Guo JJ, Keck PE Jr, Corey-Lisle PK, et al. Risk of diabetes mellitus associated with atypical antipsychotic use among patients with bipolar disorder: a retrospective, population-based, case-control study
Drug-induced diabetes onset has not been adequately quantified in patients with bipolar disorder, although atypical antipsychotics have been widely used as new mood stabilizers.
To quantify the association between atypical antipsychotics and diabetes mellitus.
A retrospective, population-based, case-control study was conducted using the medical claims database from U.S. managed care organizations from January 1, 1998, to December 31, 2002. Nine hundred twenty incident cases of diabetes were matched with 5258 controls by age, sex, and bipolar index month and year. Diabetes cases were identified by either diagnosis of ICD-9 codes or diabetic medications. Patients with diabetes had a minimum 3-month exposure to any medications or at least 3 prescriptions for their bipolar or comorbidity treatment. Cox proportional hazard regression was conducted to assess the risk of diabetes associated with antipsychotic use.
Of 920 cases, 41% received atypical antipsychotics (e.g., olanzapine, risperidone, quetiapine, ziprasidone, clozapine) and 34% received conventional antipsychotics. Compared to patients receiving conventional antipsychotics, the risk of diabetes was greatest among patients taking clozapine (hazard ratio [HR] = 7.0, 95% confidence interval [CI] = 1.7 to 28.9), risperidone (HR = 3.4, 95% CI = 2.8 to 4.2), olanzapine (HR = 3.2, 95% CI = 2.7 to 3.8), and quetiapine (HR = 1.8, 95% CI =1.4 to 2.4), with controlling covariates of age; sex; duration of follow-up; use of lithium, anticonvulsants, antidepressants, or concomitant drugs; and psychiatric and medical comorbidities.
Development or exacerbation of diabetes mellitus is associated with antipsychotic use in bipolar patients. Metabolic complications are a major issue in patients receiving antipsychotic therapy. Thus, the propensity of an antipsychotic to induce diabetes should be a consideration when selecting an agent for patients with bipolar disorder.
"In addition, there are several risks associated with antipsychotic medications. For example, the dosage for treatment of insomnia has been unpredictable, the risk of side effects is high, and the results of these agents may lead to hyperglycemia—thereby increasing the risk of hyperglycemic reactions in older adults with diabetes (Guo et al., 2006). Antihistamines are commonly used over-the-counter drugs to treat insomnia (Erman, 2007). "
[Show abstract][Hide abstract] ABSTRACT: Purpose:
The purpose of this article is to provide an overview of changing sleep patterns and common sleep disorders in older adults and to discuss treatment options of sleep disturbances within inpatient rehabilitation facilities (IRFs).
Through extensive review of the existing literature, common sleep disorders among older adults and several key factors that may impact sleep in older adults in inpatient rehabilitation facilities, such as behavioral and environmental factors, psychosocial and emotional factors, medical conditions, and medications were identified.
Current literature on the factors associated with sleep disturbance in older adults in IRFs is based on work with community-dwelling older adults and those in long-term care facilities. While interventions to address these disorders and research investigation key factors associated with sleep problems among older adults appear in the literature, there is very little work that applies these interventions within IRFs.
Conclusions and clinical relevance:
Research is needed to examine the impact of sleep problems on older adults in IRFs, including work that focuses on intervention trials to identify successful treatments for these problems and translate those approaches into practice.
Rehabilitation nursing: the official journal of the Association of Rehabilitation Nurses 09/2013; 38(5). DOI:10.1002/rnj.88 · 1.15 Impact Factor
"Medication treatment patterns are variable in the acute and long-term management of bipolar disorder, with 42-64% of patients receiving mood stabilizers, such as lithium, valproate or carbamazapine, and 44-60% receiving adjunctive antipsychotics [4-6]. Atypical antipsychotics are used alone or in combination with mood stabilizers for more severe manic episodes [7-11]. "
[Show abstract][Hide abstract] ABSTRACT: This study compared 1-year risk of psychiatric hospitalization and treatment costs in commercially insured patients with bipolar disorder, treated with aripiprazole, ziprasidone, olanzapine, quetiapine or risperidone.
This was a retrospective propensity score-matched cohort study using the Ingenix Lab/Rx integrated insurance claims dataset. Patients with bipolar disorder and 180 days of pre-index enrollment without antipsychotic exposure who received atypical antipsychotic agents were followed for up to 12 months following the initial antipsychotic prescription. The primary analysis used Cox proportional hazards regression to evaluate time-dependent risk of hospitalization, adjusting for age, sex and pre-index hospitalization. Generalized gamma regression compared post-index costs between treatment groups.
Compared to aripiprazole, ziprasidone, olanzapine and quetiapine had higher risks for hospitalization (hazard ratio 1.96, 1.55 and 1.56, respectively; p < 0.05); risperidone had a numerically higher but not statistically different risk (hazard ratio 1.37; p = 0.10). Mental health treatment costs were significantly lower for aripiprazole compared with ziprasidone (p = 0.004) and quetiapine (p = 0.007), but not compared to olanzapine (p = 0.29) or risperidone (p = 0.80). Total healthcare costs were significantly lower for aripiprazole compared to quetiapine (p = 0.040) but not other comparators.
In commercially insured adults with bipolar disorder followed for 1 year after initiation of atypical antipsychotics, treatment with aripiprazole was associated with a lower risk of psychiatric hospitalization than ziprasidone, quetiapine, olanzapine and risperidone, although this did not reach significance with the latter. Aripiprazole was also associated with significantly lower total healthcare costs than quetiapine, but not the other comparators.
"Moreover, patients with BD are exposed to lifelong use of medications such as antipsychotics or mood stabilizers that have been associated to weight gain, dyslipidemia and development of diabetes  . Finally, the association between BD and polycystic ovary syndrome, whether or not driven by the use of valproate, is another risk factor for metabolic disturbances  . "
[Show abstract][Hide abstract] ABSTRACT: This study aimed to evaluate the prevalence of metabolic syndrome (MetS) in Italian patients with bipolar disorder (BD) and to determine the sociodemographic and clinical correlates of MetS in this patient population.
Subjects with BD I and II were included. Sociodemographic and clinical characteristics, lifestyle information (alcohol and smoking habits and rate of physical exercise) and comorbidity for cardiovascular diseases and diabetes were collected. Patients were assessed for MetS according to both National Cholesterol Education Program Adult Treatment Panel III and International Diabetes Federation (IDF) criteria.
MetS was evaluated in 99 patients out of 108 who were enrolled. MetS was present in 25.3% of the sample. Abdominal obesity was present in 50%, hypertension in 40%, high triglycerides in 34.7%, low HDL-C levels in 32.3% and fasting hyperglycemia in 11% of the sample. Prevalence of MetS was 30% when IDF criteria were employed. Of the investigated variables, age, duration of illness, rate of obesity and cardiovascular disease were higher in patients with MetS. After the regression analysis, only age and obesity were associated to MetS.
MetS is highly prevalent in Italian patients with BD. Our 25.3% prevalence rate is consistent with the 21-22% reported in other European studies and lower than that in U.S. studies. Elderly and obese patients with BD are at particularly high risk for MetS.
General Hospital Psychiatry 07/2008; 30(4):318-23. DOI:10.1016/j.genhosppsych.2008.04.009 · 2.61 Impact Factor
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