Utilizing a nomogram to predict the one-year postoperative mortality risk for geriatric patients with a hip fracture

• Published in: Scientific reports 2023-07, Vol.13 (1), p.11091-11091, Article 11091
• Main Authors: Wu, Cheng-Yi, Tsai, Ching-Fang, Yang, Hsin-Yi
• Format: Article
• Language: English
• Subjects: 692/308; 692/499; 692/699; Fractures; Geriatrics; Health risks; Hemoglobin; Hip; Hip joint; Humanities and Social Sciences; Mortality; Mortality risk; multidisciplinary; Nomograms; Patients; Prediction models; Risk factors; Risk groups; Science; Science (multidisciplinary); Surgery
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-38297-1

Despite the abundance of research on the risk factors for mortality following hip fracture surgery, there has been a dearth of studies on prediction models in this population. The objective of this research was to explore the influencing factors and construct a clinical nomogram to predict one-year postoperative mortality in patients with hip fracture surgeries. Using the Ditmanson Research Database (DRD), we included 2333 subjects, aged ≥ 50 years who underwent hip fracture surgery between October, 2008 and August, 2021. The endpoint was all-cause mortality. A least absolute shrinkage and selection operator (LASSO) derived Cox regression was performed to select the independent predictors of one-year postoperative mortality. A nomogram was built for predicting one-year postoperative mortality. The prognostic performance of nomogram was evaluated. On the basis of tertiary points in a nomogram, the patients were divided into low, middle and high risk groups, and compared by the Kaplan–Meier analysis. Within 1 year after hip fracture surgery, 274 patients (11.74%) died. Variables retained in the final model comprised age, sex, length of stay, RBC transfusions, hemoglobin, platelet, and eGFR. The AUC for one-year mortality predictions were 0.717 (95% CI = 0.685–0.749). The Kaplan–Meier curves were significantly different among the three risk groups (p