Prognostic factors and prediction model for 1-year mortality after proximal humeral fracture

被引:2
|
作者
Van Grootven, Bastiaan [1 ]
Janssens, Sigrid [2 ]
De Keyser, Laurence [2 ]
Voortmans, Jens [3 ]
Nijs, Stefaan [3 ]
Flamaing, Johan [2 ,4 ]
Dejaeger, Marian [2 ,4 ]
机构
[1] Katholieke Univ Leuven, Acad Ctr Nursing & Midwifery, Dept Publ Hlth & Primary Care, Leuven, Belgium
[2] Katholieke Univ Leuven, Dept Publ Hlth & Primary Care, Gerontol & Geriatr Res Unit, Leuven, Belgium
[3] Katholieke Univ Leuven, Dept Dev & Regenerat, Locomotor & Neurol Disorders Res Unit, Leuven, Belgium
[4] Univ Hosp Leuven, Dept Geriatr, Herestr 49, B-3000 Leuven, Belgium
关键词
Proximal humeral fracture; Prediction model; Mortality; Osteoporosis; EPIDEMIOLOGY; COMORBIDITY; VALIDATION; SURGERY; SCORE;
D O I
10.1007/s11657-023-01260-8
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The goal was to investigate if patient characteristics can be used to predict 1-year post-fracture mortality after proximal humeral fracture (PHF). A clinical prediction model showed that the combination of 6 pre-fracture characteristics demonstrated good predictive properties for mortality within 1 year of PHF.IntroductionProximal humeral fractures (PFH) are the third most common major non-vertebral osteoporotic fractures in older persons and result in an increased mortality risk. The aim of this study was to investigate if patient characteristics can be used to predict 1-year post-fracture mortality.MethodsRetrospective study with 261 patients aged 65 and older who were treated for a PHF in University Hospitals Leuven between 2016 and 2018. Baseline variables including demographics, residential status, and comorbidities were collected. The primary outcome was 1-year mortality. A clinical prediction model was developed using LASSO regression and validated using split sample and bootstrapping methods. The discrimination and calibration were evaluated.ResultsTwenty-seven (10.3%) participants died within 1-year post-PHF. Pre-fracture independent ambulation (p < 0.001), living at home at time of fracture (p < 0.001), younger age (p = 0.006), higher BMI (p = 0.012), female gender (p = 0.014), and low number of comorbidities (p < 0.001) were predictors for 1-year survival. LASSO regression identified 6 stable predictors for a prediction model: age, gender, Charlson comorbidity score, BMI, cognitive impairment, and pre-fracture nursing home residency. The discrimination was 0.891 (95% CI, 0.833 to 0.949) in the training sample, 0.878 (0.792 to 0.963) in the validation sample and 0.756 (0.636 to 0.876) in the bootstrapping samples. A similar performance was observed for patients with and without surgery. The developed model demonstrated good calibration.ConclusionsThe combination of 6 pre-fracture characteristics demonstrated good predictive properties for mortality within 1 year of PHF. These findings can guide PHF treatment decisions.
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页数:6
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