Incidence and associated factors of elderly mortality following hip fracture in Brazil: a systematic review and meta-analysis

Abstract

AbstractIntroductionHip fractures are an important health problem worldwide, and several factors are associated with the mortality. This study aimed to investigate the factors associated with hip fractures in the elderly, based on studies on the population residing in Brazil, and the relationship of fractures with mortality.MethodProspective and retrospective primary observational studies including hospitalized men and/or women aged 60 or older presenting hip fracture due to bone fragility were selected on the Databases. Independent researchers conducted the study selection process and data extraction. A meta-analysis was performed to determine the hospital mortality rate at 90 days, six months, and one year. The Newcastle-Ottawa scale (NOS) was used to assess the quality of the included studies, and the meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).ResultTwenty-five studies totalizing 3,949 patients were included in the systematic review. The population was mainly composed of women (2,680/67.86%). Most patients were in the age group of 70 to 80 years old. Meta-analysis findings: 1) hospital mortality (19 studies, n = 3,175), 10.22% (95% CI 7.27–14.17%; I2 88%); 2) 90-day mortality (3 studies, n = 543), 9.74% (95% CI 3.44–24.62%; I2 90%); 3) six-month mortality (3 studies, n = 205), 24.78% (95% CI 17.07–34.51%; I2 51%); 4) one-year mortality (13 studies, n = 2,790), 21.88% (95% CI 17.5–26.99%; I2 88%). The factors most related to mortality in the studies were: 1) demographic: Older age, male sex; 2) Attributed to clinical conditions: high scoring in preoperative risk scores, comorbidities, neurological/cognitive disorders, functional status; and 3) hospital factors: preoperative period and infections.ConclusionThis review identified variables, including functional status and cognitive changes, related to hip fracture mortality. Knowing these predictors allows for early intervention and planning to adapt health systems to the growing demands of the elderly population.