Prevalence of depression, anxiety and post-traumatic stress disorder (PTSD) after acute myocardial infarction: a systematic review and meta-analysis
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,022 | 0,039 |
| Bibliométrie | 0,009 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».