The predictive value of mini-nutritional assessment on survival outcome of elderly inpatients
Objective:To explore the predictive value of the Miniature Nutritional Assessment(MNA)for all-cause death of elderly inpatients.Methods:To investigate retrospectively the patients over 80 years old who were hospitalized in the geriatrics department of our hospital from January 1,2016 to December 31,2020.The clinical indicators of patients were obtained through the hospital case system,including demographic data,biochemical examination,age adjusted Charlson combined index(ACCI),MNA evaluation,and other indicators.The clinical outcomes of patients were followed up by consulting cases or telephone calls.The follow-up time was 3 years until December 31,2023,and the primary outcome was all-cause death.The Kaplan-Meier plot was used to draw the survival curve,the COX proportional hazard model was used to explore the risk factors of all-cause death,and the receiver operating characteristic curve of MNA was drawn to evaluate and predict all-cause death of patients.Results:According to MNA evaluation,the malnutrition rate was 56.41%(88/156),the nutritional risk rate was 28.85%(45/156),and the good nutrition rate was 14.74%(23/156).Univariate and multivariate analysis showed that MNA and ACCI were independent risk factors for all-cause death.The worse the nutritional status,the shorter the expected survival time of patients.The area under the receiver operating characteristic curve predicted by MNA is 0.816,the sensitivity is 0.780,the specificity is 0.906,and the best cut-off point is 19.25;that is,MNA exceeds 20,which predicts the increased risk for all-cause death.Conclusion:The proportion of malnutrition in elderly inpatients is high,and MNA can be used as an independent predictor of death.It is suggested that the cut-off point of MNA should be set at 20 for older people over 80;that is,the MNA score below 20 is malnutrition.Clinically,nutritional intervention can be carried out in advance according to MNA evaluation to obtain the best clinical outcome.
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