Development and Validation of a Nomogram for Adverse Outcomes of Geriatric Trauma Patients Based on Frailty Syndrome

Abstract

Yangfan Zhuang,1 Hao Tu,1 Quanrui Feng,2 Huiming Tang,3 Li Fu,1 Yuchang Wang,1 Xiangjun Bai1 1Trauma Center/Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 2Department of Intensive Care Unit, First Hospital of Wuhan, Wuhan, Hubei Province, People’s Republic of China; 3Department of Intensive Care Unit, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Xiangjun Bai, Trauma Center/Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China, Email [email protected]: Currently, assessing trauma severity alone in geriatric trauma patients (GTPs) cannot accurately predict the risk of serious adverse outcomes during hospitalization. As an emerging concept in recent years, frailty syndrome is closely related to the poor prognosis of many diseases in elderly patients, including trauma. A logistic model for predicting adverse outcomes in elderly trauma patients during hospitalization was constructed in elderly patients, and the predictive efficacy of the model was verified.Patients and Methods: Trauma patients aged ≥ 65 years between June 2020 and September 2021 were selected and randomly divided into a training set and validation set at a ratio of 3:1. Mid arm muscle circumference (MAMC) was measured to determine the degree of frailty. LASSO regression was used to screen appropriate variables for the construction of a prognostic model. The logistic regression model was established and presented in the form of a nomogram. Calibration curves and ROC curves were used to verify the performance of the model.Results: A total of 209 patients were enrolled, including 143 (68.4%) males and 66 (31.6%) females, with an average age of 70.8 ± 4.8 years. Ageless Charlson comorbidity index, BT unit, ISS, GCS, MAMC, prealbumin and lactic acid levels were screened by LASSO regression to construct a prognostic model. The AUC of the ROC analysis prediction model was 0.89 (95% CI 0.80– 0.97) in the validation set. The results of the Hosmer–Lemeshow test for the validation set were χ 2 = 11.23, P = 0.189.Conclusion: The prognostic model of adverse outcomes in GTPs has good accuracy and differentiation, which can improve the prediction results of risk stratification of GTPs during hospitalization by medical staff and provide a new idea for prognostic prediction.Keywords: geriatric trauma patients, frailty, MAMC, prognostic model for adverse outcomes

Keywords

• geriatric trauma patients
• frailty
• mamc
• prognostic model for adverse outcomes