The CoNUT score predicts the length of hospital stay and the risk of long CoVID / La puntuación CONUT predice la duración de la estancia hospitalaria y el riesgo de COVID persistente

Objective: the Controlling Nutritional Status (CONUT) score is an objective tool widely used to assess nutritional status of patients. We aimed toinvestigate the value of CONUT score on predicting length of hospital stay (LOS) and the risk of long COVID in patients with COVID-19.Methods: a total of 151 patients with COVID-19 were enrolled for analysis. Patients were followed up for two years from three months after theonset of SARS-CoV-2 infection. CONUT score was calculated on admission. The correlation between CONUT score and LOS were assessed bySpearman’s rank correlation coefficient and multivariate linear analysis. The association between different CONUT grade and long COVID wasevaluated by Kaplan-Meier survival curves with log-rank test and Cox proportional hazard models.Results: Spearman’s rank correlation coefficient showed that CONUT scores were positively correlated with LOS (r = 0.469, p < 0.001). Multivari-ate linear analysis showed that CONUT score is the only independent determinant of LOS (B 2.055, 95 % CI: 1.067-3.043, p < 0.001). A total of 53(35.10 %) patients with long COVID were identified. Kaplan-Meier cumulative survival curves and Cox proportional hazards analyses showed thatthe incidence of long COVID in patients with a higher CONUT score was significantly higher than in patients with lower CONUT score (p < 0.001).Conclusions: higher CONUT score predicts longer LOS and the risk of long COVID in patients with COVID-19. The CONUT score might be usefulfor risk stratification in COVID-19 patients and help to develop new nutritional treatment strategies for long COVID.(AU)

Objetivo: la escala de valoración del estado nutricional CONUT es una herramienta objetiva ampliamente utilizada para evaluar el estado nutricionalde los pacientes. Nuestro objetivo fue investigar el valor de la puntuación CONUT para predecir la duración de la estancia hospitalaria (LOS) y elriesgo de COVID persistente en pacientes con COVID-19.Métodos: se inscribieron para el análisis un total de 151 pacientes con COVID-19. Los pacientes se sometieron a un seguimiento de dos añosa partir de los tres meses posteriores al inicio de la infección por SARS-CoV-2. La puntuación CONUT se calculó al ingreso. La correlación entrela puntuación CONUT y la LOS se evaluó mediante el coeficiente de correlación de rangos de Spearman y el análisis lineal multivariante. Laasociación entre diferentes grados CONUT y COVID persistente se evaluó mediante curvas de supervivencia de Kaplan-Meier con prueba derango logarítmico y modelos de riesgo proporcional de Cox.Resultados: el coeficiente de correlación de rango de Spearman mostró que las puntuaciones CONUT se correlacionaron positivamente con LOS(r = 0,469, p <0,001). El análisis lineal multivariante mostró que la puntuación CONUT es el único determinante independiente de LOS (B 2,055,IC 95 %: 1,067-3,043, p < 0,001). Se identificaron un total de 53 (35,10 %) pacientes con COVID persistente. Las curvas de supervivenciaacumulada de Kaplan-Meier y los análisis de riesgos proporcionales de Cox mostraron que la incidencia de COVID persistente en pacientes conuna puntuación CONUT más alta fue significativamente mayor que en pacientes con una puntuación CONUT más baja (p < 0,001).Conclusiones: una puntuación CONUT más alta predice una LOS más larga y el riesgo de COVID persistente en pacientes con COVID-19. Lapuntuación CONUT podría ser útil para la estratificación de riesgo en pacientes con COVID-19 y ayudar a desarrollar nuevas estrategias detratamiento nutricional para COVID persistente.(AU)

Elevated plasma pyruvate kinase M2 concentrations are associated with the clinical severity and prognosis of coronary artery disease.

Introduction: Pyruvate kinase M2 (PKM2) was involved in the pathophysiology of atherosclerosis and coronary artery disease (CAD). We tested whether plasma PKM2 concentrations were correlated with clinical severity and major adverse cardiovascular events (MACEs) in CAD patients. Materials and methods: A total of 2443 CAD patients and 238 controls were enrolled. The follow-up time was two years. Plasma PKM2 concentrations were detected by enzyme-linked immunosorbent assay (ELISA) kits (Cloud-Clone, Wuhan, China) using SpectraMax i3x Multi-Mode Microplate Reader (Molecular Devices, San Jose, USA). The predictors of acute coronary syndrome (ACS) were assessed by logistic regression analysis. The association between PKM2 concentration in different quartiles and MACEs was evaluated by Kaplan-Meier (KM) curves with log-rank test and Cox proportional hazard models. The predictive value of PKM2 and a cluster of conventional risk factors was determined by Receiver operating characteristic (ROC) curves. The net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) were utilized to evaluate the enhancement in risk prediction when PKM2 was added to a predictive model containing a cluster of conventional risk factors. Results: In CAD patients, PKM2 concentration was the independent predictor of ACS (P < 0.001). Kaplan-Meier cumulative survival curves and Cox proportional hazards analyses revealed that patients with a higher PKM2 concentration had higher incidence of MACEs compared to those with a lower PKM2 concentration (P < 0.001). The addition of PKM2 to a cluster of conventional risk factors significantly increased its prognostic value of MACEs. Conclusion: Baseline plasma PKM2 concentrations predict the clinical severity and prognosis of CAD.