Abstract

Introduction: Mental health disorders are an important global health issue, causing a significant burden of disease worldwide. Incidental findings suggest that patients with a pre-existing mental health disorder (PMHD) may experience worse outcomes following an Intensive Care Unit (ICU) admission compared with other ICU survivors. Objectives/Aims: To determine the reported prevalence rate of PMHDs in patients admitted to adult ICUs and identify the commonly occurring subtypes of mental health disorders. Methods: A systematic search of Medline, CINAHL, Embase and PsychINFO was performed to identify articles that reported a prevalence rate of adult ICU patients with a PMHD. Articles had to use a reliable measure such as the International Classification of Diseases to diagnose and categorise PMHDs. Meta-analyses were performed using the quality effects model to calculate weighted pooled prevalence estimates and heterogeneity was tested for using the I2 statistic. The prevalence rate of PMHDs, as well as subtypes as proportions of all PHMDs, was reported as point estimates with 95% confidence intervals (CI). Subgroup analyses were performed on studies with medical vs medical/surgical patients, high vs low/middle income countries and high vs low risk of bias studies. Results: Seven articles were included (123,632 participants). Most studies performed a retrospective chart review, although methods of patient identification were variable. The pooled prevalence rate of all PMHDs was 14.7% (95%CI 1.6%-35.3%). Depression was the most common subtype, accounting for an estimated 60.4% (95%CI 19.2%-95.3%) of identified PMHDs. The only significant subgroup analysis finding was a higher prevalence rate amongst medical (18.9%, [95%CI 2.4%-39.2%]) compared with medical/surgical (4.3%, [95%CI 0.0%-14.3%]) populations. All analyses showed significant heterogeneity with I2>95%. Conclusion: Approximately 15% of adult ICU patients have a history of PMHD, most commonly depression. Further research is needed to improve the accuracy of this estimate as well as determine the best identification method.

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