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Risk factors for complications and in-hospital mortality following hip fractures: a study using the National Trauma Data Bank

Archived Abstract of Former PSC Researcher

Belmont, Philip J., E'Stephan J. Garcia, David Romano, Julia O. Bader, Kenneth J. Nelson, and Andrew Schoenfeld. 2014. "Risk factors for complications and in-hospital mortality following hip fractures: a study using the National Trauma Data Bank." Archives of Orthopaedic and Trauma Surgery, 134(5): 597-604.

Retrospective review of prospectively collected data.

To describe the impact of patient demographics, injury-specific factors, and medical co-morbidities on outcomes after hip fracture using the National Sample Program (NSP) of the National Trauma Data Bank (NTDB).

The 2008 NSP-NTDB was queried to identify patients sustaining hip fractures. Patient demographics, co-morbidities, injury-specific factors, and outcomes (including mortality and complications) were recorded and a national estimate model was developed. Unadjusted differences for risk factors were evaluated using t test/Wald Chi square analyses. Weighted logistic regression and sensitivity analyses were performed to control for all factors in the model.

The weighted sample contained 44,419 incidents of hip fracture. The average age was 72.7. Sixty-two percent of the population was female and 80 % was white. The mortality rate was 4.5 % and 12.5 % sustained at least one complication. Seventeen percent of patients who sustained at least one complication died. Dialysis, presenting in shock, cardiac disease, male sex, and ISS were significant predictors of mortality, while dialysis, obesity, cardiac disease, diabetes, and a procedure delay of a parts per thousand yen2 days influenced complications. The major potential modifiable risk factor appears to be time to procedure, which had a significant impact on complications.

This is the first study to postulate predictors of morbidity and mortality following hip fracture in a US national model. While many co-morbidities appear to be influential in predicting outcome, some of the more significant factors include the presence of shock, dialysis, obesity, and time to surgery.

DOI:10.1007/s00402-014-1959-y (Full Text)

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