Da-Hye Son1, Kyung-Sub Kim2, Hye-Sun Lee3, Ji-Won Lee4, Cheung-Soo Shin5. 1. Department of Family Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. 2. Department of Anesthesiology and Pain Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. 3. Biostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, Seoul, Republic of Korea. 4. Department of Family Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. Electronic address: indi5645@yuhs.ac. 5. Department of Anesthesiology and Pain Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. Electronic address: cheung56@yuhs.ac.
Abstract
BACKGROUND/ PURPOSE: Predicting the mortality in patients admitted to the ICU is important for determining a treatment strategy and public health policy. Although many scores have been developed to predict the mortality, these scores were based on Caucasian population. We aimed to develop a new prognostic index, the New nutritional index (NNI), to predict 90-days mortality after ICU admission based on Korean population. METHODS: Patients (1453) who admitted intensive care unit (ICU) of the Gangnam Severance hospital were analyzed. After exclusion, 984 patients were randomly divided into internal (n = 702) and external validation (n = 282) data set. The new nutritional index (NNI) was developed using univariate and multivariate logistic regression with backward selection of predictors. Receiver operating characteristic (ROC) curve analysis and comparison of the area under the curve (AUC) verified the better predictor of 90 days-mortality after ICU admission. RESULTS: The NNI better predicted 90 days-mortality compared to modified NUTRIC score, APACHE II scores, SOFA scores, CRP, glucose, total protein, and albumin level in internal and external data sets, with AUC of 0.862 (SE: 0.017, 95% CI: 0.829-0.895) and 0.858 (SE: 0.015, 95% CI: 0.829-0.887), respectively. The calibration plots using external data set for validation showed a close approximation to the logistic calibration of each nomogram, and p-value of Hosmer and Lemeshow test was 0.1804. CONCLUSION: The NNI has advantages as a predictor of 90 days mortality based on nutritional status in the Korean population.
BACKGROUND/ PURPOSE: Predicting the mortality in patients admitted to the ICU is important for determining a treatment strategy and public health policy. Although many scores have been developed to predict the mortality, these scores were based on Caucasian population. We aimed to develop a new prognostic index, the New nutritional index (NNI), to predict 90-days mortality after ICU admission based on Korean population. METHODS:Patients (1453) who admitted intensive care unit (ICU) of the Gangnam Severance hospital were analyzed. After exclusion, 984 patients were randomly divided into internal (n = 702) and external validation (n = 282) data set. The new nutritional index (NNI) was developed using univariate and multivariate logistic regression with backward selection of predictors. Receiver operating characteristic (ROC) curve analysis and comparison of the area under the curve (AUC) verified the better predictor of 90 days-mortality after ICU admission. RESULTS: The NNI better predicted 90 days-mortality compared to modified NUTRIC score, APACHE II scores, SOFA scores, CRP, glucose, total protein, and albumin level in internal and external data sets, with AUC of 0.862 (SE: 0.017, 95% CI: 0.829-0.895) and 0.858 (SE: 0.015, 95% CI: 0.829-0.887), respectively. The calibration plots using external data set for validation showed a close approximation to the logistic calibration of each nomogram, and p-value of Hosmer and Lemeshow test was 0.1804. CONCLUSION: The NNI has advantages as a predictor of 90 days mortality based on nutritional status in the Korean population.