Establishment of Nomogram prediction model for postoperative blood transfusion in elderly hip fractures using R software

doi:10.12307/2023.692

Abstract

Abstract: BACKGROUND: With the gradual aging of the population, the number of elderly patients with hip fractures is increasing. Blood transfusion is very common after hip fracture, but the risk factors of blood transfusion are still under debate.
OBJECTIVE: To construct a Nomogram prediction model for evaluating the risk of the allogeneic erythrocyte blood transfusion after hip fracture in elderly patients.
METHODS: From June 2016 to June 2020, 392 elderly patients with hip fractures who underwent surgical treatment in the Dade Road General Hospital of Guangdong Provincial Hospital of Chinese Medicine were selected as the research objects. Lasso regression and multivariate Logistic analysis were used to determine the risk factors and R software was utilized to build Nomogram prediction model.
RESULTS AND CONCLUSION: (1) Lasso regression and multivariate Logistic regression analysis showed that age, operation time, American Society of Anesthesiologists classification, hypertension, preoperative anemia, intraoperative blood loss, and fracture type were independent influencing factors of postoperative blood transfusion in elderly hip fractures. The area under the curve of the prediction model constructed by the seven indicators was 0.814. (2) Clinical decision curve analysis showed that the model had good clinical utility. (3) It is concluded that the prediction model established based on seven indicators of age, operation time, American Society of Anesthesiologists classification, hypertension, preoperative anemia, intraoperative blood loss, and fracture type has good performance in predicting the risk of blood transfusion after hip fracture in the elderly, and can provide an important reference for guiding postoperative blood transfusion in elderly hip fractures.

Key words: hip fracture, elderly, postoperative blood transfusion, allogeneic erythrocyte, prediction model

CLC Number:

Niu Feng, Su Baotong, Chen Yulin, Xie Yajuan, Xu Yilang, Li Cong, Cheng Zhian. Establishment of Nomogram prediction model for postoperative blood transfusion in elderly hip fractures using R software[J]. Chinese Journal of Tissue Engineering Research, 2023, 27(31): 4932-4936.

Figures/Tables 8

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