Usefulness of the CONUT index upon hospital admission as a potential prognostic indicator of COVID-19 health outcomes

Background: In-hospital mortality in patients with coronavirus disease 2019 (COVID-19) is high. Simple prognostic indices are needed to identify patients at high-risk of COVID-19 health outcomes. We aimed to determine the usefulness of the CONtrolling NUTritional status (CONUT) index as a potential prognostic indicator of mortality in COVID-19 patients upon hospital admission. Methods: Our study design is of a retrospective observational study in a large cohort of COVID-19 patients. In addition to descriptive statistics, a Kaplan-Meier mortality analysis and a Cox regression were performed, as well as receiver operating curve (ROC). Results: From February 5, 2020 to January 21, 2021, there was a total of 2969 admissions for COVID-19 at our hospital, corresponding to 2844 patients. Overall, baseline (within 4 days of admission) CONUT index could be scored for 1627 (57.2%) patients. Patients' age was 67.3 ± 16.5 years and 44.9% were women. The CONUT severity distribution was: 194 (11.9%) normal (0-1); 769 (47.2%) light (2-4); 585 (35.9%) moderate (5-8); and 79 (4.9%) severe (9-12). Mortality of 30 days after admission was 3.1% in patients with normal risk CONUT, 9.0% light, 22.7% moderate, and 40.5% in those with severe CONUT (P < 0.05). An increased risk of death associated with a greater baseline CONUT stage was sustained in a multivariable Cox regression model (P < 0.05). An increasing baseline CONUT stage was associated with a longer duration of admission, a greater requirement for the use of non-invasive and invasive mechanical ventilation, and other clinical outcomes (all P < 0.05). The ROC of CONUT for mortality had an area under the curve (AUC) and 95% confidence interval of 0.711 (0.676-0746). Conclusion: The CONUT index upon admission is potentially a reliable and independent prognostic indicator of mortality and length of hospitalization in COVID-19 patientsThe work is supported by a grant from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement (No 101016216

Prognostic value of simple frailty and malnutrition screening tools in patients with acute heart failure due to left ventricular systolic dysfunction

Background: Frailty and malnutrition are common in patients with heart failure (HF), and are associated with adverse outcomes. We studied the prognostic value of three malnutrition and three frailty indices in patients admitted acutely to hospital with HF. Methods: 265 consecutive patients [62% males, median age 80 (interquartile range (IQR): 72–86) years, median NTproBNP 3633 (IQR: 2025–6407) ng/l] admitted with HF between 2013 and 2014 were enrolled. Patients were screened for frailty using the Derby frailty index (DFI), acute frailty network (AFN) frailty criteria, and clinical frailty scale (CFS) and for malnutrition using the geriatric nutritional risk index (GNRI), controlling nutritional status (CONUT) score and prognostic nutritional index (PNI). Results: According to the CFS (> 4), DFI, and AFN, 53, 50, and 53% were frail, respectively. According to the GNRI (≤ 98), CONUT score (> 4), and PNI (≤ 38), 46, 46, and 42% patients were malnourished, respectively. During a median follow-up of 598 days (IQR 319–807 days), 113 patients died. One year mortality was 1% for those who were neither frail nor malnourished; 15% for those who were either malnourished or frail; and 65% for those who were both malnourished and frail. Amongst the malnutrition scores, PNI, and amongst the frailty scores, CFS increased model performance most compared with base model. A final model, including CFS and PNI, increased c-statistic for mortality prediction from 0.68 to 0.84. Conclusion: Worsening frailty and malnutrition indices are strongly related to worse outcome in patients hospitalised with HF

CONUT: A tool for Controlling Nutritional Status. First validation in a hospital population CONUT: una herramienta para controlar el estado nutritivo. Primera validación en una población hospitalaria

Background: The serious problem of hospital undernutrition is still being underestimated, despite its impact on clinical evolution and costs. The screening methods developed so far are not useful for daily clinical practice due to their low effectiveness/cost ratio. Objective:We present an screening tool for CONtrolling NUTritional status (CONUT) that allows an automatic daily assessment of nutritional status of all inpatients that undergo routine analysis. Design: The system is based on a computer application that compiles daily all useful patient information available in hospital databases, through the internal network. It automatically assesses the nutritional status taking into account laboratory information including serum albumin, total cholesterol level and total lymphocyte count. We have studied the association between the results of the Subjective Global Assessment (SGA) and Full Nutritional Assessment (FNA) with those from CONUT, in a sample of 53 individuals. Results: The agreement degree between CONUT and FNA as measured by kappa index is 0.669 (p = 0.003), and between CONUT and SGA is 0.488 (p = 0.034). Considering FNA as "gold standard" we obtain a sensitivity of 92.3 and a specificity of 85.0. Conclusions: CONUT seems to be an efficient tool for early detection and continuous control of hospital undernutrition, with the suitable characteristics for these screening functions.Antecedentes: El grave problema de la desnutrición hospitalaria sigue siendo infravalorado, pese a sus repercusiones sobre la evolución clínica y los costes de la hospitalización. Los procedimientos de filtro desarrollados hasta ahora no son útiles para la práctica diaria por su baja relación efectividad/costo. Objetivo: Presentamos un sistema de cribado para el CONtrol NUTricional que permite valorar a diario, de manera automática, la situación nutricional de la totalidad de los pacientes ingresados a los que se practica análisis de rutina. Diseño: El sistema se basa en una aplicación informática que recopila a diario, a través de la red interna, aquellos datos de los pacientes ingresados que se consideran útiles para evaluar su estado nutricional y que están disponibles en bases de datos del hospital. Automáticamente determina la situación nutricional de los pacientes considerando los datos de laboratorio: albúmina, colesterol y linfocitos totales. Hemos estudiado la asociación entre los resultados del Subjective Global Assessment (SGA) y del Full Nutritional Assessment (FNA) con aquellos del CONUT, en una muestra de 53 individuos. Resultados: El grado de concordancia entre el CONUT y el FNA, medido por el índice kappa es de 0,699 (p = 0,003), y entre el CONUT y el SGA es de 0,488 (p = 0,034). Si consideramos que el FNA es la "prueba de referencia", obtenemos una sensibilidad del 92,3 y una especificidad del 85,0. Conclusiones: Parece que CONUT es una herramienta eficaz para la detección precoz y el control continuo de la desnutrición hospitalaria, con las características adecuadas a las funciones de cribado