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Prior neuropsychiatric disturbances are risk factors for stroke. There is a knowledge gap on the predictors of prestroke psychopathology, as well as their association with stroke outcomes in survivors living in low- and middle-income countries (LMICs). We estimated prevalence, predictors, and association of prestroke neuropsychiatric symptoms with poststroke depression (PSD), disability, and mortality.
Adult ischemic and hemorrhagic stroke survivors.
Prestroke psychopathology were ascertained using the Neuropsychiatric Inventory Questionnaire (NPI-Q). Outcomes were assessed using validated tools, including the Centre for Epidemiologic Studies – Depression Scale (CES-D 10) and modified Rankin scale (mRS). Independent associations were investigated using regression models with Bonferroni corrections, and presented as standardized mean differences (SMD) and odds ratios (OR) within 95% confidence intervals (CI).
Among 150 participants, prestroke neuropsychiatric symptoms were found in 78 (52%). In multivariate logistic regression analyses, prestroke sleep disturbance was associated with systemic hypertension (OR = 5.39, 95% CI = 1.70–17.08). Prestroke neuropsychiatric symptoms independently predicted worse motor disability scores (SMD = 0.92, 95% CI = 0.21–1.62) and greater odds of poststroke mortality (OR = 2.7, 95% CI = 1.1–7.0) at 3 months. However, prestroke depression was not significantly associated with PSD.
Prestroke sleep disturbances was associated with systemic hypertension, a key index of high cardiovascular risk profile and stroke. The findings should energize before-the-stroke identification and prioritization of limited treatment resources in LMICs to persons with sleep symptoms who have multiple, additional, risks of stroke.
Depressive and anxiety disorders are highly comorbid, which has been theorized to be due to an underlying internalizing vulnerability. We aimed to identify groups of participants with differing vulnerabilities by examining the course of internalizing psychopathology up to age 45.
We used data from 24158 participants (aged 45+) in 23 population-based cross-sectional World Mental Health Surveys. Internalizing disorders were assessed with the Composite International Diagnostic Interview (CIDI). We applied latent class growth analysis (LCGA) and investigated the characteristics of identified classes using logistic or linear regression.
The best-fitting LCGA solution identified eight classes: a healthy class (81.9%), three childhood-onset classes with mild (3.7%), moderate (2.0%), or severe (1.1%) internalizing comorbidity, two puberty-onset classes with mild (4.0%) or moderate (1.4%) comorbidity, and two adult-onset classes with mild comorbidity (2.7% and 3.2%). The childhood-onset severe class had particularly unfavorable sociodemographic outcomes compared to the healthy class, with increased risks of being never or previously married (OR = 2.2 and 2.0, p < 0.001), not being employed (OR = 3.5, p < 0.001), and having a low/low-average income (OR = 2.2, p < 0.001). Moderate or severe (v. mild) comorbidity was associated with 12-month internalizing disorders (OR = 1.9 and 4.8, p < 0.001), disability (B = 1.1–2.3, p < 0.001), and suicidal ideation (OR = 4.2, p < 0.001 for severe comorbidity only). Adult (v. childhood) onset was associated with lower rates of 12-month internalizing disorders (OR = 0.2, p < 0.001).
We identified eight transdiagnostic trajectories of internalizing psychopathology. Unfavorable outcomes were concentrated in the 1% of participants with childhood onset and severe comorbidity. Early identification of this group may offer opportunities for preventive interventions.
Major depressive disorder (MDD) is a leading cause of morbidity and mortality. Shortfalls in treatment quantity and quality are well-established, but the specific gaps in pharmacotherapy and psychotherapy are poorly understood. This paper analyzes the gap in treatment coverage for MDD and identifies critical bottlenecks.
Seventeen surveys were conducted across 15 countries by the World Health Organization-World Mental Health Surveys Initiative. Of 35 012 respondents, 3341 met DSM-IV criteria for 12-month MDD. The following components of effective treatment coverage were analyzed: (a) any mental health service utilization; (b) adequate pharmacotherapy; (c) adequate psychotherapy; and (d) adequate severity-specific combination of both.
MDD prevalence was 4.8% (s.e., 0.2). A total of 41.8% (s.e., 1.1) received any mental health services, 23.2% (s.e., 1.5) of which was deemed effective. This 90% gap in effective treatment is due to lack of utilization (58%) and inadequate quality or adherence (32%). Critical bottlenecks are underutilization of psychotherapy (26 percentage-points reduction in coverage), underutilization of psychopharmacology (13-point reduction), inadequate physician monitoring (13-point reduction), and inadequate drug-type (10-point reduction). High-income countries double low-income countries in any mental health service utilization, adequate pharmacotherapy, adequate psychotherapy, and adequate combination of both. Severe cases are more likely than mild-moderate cases to receive either adequate pharmacotherapy or psychotherapy, but less likely to receive an adequate combination.
Decision-makers need to increase the utilization and quality of pharmacotherapy and psychotherapy. Innovations such as telehealth for training and supervision plus non-specialist or community resources to deliver pharmacotherapy and psychotherapy could address these bottlenecks.
There is a substantial proportion of patients who drop out of treatment before they receive minimally adequate care. They tend to have worse health outcomes than those who complete treatment. Our main goal is to describe the frequency and determinants of dropout from treatment for mental disorders in low-, middle-, and high-income countries.
Respondents from 13 low- or middle-income countries (N = 60 224) and 15 in high-income countries (N = 77 303) were screened for mental and substance use disorders. Cross-tabulations were used to examine the distribution of treatment and dropout rates for those who screened positive. The timing of dropout was examined using Kaplan–Meier curves. Predictors of dropout were examined with survival analysis using a logistic link function.
Dropout rates are high, both in high-income (30%) and low/middle-income (45%) countries. Dropout mostly occurs during the first two visits. It is higher in general medical rather than in specialist settings (nearly 60% v. 20% in lower income settings). It is also higher for mild and moderate than for severe presentations. The lack of financial protection for mental health services is associated with overall increased dropout from care.
Extending financial protection and coverage for mental disorders may reduce dropout. Efficiency can be improved by managing the milder clinical presentations at the entry point to the mental health system, providing adequate training, support and specialist supervision for non-specialists, and streamlining referral to psychiatrists for more severe cases.
Traumatic events are associated with increased risk of psychotic experiences, but it is unclear whether this association is explained by mental disorders prior to psychotic experience onset.
To investigate the associations between traumatic events and subsequent psychotic experience onset after adjusting for post-traumatic stress disorder and other mental disorders.
We assessed 29 traumatic event types and psychotic experiences from the World Mental Health surveys and examined the associations of traumatic events with subsequent psychotic experience onset with and without adjustments for mental disorders.
Respondents with any traumatic events had three times the odds of other respondents of subsequently developing psychotic experiences (OR=3.1, 95% CI 2.7–3.7), with variability in strength of association across traumatic event types. These associations persisted after adjustment for mental disorders.
Exposure to traumatic events predicts subsequent onset of psychotic experiences even after adjusting for comorbid mental disorders.
The time required in completing the 26 items of neurological examinations in the standard Neurological Evaluation Scale (NES) may limit its utility in pragmatic clinical situations. We propose the Short Neurological Evaluation Scale (S-NES) for use in busy clinical settings, and in research.
Using confirmatory factor analyses, we identified 12 items of neurological examination showing significant overlap with previously reported theoretical and empirical categories of neurological soft signs (NSS) in schizophrenia. This provided justification for the development of a shorter version of the NES based on the empirically identified NSS. In the present study, we relied on existing data to present an initial validation of the S-NES against the referent standard 26-item NES. We determined sensitivity, specificity, and likelihood ratios. Posterior-test probability was estimated using a Bayesian nomogram plot.
Using data derived from 84 unmedicated or minimally treated patients with first-episode schizophrenia, 12 empirically determined items of neurological examinations showed high agreement with the 26 items in the standard NES battery (sensitivity=96.3%, specificity=100%, and posterior-test probability=100%).
Within limitations of validity estimates derived from existing data, the present results suggest that the design of the S-NES based on empirically identified 12 items of neurological examination is a logical step. If successful, the S-NES will be useful for rapid screening of NSS in busy clinical settings, and also in research.
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