Prevalence and predictors of post-stroke mood disorders: A meta-analysis and meta-regression of depression, anxiety and adjustment disorder.

OBJECTIVE: To ascertain the prevalence and predictors of mood disorders, determined by structured clinical interviews (ICD or DSM criteria) in people after stroke. METHODS: Major electronic databases were searched from inception to June 2016 for studies involving major depression (MDD), minor depression (MnD), dysthymia, adjustment disorder, any depressive disorder (any depressive disorder) and anxiety disorders. Studies were combined using both random and fixed effects meta-analysis and results were stratified as appropriate. RESULTS: Depression was examined on 147 occasions from 2days to 7years after stroke (mean 6.87months, N=33 in acute, N=43 in rehabilitation and N=69 in the community/outpatients). Across 128 analyses involving 15,573 patients assessed for major depressive disorder (MDD), the point prevalence of depression was 17.7% (95% CI=15.6% to 20.0%) 0.65 analyses involving 9720 patients determined MnD was present in 13.1% in all settings (95% CI=10.9% to 15.8%). Dysthymia was present in 3.1% (95% CI=2.1% to 5.3%), adjustment disorder in 6.9% (95% CI=4.6 to 9.7%) and anxiety in 9.8% (95% CI=5.9% to 14.8%). Any depressive disorder was present in 33.5% (95% CI=30.3% to 36.8%). The relative risk of any depressive disorder was higher following left (dominant) hemisphere stroke, aphasia, and among people with a family history and past history of mood disorders. CONCLUSION: Depression, adjustment disorder and anxiety are common after stroke. Risk factors are aphasia, dominant hemispheric lesions and past personal/family history of depression but not time since stroke.

Case finding and screening clinical utility of the Patient Health Questionnaire (PHQ-9 and PHQ-2) for depression in primary care: a diagnostic meta-analysis of 40 studies.

BACKGROUND: The Patient Health Questionnaire (PHQ) is the most commonly used measure to screen for depression in primary care but there is still lack of clarity about its accuracy and optimal scoring method. AIMS: To determine via meta-analysis the diagnostic accuracy of the PHQ-9-linear, PHQ-9-algorithm and PHQ-2 questions to detect major depressive disorder (MDD) among adults. METHOD: We systematically searched major electronic databases from inception until June 2015. Articles were included that reported the accuracy of PHQ-9 or PHQ-2 questions for diagnosing MDD in primary care defined according to standard classification systems. We carried out a meta-analysis, meta-regression, moderator and sensitivity analysis. RESULTS: Overall, 26 publications reporting on 40 individual studies were included representing 26 902 people (median 502, s.d.=693.7) including 14 760 unique adults of whom 14.3% had MDD. The methodological quality of the included articles was acceptable. The meta-analytic area under the receiver operating characteristic curve of the PHQ-9-linear and the PHQ-2 was significantly higher than the PHQ-9-algorithm, a difference that was maintained in head-to-head meta-analysis of studies. Our best estimates of sensitivity and specificity were 81.3% (95% CI 71.6-89.3) and 85.3% (95% CI 81.0-89.1), 56.8% (95% CI 41.2-71.8) and 93.3% (95% CI 87.5-97.3) and 89.3% (95% CI 81.5-95.1) and 75.9% (95% CI 70.1-81.3) for the PHQ-9-linear, PHQ-9-algorithm and PHQ-2 respectively. For case finding (ruling in a diagnosis), none of the methods were suitable but for screening (ruling out non-cases), all methods were encouraging with good clinical utility, although the cut-off threshold must be carefully chosen. CONCLUSIONS: The PHQ can be used as an initial first step assessment in primary care and the PHQ-2 is adequate for this purpose with good acceptability. However, neither the PHQ-2 nor the PHQ-9 can be used to confirm a clinical diagnosis (case finding). DECLARATION OF INTEREST: None. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

Breast cancer screening in women with mental illness: comparative meta-analysis of mammography uptake.

BACKGROUND: There is a higher mortality rate due to cancer in people with mental illness and previous work suggests suboptimal medical care in this population. It remains unclear if this extends to breast cancer population screening. AIMS: To conduct a systematic review and meta-analysis to establish if women with a mental health condition are less likely to receive mammography screening compared with those without mental ill health. METHOD: Major electronic databases were searched from inception until February 2014. We calculated odds ratios (OR) with a random effects meta-analysis comparing mammography screening rates among women with and without a mental illness. Results were stratified according to primary diagnosis including any mental illness, mood disorders, depression, severe mental illness (SMI), distress and anxiety. RESULTS: We identified 24 publications reporting breast cancer screening practices in women with mental illness (n = 715,705). An additional 5 studies investigating screening for those with distress (n = 21,491) but no diagnosis of mental disorder were identified. The pooled meta-analysis showed significantly reduced rates of mammography screening in women with mental illness (OR = 0.71, 95% CI 0.66-0.77), mood disorders (OR = 0.83, 95% CI 0.76-0.90) and particularly SMI (OR = 0.54, 95% CI 0.45-0.65). No disparity was evident among women with distress alone. CONCLUSIONS: Rates of mammography screening are lower in women with mental illness, particularly women with SMI, and this is not explained by the presence of emotional distress. Disparities in medical care due to mental illness clearly extend into preventive population screening.