Risk factors for falls among hospitalized medical patients - A systematic review and meta-analysis.

OBJECTIVE: To identify and quantify risk factors for in-hospital falls in medical patients. DATA SOURCES: Six databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, CINAHL, and Google Scholar) were systematically screened until April 11, 2023, to identify relevant articles. STUDY SELECTION: All titles and abstracts of the retrieved articles were independently screened by two researchers who also read the full texts of the remaining articles. Quantitative studies that assessed risk factors for falls among adult patients acutely hospitalized were included in the review. Publications that did not capture internal medicine patients or focused on other specific populations were excluded. DATA EXTRACTION: Information on study characteristics and potential risk factors were systematically extracted. Risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool. PRISMA and MOOSE guidelines were followed for reporting. DATA SYNTHESIS: The main outcome was any in-hospital falls. Using a random-effects meta-analysis model, association measures for each risk factor reported in five or more studies were pooled. Separate analyses according to effect measure and studies adjusted for sex and age at least were performed. Of 5,067 records retrieved, 119 original publications from 25 countries were included. In conclusion, 23 potential risk factors were meta-analyzed. Strong evidence with large effect sizes was found for a history of falls (OR 2.54; 95% CI 1.63- 3.96; I2 91%), antidepressants (pooled OR 2.25; 95% confidence interval [95% CI] 1.92-2.65; I2 0%), benzodiazepines (OR 1.97; 95% CI 1.68-2.31; I2 0%), hypnotics-sedatives (OR 1.90; 95% CI 1.53-2.36; I2 46%), and antipsychotics (OR 1.61; 95% CI 1.33-1.95; I2 0%). Furthermore, evidence of associations with male sex (OR 1.22, 95% CI 0.99-1.50, I2 65%) and age (OR 1.17, 95% CI 1.02-1.35, I2 72%) were found, but effect sizes were small. CONCLUSIONS: The comprehensive list of risk factors, which specifies the strength of evidence and effect sizes, could assist in the prioritization of preventive measures and interventions.