Development and validation of a nomogram for 30-day readmission after hip fracture surgery in geriatric patients

被引:0
作者
Tang, W. -Y. [1 ]
Yao, W. [1 ]
Wang, W. [1 ]
Lv, Q. -M. [2 ]
Ding, W. -B. [1 ]
He, R. -J. [3 ]
机构
[1] China Med Univ, Dandong Cent Hosp, Dept Orthoped, Dandong, Peoples R China
[2] China Med Univ, Dandong Cent Hosp, Dept Oncol, Dandong, Peoples R China
[3] Zigong First Peoples Hosp, Dept Orthoped, Zigong, Peoples R China
关键词
Hip fracture; Readmission; Geriatric; Prediction model; Nomogram; RISK-FACTORS; HOSPITAL READMISSION; LIVER-DISEASE; URIC-ACID; MORTALITY; PREDICTORS; SARCOPENIA; PNEUMONIA; BONE; REHOSPITALIZATION;
D O I
暂无
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
OBJECTIVE: 30-day readmission after hip fracture surgery in the elderly is common and costly. A predictive tool to identify high-risk patients could significantly improve outcomes. This study aims to develop and validate a risk nomogram for 30-day readmission after hip fracture surgery in geriatric patients. PATIENTS AND METHODS: We retrospectively analyzed 1,249 geriatric hip fracture patients (>= 60 years) undergoing surgery at Dan-dong Central Hospital from October 2011 to October 2023. Using a 7:3 ratio, patients were randomly divided into training (n=877) and validation (n=372) sets. Independent risk factors for 30-day readmission were identified using LAS-SO regression and logistic regression in the training set. A nomogram was constructed using the identified predictors. Finally, the C-index, ROC curve, calibration curve, and decision curve analysis were used to validate the model in the training and validation sets respectively. RESULTS: The nomogram was developed based on the 8 predictors of age, prior stroke, chronic liver disease, treatment, uric acid (UA), total protein (TP), albumin (ALB), and pneumonia that were found to be independently associated with 30-day readmission. The nomogram showed good discrimination with a C-index of 0.88 in the training set and 0.84 in the validation set. Calibration curves exhibited good agreement be-tween predicted and observed outcomes. Decision curve analysis demonstrated clinical utility. CONCLUSIONS: We developed and validated a nomogram incorporating eight clinical variables to accurately predict the individualized risk of 30-day readmission after hip fracture surgery in elderly patients. The model demonstrated favorable discrimination, calibration, and clinical utility. It can help to identify high-risk patients needing additional interventions to pre-vent avoidable hospital readmissions.
引用
收藏
页码:11517 / 11534
页数:18
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