Abstract:
ObjectiveTo explore the nutritional status and risk factors of malnutrition in patients after traumatic fracture surgery, and to construct a nomograph model to predict malnutrition in patients after traumatic fracture surgery.
MethodsA total of 400 patients undergoing traumatic fracture surgery were selected as the study subjects, and their nutritional status was evaluated using the mini-nutritional assessment (MNA).The patients were divided into malnutrition group (n=110) and non-malnutrition group (n=290) according to the MVA scores.Univariate analysis and logistic regression analysis were applied to evaluate the risk factors of malnutrition in patients after traumatic fracture surgery, and a nomograph model was constructed to predict the incidence of malnutrition in patients after traumatic fracture surgery.
ResultsAmong the 400 patients undergoing trauma fracture surgery, 110 cases (27.50%) had malnutrition.The results of univariate analysis showed that there were significant differences in age, body mass index, smoking history, hypertension, diabetes mellitus, chronic gastritis, fracture type, hemoglobin, albumin, and blood loss between the two groups (P < 0.05 to P < 0.01).Multivariate logistic regression analysis showed that age, diabetes mellitus, chronic gastritis, fracture type, hemoglobin and albumin were independent influencing factors for malnutrition in patients after traumatic fracture surgery (P < 0.05 to P < 0.01).Using the above indicators to construct a nomograph model, the area under the curve for predicting malnutrition after traumatic fracture surgery was 0.865 (95%CI: 0.825-0.905), with a sensitivity of 81.51% and a specificity of 79.82%.
ConclusionsThe incidence of malnutrition or malnutrition risk in patients after traumatic fracture surgery is high.Age, diabetes mellitus, chronic gastritis, fracture type, hemoglobin and albumin are independent influencing factors of malnutrition after traumatic fracture surgery.The nomograph model can directly and concisely provide personalized malnutrition risk prediction for patients after traumatic fracture surgery.