Procalcitonina es superior a recuento linfocitario, índice neutrófilo/linfocito y proteína C reactiva para la predicción de mortalidad a 30 días de pacientes con COVID-19 en el servicio de urgencias / Procalcitonin concentration in the emergency department predicts 30-day mortality in COVID-19 better than the lymphocyte count, the neutrophil-to- lymphocyte ratio, or the C-reactive protein level

Introducción. Existen múltiples variables demográficas y clínicas predictivas de mortalidad en pacientes con COVID-19. Sin embargo, hay menos información sobre el valor pronóstico de los biomarcadores inflamatorios. Métodos. Estudio de cohorte retrospectivo. Se incluyeron de forma consecutiva todos los pacientes con COVID-19, confirmado por laboratorio, atendidos en un servicio de urgencias hospitalario (SUH) y con valor basal de los siguientes biomarcadores: recuento linfocitario, índice neutrófilo/linfocito (INL), proteína C reactiva (PCR) y procalcitonina (PCT). La relación entre los biomarcadores y la mortalidad total a 30 días se analizó mediante una regresión de Cox y gráficos de dosis-respuesta. Resultados. Se incluyeron 896 pacientes, 151 (17%) fallecieron en los primeros 30 días. La mediana de edad fue de 63 años (51-78) y 494 (55%) eran hombres. El valor de INL, PCR y PCT fue mayor, mientras que el recuento linfocitario fue menor, en los pacientes que fallecieron respecto a los que sobrevivieron (p < 0,001). La PCT fue superior al recuento linfocitario, INL y PCR en la predicción de mortalidad a 30 días (ABC 0,79 [IC 95%: 0,75-0,83] vs 0,70 [IC 95%: 0,65-0,74], p < 0,001; 0,74 [IC 95%: 0,69-0,78], p = 0,03; y 0,72 [IC 95%: 0,68-0,76], p < 0,001). Los puntos de decisión de PCT propuestos, 0,06 ng/l para exclusión y 0,72 ng/l para inclusión de muerte a 30 días, podrían facilitar la toma de decisiones en urgencias. Hubo 357 pacientes (40%) con valores de PCT en estas categorías. El análisis multivariable mostró una mayor asociación con la mortalidad para PCT que en los otros biomarcadores estudiados. Conclusión. PCT es el biomarcador con mejor capacidad para predecir mortalidad a 30 días por cualquier causa en pacientes con COVID-19 valorados en un SUH.

Background. Although many demographic and clinical predictors of mortality have been studied in relation to COVID-19, little has been reported about the prognostic utility of inflammatory biomarkers. Methods. Retrospective cohort study. All patients with laboratory-confirmed COVID-19 treated in a hospital emergency department were included consecutively if baseline measurements of the following biomarkers were on record: lymphocyte counts, neutrophil-to-lymphocyte ratio NRL, and C-reactive protein (CRP) and procalcitonin (PCT) levels. We analyzed associations between the biomarkers and all-cause 30-day mortality using Cox regression models and dose–response curves. Results. We included 896 patients, 151 (17%) of whom died within 30 days. The median (interquartile range) age was 63 (51-78) years, and 494 (55%) were men. NLR, CRP and PCT levels at ED presentation were higher, while lymphocyte counts were lower, in patients who died compared to those who survived (P < .001). The areas under the receiver operating characteristic curves revealed the PCT concentration (0.79; 95% CI, 0.75-0.83) to be a better predictor of 30-day mortality than the lymphocyte count (0.70; 95% CI, 0.65-0.74; P < .001), the NLR (0.74; 95% CI, 0.69-0.78; P = .03), or the CRP level (0.72; 95% CI, 0.68-0.76; P < .001). The proposed PCT concentration decision points for use in emergency department case management were 0.06 ng/L (negative) and 0.72 ng/L (positive). These cutoffs helped classify risk in 357 patients (40%). Multivariable analysis demonstrated that the PCT concentration had the strongest association with mortality. Conclusion. PCT concentration in the emergency department predicts all-cause 30-day mortality in patients with COVID-19 better than other inflammatory biomarkers.

Socio-Demographic Health Determinants Are Associated with Poor Prognosis in Spanish Patients Hospitalized with COVID-19.

INTRODUCTION: Social vulnerability is a known determinant of health in respiratory diseases. Our aim was to identify whether there are socio-demographic factors among COVID-19 patients hospitalized in Spain and their potential impact on health outcomes during the hospitalization. METHODS: A multicentric retrospective case series study based on administrative databases that included all COVID-19 cases admitted in 19 Spanish hospitals from 1 March to 15 April 2020. Socio-demographic data were collected. Outcomes were critical care admission and in-hospital mortality. RESULTS: We included 10,110 COVID-19 patients admitted to 18 Spanish hospitals (median age 68 (IQR 54-80) years old; 44.5% female; 14.8% were not born in Spain). Among these, 779 (7.7%) cases were admitted to critical care units and 1678 (16.6%) patients died during the hospitalization. Age, male gender, being immigrant, and low hospital saturation were independently associated with being admitted to an intensive care unit. Age, male gender, being immigrant, percentile of average per capita income, and hospital experience were independently associated with in-hospital mortality. CONCLUSIONS: Social determinants such as residence in low-income areas and being born in Latin American countries were associated with increased odds of being admitted to an intensive care unit and of in-hospital mortality. There was considerable variation in outcomes between different Spanish centers.

El impacto del tiempo hasta el confinamiento en los casos y la mortalidad por COVID-19 en países europeos / The impact of time to impose lockdown on COVID-19 cases and deaths in European countries

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Impact of Spanish Public Health Measures on Emergency Visits and COVID- 19 diagnosed cases during the pandemic in Madrid / Impacto de las medidas de Salud Pública españolas en las visitas a Urgencias y en los casos diagnosticados de COVID- 19 durante la pandemia en Madrid

INTRODUCTION: Changes in Public Health recommendations may have changed the number of emergency visits and COVID-19 diagnosed cases in an Emergency Department in Madrid. MATERIAL AND METHODS: This retrospective case series study included all consecutive patients in a tertiary and urban ED in Madrid from 1st to 31st March. The sample was divided: NonCOVID-19, Non-investigated COVID-19, Possible COVID-19, Probable COVID-19, Confirmed COVID-19. Differences between public health periods were tested by ANOVA for each cohort, and by ANCOVA including the number of PCR tests (%) as covariate. RESULTS: A total of 7,163 (4,071 Non-COVID-19, 563 Non-investigated COVID-19, 870 Possible, 648 Probable and 1,011 Confirmed COVID-19) cases were included. Public Health measurements applied during each period showed a clear effect on the case proportion for the five cohorts. CONCLUSION: The variability of case definitions and diagnostic test criteria may have impact on the number of emergency visits and COVID-19 diagnosed cases in Emergency Department

INTRODUCCIÓN: Los cambios en las recomendaciones de Salud Pública pueden haber modificado la cantidad de visitas y los casos diagnosticados por COVID-19 en un servicio de urgencias de Madrid. MATERIAL Y MÉTODOS: Estudio retrospectivo de series de casos que incluyó a todos los pacientes atendidos de manera consecutiva en un servicio de urgencias terciario y urbano en Madrid, del 1 al 31 de marzo. La muestra se dividió: no COVID-19, COVID-19 no investigado, COVID-19 posible, COVID-19 probable, COVID-19 confirmado. Las diferencias entre los diferentes periodos establecidos por Salud Pública se evaluaron por el test de ANOVA para cada cohorte, incluyendo el número porcentual de test de PCR como covariable. RESULTADOS: Se incluyeron un total de 7.163 casos (4.071 no COVID-19, 563 COVID-19 no investigados, 870 posibles, 648 probables y 1.011 confirmados COVID-19). Las medidas de Salud Pública aplicadas durante cada período mostraron un claro efecto en la proporción de casos para las cinco cohortes. CONCLUSIÓN: La variabilidad de las definiciones de casos y los criterios de las pruebas de diagnóstico pueden tener un impacto en la cantidad de visitas a urgencias y en los casos diagnosticados de COVID-19 en el servicio de Urgencias