Prognostic factors and predictive model for in-hospital mortality following hip fractures in the elderly

被引:0
|
作者
J.Sanz-Reig [1 ]
J.Salvador Marín [1 ]
J.Ferrández Martínez [1 ]
D.Orozco Beltrán [2 ]
J.F.Martínez Lopez [1 ]
J.A.Quesada Rico [2 ]
机构
[1] Department of Orthopedic Surgery, Sant Joan d'Alacant University Hospital
[2] Department of Medicine, Miguel Hernandez University
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中图分类号
R687.3 [骨骼手术];
学科分类号
1002 ; 100210 ;
摘要
Purpose: The incidence of hip fractures is increasing within the aging population. Our objective was to identify and quantify the risk factors and develop a predictive model for the in-hospital mortality among hip fracture patients older than 65 years.Methods: This is a prospective study conducted on 331 hip fracture patients older than 65 years admitted to our hospital from 2011 to 2014. Patients’ demographics, prehospitalization residential status, prefracture comorbidity data, anti-aggregant and anticoagulant medication, preoperative hemoglobin value,type of fractures, type of treatments, time to surgery, and complications were recorded.Results: The average age was 83 years, 73% female, and 57% of them sustained a femoral neck fracture. In 62.8% of patients, the number of pre-fracture baseline comorbidities was >2. The in-hospital mortality rate was 11.4%. In multivariate analysis, age over 90 years, congestive heart failure, asthma, rheumatologic disease, lung cancer, and not taking antiaggregant medication were independently associated with in-hospital mortality. A formula and risk stratification scoring for predicting the risk for in-hospital mortality was developed. Risk-adjustment model based on these variables had acceptable accuracy for predicting in-hospital mortality(c-statistic 0.77).Conclusion: Advanced age, and five prefracture comorbidities have a strong association with in-hospital mortality in a hip fracture patient older than 65 years old. Our predictive model was specifically designed for the old hip fracture population. It has an accuracy similar to other risk models. The specificity, positive predictive value, and negative predictive value are high. In addition, it could discriminate a high risk patient from a low risk patient for in-hospital mortality.
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页码:163 / 169
页数:7
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