Somatic multicomorbidity and disability in patients with psychiatric disorders in comparison to the general population: a quasi-epidemiological investigation in 54,826 subjects from 40 countries (COMET-G study).

BACKGROUND: The prevalence of medical illnesses is high among patients with psychiatric disorders. The current study aimed to investigate multi-comorbidity in patients with psychiatric disorders in comparison to the general population. Secondary aims were to investigate factors associated with metabolic syndrome and treatment appropriateness of mental disorders. METHODS: The sample included 54,826 subjects (64.73% females; 34.15% males; 1.11% nonbinary gender) from 40 countries (COMET-G study). The analysis was based on the registration of previous history that could serve as a fair approximation for the lifetime prevalence of various medical conditions. RESULTS: About 24.5% reported a history of somatic and 26.14% of mental disorders. Mental disorders were by far the most prevalent group of medical conditions. Comorbidity of any somatic with any mental disorder was reported by 8.21%. One-third to almost two-thirds of somatic patients were also suffering from a mental disorder depending on the severity and multicomorbidity. Bipolar and psychotic patients and to a lesser extent depressives, manifested an earlier (15-20 years) manifestation of somatic multicomorbidity, severe disability, and probably earlier death. The overwhelming majority of patients with mental disorders were not receiving treatment or were being treated in a way that was not recommended. Antipsychotics and antidepressants were not related to the development of metabolic syndrome. CONCLUSIONS: The finding that one-third to almost two-thirds of somatic patients also suffered from a mental disorder strongly suggests that psychiatry is the field with the most trans-specialty and interdisciplinary value and application points to the importance of teaching psychiatry and mental health in medical schools and also to the need for more technocratically oriented training of psychiatric residents.

Results of the COVID-19 mental health international for the health professionals (COMET-HP) study: depression, suicidal tendencies and conspiracism.

INTRODUCTION: The current study aimed to investigate the rates of anxiety, clinical depression, and suicidality and their changes in health professionals during the COVID-19 outbreak. MATERIALS AND METHODS: The data came from the larger COMET-G study. The study sample includes 12,792 health professionals from 40 countries (62.40% women aged 39.76 ± 11.70; 36.81% men aged 35.91 ± 11.00 and 0.78% non-binary gender aged 35.15 ± 13.03). Distress and clinical depression were identified with the use of a previously developed cut-off and algorithm, respectively. STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses, and Factorial Analysis of Variance (ANOVA) tested relations among variables. RESULTS: Clinical depression was detected in 13.16% with male doctors and 'non-binary genders' having the lowest rates (7.89 and 5.88% respectively) and 'non-binary gender' nurses and administrative staff had the highest (37.50%); distress was present in 15.19%. A significant percentage reported a deterioration in mental state, family dynamics, and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (24.64% vs. 9.62%; p < 0.0001). Suicidal tendencies were at least doubled in terms of RASS scores. Approximately one-third of participants were accepting (at least to a moderate degree) a non-bizarre conspiracy. The highest Relative Risk (RR) to develop clinical depression was associated with a history of Bipolar disorder (RR = 4.23). CONCLUSIONS: The current study reported findings in health care professionals similar in magnitude and quality to those reported earlier in the general population although rates of clinical depression, suicidal tendencies, and adherence to conspiracy theories were much lower. However, the general model of factors interplay seems to be the same and this could be of practical utility since many of these factors are modifiable.

Digital conversations about depression among Hispanics and non-Hispanics in the US: a big-data, machine learning analysis identifies specific characteristics of depression narratives in Hispanics.

BACKGROUND: Digital conversations can offer unique information into the attitudes of Hispanics with depression outside of formal clinical settings and help generate useful information for medical treatment planning. Our study aimed to explore the big data from open-source digital conversations among Hispanics with regard to depression, specifically attitudes toward depression comparing Hispanics and non-Hispanics using machine learning technology. METHODS: Advanced machine-learning empowered methodology was used to mine and structure open-source digital conversations of self-identifying Hispanics and non-Hispanics who endorsed suffering from depression and engaged in conversation about their tone, topics, and attitude towards depression. The search was limited to 12 months originating from US internet protocol (IP) addresses. In this cross-sectional study, only unique posts were included in the analysis and were primarily analyzed for their tone, topic, and attitude towards depression between the two groups using descriptive statistical tools. RESULTS: A total of 441,000 unique conversations about depression, including 43,000 (9.8%) for Hispanics, were posted. Source analysis revealed that 48% of conversations originated from topical sites compared to 16% on social media. Several critical differences were noted between Hispanics and non-Hispanics. In a higher percentage of Hispanics, their conversations portray "negative tone" due to depression (66% vs 39% non-Hispanics), show a resigned/hopeless attitude (44% vs. 30%) and were about 'living with' depression (44% vs. 25%). There were important differences in the author's determined sentiments behind the conversations among Hispanics and non-Hispanics. CONCLUSION: In this first of its kind big data analysis of nearly a half-million digital conversations about depression using machine learning, we found that Hispanics engage in an online conversation about negative, resigned, and hopeless attitude towards depression more often than non-Hispanic.

Digital conversations about suicide among teenagers and adults with epilepsy: A big-data, machine learning analysis.

OBJECTIVE: Digital media conversations can provide important insight into the concerns and struggles of people with epilepsy (PWE) outside of formal clinical settings and help generate useful information for treatment planning. Our study aimed to explore the big data from open-source digital conversations among PWE with regard to suicidality, specifically comparing teenagers and adults, using machine learning technology. METHODS: Advanced machine-learning empowered methodology was used to mine and structure open-source digital conversations of self-identifying teenagers and adults who endorsed suffering from epilepsy and engaged in conversation about suicide. The search was limited to 12 months and included only conversations originating from US internet protocol (IP) addresses. Natural language processing and text analytics were employed to develop a thematic analysis. RESULTS: A total of 222 000 unique conversations about epilepsy, including 9000 (4%) related to suicide, were posted during the study period. The suicide-related conversations were posted by 7.8% of teenagers and 3.2% of adults in the study. Several critical differences were noted between teenagers and adults. A higher percentage of teenagers are: fearful of "the unknown" due to seizures (63% vs 12% adults), concerned about social consequences of seizures (30% vs 21%), and seek emotional support (29% vs 19%). In contrast, a significantly higher percentage of adults show a defeatist ("given up") attitude compared to teenagers (42% vs 4%). There were important differences in the author's determined sentiments behind the conversations among teenagers and adults. SIGNIFICANCE: In this first of its kind big data analysis of nearly a quarter-million digital conversations about epilepsy using machine learning, we found that teenagers engage in an online conversation about suicide more often than adults. There are some key differences in the attitudes and concerns, which may have implications for the treatment of younger patients with epilepsy.

Differences in BMI between Mexican and Colombian patients receiving antipsychotics: results from the International Study of Latinos on Antipsychotics (ISLA).

Objective: The objective of this study is to examine the association of country of residence with body mass index (BMI) between Mexican and Colombian patients exposed to antipsychotics. We hypothesize that there will be a significant association between country of residence and BMI and that Mexican patients will have higher BMI than their Colombian counterparts.Design: The International Study of Latinos on Antipsychotics (ISLA) is a multisite, international, cross sectional study of adult Latino patients exposed to antipsychotics in two Latin American Countries (i.e. Mexico and Colombia). Data were collected from a total of 205 patients (149 from Mexico and 56 from Colombia). The sites in Mexico included outpatient clinics in Mexicali, Monterrey and Tijuana. In Colombia, data were collected from outpatient clinics in Bogotá. For this study we included patients attending outpatient psychiatric community clinics that received at least one antipsychotic (new and old generation) for the last 3 months. A linear regression model was used to determine the association of country of residence with BMI for participants exposed to an antipsychotic.Results: After controlling for demographics, behaviors, biological and comorbid psychiatric variables, there was a significant difference between Colombia vs. Mexico in the BMI of patients exposed to antipsychotics (ß = 4.9; p < 0.05).Conclusion: Our hypotheses were supported. These results suggest that differences in BMI in patients exposed to antipsychotics in Mexico and Colombia may reflect differences in prevalence of overweight/obesity at the population level in the respective countries, and highlights the involvement of other risk factors, which may include genetics.

Comorbid Medical Conditions in Vascular Dementia: A Matched Case-Control Study.

The objective of the study was to compare the presence of comorbid medical conditions between patients with a vascular dementia (VaD) and a control group, from the Integrated Healthcare Information Services (IHCIS) database. VaD was defined by the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes 290.40, 290.4, 290.41, 290.42, and, 290.43. An individual matching method was used to select the controls, which were matched to cases on a 15:1 ratio by age, gender, type of health plan, and pharmacy benefits. Alzheimer's disease, any other dementia or cognitive deficits associated were considered exclusion criteria. Among the IHCIS patients 60 years of age or older and full year of eligibility during 2010, there were 898 VaD patients, from which 63.6% were women. Concurrent presence of cerebrovascular disease, atherosclerosis, heart failure, and atrial fibrillation were found at 12.6, 4.6, 2.8, and 1.7 times higher in VaD patients, respectively. Compared to controls, VaD patients had more septicemia, injuries, lung diseases including chronic obstructive pulmonary disease, and urinary diseases (all with df = 897,1; p < 0.0001). The present study confirms that these four medical comorbidities are frequent complications of VaD and physicians should be alert to the presence of them in patients with VaD.

Non-binary gender, vulnerable populations and mental health during the COVID-19 pandemic: Data from the COVID-19 MEntal health inTernational for the general population (COMET-G) study.

BACKGROUND: The COVID-19 pandemic has brought significant mental health challenges, particularly for vulnerable populations, including non-binary gender individuals. The COMET international study aimed to investigate specific risk factors for clinical depression or distress during the pandemic, also in these special populations. METHODS: Chi-square tests were used for initial screening to select only those variables which would show an initial significance. Risk Ratios (RR) were calculated, and a Multiple Backward Stepwise Linear Regression Analysis (MBSLRA) was followed with those variables given significant results at screening and with the presence of distress or depression or the lack of both of them. RESULTS: The most important risk factors for depression were female (RR = 1.59-5.49) and non-binary gender (RR = 1.56-7.41), unemployment (RR = 1.41-6.57), not working during lockdowns (RR = 1.43-5.79), bad general health (RR = 2.74-9.98), chronic somatic disorder (RR = 1.22-5.57), history of mental disorders (depression RR = 2.31-9.47; suicide attempt RR = 2.33-9.75; psychosis RR = 2.14-10.08; Bipolar disorder RR = 2.75-12.86), smoking status (RR = 1.15-5.31) and substance use (RR = 1.77-8.01). The risk factors for distress or depression that survived MBSLRA were younger age, being widowed, living alone, bad general health, being a carer, chronic somatic disorder, not working during lockdowns, being single, self-reported history of depression, bipolar disorder, self-harm, suicide attempts and of other mental disorders, smoking, alcohol, and substance use. CONCLUSIONS: Targeted preventive interventions are crucial to safeguard the mental health of vulnerable groups, emphasizing the importance of diverse samples in future research. LIMITATIONS: Online data collection may have resulted in the underrepresentation of certain population groups.

Anxiety disorders and rapid cycling: data from a cohort of 8129 youths with bipolar disorder.

Anxiety disorders (ADs) are common in youths with bipolar disorder (BD). We examine psychiatric comorbidity, hospitalization, and treatment in youths with versus without AD and rapid cycling (four or more cycles per year). Data from the Integrated Healthcare Information Services cohort were used and included 8129 youths (ages ≤18 years). Prevalence of AD, demographic, type of AD, hospitalization, and use of psychotropics were compared between rapid and nonrapid cycling. Overall, 51% of the youths met criteria for at least one comorbid AD; they were predominantly female and were between 12 and 17 years of age. The most common comorbid ADs were generalized ADs and separation ADs. In the patients with rapid cycling, 65.5% met criteria for comorbid AD. The BD youths with AD were more likely to have major depressive disorders and other comorbid ADs, to be given more psychotropics, and to be hospitalized for depression and medical conditions more often than were those without AD.

Applying the Health Belief Model to Characterize Racial/Ethnic Differences in Digital Conversations Related to Depression Pre- and Mid-COVID-19: Descriptive Analysis.

BACKGROUND: The prevalence of depression in the United States is >3 times higher mid-COVID-19 versus prepandemic. Racial/ethnic differences in mindsets around depression and the potential impact of the COVID-19 pandemic are not well characterized. OBJECTIVE: This study aims to describe attitudes, mindsets, key drivers, and barriers related to depression pre- and mid-COVID-19 by race/ethnicity using digital conversations about depression mapped to health belief model (HBM) concepts. METHODS: Advanced search, data extraction, and artificial intelligence-powered tools were used to harvest, mine, and structure open-source digital conversations of US adults who engaged in conversations about depression pre- (February 1, 2019-February 29, 2020) and mid-COVID-19 pandemic (March 1, 2020-November 1, 2020) across the internet. Natural language processing, text analytics, and social data mining were used to categorize conversations that included a self-identifier into racial/ethnic groups. Conversations were mapped to HBM concepts (ie, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy). Results are descriptive in nature. RESULTS: Of 2.9 and 1.3 million relevant digital conversations pre- and mid-COVID-19, race/ethnicity was determined among 1.8 million (62.2%) and 979,000 (75.3%) conversations, respectively. Pre-COVID-19, 1.3 million (72.1%) conversations about depression were analyzed among non-Hispanic Whites (NHW), 227,200 (12.6%) among Black Americans (BA), 189,200 (10.5%) among Hispanics, and 86,800 (4.8%) among Asian Americans (AS). Mid-COVID-19, a total of 736,100 (75.2%) conversations about depression were analyzed among NHW, 131,800 (13.5%) among BA, 78,300 (8.0%) among Hispanics, and 32,800 (3.3%) among AS. Conversations among all racial/ethnic groups had a negative tone, which increased pre- to mid-COVID-19; finding support from others was seen as a benefit among most groups. Hispanics had the highest rate of any racial/ethnic group of conversations showing an avoiding mindset toward their depression. Conversations related to external barriers to seeking treatment (eg, stigma, lack of support, and lack of resources) were generally more prevalent among Hispanics, BA, and AS than among NHW. Being able to benefit others and building a support system were key drivers to seeking help or treatment for all racial/ethnic groups. CONCLUSIONS: There were considerable racial/ethnic differences in drivers and barriers to seeking help and treatment for depression pre- and mid-COVID-19. As expected, COVID-19 has made conversations about depression more negative and with frequent discussions of barriers to seeking care. Applying concepts of the HBM to data on digital conversation about depression allowed organization of the most frequent themes by race/ethnicity. Individuals of all groups came online to discuss their depression. These data highlight opportunities for culturally competent and targeted approaches to addressing areas amenable to change that might impact the ability of people to ask for or receive mental health help, such as the constructs that comprise the HBM.

Results of the COVID-19 mental health international for the general population (COMET-G) study.

INTRODUCTION: There are few published empirical data on the effects of COVID-19 on mental health, and until now, there is no large international study. MATERIAL AND METHODS: During the COVID-19 pandemic, an online questionnaire gathered data from 55,589 participants from 40 countries (64.85% females aged 35.80 ± 13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively. STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses and Factorial Analysis of Variance (ANOVA) tested relations among variables. RESULTS: Probable depression was detected in 17.80% and distress in 16.71%. A significant percentage reported a deterioration in mental state, family dynamics and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (31.82% vs. 13.07%). At least half of participants were accepting (at least to a moderate degree) a non-bizarre conspiracy. The highest Relative Risk (RR) to develop depression was associated with history of Bipolar disorder and self-harm/attempts (RR = 5.88). Suicidality was not increased in persons without a history of any mental disorder. Based on these results a model was developed. CONCLUSIONS: The final model revealed multiple vulnerabilities and an interplay leading from simple anxiety to probable depression and suicidality through distress. This could be of practical utility since many of these factors are modifiable. Future research and interventions should specifically focus on them.

The effect of different degrees of lockdown and self-identified gender on anxiety, depression and suicidality during the COVID-19 pandemic: Data from the international COMET-G study.

INTRODUCTION: During the COVID-19 pandemic various degrees of lockdown were applied by countries around the world. It is considered that such measures have an adverse effect on mental health but the relationship of measure intensity with the mental health effect has not been thoroughly studied. Here we report data from the larger COMET-G study pertaining to this question. MATERIAL AND METHODS: During the COVID-19 pandemic, data were gathered with an online questionnaire from 55,589 participants from 40 countries (64.85% females aged 35.80 ± 13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Anxiety was measured with the STAI, depression with the CES-D and suicidality with the RASS. Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively. STATISTICAL ANALYSIS: It included the calculation of Relative Risk (RR), Factorial ANOVA and Multiple backwards stepwise linear regression analysis RESULTS: Approximately two-thirds were currently living under significant restrictions due to lockdown. For both males and females the risk to develop clinical depression correlated significantly with each and every level of increasing lockdown degree (RR 1.72 and 1.90 respectively). The combined lockdown and psychiatric history increased RR to 6.88 The overall relationship of lockdown with severity of depression, though significant was small. CONCLUSIONS: The current study is the first which reports an almost linear relationship between lockdown degree and effect in mental health. Our findings, support previous suggestions concerning the need for a proactive targeted intervention to protect mental health more specifically in vulnerable groups.

Dementia, Subtype of Seizures, and the Risk of New Onset Seizures: A Cohort Study.

BACKGROUND: Seizure disorders have been identified in patients suffering from different types of dementia. However, the risks associated with the seizure subtypes have not been characterized. OBJECTIVE: To compare the occurrence and risk of various seizure subtypes (focal and generalized) between patients with and without a dementia diagnosis. METHODS: Data from 40.7 million private insured patient individual electronic health records from the U.S., were utilized. Patients 60 years of age or more from the Optum Insight Clinformatics-data Mart database were included in this study. Using ICD-9 diagnoses, the occurrence of generalized or focal seizure disorders was identified. The risk of new-onset seizures and the types of seizures associated with a dementia diagnosis were estimated in a cohort of 2,885,336 patients followed from 2005 to 2014. Group differences were analyzed using continuity-adjusted chi-square and hazard ratios with 95%confidence intervals calculated after a logistic regression analysisResults:A total of 79,561 patient records had a dementia diagnosis, and 56.38%of them were females. Patients with dementia when compared to those without dementia had higher risk for seizure disorders [Hazard ratio (HR) = 6.5 95%CI = 4.4-9.5]; grand mal status (HR = 6.5, 95%CI = 5.7-7.3); focal seizures (HR = 6.0, 95%CI = 5.5-6.6); motor simple focal status (HR = 5.6, 95%CI = 3.5-9.0); epilepsy (HR = 5.0, 95%CI = 4.8-5.2); generalized convulsive epilepsy (HR = 4.8, 95%CI = 4.5-5.0); localization-related epilepsy (HR = 4.5, 95%CI = 4.1-4.9); focal status (HR = 4.2, 95%CI = 2.9-6.1); and fits convulsions (HR = 3.5, 95%CI = 3.4-3.6). CONCLUSION: The study confirms that patients with dementia have higher risks of generalized or focal seizure than patients without dementia.

Characteristics of patients with major depressive disorder switching SSRI/SNRI therapy compared with those augmenting with an atypical antipsychotic in a real-world setting.

BACKGROUND: Following a partial response of first-line antidepressant therapy for the treatment of major depressive disorder (MDD), there is a choice to augment treatment with another agent or switch to a different antidepressant. OBJECTIVE: To report the prevalence and compare the characteristics of patients switching from their initial selective serotonin reuptake inhibitor or serotonin-norepinephrine reuptake inhibitor (SSRI/SNRI) to a new SSRI/SNRI versus those augmenting SSRI/SNRI therapy with a second-generation antipsychotic (SGA). METHODS: MDD patients receiving first-line SSRI/SNRI treatment were identified from a large US-based claims database during 2000-2019. Patients augmenting therapy with an SGA were compared with those who switched to a new SSRI/SNRI. The date of the treatment change was the index date. Previously diagnosed comorbid conditions, medication use and demographics were captured. Treatment patterns following the index date were also captured. Standardized differences (StdDiff) were used to quantify dissimilarities between the two groups. RESULTS: There were 4572 SGA add-on and 24,409 switching patients identified. SGA augmentation patients had more severe disease (diagnosed severe recurrent major depression: 24.7% vs. 9.5%, StdDiff = 0.41) and more diagnosed psychiatric conditions, including: suicidal thoughts (10.7% vs. 3.2%, StdDiff = 0.29), post-traumatic stress disorder (6.1% vs. 2.6%, StdDiff = 0.17) and alcohol abuse (5.4% vs. 2.7%, StdDiff = 0.14). SGA augmentation patients had higher rates of prior use of anxiolytics (37.4% vs. 28.2%, StdDiff = 0.20) and anticonvulsants (26.0% vs. 13.1%, StdDiff = 0.33). CONCLUSIONS: Patients adding an SGA to their SSRI/SNRI therapy appeared to have more severe depression and comorbid psychiatric profile than those switching their SSRI/SNRI. These differences are important to consider and adequately control for in any future comparative outcome research between these two groups.

Subtypes of depression among patients with Alzheimer's disease and other dementias.

OBJECTIVES: We compared the prevalence of subtypes of depression in patients with Alzheimer's disease (AD), vascular dementia (VaD), and unspecified dementia (UD). METHODS: Using the Integrated Healthcare Information Services database, we conducted an analysis of subtypes of depression (major depressive disorder, depressive disorder not otherwise specified, dysthymic disorder; depressive psychosis, and adjustment disorder depressive) among patients with AD, VaD, and UD. Six thousand four hundred and forty patients aged 60 years or older with dementia (2947 with AD, 725 with VaD, and 2768 with UD) were identified from January 1 to December 31, 2001. Both subtypes of depression and dementia subgroups were diagnosed using criteria from the International Classification of Diseases, 9th version. RESULTS: The overall prevalence of depressive disorders was 27.41%. The prevalence of depressive disorders was significantly higher in VaD (44.14%) and UD (32.48%) patients compared with AD (18.53%, P < .0001) patients. The AD patients had the lowest prevalence of all subtypes of depression. The VaD patients, compared with both AD and UD (P < .005), had a significantly higher prevalence of: 1) depressive disorder not otherwise specified, 2) major depressive disorder, and 3) dysthymic disorder. Adjustment disorder with depressive symptoms was more common in the UD subgroup, whereas the rate of depressive psychosis was similar in all dementia subgroups CONCLUSIONS: This study supports the view that depressive disorders are more prevalent in VaD compared with UD and AD, and provides indicators to the clinician for further evaluation of depression in dementia subgroups.

A multicenter study of major depressive disorder among emergency department patients in Latin-American countries.

This multicenter study estimated the prevalence of major depressive disorder (MDD) among emergency department patients in Latin America. To identify patients with MDD, we used a combination of DSM IV- criteria interview and a questionnaire screen including the center for Epidemiological Studies Depression Scale. We analyzed data from consecutive adult patients from hospitals in Argentina, Brazil, Chile, Colombia, and Mexico and described the demographic and health status differences between MDD and non-MDD patients. Prevalence of MDD ranges from 23.0 to 35.0%. The estimates are based on a total of 1,835 patients aged 18 years and over, with response rates of 83.0%. Compared to non-MDD patients, MDD patients were more likely to be middle-aged, female, smokers, of lower socioeconomic status, and to report a diagnosis of asthma or arthritis/rheumatism. Multivariate analysis identified a lower level of education, smoking, and self-reported anxiety, chronic fatigue, and back problems to be independently associated with MDD. Our data suggest that the prevalence of MDD is elevated among emergency department patients in Latin American countries. The integration of depression screening into routine emergency care merits serious consideration, especially if such screening can be linked to psychiatric treatment.

Mental disorders among English-speaking Mexican immigrants to the US compared to a national sample of Mexicans.

Our understanding of the relationship between immigration and mental health can be advanced by comparing immigrants pre- and post-immigration with residents of the immigrants' home countries. DSM-IV anxiety and mood disorders were assessed using identical methods in representative samples of English-speaking Mexican immigrants to the US, a subsample of the US National Comorbidity Survey Replication (NCSR), and Mexicans, the Mexican National Comorbidity Survey (MNCS). Retrospective reports of age of onset of disorders and, in the immigrant sample, age of immigration were analyzed to study the associations of pre-existing mental disorders with immigration and of immigration with the subsequent onset and persistence of mental disorders. Pre-existing anxiety disorders predicted immigration (OR=3.0; 95% CI 1.2-7.4). Immigration predicted subsequent onset of anxiety (OR=1.9; 95% CI 0.9-3.9) and mood (OR=2.3; 95% CI 1.3-4.0) disorders and persistence of anxiety (OR=3.7 95% CI 1.2-11.2) disorders. The results are inconsistent with the "healthy immigrant" hypothesis (that mentally healthy people immigrate) and partly consistent with the "acculturation stress" hypothesis (i.e., that stresses of living in a foreign culture promote mental disorder). Replication and extension of these results in a larger bi-national sample using a single field staff are needed.

Does panic disorder increase the risk of coronary heart disease? A cohort study of a national managed care database.

OBJECTIVE: The association between panic disorder (PD) and coronary heart disease (CHD) was examined in a large national managed care database. METHODS: The Integrated Health Care Information Services managed care database is a fully de-identified, Health Insurance Portability and Accountability Act-compliant database and includes complete medical history for more than 17 million managed care lives; data from more than 30 United States health plans covering 7 census regions and from patient demographics, including morbidity, age, and gender. A cohort study was designed with a total of 39,920 PD patients and an equal number of patients without PD. The Cox proportional hazards regression models were used to assess the risk of CHD adjusted for age at entry into the cohort, tobacco use, obesity, depression, and use of medications including angiotensin converting enzyme inhibitors, beta blockers, and statins. RESULTS: Patients with PD were observed to have nearly a 2-fold increased risk for CHD (HR = 1.87, 95% CI = 1.80-1.91) after adjusting for these factors. There was some evidence of a possible trend toward increased risk in a subgroup of patients diagnosed with depression. After controlling for the aforementioned covariates and comparing these patients with those who did not have a diagnosis of depression, it was noted that patients with a comorbid diagnosis of depression were almost 3 times more likely to develop CHD (HR = 2.60, 95% CI = 2.30-3.01). CONCLUSIONS: The risk of CHD associated with a diagnosis of PD suggests the need for cardiologists and internists to monitor panic disorder to ensure a reduction in the risk of CHD.

Topiramate monotherapy use in women with and without epilepsy: pregnancy and neonatal outcomes.

PURPOSE: To evaluate fetal or neonatal outcomes (with a focus on major congenital anomalies) with use of topiramate monotherapy and to examine whether differences occurred in the reporting and patterns of these outcomes for pregnant women with and without epilepsy. METHODS: Spontaneous, postmarketing reports involving women who used topiramate monotherapy during pregnancy from 18 July 1995 (International Birth Date of topiramate) through 30 April 2011 were retrieved from the sponsor's (Janssen Research & Development, LLC) Global Medical Safety database. All formulations for topiramate, used as monotherapy, were selected for the analysis. Monotherapy was defined as any situation where no other AED was listed in the pregnancy case report, either as a suspect or concomitant medication, regardless of indication. Results were summarized descriptively. RESULTS: A total of 1163 cases of women who used topiramate monotherapy during pregnancy (for any indication) were retrieved from the Global Medical Safety database. Since some women used topiramate for more than one indication, there were a total of 1199 reported indications for topiramate monotherapy, which were primarily for treatment of epilepsy (n=599), accounting for half of the indications, and migraine prophylaxis (n=240, 20.0%). Out of 1163 cases, pregnancy outcome was reported in 50.6% (n=589). Live birth was the most frequently reported outcome, regardless of indication (epilepsy, 78.8% [312/396]; prophylaxis of migraine, 59. 3% [48/81]; other indication, 64.4% [85/132]). Cleft lip or palate anomalies (epilepsy, n=15; migraine, n=2; other indication, n=4; and indication not reported, n=2), limb, hand, or other skeletal anomalies (epilepsy, n=13; migraine, n=2; other indication, n=0; and indication not reported, n=1), and respiratory or cardiovascular anomalies (epilepsy, n=12; migraine, n=1; other indication, n=1; and indication not reported, n=2) were the most often reported major fetal or neonatal anomalies. More reported major fetal or neonatal anomalies occurred in patients being treated for epilepsy (53/79 anomaly-indication pairs) compared with patients being treated for migraine prophylaxis (10/79 anomaly-indication pairs). CONCLUSION: Although incidence rates cannot be calculated based on spontaneous adverse event reporting, this summary of reported pregnancy and neonatal outcomes with use of topiramate monotherapy suggests that the risk for major fetal or neonatal anomalies may differ based on the indication for topiramate.

Different neurological conditions between urban and rural samples from central Colombia.

OBJECTIVES: Despite availability of neuroepidemiological data, urban-rural differences on neurological diseases have almost never been considered. Our goal is to identify differences in the frequency of neurological conditions between a rural and an urban sample from central Colombia. METHODS: We compared frequencies of neurological encounters of an urban sample from Bogotá (N=2932), to our rural sample from Tunja (N=2664), collected both circa to 2000. The classification of neurological conditions used is based on the 9th revision of the International Classification of Diseases, clinical modification. A clustered sampling was used. Information collection was performed in a format designed for this purpose and already used in Colombia. RESULTS: Highly significant statistical differences (p<0.0001) were found for cerebrovascular diseases, seizure disorder, headache, Parkinson's disease and other movement disorders, and, inflammatory (infectious) conditions. Neurodevelopmental disorders (p=0.0029), dizziness and balance problems (p=0.0018), and neuropathies (p=0.0007), also showed statistically significant differences. CONCLUSIONS: Our study showed significant differences on all categories and diagnostics between the samples. Cerebrovascular disease the most frequent reason of neurological consultation in the rural sample could be confounded by sociodemographic (aging of the population, urbanization process), or the concomitant presence of medical (chronic pulmonary) and/or environmental (air pollution) conditions.

A multicenter study of bipolar disorder among emergency department patients in Latin-American countries.

OBJECTIVE: This multicenter study estimated the prevalence of bipolar disorder (BPD) among emergency department (ED) patients in Latin America. METHODS: To identify patients with BPD, a combination of DSM IV-criteria interview and the Mood Disorder Questionnaire (MDQ) was used. Data from 1,505 patients from hospitals in Argentina, Brazil, Chile, Colombia, and Mexico was analyzed. RESULTS: The prevalence ofBPD in this sample was 5.2% (95% CI = 4.5% to 6.9%). The mean age was 37 years (response rate of 83.0%). Compared to non-BPD patients, BPD patients were more likely to report asthma (16.7% vs. 9%), thyroid problems (12.8% vs. 5.8%), seizures (23.1% vs. 3.0%), obesity (39.7% vs. 26.9%), alcohol abuse (30.8% vs. 10.0%), attention deficit hyperactivity disorders (50.0% vs. 12.0%), depression (81.6% vs. 45.7%), obsessive compulsive disorder (20.1% vs. 3.0%), panic disorders (23.1% vs. 12.3%), phobic disorders (11.2% vs. 3.1%), and any anxiety disorder (82.1 % vs. 41.8%; all p < or = 0.05). Suicidal plans and attempts were also significant higher in the bipolar group (11.5% vs. 2.8% and 10.3% vs. 1.8% respectively). Multivariate analysis identified ADHD, depression, alcohol abuse, anxiety disorder, and last month suicide plans and attempts to be independently associated with BPD. CONCLUSION: Our study supports that BPD is prevalent in ED in Latin-American countries and that comorbidity is the rule, not the exception. Patients presenting at ED with irritability, anxiety, pressure speech, euphoria, with suicidal tendencies, involved in risky behaviors, alcohol abuse, dependence or those with history of mental health hospitalization in the past 12 months must be assessed for comorbid BPD.