Construction of the risk prediction model of malnutrition after heart valve replacement

ObjectiveTo construct a risk prediction model of malnutrition after heart valve replacement, and provide the strategic support for nursing intervention.

MethodsA total of 83 patients treated with prosthetic heart valve replacement from November 2019 to October 2021 were selected by convenience sampling method.According to the serum albumin(ALB) detection value on the first day after operation, the patients were divided into the case group and control group, and the general information and biochemical nutrition indexes of two groups were collected.The NRS 2002 was used to assess the nutritional risk in two groups before and after surgery.The risk prediction model of malnutrition after heart valve replacement was established by logistic regression analysis.

ResultsA total of 32 patients(38.6%) suffered from malnutrition after heart valve replacement.The results of univariate analysis showed that the differences of the course of disease, replacement site, body mass index(BMI), serum ALB, hemoglobin, prealbumin, total cholesterol and preoperative and postoperative NRS 2002 scores were statistically significant between two groups(P<0.05 0.05 to P<0.01).The model equation was LogitP=-4.132+3.512BMI+4.124ALB+4.911 preoperative NRS 2002+5.109 postoperative NRS 2002.BMI, ALB value, and preoperative and postoperative NRS 2002 scores were the independent predictors of the risk of malnutrition after heart valve replacement(P<0.01).

ConclusionsA predicition model for the risk of malnutriton afte heart value replacemenat is successfully constructed which can be used to predict the nutritional risk of patients undergoing heart value replacement.