OBJECTIVE: To assess factors associated to mortality in patients with hip fracture and to describe different risk adjustment measures. METHODS: Non-concurrent cohort study comprising 390 patients aged 50 years and more. Patients were identified from the Brazilian Unified Health System Hospital Information System, admitted for hip fracture surgery in a teaching hospital in Rio de Janeiro, southeastern Brazil, between 1995 and 2000. Data from medical records were collected and analyzed by logistic regression models to study 90-day mortality odds after admission according to patient and treatment profiles. Severity of illness classification indexes were estimated. RESULTS: Mortality rate was 7.4% and factors affecting mortality were age (OR=1.06; 95% CI: 1.02;1.11), number of co-morbidities (OR=1.44; 95% CI: 1.12;1.69), Charlson co-morbidity index (OR=6.67; 95% CI: 2.98;22.16) and time to surgery (OR=1.04; 95% CI: 1.02;1.07). CONCLUSIONS: Number of co-morbidities and Charlson co-morbidity index helped predicting the mortality rate.
OBJECTIVE: To assess factors associated to mortality in patients with hip fracture and to describe different risk adjustment measures. METHODS: Non-concurrent cohort study comprising 390 patients aged 50 years and more. Patients were identified from the Brazilian Unified Health System Hospital Information System, admitted for hip fracture surgery in a teaching hospital in Rio de Janeiro, southeastern Brazil, between 1995 and 2000. Data from medical records were collected and analyzed by logistic regression models to study 90-day mortality odds after admission according to patient and treatment profiles. Severity of illness classification indexes were estimated. RESULTS: Mortality rate was 7.4% and factors affecting mortality were age (OR=1.06; 95% CI: 1.02;1.11), number of co-morbidities (OR=1.44; 95% CI: 1.12;1.69), Charlson co-morbidity index (OR=6.67; 95% CI: 2.98;22.16) and time to surgery (OR=1.04; 95% CI: 1.02;1.07). CONCLUSIONS: Number of co-morbidities and Charlson co-morbidity index helped predicting the mortality rate.
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