that the patient was catatonic. In all 3 cases, the BFCRS resulted in a positive screen for catatonia. Following this, the patients described in Case 2 and Case 3 received a lorazepam challenge, which confirmed their catatonia. No lorazepam challenge was performed in Case 1 because the patient was already receiving lorazepam when the BFCRS was completed. Although most catatonic patients will respond to a lorazepam challenge, not all will. Therefore, clinicians should maintain some degree of suspicion for catatonia if a patient has a positive screen on the BFCRS but a negative lorazepam challenge.

In all 3 cases, after catatonia was confirmed, the patient’s psychotropic medications were discontinued. In all 3 cases, the antipsychotic was held to prevent progression to neuroleptic malignant syndrome (NMS) or malignant catatonia. Rasmussen et al³ found that 3.6% of the catatonic patients in their sample who were treated with antipsychotics developed NMS. A review of prospective studies looking at patients treated with antipsychotics found the incidence of NMS was .07% to 1.8%.⁵ Because NMS is often clinically indistinguishable from malignant catatonia,^4,6 this incidence of NMS may have represented an increased incidence in malignant catatonia.

In all 3 cases, the mood stabilizer was held to prevent it from complicating the clinical picture. Discontinuing the mood stabilizer and focusing on treating the catatonia before targeting the underlying mania increased the likelihood of differentiating the patient’s catatonic symptoms from manic symptoms. This resulted in more precise medication selection and titration by allowing us to identify the specific symptoms that were being targeted by each medication.

Oral lorazepam was prescribed to target catatonia in all 3 cases, and the dosage was gradually increased until symptoms began to resolve. As the catatonia resolved, the manic symptoms became more easily identifiable, and at this point a mood stabilizer was started and titrated to a therapeutic dose to target the mania. In Case 1 and Case 3, the antipsychotic was restarted to treat the mania more effectively. It was not restarted in Case 2 because the patient’s mania was effectively being managed by 2 mood stabilizers. The risks and benefits of starting an antipsychotic in a catatonic or recently catatonic patient should be carefully considered. In the 2 cases where the antipsychotic was restarted, the patients were closely monitored, and there were no signs of NMS or malignant catatonia.

Continue to: As discharge approached...

As discharge approached, the dosages of oral lorazepam were reevaluated. Catatonic patients can typically tolerate high doses of benzodiazepines without becoming overly sedated, but each patient has a different threshold at which the dosage causes oversedation. In all 3 patients, lorazepam was initially titrated to a dose that treated their catatonic symptoms without causing intolerable sedation. In Case 2 and Case 3, as the catatonia began to resolve, the patients became increasingly sedated on their existing lorazepam dosage, so it was decreased. Because the patient in Case 1 did not become overly sedated, his lorazepam dosage did not need to be reduced.

For 2 of these patients, our approach resulted in a shorter LOS compared to their previous hospitalizations. The LOS in Case 2 was 25 days; 5 years earlier, he had a 49-day LOS for mania and catatonia. During the past admission, the identification and treatment of the catatonia was delayed, which resulted in the patient requiring multiple transfers to the medical unit for unstable vital signs. The LOS in Case 3 was 22 days; 6 months prior to this admission, the patient had 2 psychiatric admissions that totaled 37 days. Although the patient’s presentation in the 2 previous admissions was similar to his presentation as described in Case 3, catatonia had not been identified or treated in either admission. Since his catatonia and mania were treated in Case 3, he has not required a readmission. The patient in Case 1 was previously hospitalized, but information about the LOS of these admissions was not available. These results suggest that early identification and treatment of catatonia via the approach we used can improve patient outcomes.

Bottom Line

Excited catatonia can be challenging to diagnose and treat because it can present with symptoms similar to those seen in mania or psychosis. We describe 3 cases in which we used a stepwise approach to optimize treatment and improve outcomes for patients with excited catatonia. This approach may work equally well for other catatonia subtypes.

Related Resources

• Dubovsky SL, Dubovsky AN. Catatonia: how to identify and treat it. Current Psychiatry. 2018;17(8):16-26.
• Crouse EL, Joel B. Moran JB. Catatonia: recognition, management, and prevention of complications. Current Psychiatry. 2018;17(12):45-49.

Drug Brand Names

Clozapine • Clozaril
Lithium • Eskalith, Lithobid
Lorazepam • Ativan
Risperidone • Risperdal
Divalproex sodium • Depakote

Outpatient behavioral health treatment (OPBHT) for patients newly diagnosed with depression, substance use disorder, or other behavioral health condition (BHC) is cost-effective.

Results of a large retrospective study showed that patients newly diagnosed with a BHC who receive OPBHT following diagnosis incur lower medical and pharmacy costs over roughly the next 1 to 2 years, compared with peers who don’t receive OPBHT.

“Our findings suggest that promoting OPBHT as part of a population health strategy is associated with improved overall medical spending, particularly among adults,” the investigators write.

The study was published online in JAMA Network Open.
 

Common, undertreated

Nearly a quarter of adults in the United States have a BHC, and they incur greater medical costs than those without a BHC. However, diagnosis of a BHC is often delayed, and most affected individuals receive little to no treatment.

In their cost analysis, Johanna Bellon, PhD, and colleagues with Evernorth Health, St. Louis, analyzed commercial insurance claims data for 203,401 U.S. individuals newly diagnosed with one or more BHCs between 2017 and 2018.

About half of participants had depression and/or anxiety, 11% had substance use or alcohol use disorder, and 6% had a higher-acuity diagnosis, such as bipolar disorder, severe depression, eating disorder, psychotic disorder, or autism spectrum disorder.

About 1 in 5 (22%) had at least one chronic medical condition along with their BHC.

The researchers found that having at least one OPBHT visit was associated with lower medical and pharmacy costs during 15- and 27-month follow-up periods.

Over 15 months, the adjusted mean per member per month (PMPM) medical/pharmacy cost was $686 with no OPBHT visit, compared with $571 with one or more OPBHT visits.

Over 27 months, the adjusted mean PMPM was $464 with no OPBHT, versus $391 with one or more OPBHT visits.
 

Dose-response effect

In addition, there was a “dose-response” relationship between OPBHT and medical/pharmacy costs, such that estimated cost savings were significantly lower in the treated versus the untreated groups at almost every level of treatment.

“Our findings were also largely age independent, especially over 15 months, suggesting that OPBHT has favorable effects among children, young adults, and adults,” the researchers report.

“This is promising given that disease etiology and progression, treatment paradigms, presence of comorbid medical conditions, and overall medical and pharmacy costs differ among the three groups,” they say.

Notably, the dataset largely encompassed in-person OPBHT, because the study period preceded the transition into virtual care that occurred in 2020.

However, overall use of OPBHT was low – older adults, adults with lower income, individuals with comorbid medical conditions, and persons of racial and ethnic minorities were less likely to receive OPBHT, they found.

“These findings support the cost-effectiveness of practitioner- and insurance-based interventions to increase OPBHT utilization, which is a critical resource as new BHC diagnoses continue to increase,” the researchers say.

“Future research should validate these findings in other populations, including government-insured individuals, and explore data by chronic disease category, over longer time horizons, by type and quality of OPBHT, by type of medical spending, within subpopulations with BHCs, and including virtual and digital behavioral health services,” they suggest.

The study had no specific funding. The authors have disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Outpatient behavioral health treatment (OPBHT) for patients newly diagnosed with depression, substance use disorder, or other behavioral health condition (BHC) is cost-effective.

Results of a large retrospective study showed that patients newly diagnosed with a BHC who receive OPBHT following diagnosis incur lower medical and pharmacy costs over roughly the next 1 to 2 years, compared with peers who don’t receive OPBHT.

“Our findings suggest that promoting OPBHT as part of a population health strategy is associated with improved overall medical spending, particularly among adults,” the investigators write.

The study was published online in JAMA Network Open.
 

Common, undertreated

Nearly a quarter of adults in the United States have a BHC, and they incur greater medical costs than those without a BHC. However, diagnosis of a BHC is often delayed, and most affected individuals receive little to no treatment.

In their cost analysis, Johanna Bellon, PhD, and colleagues with Evernorth Health, St. Louis, analyzed commercial insurance claims data for 203,401 U.S. individuals newly diagnosed with one or more BHCs between 2017 and 2018.

About half of participants had depression and/or anxiety, 11% had substance use or alcohol use disorder, and 6% had a higher-acuity diagnosis, such as bipolar disorder, severe depression, eating disorder, psychotic disorder, or autism spectrum disorder.

About 1 in 5 (22%) had at least one chronic medical condition along with their BHC.

The researchers found that having at least one OPBHT visit was associated with lower medical and pharmacy costs during 15- and 27-month follow-up periods.

Over 15 months, the adjusted mean per member per month (PMPM) medical/pharmacy cost was $686 with no OPBHT visit, compared with $571 with one or more OPBHT visits.

Over 27 months, the adjusted mean PMPM was $464 with no OPBHT, versus $391 with one or more OPBHT visits.
 

Dose-response effect

In addition, there was a “dose-response” relationship between OPBHT and medical/pharmacy costs, such that estimated cost savings were significantly lower in the treated versus the untreated groups at almost every level of treatment.

“Our findings were also largely age independent, especially over 15 months, suggesting that OPBHT has favorable effects among children, young adults, and adults,” the researchers report.

“This is promising given that disease etiology and progression, treatment paradigms, presence of comorbid medical conditions, and overall medical and pharmacy costs differ among the three groups,” they say.

Notably, the dataset largely encompassed in-person OPBHT, because the study period preceded the transition into virtual care that occurred in 2020.

However, overall use of OPBHT was low – older adults, adults with lower income, individuals with comorbid medical conditions, and persons of racial and ethnic minorities were less likely to receive OPBHT, they found.

“These findings support the cost-effectiveness of practitioner- and insurance-based interventions to increase OPBHT utilization, which is a critical resource as new BHC diagnoses continue to increase,” the researchers say.

“Future research should validate these findings in other populations, including government-insured individuals, and explore data by chronic disease category, over longer time horizons, by type and quality of OPBHT, by type of medical spending, within subpopulations with BHCs, and including virtual and digital behavioral health services,” they suggest.

The study had no specific funding. The authors have disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Outpatient behavioral health treatment (OPBHT) for patients newly diagnosed with depression, substance use disorder, or other behavioral health condition (BHC) is cost-effective.

Results of a large retrospective study showed that patients newly diagnosed with a BHC who receive OPBHT following diagnosis incur lower medical and pharmacy costs over roughly the next 1 to 2 years, compared with peers who don’t receive OPBHT.

“Our findings suggest that promoting OPBHT as part of a population health strategy is associated with improved overall medical spending, particularly among adults,” the investigators write.

The study was published online in JAMA Network Open.
 

Common, undertreated

Nearly a quarter of adults in the United States have a BHC, and they incur greater medical costs than those without a BHC. However, diagnosis of a BHC is often delayed, and most affected individuals receive little to no treatment.

In their cost analysis, Johanna Bellon, PhD, and colleagues with Evernorth Health, St. Louis, analyzed commercial insurance claims data for 203,401 U.S. individuals newly diagnosed with one or more BHCs between 2017 and 2018.

About half of participants had depression and/or anxiety, 11% had substance use or alcohol use disorder, and 6% had a higher-acuity diagnosis, such as bipolar disorder, severe depression, eating disorder, psychotic disorder, or autism spectrum disorder.

About 1 in 5 (22%) had at least one chronic medical condition along with their BHC.

The researchers found that having at least one OPBHT visit was associated with lower medical and pharmacy costs during 15- and 27-month follow-up periods.

Over 15 months, the adjusted mean per member per month (PMPM) medical/pharmacy cost was $686 with no OPBHT visit, compared with $571 with one or more OPBHT visits.

Over 27 months, the adjusted mean PMPM was $464 with no OPBHT, versus $391 with one or more OPBHT visits.
 

Dose-response effect

In addition, there was a “dose-response” relationship between OPBHT and medical/pharmacy costs, such that estimated cost savings were significantly lower in the treated versus the untreated groups at almost every level of treatment.

“Our findings were also largely age independent, especially over 15 months, suggesting that OPBHT has favorable effects among children, young adults, and adults,” the researchers report.

“This is promising given that disease etiology and progression, treatment paradigms, presence of comorbid medical conditions, and overall medical and pharmacy costs differ among the three groups,” they say.

Notably, the dataset largely encompassed in-person OPBHT, because the study period preceded the transition into virtual care that occurred in 2020.

However, overall use of OPBHT was low – older adults, adults with lower income, individuals with comorbid medical conditions, and persons of racial and ethnic minorities were less likely to receive OPBHT, they found.

“These findings support the cost-effectiveness of practitioner- and insurance-based interventions to increase OPBHT utilization, which is a critical resource as new BHC diagnoses continue to increase,” the researchers say.

“Future research should validate these findings in other populations, including government-insured individuals, and explore data by chronic disease category, over longer time horizons, by type and quality of OPBHT, by type of medical spending, within subpopulations with BHCs, and including virtual and digital behavioral health services,” they suggest.

The study had no specific funding. The authors have disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Being male, being older, and having a clear intent to die were among the key independent predictors of psychiatric hospital admission after self-harm, based on data from more than 1,800 individuals.

Clinicians who assess suicidal patients in the emergency department setting face the challenge of whether to admit the patient to inpatient or outpatient care, and data on predictors of compulsory admission are limited, wrote Laurent Michaud, MD, of the University of Lausanne, Switzerland, and colleagues.

To better identify predictors of hospitalization after self-harm, the researchers reviewed data from 1,832 patients aged 18 years and older admitted to four emergency departments in Switzerland between December 2016 and November 2019 .

Self-harm (SH) was defined in this study as “all nonfatal intentional acts of self-poisoning or self-injury, irrespective of degree of suicidal intent or other types of motivation,” the researchers noted. The study included 2,142 episodes of self-harm.

The researchers conducted two analyses. They compared episodes followed by any hospitalization and those with outpatient follow-up (1,083 episodes vs. 1,059 episodes) and episodes followed by compulsory hospitalization (357 episodes) with all other episodes followed by either outpatient care or voluntary hospitalization (1,785 episodes).

Overall, women were significantly more likely to be referred to outpatient follow-up compared with men (61.8% vs. 38.1%), and hospitalized patients were significantly older than outpatients (mean age of 41 years vs. 36 years, P < .001 for both).

“Not surprisingly, major psychopathological conditions such as depression, mania, dementia, and schizophrenia were predictive of hospitalization,” the researchers noted.

Other sociodemographic factors associated with hospitalization included living alone, no children, problematic socioeconomic status, and unemployment. Clinical factors associated with hospitalization included physical pain, more lethal suicide attempt method, and clear intent to die.

In a multivariate analysis, independent predictors of any hospitalization included male gender, older age, assessment in the Neuchatel location vs. Lausanne, depression vs. personality disorders, substance use, or anxiety disorder, difficult socioeconomic status, a clear vs. unclear intent to die, and a serious suicide attempt vs. less serious.

Differences in hospitalization based on hospital setting was a striking finding, the researchers wrote in their discussion. These differences may be largely explained by the organization of local mental health services and specific institutional cultures; the workload of staff and availability of beds also may have played a role in decisions to hospitalize, they said.

The findings were limited by several factors including the lack of data on the realization level of a self-harm episode and significant events such as a breakup, the researchers explained. Other limitations included missing data, multiple analyses that could increase the risk of false positives, the reliance on clinical diagnosis rather than formal instruments, and the cross-sectional study design, they said.

However, the results have clinical implications, as the clinical factors identified could be used to target subgroups of suicidal populations and refine treatment strategies, they concluded.

The study was supported by institutional funding and the Swiss Federal Office of Public Health. The researchers had no financial conflicts to disclose.

Being male, being older, and having a clear intent to die were among the key independent predictors of psychiatric hospital admission after self-harm, based on data from more than 1,800 individuals.

Clinicians who assess suicidal patients in the emergency department setting face the challenge of whether to admit the patient to inpatient or outpatient care, and data on predictors of compulsory admission are limited, wrote Laurent Michaud, MD, of the University of Lausanne, Switzerland, and colleagues.

To better identify predictors of hospitalization after self-harm, the researchers reviewed data from 1,832 patients aged 18 years and older admitted to four emergency departments in Switzerland between December 2016 and November 2019 .

Self-harm (SH) was defined in this study as “all nonfatal intentional acts of self-poisoning or self-injury, irrespective of degree of suicidal intent or other types of motivation,” the researchers noted. The study included 2,142 episodes of self-harm.

The researchers conducted two analyses. They compared episodes followed by any hospitalization and those with outpatient follow-up (1,083 episodes vs. 1,059 episodes) and episodes followed by compulsory hospitalization (357 episodes) with all other episodes followed by either outpatient care or voluntary hospitalization (1,785 episodes).

Overall, women were significantly more likely to be referred to outpatient follow-up compared with men (61.8% vs. 38.1%), and hospitalized patients were significantly older than outpatients (mean age of 41 years vs. 36 years, P < .001 for both).

“Not surprisingly, major psychopathological conditions such as depression, mania, dementia, and schizophrenia were predictive of hospitalization,” the researchers noted.

Other sociodemographic factors associated with hospitalization included living alone, no children, problematic socioeconomic status, and unemployment. Clinical factors associated with hospitalization included physical pain, more lethal suicide attempt method, and clear intent to die.

In a multivariate analysis, independent predictors of any hospitalization included male gender, older age, assessment in the Neuchatel location vs. Lausanne, depression vs. personality disorders, substance use, or anxiety disorder, difficult socioeconomic status, a clear vs. unclear intent to die, and a serious suicide attempt vs. less serious.

Differences in hospitalization based on hospital setting was a striking finding, the researchers wrote in their discussion. These differences may be largely explained by the organization of local mental health services and specific institutional cultures; the workload of staff and availability of beds also may have played a role in decisions to hospitalize, they said.

The findings were limited by several factors including the lack of data on the realization level of a self-harm episode and significant events such as a breakup, the researchers explained. Other limitations included missing data, multiple analyses that could increase the risk of false positives, the reliance on clinical diagnosis rather than formal instruments, and the cross-sectional study design, they said.

However, the results have clinical implications, as the clinical factors identified could be used to target subgroups of suicidal populations and refine treatment strategies, they concluded.

The study was supported by institutional funding and the Swiss Federal Office of Public Health. The researchers had no financial conflicts to disclose.

Being male, being older, and having a clear intent to die were among the key independent predictors of psychiatric hospital admission after self-harm, based on data from more than 1,800 individuals.

Clinicians who assess suicidal patients in the emergency department setting face the challenge of whether to admit the patient to inpatient or outpatient care, and data on predictors of compulsory admission are limited, wrote Laurent Michaud, MD, of the University of Lausanne, Switzerland, and colleagues.

To better identify predictors of hospitalization after self-harm, the researchers reviewed data from 1,832 patients aged 18 years and older admitted to four emergency departments in Switzerland between December 2016 and November 2019 .

Self-harm (SH) was defined in this study as “all nonfatal intentional acts of self-poisoning or self-injury, irrespective of degree of suicidal intent or other types of motivation,” the researchers noted. The study included 2,142 episodes of self-harm.

The researchers conducted two analyses. They compared episodes followed by any hospitalization and those with outpatient follow-up (1,083 episodes vs. 1,059 episodes) and episodes followed by compulsory hospitalization (357 episodes) with all other episodes followed by either outpatient care or voluntary hospitalization (1,785 episodes).

Overall, women were significantly more likely to be referred to outpatient follow-up compared with men (61.8% vs. 38.1%), and hospitalized patients were significantly older than outpatients (mean age of 41 years vs. 36 years, P < .001 for both).

“Not surprisingly, major psychopathological conditions such as depression, mania, dementia, and schizophrenia were predictive of hospitalization,” the researchers noted.

Other sociodemographic factors associated with hospitalization included living alone, no children, problematic socioeconomic status, and unemployment. Clinical factors associated with hospitalization included physical pain, more lethal suicide attempt method, and clear intent to die.

In a multivariate analysis, independent predictors of any hospitalization included male gender, older age, assessment in the Neuchatel location vs. Lausanne, depression vs. personality disorders, substance use, or anxiety disorder, difficult socioeconomic status, a clear vs. unclear intent to die, and a serious suicide attempt vs. less serious.

Differences in hospitalization based on hospital setting was a striking finding, the researchers wrote in their discussion. These differences may be largely explained by the organization of local mental health services and specific institutional cultures; the workload of staff and availability of beds also may have played a role in decisions to hospitalize, they said.

The findings were limited by several factors including the lack of data on the realization level of a self-harm episode and significant events such as a breakup, the researchers explained. Other limitations included missing data, multiple analyses that could increase the risk of false positives, the reliance on clinical diagnosis rather than formal instruments, and the cross-sectional study design, they said.

However, the results have clinical implications, as the clinical factors identified could be used to target subgroups of suicidal populations and refine treatment strategies, they concluded.

The study was supported by institutional funding and the Swiss Federal Office of Public Health. The researchers had no financial conflicts to disclose.

Hypercalcemia is a well-known but underrecognized adverse effect of lithium. Most patients with lithium-associated hypercalcemia (LAH) have either nonspecific symptoms (eg, persistent tiredness, constipation, polyuria, polydipsia) or no symptoms. Clinically, LAH differs from primary hyperparathyroidism, though the management protocol of these 2 conditions is almost the same. In this article, we discuss how lithium can affect calcium and parathyroid hormone (PTH) levels and how LAH and lithium-associated hyperparathyroidism (LAHP) differs from primary hyperparathyroidism. We also outline a suggested approach to monitoring and management.

An insidious problem

Due to the varying definitions and methods used to assess hypercalcemia, the reported prevalence of LAH varies from 4.3% to 80%.¹ McKnight et al² conducted a systematic review and meta-analysis of studies of the relationship between lithium and parathyroid function that included 14 case-control studies, 36 case reports, and 6 cross-sectional studies without a control group. They found that the levels of calcium and PTH were 10% higher in lithium-treated patients than in controls.²

Pathophysiology. Lithium is known to increase both calcium and PTH levels. PTH is responsible for calcium homeostasis. It is secreted in response to low calcium levels, which it increases by its action on bones, intestines, and kidneys. Vitamin D also plays a crucial role in calcium homeostasis. A deficiency of vitamin D triggers a compensatory increase in PTH to maintain calcium levels.³

Calcium and PTH levels increase soon after administration of lithium, but the rise is usually mild and insidious. In a small proportion of patients who receive long-term lithium treatment, calcium levels can exceed the normal range. Patients who develop LAH typically have serum calcium levels slightly above the normal range and PTH levels ranging from the higher side of the normal range to several times the upper limit of the normal range. Patients might also experience elevated PTH levels without any increase in calcium levels. Lithium can affect calcium and PTH levels in multiple ways. For instance, it increases the reabsorption of calcium in the kidney as well as the reset point of calcium-sensing receptors. Therefore, only higher levels of calcium can inhibit the release of PTH. Hence, in cases where the PTH level is within the normal range, it is generally higher than would be expected for a given serum calcium level. Lithium can also directly affect the parathyroid glands and can lead to either single-nodule or multimodule hyperplasia.⁴

Long-term lithium use can cause chronic kidney disease (CKD), which in turn leads to vitamin D deficiency and hyperparathyroidism. However, secondary hyperparathyroidism with CKD is usually seen in the more advanced stages of CKD, and is associated with low-to-normal calcium levels (as opposed to the high levels seen in LAH).^3-5

Lithium-associated hyperparathyroidism

Primary hyperparathyroidism is the most common cause of hypercalcemia. Its prevalence ranges from 1 to 7 cases per 1,000 adults. The incidence of LAH/LAHP is 4- to 6-fold higher compared to the general population.⁶ Similar to LAH/LAHP, primary hyperparathyroidism is more common in older adults (age >60) and females. Hence, some researchers have suggested that lithium probably unmasks hyperparathyroidism in patients who are susceptible to primary hyperparathyroidism.³

Look for these clinical manifestations

Symptoms of primary hyperparathyroidism are related to high calcium and PTH levels. They are commonly described as “painful bones, renal stones, abdominal groans (due to hypercalcemia-induced ileus), and psychic moans (lethargy, poor concentration, depression).” Common adverse outcomes associated with primary hyperparathyroidism are renal stones, high risk of fracture, constipation, peptic ulcer, and pancreatitis.^3,7

Continue: In contrast...

In contrast, LAHP is characterized by mild, intermittent, and/or persistent hypercalcemia and mildly increased PTH (Table 1).^1,3,4 In some patients, it could improve without active intervention. Because lithium increases the absorption of urinary calcium, it is associated with hypocalciuria and a lower risk of renal stones. Additionally, lithium has osteoprotective effects and has not been associated with an increased risk of fracture. Some researchers have suggested that the presentation of LAHP is more like familial hypocalciuric hypercalcemia (FHC), which is also associated with hypocalciuria. FHC is a benign condition and does not require active intervention.^3,4 Similar to those with FHC, many patients with LAHP may live with chronic asymptomatic hypercalcemia without any significant adverse outcome.

A suggested approach to monitoring

In most cases, LAH is an insidious adverse effect that is usually detected on blood tests after many years of lithium therapy.⁸ For patients starting lithium therapy, International Society of Bipolar Disorder guidelines recommend testing calcium levels at baseline, 6 months, and annually thereafter, or as clinically indicated, to detect and monitor hypercalcemia and hyperparathyroidism. However, these guidelines do not provide any recommendations regarding how to manage abnormal findings.⁹

Clinical laboratories report both total and adjusted calcium values. The adjusted calcium value takes into account albumin levels. This is a way to compensate for an abnormal concentration of albumin (establishing what a patient’s total calcium concentration would be if the albumin concentration was normal). Table 2⁵ shows the categorization of adjusted calcium values.For patients receiving lithium, some researchers have suggested monitoring PTH as well as calcium.¹

The Figure outlines our proposed approach to monitoring for LAH in patients receiving lithium. An isolated high value of calcium could be due to prolonged venous stasis if a tourniquet is used for phlebotomy. In such instances, the calcium level should be tested again without a tourniquet.¹⁰ If the repeat blood test shows elevated calcium levels, then both PTH and serum calcium should be tested.

If the PTH level is higher than the midpoint of the reference range, LAH should be suspected, though sometimes hypercalcemia can present without raised PTH. LAH has also been reported to cause a transient increase in calcium levels. If hypercalcemia frequently recurs, PTH levels should be monitored. If PTH is suppressed, then the raised calcium levels are probably secondary to something other than lithium; common reasons for this include the use of vitamin D supplements or thiazide diuretics, or malignancies such as multiple myeloma.^3,5,8

Continue to: Treatment

There are several options for treating LAH. Lithium may be continued or discontinued following close monitoring of calcium and PTH levels, with or without active interventions such as surgery or pharmacotherapy, and as deemed appropriate after consultation with an endocrinologist. The decision should be informed by evaluating the risks and benefits to the patient’s physical and mental health. LAH can be reversed by discontinuing lithium, but this might not be the case in patients receiving long-term lithium therapy, especially if their elevated calcium levels are associated with parathyroid adenomas or hyperplasia. Hence, close monitoring of calcium and PTH is required even after discontinuing lithium.^3,8

Surgical treatment. The primary treatment of LAH and primary hyperparathyroidism is parathyroidectomy. The possibility of recovery after parathyroidectomy for primary hyperparathyroidism is 60% to 80%, though a small proportion of patients might experience recurrence. This figure might be higher for LAH, because it is more likely to affect multiple glands.^1,11 Other potential complications of parathyroidectomy are recurrent laryngeal nerve injury causing paralysis of vocal cords leading to hoarseness of voice, stridor, or aspiration, and local hematoma and hypocalcemia (requiring vitamin D and/or calcium supplements).¹²

Pharmacotherapy. Cinacalcet is a calcimimetic drug that decreases the reset point of the calcium-sensing receptor. It can be used if a patient is not suitable for or apprehensive about surgical intervention.^1,8

Bottom Line

Calcium levels should be regularly monitored in patients receiving lithium. If calcium levels are persistently high, parathyroid hormone levels should also be measured. Management of lithium-associated hypercalcemia includes watchful waiting, discontinuing lithium, parathyroidectomy, and pharmacotherapy with cinacalcet.

Related Resources

• Laski M, Foreman R, Hancock H, et al. Lithium: an underutilized element. Current Psychiatry. 2021;20(12):27-30,34. doi:10.12788/cp.0193
• Pelekanos M, Foo K. A resident’s guide to lithium. Current Psychiatry. 2021;20(4):e3-e7. doi:10.12788/cp.0113

Drug Brand Names

Cinacalcet • Sensipar

Hypercalcemia is a well-known but underrecognized adverse effect of lithium. Most patients with lithium-associated hypercalcemia (LAH) have either nonspecific symptoms (eg, persistent tiredness, constipation, polyuria, polydipsia) or no symptoms. Clinically, LAH differs from primary hyperparathyroidism, though the management protocol of these 2 conditions is almost the same. In this article, we discuss how lithium can affect calcium and parathyroid hormone (PTH) levels and how LAH and lithium-associated hyperparathyroidism (LAHP) differs from primary hyperparathyroidism. We also outline a suggested approach to monitoring and management.

An insidious problem

Due to the varying definitions and methods used to assess hypercalcemia, the reported prevalence of LAH varies from 4.3% to 80%.¹ McKnight et al² conducted a systematic review and meta-analysis of studies of the relationship between lithium and parathyroid function that included 14 case-control studies, 36 case reports, and 6 cross-sectional studies without a control group. They found that the levels of calcium and PTH were 10% higher in lithium-treated patients than in controls.²

Pathophysiology. Lithium is known to increase both calcium and PTH levels. PTH is responsible for calcium homeostasis. It is secreted in response to low calcium levels, which it increases by its action on bones, intestines, and kidneys. Vitamin D also plays a crucial role in calcium homeostasis. A deficiency of vitamin D triggers a compensatory increase in PTH to maintain calcium levels.³

Calcium and PTH levels increase soon after administration of lithium, but the rise is usually mild and insidious. In a small proportion of patients who receive long-term lithium treatment, calcium levels can exceed the normal range. Patients who develop LAH typically have serum calcium levels slightly above the normal range and PTH levels ranging from the higher side of the normal range to several times the upper limit of the normal range. Patients might also experience elevated PTH levels without any increase in calcium levels. Lithium can affect calcium and PTH levels in multiple ways. For instance, it increases the reabsorption of calcium in the kidney as well as the reset point of calcium-sensing receptors. Therefore, only higher levels of calcium can inhibit the release of PTH. Hence, in cases where the PTH level is within the normal range, it is generally higher than would be expected for a given serum calcium level. Lithium can also directly affect the parathyroid glands and can lead to either single-nodule or multimodule hyperplasia.⁴

Long-term lithium use can cause chronic kidney disease (CKD), which in turn leads to vitamin D deficiency and hyperparathyroidism. However, secondary hyperparathyroidism with CKD is usually seen in the more advanced stages of CKD, and is associated with low-to-normal calcium levels (as opposed to the high levels seen in LAH).^3-5

Lithium-associated hyperparathyroidism

Primary hyperparathyroidism is the most common cause of hypercalcemia. Its prevalence ranges from 1 to 7 cases per 1,000 adults. The incidence of LAH/LAHP is 4- to 6-fold higher compared to the general population.⁶ Similar to LAH/LAHP, primary hyperparathyroidism is more common in older adults (age >60) and females. Hence, some researchers have suggested that lithium probably unmasks hyperparathyroidism in patients who are susceptible to primary hyperparathyroidism.³

Look for these clinical manifestations

Symptoms of primary hyperparathyroidism are related to high calcium and PTH levels. They are commonly described as “painful bones, renal stones, abdominal groans (due to hypercalcemia-induced ileus), and psychic moans (lethargy, poor concentration, depression).” Common adverse outcomes associated with primary hyperparathyroidism are renal stones, high risk of fracture, constipation, peptic ulcer, and pancreatitis.^3,7

Continue: In contrast...

In contrast, LAHP is characterized by mild, intermittent, and/or persistent hypercalcemia and mildly increased PTH (Table 1).^1,3,4 In some patients, it could improve without active intervention. Because lithium increases the absorption of urinary calcium, it is associated with hypocalciuria and a lower risk of renal stones. Additionally, lithium has osteoprotective effects and has not been associated with an increased risk of fracture. Some researchers have suggested that the presentation of LAHP is more like familial hypocalciuric hypercalcemia (FHC), which is also associated with hypocalciuria. FHC is a benign condition and does not require active intervention.^3,4 Similar to those with FHC, many patients with LAHP may live with chronic asymptomatic hypercalcemia without any significant adverse outcome.

A suggested approach to monitoring

In most cases, LAH is an insidious adverse effect that is usually detected on blood tests after many years of lithium therapy.⁸ For patients starting lithium therapy, International Society of Bipolar Disorder guidelines recommend testing calcium levels at baseline, 6 months, and annually thereafter, or as clinically indicated, to detect and monitor hypercalcemia and hyperparathyroidism. However, these guidelines do not provide any recommendations regarding how to manage abnormal findings.⁹

Clinical laboratories report both total and adjusted calcium values. The adjusted calcium value takes into account albumin levels. This is a way to compensate for an abnormal concentration of albumin (establishing what a patient’s total calcium concentration would be if the albumin concentration was normal). Table 2⁵ shows the categorization of adjusted calcium values.For patients receiving lithium, some researchers have suggested monitoring PTH as well as calcium.¹

The Figure outlines our proposed approach to monitoring for LAH in patients receiving lithium. An isolated high value of calcium could be due to prolonged venous stasis if a tourniquet is used for phlebotomy. In such instances, the calcium level should be tested again without a tourniquet.¹⁰ If the repeat blood test shows elevated calcium levels, then both PTH and serum calcium should be tested.

If the PTH level is higher than the midpoint of the reference range, LAH should be suspected, though sometimes hypercalcemia can present without raised PTH. LAH has also been reported to cause a transient increase in calcium levels. If hypercalcemia frequently recurs, PTH levels should be monitored. If PTH is suppressed, then the raised calcium levels are probably secondary to something other than lithium; common reasons for this include the use of vitamin D supplements or thiazide diuretics, or malignancies such as multiple myeloma.^3,5,8

Continue to: Treatment

There are several options for treating LAH. Lithium may be continued or discontinued following close monitoring of calcium and PTH levels, with or without active interventions such as surgery or pharmacotherapy, and as deemed appropriate after consultation with an endocrinologist. The decision should be informed by evaluating the risks and benefits to the patient’s physical and mental health. LAH can be reversed by discontinuing lithium, but this might not be the case in patients receiving long-term lithium therapy, especially if their elevated calcium levels are associated with parathyroid adenomas or hyperplasia. Hence, close monitoring of calcium and PTH is required even after discontinuing lithium.^3,8

Surgical treatment. The primary treatment of LAH and primary hyperparathyroidism is parathyroidectomy. The possibility of recovery after parathyroidectomy for primary hyperparathyroidism is 60% to 80%, though a small proportion of patients might experience recurrence. This figure might be higher for LAH, because it is more likely to affect multiple glands.^1,11 Other potential complications of parathyroidectomy are recurrent laryngeal nerve injury causing paralysis of vocal cords leading to hoarseness of voice, stridor, or aspiration, and local hematoma and hypocalcemia (requiring vitamin D and/or calcium supplements).¹²

Pharmacotherapy. Cinacalcet is a calcimimetic drug that decreases the reset point of the calcium-sensing receptor. It can be used if a patient is not suitable for or apprehensive about surgical intervention.^1,8

Bottom Line

Calcium levels should be regularly monitored in patients receiving lithium. If calcium levels are persistently high, parathyroid hormone levels should also be measured. Management of lithium-associated hypercalcemia includes watchful waiting, discontinuing lithium, parathyroidectomy, and pharmacotherapy with cinacalcet.

Related Resources

• Laski M, Foreman R, Hancock H, et al. Lithium: an underutilized element. Current Psychiatry. 2021;20(12):27-30,34. doi:10.12788/cp.0193
• Pelekanos M, Foo K. A resident’s guide to lithium. Current Psychiatry. 2021;20(4):e3-e7. doi:10.12788/cp.0113

Drug Brand Names

Cinacalcet • Sensipar

Hypercalcemia is a well-known but underrecognized adverse effect of lithium. Most patients with lithium-associated hypercalcemia (LAH) have either nonspecific symptoms (eg, persistent tiredness, constipation, polyuria, polydipsia) or no symptoms. Clinically, LAH differs from primary hyperparathyroidism, though the management protocol of these 2 conditions is almost the same. In this article, we discuss how lithium can affect calcium and parathyroid hormone (PTH) levels and how LAH and lithium-associated hyperparathyroidism (LAHP) differs from primary hyperparathyroidism. We also outline a suggested approach to monitoring and management.

An insidious problem

Due to the varying definitions and methods used to assess hypercalcemia, the reported prevalence of LAH varies from 4.3% to 80%.¹ McKnight et al² conducted a systematic review and meta-analysis of studies of the relationship between lithium and parathyroid function that included 14 case-control studies, 36 case reports, and 6 cross-sectional studies without a control group. They found that the levels of calcium and PTH were 10% higher in lithium-treated patients than in controls.²

Pathophysiology. Lithium is known to increase both calcium and PTH levels. PTH is responsible for calcium homeostasis. It is secreted in response to low calcium levels, which it increases by its action on bones, intestines, and kidneys. Vitamin D also plays a crucial role in calcium homeostasis. A deficiency of vitamin D triggers a compensatory increase in PTH to maintain calcium levels.³

Calcium and PTH levels increase soon after administration of lithium, but the rise is usually mild and insidious. In a small proportion of patients who receive long-term lithium treatment, calcium levels can exceed the normal range. Patients who develop LAH typically have serum calcium levels slightly above the normal range and PTH levels ranging from the higher side of the normal range to several times the upper limit of the normal range. Patients might also experience elevated PTH levels without any increase in calcium levels. Lithium can affect calcium and PTH levels in multiple ways. For instance, it increases the reabsorption of calcium in the kidney as well as the reset point of calcium-sensing receptors. Therefore, only higher levels of calcium can inhibit the release of PTH. Hence, in cases where the PTH level is within the normal range, it is generally higher than would be expected for a given serum calcium level. Lithium can also directly affect the parathyroid glands and can lead to either single-nodule or multimodule hyperplasia.⁴

Long-term lithium use can cause chronic kidney disease (CKD), which in turn leads to vitamin D deficiency and hyperparathyroidism. However, secondary hyperparathyroidism with CKD is usually seen in the more advanced stages of CKD, and is associated with low-to-normal calcium levels (as opposed to the high levels seen in LAH).^3-5

Lithium-associated hyperparathyroidism

Primary hyperparathyroidism is the most common cause of hypercalcemia. Its prevalence ranges from 1 to 7 cases per 1,000 adults. The incidence of LAH/LAHP is 4- to 6-fold higher compared to the general population.⁶ Similar to LAH/LAHP, primary hyperparathyroidism is more common in older adults (age >60) and females. Hence, some researchers have suggested that lithium probably unmasks hyperparathyroidism in patients who are susceptible to primary hyperparathyroidism.³

Look for these clinical manifestations

Symptoms of primary hyperparathyroidism are related to high calcium and PTH levels. They are commonly described as “painful bones, renal stones, abdominal groans (due to hypercalcemia-induced ileus), and psychic moans (lethargy, poor concentration, depression).” Common adverse outcomes associated with primary hyperparathyroidism are renal stones, high risk of fracture, constipation, peptic ulcer, and pancreatitis.^3,7

Continue: In contrast...

In contrast, LAHP is characterized by mild, intermittent, and/or persistent hypercalcemia and mildly increased PTH (Table 1).^1,3,4 In some patients, it could improve without active intervention. Because lithium increases the absorption of urinary calcium, it is associated with hypocalciuria and a lower risk of renal stones. Additionally, lithium has osteoprotective effects and has not been associated with an increased risk of fracture. Some researchers have suggested that the presentation of LAHP is more like familial hypocalciuric hypercalcemia (FHC), which is also associated with hypocalciuria. FHC is a benign condition and does not require active intervention.^3,4 Similar to those with FHC, many patients with LAHP may live with chronic asymptomatic hypercalcemia without any significant adverse outcome.

A suggested approach to monitoring

In most cases, LAH is an insidious adverse effect that is usually detected on blood tests after many years of lithium therapy.⁸ For patients starting lithium therapy, International Society of Bipolar Disorder guidelines recommend testing calcium levels at baseline, 6 months, and annually thereafter, or as clinically indicated, to detect and monitor hypercalcemia and hyperparathyroidism. However, these guidelines do not provide any recommendations regarding how to manage abnormal findings.⁹

Clinical laboratories report both total and adjusted calcium values. The adjusted calcium value takes into account albumin levels. This is a way to compensate for an abnormal concentration of albumin (establishing what a patient’s total calcium concentration would be if the albumin concentration was normal). Table 2⁵ shows the categorization of adjusted calcium values.For patients receiving lithium, some researchers have suggested monitoring PTH as well as calcium.¹

The Figure outlines our proposed approach to monitoring for LAH in patients receiving lithium. An isolated high value of calcium could be due to prolonged venous stasis if a tourniquet is used for phlebotomy. In such instances, the calcium level should be tested again without a tourniquet.¹⁰ If the repeat blood test shows elevated calcium levels, then both PTH and serum calcium should be tested.

If the PTH level is higher than the midpoint of the reference range, LAH should be suspected, though sometimes hypercalcemia can present without raised PTH. LAH has also been reported to cause a transient increase in calcium levels. If hypercalcemia frequently recurs, PTH levels should be monitored. If PTH is suppressed, then the raised calcium levels are probably secondary to something other than lithium; common reasons for this include the use of vitamin D supplements or thiazide diuretics, or malignancies such as multiple myeloma.^3,5,8

Continue to: Treatment

There are several options for treating LAH. Lithium may be continued or discontinued following close monitoring of calcium and PTH levels, with or without active interventions such as surgery or pharmacotherapy, and as deemed appropriate after consultation with an endocrinologist. The decision should be informed by evaluating the risks and benefits to the patient’s physical and mental health. LAH can be reversed by discontinuing lithium, but this might not be the case in patients receiving long-term lithium therapy, especially if their elevated calcium levels are associated with parathyroid adenomas or hyperplasia. Hence, close monitoring of calcium and PTH is required even after discontinuing lithium.^3,8

Surgical treatment. The primary treatment of LAH and primary hyperparathyroidism is parathyroidectomy. The possibility of recovery after parathyroidectomy for primary hyperparathyroidism is 60% to 80%, though a small proportion of patients might experience recurrence. This figure might be higher for LAH, because it is more likely to affect multiple glands.^1,11 Other potential complications of parathyroidectomy are recurrent laryngeal nerve injury causing paralysis of vocal cords leading to hoarseness of voice, stridor, or aspiration, and local hematoma and hypocalcemia (requiring vitamin D and/or calcium supplements).¹²

Pharmacotherapy. Cinacalcet is a calcimimetic drug that decreases the reset point of the calcium-sensing receptor. It can be used if a patient is not suitable for or apprehensive about surgical intervention.^1,8

Bottom Line

Calcium levels should be regularly monitored in patients receiving lithium. If calcium levels are persistently high, parathyroid hormone levels should also be measured. Management of lithium-associated hypercalcemia includes watchful waiting, discontinuing lithium, parathyroidectomy, and pharmacotherapy with cinacalcet.

Related Resources

• Laski M, Foreman R, Hancock H, et al. Lithium: an underutilized element. Current Psychiatry. 2021;20(12):27-30,34. doi:10.12788/cp.0193
• Pelekanos M, Foo K. A resident’s guide to lithium. Current Psychiatry. 2021;20(4):e3-e7. doi:10.12788/cp.0113

Drug Brand Names

Cinacalcet • Sensipar

Much of the focus of reproductive psychiatry over the last 1 to 2 decades has been on issues regarding risk of fetal exposure to psychiatric medications in the context of the specific risk for teratogenesis or organ malformation. Concerns and questions are mostly focused on exposure to any number of medications that women take during the first trimester, as it is during that period that the major organs are formed.

More recently, there has been appropriate interest in the effect of fetal exposure to psychiatric medications with respect to risk for obstetrical and neonatal complications. This particularly has been the case with respect to antidepressants where fetal exposure to these medications, which while associated with symptoms of transient jitteriness and irritability about 20% of the time, have not been associated with symptoms requiring frank clinical intervention.

Concerning mood stabilizers, the risk for organ dysgenesis following fetal exposure to sodium valproate has been very well established, and we’ve known for over a decade about the adverse effects of fetal exposure to sodium valproate on behavioral outcomes (Lancet Neurol. 2013 Mar;12[3]:244-52). We also now have ample data on lamotrigine, one of the most widely used medicines by reproductive-age women for treatment of bipolar disorder that supports the absence of a risk of organ malformation in first-trimester exposure.

Most recently, in a study of 292 children of women with epilepsy, an evaluation of women being treated with more modern anticonvulsants such as lamotrigine and levetiracetam alone or as polytherapy was performed. The results showed no difference in language, motor, cognitive, social, emotional, and general adaptive functioning in children exposed to either lamotrigine or levetiracetam relative to unexposed children of women with epilepsy. However, the researchers found an increase in anti-epileptic drug plasma level appeared to be associated with decreased motor and sensory function. These are reassuring data that really confirm earlier work, which failed to reveal a signal of concern for lamotrigine and now provide some of the first data on levetiracetam, which is widely used by reproductive-age women with epilepsy (JAMA Neurol. 2021 Aug 1;78[8]:927-936). While one caveat of the study is a short follow-up of 2 years, the absence of a signal of concern is reassuring. With more and more data demonstrating bipolar disorder is an illness that requires chronic treatment for many people, and that discontinuation is associated with high risk for relapse, it is an advance in the field to have data on risk for teratogenesis and data on longer-term neurobehavioral outcomes.

There is vast information regarding reproductive safety, organ malformation, and acute neonatal outcomes for antidepressants. The last decade has brought interest in and analysis of specific reports of increased risk of both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) following fetal exposure to antidepressants. What can be said based on reviews of pooled meta-analyses is that the risk for ASD and ADHD has been put to rest for most clinicians and patients (J Clin Psychiatry. 2020 May 26;81[3]:20f13463). With other neurodevelopmental disorders, results have been somewhat inconclusive. Over the last 5-10 years, there have been sporadic reports of concerns about problems in a specific domain of neurodevelopment in offspring of women who have used antidepressants during pregnancy, whether it be speech, language, or motor functioning, but no signal of concern has been consistent.

In a previous column, I addressed a Danish study that showed no increased risk of longer-term sequelae after fetal exposure to antidepressants. Now, a new study has examined 1.93 million pregnancies in the Medicaid Analytic eXtract and 1.25 million pregnancies in the IBM MarketScan Research Database with follow-up up to 14 years of age where the specific interval for fetal exposure was from gestational age of 19 weeks to delivery, as that is the period that corresponds most to synaptogenesis in the brain. The researchers examined a spectrum of neurodevelopmental disorders such as developmental speech issues, ADHD, ASD, dyslexia, and learning disorders, among others. They found a twofold increased risk for neurodevelopmental disorders in the unadjusted models that flattened to no finding when factoring in environmental and genetic risk variables, highlighting the importance of dealing appropriately with confounders when performing these analyses. Those confounders examined include the mother’s use of alcohol and tobacco, and her body mass index and overall general health (JAMA Intern Med. 2022;182[11]:1149-60).

Given the consistency of these results with earlier data, patients can be increasingly comfortable as they weigh the benefits and risks of antidepressant use during pregnancy, factoring in the risk of fetal exposure with added data on long-term neurobehavioral sequelae. With that said, we need to remember the importance of initiatives to address alcohol consumption, poor nutrition, tobacco use, elevated BMI, and general health during pregnancy. These are modifiable risks that we as clinicians should focus on in order to optimize outcomes during pregnancy.

We have come so far in knowledge about fetal exposure to antidepressants relative to other classes of medications women take during pregnancy, about which, frankly, we are still starved for data. As use of psychiatric medications during pregnancy continues to grow, we can rest a bit more comfortably. But we should also address some of the other behaviors that have adverse effects on maternal and child well-being.

Dr. Cohen is the director of the Ammon-Pinizzotto Center for Women’s Mental Health at Massachusetts General Hospital (MGH) in Boston, which provides information resources and conducts clinical care and research in reproductive mental health. He has been a consultant to manufacturers of psychiatric medications. Email Dr. Cohen at [email protected].

Much of the focus of reproductive psychiatry over the last 1 to 2 decades has been on issues regarding risk of fetal exposure to psychiatric medications in the context of the specific risk for teratogenesis or organ malformation. Concerns and questions are mostly focused on exposure to any number of medications that women take during the first trimester, as it is during that period that the major organs are formed.

More recently, there has been appropriate interest in the effect of fetal exposure to psychiatric medications with respect to risk for obstetrical and neonatal complications. This particularly has been the case with respect to antidepressants where fetal exposure to these medications, which while associated with symptoms of transient jitteriness and irritability about 20% of the time, have not been associated with symptoms requiring frank clinical intervention.

Concerning mood stabilizers, the risk for organ dysgenesis following fetal exposure to sodium valproate has been very well established, and we’ve known for over a decade about the adverse effects of fetal exposure to sodium valproate on behavioral outcomes (Lancet Neurol. 2013 Mar;12[3]:244-52). We also now have ample data on lamotrigine, one of the most widely used medicines by reproductive-age women for treatment of bipolar disorder that supports the absence of a risk of organ malformation in first-trimester exposure.

Most recently, in a study of 292 children of women with epilepsy, an evaluation of women being treated with more modern anticonvulsants such as lamotrigine and levetiracetam alone or as polytherapy was performed. The results showed no difference in language, motor, cognitive, social, emotional, and general adaptive functioning in children exposed to either lamotrigine or levetiracetam relative to unexposed children of women with epilepsy. However, the researchers found an increase in anti-epileptic drug plasma level appeared to be associated with decreased motor and sensory function. These are reassuring data that really confirm earlier work, which failed to reveal a signal of concern for lamotrigine and now provide some of the first data on levetiracetam, which is widely used by reproductive-age women with epilepsy (JAMA Neurol. 2021 Aug 1;78[8]:927-936). While one caveat of the study is a short follow-up of 2 years, the absence of a signal of concern is reassuring. With more and more data demonstrating bipolar disorder is an illness that requires chronic treatment for many people, and that discontinuation is associated with high risk for relapse, it is an advance in the field to have data on risk for teratogenesis and data on longer-term neurobehavioral outcomes.

There is vast information regarding reproductive safety, organ malformation, and acute neonatal outcomes for antidepressants. The last decade has brought interest in and analysis of specific reports of increased risk of both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) following fetal exposure to antidepressants. What can be said based on reviews of pooled meta-analyses is that the risk for ASD and ADHD has been put to rest for most clinicians and patients (J Clin Psychiatry. 2020 May 26;81[3]:20f13463). With other neurodevelopmental disorders, results have been somewhat inconclusive. Over the last 5-10 years, there have been sporadic reports of concerns about problems in a specific domain of neurodevelopment in offspring of women who have used antidepressants during pregnancy, whether it be speech, language, or motor functioning, but no signal of concern has been consistent.

In a previous column, I addressed a Danish study that showed no increased risk of longer-term sequelae after fetal exposure to antidepressants. Now, a new study has examined 1.93 million pregnancies in the Medicaid Analytic eXtract and 1.25 million pregnancies in the IBM MarketScan Research Database with follow-up up to 14 years of age where the specific interval for fetal exposure was from gestational age of 19 weeks to delivery, as that is the period that corresponds most to synaptogenesis in the brain. The researchers examined a spectrum of neurodevelopmental disorders such as developmental speech issues, ADHD, ASD, dyslexia, and learning disorders, among others. They found a twofold increased risk for neurodevelopmental disorders in the unadjusted models that flattened to no finding when factoring in environmental and genetic risk variables, highlighting the importance of dealing appropriately with confounders when performing these analyses. Those confounders examined include the mother’s use of alcohol and tobacco, and her body mass index and overall general health (JAMA Intern Med. 2022;182[11]:1149-60).

Given the consistency of these results with earlier data, patients can be increasingly comfortable as they weigh the benefits and risks of antidepressant use during pregnancy, factoring in the risk of fetal exposure with added data on long-term neurobehavioral sequelae. With that said, we need to remember the importance of initiatives to address alcohol consumption, poor nutrition, tobacco use, elevated BMI, and general health during pregnancy. These are modifiable risks that we as clinicians should focus on in order to optimize outcomes during pregnancy.

We have come so far in knowledge about fetal exposure to antidepressants relative to other classes of medications women take during pregnancy, about which, frankly, we are still starved for data. As use of psychiatric medications during pregnancy continues to grow, we can rest a bit more comfortably. But we should also address some of the other behaviors that have adverse effects on maternal and child well-being.

Dr. Cohen is the director of the Ammon-Pinizzotto Center for Women’s Mental Health at Massachusetts General Hospital (MGH) in Boston, which provides information resources and conducts clinical care and research in reproductive mental health. He has been a consultant to manufacturers of psychiatric medications. Email Dr. Cohen at [email protected].

Much of the focus of reproductive psychiatry over the last 1 to 2 decades has been on issues regarding risk of fetal exposure to psychiatric medications in the context of the specific risk for teratogenesis or organ malformation. Concerns and questions are mostly focused on exposure to any number of medications that women take during the first trimester, as it is during that period that the major organs are formed.

More recently, there has been appropriate interest in the effect of fetal exposure to psychiatric medications with respect to risk for obstetrical and neonatal complications. This particularly has been the case with respect to antidepressants where fetal exposure to these medications, which while associated with symptoms of transient jitteriness and irritability about 20% of the time, have not been associated with symptoms requiring frank clinical intervention.

Concerning mood stabilizers, the risk for organ dysgenesis following fetal exposure to sodium valproate has been very well established, and we’ve known for over a decade about the adverse effects of fetal exposure to sodium valproate on behavioral outcomes (Lancet Neurol. 2013 Mar;12[3]:244-52). We also now have ample data on lamotrigine, one of the most widely used medicines by reproductive-age women for treatment of bipolar disorder that supports the absence of a risk of organ malformation in first-trimester exposure.

Most recently, in a study of 292 children of women with epilepsy, an evaluation of women being treated with more modern anticonvulsants such as lamotrigine and levetiracetam alone or as polytherapy was performed. The results showed no difference in language, motor, cognitive, social, emotional, and general adaptive functioning in children exposed to either lamotrigine or levetiracetam relative to unexposed children of women with epilepsy. However, the researchers found an increase in anti-epileptic drug plasma level appeared to be associated with decreased motor and sensory function. These are reassuring data that really confirm earlier work, which failed to reveal a signal of concern for lamotrigine and now provide some of the first data on levetiracetam, which is widely used by reproductive-age women with epilepsy (JAMA Neurol. 2021 Aug 1;78[8]:927-936). While one caveat of the study is a short follow-up of 2 years, the absence of a signal of concern is reassuring. With more and more data demonstrating bipolar disorder is an illness that requires chronic treatment for many people, and that discontinuation is associated with high risk for relapse, it is an advance in the field to have data on risk for teratogenesis and data on longer-term neurobehavioral outcomes.

There is vast information regarding reproductive safety, organ malformation, and acute neonatal outcomes for antidepressants. The last decade has brought interest in and analysis of specific reports of increased risk of both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) following fetal exposure to antidepressants. What can be said based on reviews of pooled meta-analyses is that the risk for ASD and ADHD has been put to rest for most clinicians and patients (J Clin Psychiatry. 2020 May 26;81[3]:20f13463). With other neurodevelopmental disorders, results have been somewhat inconclusive. Over the last 5-10 years, there have been sporadic reports of concerns about problems in a specific domain of neurodevelopment in offspring of women who have used antidepressants during pregnancy, whether it be speech, language, or motor functioning, but no signal of concern has been consistent.

In a previous column, I addressed a Danish study that showed no increased risk of longer-term sequelae after fetal exposure to antidepressants. Now, a new study has examined 1.93 million pregnancies in the Medicaid Analytic eXtract and 1.25 million pregnancies in the IBM MarketScan Research Database with follow-up up to 14 years of age where the specific interval for fetal exposure was from gestational age of 19 weeks to delivery, as that is the period that corresponds most to synaptogenesis in the brain. The researchers examined a spectrum of neurodevelopmental disorders such as developmental speech issues, ADHD, ASD, dyslexia, and learning disorders, among others. They found a twofold increased risk for neurodevelopmental disorders in the unadjusted models that flattened to no finding when factoring in environmental and genetic risk variables, highlighting the importance of dealing appropriately with confounders when performing these analyses. Those confounders examined include the mother’s use of alcohol and tobacco, and her body mass index and overall general health (JAMA Intern Med. 2022;182[11]:1149-60).

Given the consistency of these results with earlier data, patients can be increasingly comfortable as they weigh the benefits and risks of antidepressant use during pregnancy, factoring in the risk of fetal exposure with added data on long-term neurobehavioral sequelae. With that said, we need to remember the importance of initiatives to address alcohol consumption, poor nutrition, tobacco use, elevated BMI, and general health during pregnancy. These are modifiable risks that we as clinicians should focus on in order to optimize outcomes during pregnancy.

We have come so far in knowledge about fetal exposure to antidepressants relative to other classes of medications women take during pregnancy, about which, frankly, we are still starved for data. As use of psychiatric medications during pregnancy continues to grow, we can rest a bit more comfortably. But we should also address some of the other behaviors that have adverse effects on maternal and child well-being.

Dr. Cohen is the director of the Ammon-Pinizzotto Center for Women’s Mental Health at Massachusetts General Hospital (MGH) in Boston, which provides information resources and conducts clinical care and research in reproductive mental health. He has been a consultant to manufacturers of psychiatric medications. Email Dr. Cohen at [email protected].

A machine-learning risk model that incorporates childhood characteristics can predict development of bipolar disorder up to a decade later, according to investigators.

This is the first quantitative approach to predict bipolar disorder, offering sensitivity and specificity of 75% and 76%, respectively, reported lead author Mai Uchida, MD, director of the pediatric depression program at Massachusetts General Hospital and assistant professor of psychiatry at Harvard Medical School, Boston, and colleagues. With further development, the model could be used to identify at-risk children via electronic medical records, enabling earlier monitoring and intervention.

“Although longitudinal studies have found the prognosis of early-onset mood disorders to be unfavorable, research has also shown there are effective treatments and therapies that could significantly alleviate the patients’ and their families’ struggles from the diagnoses,” the investigators wrote in the Journal of Psychiatric Research. “Thus, early identification of the risks and interventions for early symptoms of pediatric mood disorders is crucial.”

To this end, Dr. Uchida and colleagues teamed up with the Gabrieli Lab at MIT, who have published extensively in the realm of neurodevelopment. They sourced data from 492 children, 6-18 years at baseline, who were involved in two longitudinal case-control family studies focused on ADHD. Inputs included psychometric scales, structured diagnostic interviews, social and cognitive functioning assessments, and sociodemographic data.

At 10-year follow-up, 10% of these children had developed bipolar disorder, a notably higher rate than the 3%-4% prevalence in the general population.

“This is a population that’s overrepresented,” Dr. Uchida said in an interview.

She offered two primary reasons for this: First, the families involved in the study were probably willing to be followed for 10 years because they had ongoing concerns about their child’s mental health. Second, the studies enrolled children diagnosed with ADHD, a condition associated with increased risk of bipolar disorder.

Using machine learning algorithms that processed the baseline data while accounting for the skewed distribution, the investigators were able to predict which of the children in the population would go on to develop bipolar disorder. The final model offered a sensitivity of 75%, a specificity of 76%, and an area under the receiver operating characteristic curve of 75%.

“To the best of our knowledge, this represents the first study using machine-learning algorithms for this purpose in pediatric psychiatry,” the investigators wrote.
 

Integrating models into electronic medical records

In the future, this model, or one like it, could be incorporated into software that automatically analyzes electronic medical records and notifies physicians about high-risk patients, Dr. Uchida predicted.

“Not all patients would connect to intervention,” she said. “Maybe it just means that you invite them in for a visit, or you observe them a little bit more carefully. I think that’s where we are hoping that machine learning and medical practice will go.”

When asked about the potential bias posed by psychiatric evaluation, compared with something like blood work results, Dr. Uchida suggested that this subjectivity can be overcome.

“I’m not entirely bothered by that,” she said, offering a list of objective data points that could be harvested from records, such as number of referrals, medications, and hospitalizations. Narrative text in medical records could also be analyzed, she said, potentially detecting key words that are more often associated with high-risk patients.

“Risk prediction is never going to be 100% accurate,” Dr. Uchida said. “But I do think that there will be things [in electronic medical records] that could guide how worried we should be, or how quickly we should intervene.”
 

Opening doors to personalized care

Martin Gignac, MD, chief of psychiatry at Montreal Children’s Hospital and associate professor at McGill University, Montreal, said the present study offers further support for the existence of pediatric-onset bipolar disorder, which “remains controversial” despite “solid evidence.”

“I’m impressed that we have 10-year-long longitudinal follow-up studies that corroborate the importance of this disorder, and show strong predictors of who is at risk,” Dr. Gignac said in an interview. “Clinicians treating a pediatric population should be aware that some of those children with mental health problems might have severe mental health problems, and you have to have the appropriate tools to screen them.”

Advanced tools like the one developed by Dr. Uchida and colleagues should lead to more personalized care, he said.

“We’re going to be able to define what your individual risk is, and maybe most importantly, what you can do to prevent the development of certain disorders,” Dr. Gignac said. “Are there any risks that are dynamic in nature, and that we can act upon? Exposure to stress, for example.”

While more work is needed to bring machine learning into daily psychiatric practice, Dr. Gignac concluded on an optimistic note.

“These instruments should translate from research into clinical practice in order to make difference for the patients we care for,” he said. “This is the type of hope that I hold – that it’s going to be applicable in clinical practice, hopefully, in the near future.”

The investigators disclosed relationships with InCarda, Baylis Medical, Johnson & Johnson, and others. Dr. Gignac disclosed no relevant competing interests.

A machine-learning risk model that incorporates childhood characteristics can predict development of bipolar disorder up to a decade later, according to investigators.

This is the first quantitative approach to predict bipolar disorder, offering sensitivity and specificity of 75% and 76%, respectively, reported lead author Mai Uchida, MD, director of the pediatric depression program at Massachusetts General Hospital and assistant professor of psychiatry at Harvard Medical School, Boston, and colleagues. With further development, the model could be used to identify at-risk children via electronic medical records, enabling earlier monitoring and intervention.

“Although longitudinal studies have found the prognosis of early-onset mood disorders to be unfavorable, research has also shown there are effective treatments and therapies that could significantly alleviate the patients’ and their families’ struggles from the diagnoses,” the investigators wrote in the Journal of Psychiatric Research. “Thus, early identification of the risks and interventions for early symptoms of pediatric mood disorders is crucial.”

To this end, Dr. Uchida and colleagues teamed up with the Gabrieli Lab at MIT, who have published extensively in the realm of neurodevelopment. They sourced data from 492 children, 6-18 years at baseline, who were involved in two longitudinal case-control family studies focused on ADHD. Inputs included psychometric scales, structured diagnostic interviews, social and cognitive functioning assessments, and sociodemographic data.

At 10-year follow-up, 10% of these children had developed bipolar disorder, a notably higher rate than the 3%-4% prevalence in the general population.

“This is a population that’s overrepresented,” Dr. Uchida said in an interview.

She offered two primary reasons for this: First, the families involved in the study were probably willing to be followed for 10 years because they had ongoing concerns about their child’s mental health. Second, the studies enrolled children diagnosed with ADHD, a condition associated with increased risk of bipolar disorder.

Using machine learning algorithms that processed the baseline data while accounting for the skewed distribution, the investigators were able to predict which of the children in the population would go on to develop bipolar disorder. The final model offered a sensitivity of 75%, a specificity of 76%, and an area under the receiver operating characteristic curve of 75%.

“To the best of our knowledge, this represents the first study using machine-learning algorithms for this purpose in pediatric psychiatry,” the investigators wrote.
 

Integrating models into electronic medical records

In the future, this model, or one like it, could be incorporated into software that automatically analyzes electronic medical records and notifies physicians about high-risk patients, Dr. Uchida predicted.

“Not all patients would connect to intervention,” she said. “Maybe it just means that you invite them in for a visit, or you observe them a little bit more carefully. I think that’s where we are hoping that machine learning and medical practice will go.”

When asked about the potential bias posed by psychiatric evaluation, compared with something like blood work results, Dr. Uchida suggested that this subjectivity can be overcome.

“I’m not entirely bothered by that,” she said, offering a list of objective data points that could be harvested from records, such as number of referrals, medications, and hospitalizations. Narrative text in medical records could also be analyzed, she said, potentially detecting key words that are more often associated with high-risk patients.

“Risk prediction is never going to be 100% accurate,” Dr. Uchida said. “But I do think that there will be things [in electronic medical records] that could guide how worried we should be, or how quickly we should intervene.”
 

Opening doors to personalized care

Martin Gignac, MD, chief of psychiatry at Montreal Children’s Hospital and associate professor at McGill University, Montreal, said the present study offers further support for the existence of pediatric-onset bipolar disorder, which “remains controversial” despite “solid evidence.”

“I’m impressed that we have 10-year-long longitudinal follow-up studies that corroborate the importance of this disorder, and show strong predictors of who is at risk,” Dr. Gignac said in an interview. “Clinicians treating a pediatric population should be aware that some of those children with mental health problems might have severe mental health problems, and you have to have the appropriate tools to screen them.”

Advanced tools like the one developed by Dr. Uchida and colleagues should lead to more personalized care, he said.

“We’re going to be able to define what your individual risk is, and maybe most importantly, what you can do to prevent the development of certain disorders,” Dr. Gignac said. “Are there any risks that are dynamic in nature, and that we can act upon? Exposure to stress, for example.”

While more work is needed to bring machine learning into daily psychiatric practice, Dr. Gignac concluded on an optimistic note.

“These instruments should translate from research into clinical practice in order to make difference for the patients we care for,” he said. “This is the type of hope that I hold – that it’s going to be applicable in clinical practice, hopefully, in the near future.”

The investigators disclosed relationships with InCarda, Baylis Medical, Johnson & Johnson, and others. Dr. Gignac disclosed no relevant competing interests.

A machine-learning risk model that incorporates childhood characteristics can predict development of bipolar disorder up to a decade later, according to investigators.

This is the first quantitative approach to predict bipolar disorder, offering sensitivity and specificity of 75% and 76%, respectively, reported lead author Mai Uchida, MD, director of the pediatric depression program at Massachusetts General Hospital and assistant professor of psychiatry at Harvard Medical School, Boston, and colleagues. With further development, the model could be used to identify at-risk children via electronic medical records, enabling earlier monitoring and intervention.

“Although longitudinal studies have found the prognosis of early-onset mood disorders to be unfavorable, research has also shown there are effective treatments and therapies that could significantly alleviate the patients’ and their families’ struggles from the diagnoses,” the investigators wrote in the Journal of Psychiatric Research. “Thus, early identification of the risks and interventions for early symptoms of pediatric mood disorders is crucial.”

To this end, Dr. Uchida and colleagues teamed up with the Gabrieli Lab at MIT, who have published extensively in the realm of neurodevelopment. They sourced data from 492 children, 6-18 years at baseline, who were involved in two longitudinal case-control family studies focused on ADHD. Inputs included psychometric scales, structured diagnostic interviews, social and cognitive functioning assessments, and sociodemographic data.

At 10-year follow-up, 10% of these children had developed bipolar disorder, a notably higher rate than the 3%-4% prevalence in the general population.

“This is a population that’s overrepresented,” Dr. Uchida said in an interview.

She offered two primary reasons for this: First, the families involved in the study were probably willing to be followed for 10 years because they had ongoing concerns about their child’s mental health. Second, the studies enrolled children diagnosed with ADHD, a condition associated with increased risk of bipolar disorder.

Using machine learning algorithms that processed the baseline data while accounting for the skewed distribution, the investigators were able to predict which of the children in the population would go on to develop bipolar disorder. The final model offered a sensitivity of 75%, a specificity of 76%, and an area under the receiver operating characteristic curve of 75%.

“To the best of our knowledge, this represents the first study using machine-learning algorithms for this purpose in pediatric psychiatry,” the investigators wrote.
 

Integrating models into electronic medical records

In the future, this model, or one like it, could be incorporated into software that automatically analyzes electronic medical records and notifies physicians about high-risk patients, Dr. Uchida predicted.

“Not all patients would connect to intervention,” she said. “Maybe it just means that you invite them in for a visit, or you observe them a little bit more carefully. I think that’s where we are hoping that machine learning and medical practice will go.”

When asked about the potential bias posed by psychiatric evaluation, compared with something like blood work results, Dr. Uchida suggested that this subjectivity can be overcome.

“I’m not entirely bothered by that,” she said, offering a list of objective data points that could be harvested from records, such as number of referrals, medications, and hospitalizations. Narrative text in medical records could also be analyzed, she said, potentially detecting key words that are more often associated with high-risk patients.

“Risk prediction is never going to be 100% accurate,” Dr. Uchida said. “But I do think that there will be things [in electronic medical records] that could guide how worried we should be, or how quickly we should intervene.”
 

Opening doors to personalized care

Martin Gignac, MD, chief of psychiatry at Montreal Children’s Hospital and associate professor at McGill University, Montreal, said the present study offers further support for the existence of pediatric-onset bipolar disorder, which “remains controversial” despite “solid evidence.”

“I’m impressed that we have 10-year-long longitudinal follow-up studies that corroborate the importance of this disorder, and show strong predictors of who is at risk,” Dr. Gignac said in an interview. “Clinicians treating a pediatric population should be aware that some of those children with mental health problems might have severe mental health problems, and you have to have the appropriate tools to screen them.”

Advanced tools like the one developed by Dr. Uchida and colleagues should lead to more personalized care, he said.

“We’re going to be able to define what your individual risk is, and maybe most importantly, what you can do to prevent the development of certain disorders,” Dr. Gignac said. “Are there any risks that are dynamic in nature, and that we can act upon? Exposure to stress, for example.”

While more work is needed to bring machine learning into daily psychiatric practice, Dr. Gignac concluded on an optimistic note.

“These instruments should translate from research into clinical practice in order to make difference for the patients we care for,” he said. “This is the type of hope that I hold – that it’s going to be applicable in clinical practice, hopefully, in the near future.”

The investigators disclosed relationships with InCarda, Baylis Medical, Johnson & Johnson, and others. Dr. Gignac disclosed no relevant competing interests.

In reading Dr. Nasrallah's August 2022 editorial (“Reversing depression: A plethora of therapeutic strategies and mechanisms,” Current Psychiatry, August 2022, p. 4-6), I was curious why he did not mention lamotrigine as an adjunctive therapy for bipolar depression. Was that an editing error, or an important statement about the questionable value of that drug for current, ongoing bipolar depression?

Dr. Nasrallah responds

Thanks for your message. Lamotrigine is not FDA-approved for bipolar or unipolar depression, either as monotherapy or as an adjunctive therapy. It has never been approved for mania, either (no efficacy at all). Its only FDA-approved psychiatric indication is maintenance therapy after a patient with bipolar I disorder emerges from mania with the help of one of the antimanic drugs. Yet many clinicians may perceive lamotrigine as useful for bipolar depression because more than 20 years ago the manufacturer sponsored several small studies (not FDA trials). Two studies that showed efficacy were published, but 4 other studies that failed to show efficacy were not published. As a result, many clinicians got the false impression that lamotrigine is an effective antidepressant. I hope this explains why lamotrigine was not included in the list of antidepressants in my editorial.

In reading Dr. Nasrallah's August 2022 editorial (“Reversing depression: A plethora of therapeutic strategies and mechanisms,” Current Psychiatry, August 2022, p. 4-6), I was curious why he did not mention lamotrigine as an adjunctive therapy for bipolar depression. Was that an editing error, or an important statement about the questionable value of that drug for current, ongoing bipolar depression?

Dr. Nasrallah responds

Thanks for your message. Lamotrigine is not FDA-approved for bipolar or unipolar depression, either as monotherapy or as an adjunctive therapy. It has never been approved for mania, either (no efficacy at all). Its only FDA-approved psychiatric indication is maintenance therapy after a patient with bipolar I disorder emerges from mania with the help of one of the antimanic drugs. Yet many clinicians may perceive lamotrigine as useful for bipolar depression because more than 20 years ago the manufacturer sponsored several small studies (not FDA trials). Two studies that showed efficacy were published, but 4 other studies that failed to show efficacy were not published. As a result, many clinicians got the false impression that lamotrigine is an effective antidepressant. I hope this explains why lamotrigine was not included in the list of antidepressants in my editorial.

In reading Dr. Nasrallah's August 2022 editorial (“Reversing depression: A plethora of therapeutic strategies and mechanisms,” Current Psychiatry, August 2022, p. 4-6), I was curious why he did not mention lamotrigine as an adjunctive therapy for bipolar depression. Was that an editing error, or an important statement about the questionable value of that drug for current, ongoing bipolar depression?

Dr. Nasrallah responds

Thanks for your message. Lamotrigine is not FDA-approved for bipolar or unipolar depression, either as monotherapy or as an adjunctive therapy. It has never been approved for mania, either (no efficacy at all). Its only FDA-approved psychiatric indication is maintenance therapy after a patient with bipolar I disorder emerges from mania with the help of one of the antimanic drugs. Yet many clinicians may perceive lamotrigine as useful for bipolar depression because more than 20 years ago the manufacturer sponsored several small studies (not FDA trials). Two studies that showed efficacy were published, but 4 other studies that failed to show efficacy were not published. As a result, many clinicians got the false impression that lamotrigine is an effective antidepressant. I hope this explains why lamotrigine was not included in the list of antidepressants in my editorial.