Yunrui Hao

Background: Mental illnesses following an acute myocardial infarction (AMI) are a growing concern, as they are associated with worse outcomes for AMI patients. Our understanding of the prevalence of mental illnesses after an AMI is incomplete, as most studies investigate depression while overlooking other conditions like anxiety and PTSD. Existing studies often rely on patient-reported questionnaires for mental illness diagnoses, a method that can be subjective. To address this, we conducted a systematic review and meta-analysis to determine the prevalence and risk factors of depression, anxiety, and PTSD after AMI, including only studies with formal mental illness diagnoses. Methods: Searches in MEDLINE, EMBASE, and PsycINFO up to 23 January 2025 identified 23 qualifying studies that assessed the prevalence of depression, anxiety, and PTSD after AMI, with cases defined exclusively by formal diagnoses established through psychiatrist-administered structured interviews according to the Diagnostic and Statistical Manual for Mental Disorders (DSM) criteria (versions III to V). For each outcome, the pooled prevalence was estimated using meta-analyses of proportions with random-effects models. If significant heterogeneity was detected, subgroup analyses and meta-regression were performed to explore the factors contributing to this heterogeneity. Results: A total of 25 studies were included in the meta-analysis. Among the 20 studies included, the pooled prevalence of depression after AMI was 23.58% (95% CI: 22.86%; 24.32%). When stratified by time since AMI, the prevalence was 19.46% (95% CI: 15.47%; 24.19%) for those assessed within 3 months and 14.87% (95% CI: 9.55%; 22.43%) for those assessed after 3 months. The pooled prevalence of anxiety (seven studies) and PTSD (three studies) was 11.96% (95% CI: 6.15; 21.96%) and 10.26% (95% CI: 5.49%; 18.36%), respectively. Further pooled prevalence subgroup analysis of depression and anxiety revealed significantly higher rates in the female sex (29.89%, 95% CI: 21.85; 39.41%), in those with hypertension (25.01%, 95% CI: 21.68; 28.67%), diabetes (25.01%, 95% CI: 21.68; 28.67%), or hyperlipidemia (28.96% 95% CI: 23.44; 35.17%), and in smokers (25.23%., 95% CI: 19.48; 32.00%), while the pooled prevalence of depression is higher in unmarried (35.44%, 95% CI: 19.61; 55.26%) than married individuals (28.63%, 95% CI: 18.67; 41.20%) and in those with a history of depression (57.41%, 95% CI: 31.47; 78.92%). The results of the meta-regression indicated that a prior history of depression was a significant predictor of depression prevalence (p = 0.0035, regression coefficient 1.54). Conclusions: The prevalence of mental illnesses, including depression, anxiety, and PTSD, is notable following an AMI. Identified risk factors encompass female sex, hypertension, diabetes mellitus, hyperlipidemia, smoking, a history of depressive illness, and social context.

Studies have indicated the potential importance of the human nasal and respiratory microbiomes in health and disease. However, the roles of these microbiomes in the pathogenesis of influenza and its complications are not fully understood. Therefore, the objective of this systematic review and analysis is to identify the patterns of nasal and respiratory microbiome dysbiosis and to define the unique signature bacteria associated with influenza compared with other respiratory tract infections. We compared the respiratory microbiome composition between influenza patients and healthy controls; across different influenza severities; in adult versus pediatric influenza patients; as well as influenza versus other respiratory infections. The desired outcomes include the signature bacteria in each cohort and the Shannon index to reflect the alpha diversity. Of the 2269 articles identified, 31 studies fulfilled the inclusion criteria. These studies investigated the respiratory tract microbiomes of patients with influenza, COVID-19, pneumonia, other respiratory infections, and chronic rhinosinusitis (CRS). Our review revealed that the phylum Firmicutes and Actinobacteria, genus Actinomyces, Streptococcus and Granulicatella, and species Neisseria are more prominent in severe influenza than mild to moderate influenza. Reduced microbiome alpha diversity is noted in influenza patients compared to healthy controls. There are some similarities and differences between the signature bacteria in pediatric and adult influenza patients, e.g., Streptococcus is common in both age groups, whereas Pseudomonas is associated with adults. Intriguingly, there is a common predominance of Streptococcus and Firmicutes among influenza and pneumonia patients. COVID-19 patients exhibit an increased abundance of Firmicutes as well as Pseudomonas. In CRS patients, Proteobacteria and Haemophilus are found in high abundance. This review highlights some similarities and differences in the respiratory microbiomes and their signature organisms in influenza of varying severity and in different age groups compared with other respiratory infections. The dysbiosis of the respiratory microbiomes in these respiratory infections enhances our understanding of their underlying pathogenic mechanisms.