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Development and Validation of Global Leadership Initiative on Malnutrition for Prognostic Prediction in Patients Who Underwent Cardiac Surgery

The Global Leadership Initiative on Malnutrition (GLIM) has achieved a consensus for the diagnosis of malnutrition in recent years. This study aims to determine the prognostic effect of the GLIM after cardiac surgery. A total of 603 patients in the training cohort and 258 patients in the validation...

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Detalles Bibliográficos
Autores principales: Liu, Zhang, Shen, Zile, Zang, Wangfu, Zhou, Jian, Yu, Zhen, Zhang, Peng, Yan, Xialin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9230873/
https://www.ncbi.nlm.nih.gov/pubmed/35745139
http://dx.doi.org/10.3390/nu14122409
Descripción
Sumario:The Global Leadership Initiative on Malnutrition (GLIM) has achieved a consensus for the diagnosis of malnutrition in recent years. This study aims to determine the prognostic effect of the GLIM after cardiac surgery. A total of 603 patients in the training cohort and 258 patients in the validation cohort were enrolled in this study. Perioperative characteristics and follow-up data were collected. A nomogram based on independent prognostic predictors was developed for survival prediction. In total, 114 (18.9%) and 48 (18.6%) patients were defined as being malnourished according to the GLIM criteria in the two cohorts, respectively. Multivariate regression analysis showed that GLIM-defined malnutrition was an independent risk factor of total complication (OR 1.661, 95% CI: 1.063–2.594) and overall survival (HR 2.339, 95% CI: 1.504–3.637). The c-index was 0.72 (95% CI: 0.66–0.79) and AUC were 0.800, 0.798, and 0.780 for 1-, 2-, and 3-year survival prediction, respectively. The calibration curves of the nomogram fit well. In conclusion, GLIM criteria can efficiently identify malnutrition and has a prognostic effect on clinical outcomes after cardiac surgery. GLIM-based nomogram has favorable performance in survival prediction.