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19 February 2020 : Clinical Research  

Development of a Nomogram for Predicting Blood Transfusion Risk After Hemiarthroplasty for Femoral Neck Fractures in Elderly Patients

Ji-Qi Wang1DE, Lu-Ying Chen2BCE, Bing-Jie Jiang1BF, You-Ming Zhao1A*

DOI: 10.12659/MSM.920255

Med Sci Monit 2020; 26:e920255

Abstract

BACKGROUND: The aim of this study was to determine the risk factors and develop a nomogram for blood transfusions after hemiarthroplasty (HA) in patients with femoral neck fractures (FNFs).

MATERIAL AND METHODS: We performed a retrospective study including consecutive elderly FNF patients treated by HA between January 2015 and December 2017. Perioperative information was obtained retrospectively, uni- and multivariate regression analyses were conducted to determine risk factors for blood transfusion, and a nomogram model was constructed to predict the risk of blood transfusion. The predictive performance and consistency of the model were evaluated by the consistency coefficient (C-index) and the calibration curve, respectively.

RESULTS: Of 178 patients, 151 were finally enrolled in the study and 21 received blood transfusion. Binary logistic regression analysis showed the low preoperative hemoglobin (Hb), longer time to surgery, general anesthesia, longer surgery duration, and higher intraoperative blood loss (IBL) were risk factors for blood transfusion. The accuracy of the contour map for predicting transfusion risk was 0.940.

CONCLUSIONS: We found a correlation between blood transfusion requirement and low preoperative Hb, longer time to surgery, general anesthesia, longer surgery duration, and higher IBL, and we then developed a nomogram. Our nomogram model can be used to evaluate the transfusion risk for FNF patients after HA, and provides better guidance for clinicians to intervene perioperatively, so as to reduce the incidence of blood transfusion.

Keywords: Blood Transfusion, Femoral Neck Fractures, hemiarthroplasty, nomograms, Risk Factors, Aged, 80 and over, Calibration, Logistic Models

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750