Prevalence of depression, anxiety and post-traumatic stress disorder (PTSD) after acute myocardial infarction: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background There is increasing recognition that patients experience a greater risk of mental illnesses after an acute myocardial infarction (AMI), with the former being linked to worse post-AMI outcomes. However, the prevalence of these conditions is largely unknown as most studies focus on depression and few on other illnesses such as anxiety and post-traumatic stress disorder (PTSD). Additionally, existing studies mostly involved diagnoses of mental illnesses through patient-reported questionnaires which may carry subjectivity (1). Therefore, we conducted a systematic review and meta-analysis to estimate the prevalence and risk factors of developing depression, anxiety and PTSD after an AMI with the inclusion of only studies with official diagnoses of the mental illnesses. Methods Searches in MEDLINE, EMBASE, and PsycINFO up to January 23, 2023, identified 25 qualifying studies that examined the risk of depression, anxiety and PTSD after AMI, with case definitions based strictly on psychiatrist-administered structured interviews according to the Diagnostic and Statistical Manual for Mental Disorders (DSM) criteria. Meta-analyses of proportions using random-effects models estimated the pooled prevalence of each outcome at the <3-month and >3-month time-points. Heterogeneity was tested using I-squared statistics, if significant heterogeneity was found, subgroup analyses and meta-regression analyses were performed to identify the source of heterogeneity. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) and Risk of Bias 2 (RoB2) Tool, and publication bias using the funnel plot and verified by the Egger’s and Begg’s tests. Results A total of 25 studies were included in the meta-analysis. The pooled prevalence of depression post-AMI (20 studies) was 16.70% (95% CI: 12.40%; 22.11%), with pooled prevalence <3-month and >3-month post-AMI at 19.46% (95% CI: 15.47%; 24.19%) and 14.87% (95% CI: 9.55%; 22.43%) respectively. Pooled prevalence of anxiety (7 studies) and PTSD (3 studies) were 11.96% (95% CI: 6.15; 21.96%) and 10.26% (95% CI:5.49;18.36%) respectively. Subgroup analysis showed that the pooled prevalence of both depression and anxiety are significantly higher in the female gender, in those with hypertension, diabetes or hyperlipidemia, and in smokers, while the pooled prevalence of depression is higher in unmarried than married individuals and in patients with a history of depression. Meta regression indicates that history of depression is a significant predictor of prevalence of depression (p= 0.0035, regression coefficient 1.54). Conclusion The prevalence of mental illnesses is high after AMI. Risk factors identified included female gender, hypertension, diabetes, hyperlipidemia, smoking, depression history, as well as one’s social set-up. These findings highlight the importance of screening at-risk patients and early intervention to improve long-term outcomes after AMI.Forest plot of depression prevalenceSubgroup analysis for depression
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".