A meta-analysis on the prevalence of anxiety and depression in patients with unruptured intracranial aneurysms: exposing critical treatment gaps.
Katrina Hannah D IgnacioJuan Silvestre Grecia PascualSedric John V FactorKathleen Joy O KhuPublished in: Neurosurgical review (2022)
Unruptured intracranial aneurysms (UIAs) are a significant cause of anxiety and depression. Though the annual rupture rate is relatively low, ensuing mortality and morbidity may be high. Most published studies have focused on functional outcomes; however, limited studies have explored and reported on psychiatric outcomes, which are equally important. We aimed to review existing data on anxiety and depression in patients with UIAs. We systematically searched the databases of Pubmed, Cochrane, Scopus, EBSCOHOST, and ClinicalTrials.gov for studies that reported on anxiety and depression in patients with UIAs. Where available, we also reported data on aneurysm characteristics, treatment modalities, and functional outcomes of these populations. We performed a meta-analysis of proportions by random-effects modeling to compute the prevalence of anxiety and depression in patients with UIAs. Eighteen studies reporting a total of 1413 patients with UIAs were included in the systematic review. The mean age was 57.8 (range 27-79); 64% of whom were female. Random-effect modeling analysis showed an overall estimated prevalence of 28% [95% CI: 0.17-0.42] for anxiety and 21% [95% CI: 0.13-0.33] for depression among patients with UIAs. No significant difference was found in the prevalence of these conditions between treated vs untreated aneurysms. Our review highlights the heterogeneity of data from existing studies and the lack of standardized methodologies in determining psychiatric outcomes in patients with UIAs. It was also limited by the small sample sizes and patient counseling bias in the included studies. Larger, well-designed epidemiologic studies on patients with UIA should include more representative samples, assess for predictors of psychological outcomes, and explore the most optimal psychiatric assessment tools.
Keyphrases
- case control
- risk factors
- systematic review
- mental health
- electronic health record
- big data
- type diabetes
- emergency department
- sleep quality
- metabolic syndrome
- single cell
- cardiovascular events
- weight loss
- coronary artery disease
- skeletal muscle
- meta analyses
- physical activity
- deep learning
- replacement therapy
- patient reported