Procalcitonin concentration in the emergency department predicts 30-day mortality in COVID-19 better than the lymphocyte count, the neutrophil-tolymphocyte ratio, or the C-reactive protein level. / 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.

OBJECTIVES: 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. MATERIAL AND 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.

OBJETIVO: 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. METODO: 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. CONCLUSIONES: 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.

Clinical presentation and outcome across age categories among patients with COVID-19 admitted to a Spanish Emergency Department.

PURPOSE: To determine the differences by age-dependent categories in the clinical profile, presentation, management, and short-term outcomes of patients with laboratory-confirmed COVID-19 admitted to a Spanish Emergency Department (ED). METHODS: Secondary analysis of COVID-19_URG-HCSC registry. We included all consecutive patients with laboratory-confirmed COVID-19 admitted to the ED of the University Hospital Clinico San Carlos (Madrid, Spain). The population was divided into six age groups. Demographic, baseline and acute clinical data, and in-hospital and 30-day outcomes were collected. RESULTS: 1379 confirmed COVID-19 cases (mean age 62 (SD 18) years old; 53.5% male) were included (18.1% < 45 years; 17.8% 45-54 years; 17.9% 55-64 years; 17.2% 65-74 years; 17.0% 75-84 years; and 11.9% ≥ 85 years). A statistically significant association was found between demographic, comorbidity, clinical, radiographic, analytical, and therapeutic variables and short-term results according to age-dependent categories. There were less COVID-specific symptoms and more atypical symptoms among older people. Age was a prognostic factor for hospital admission (aOR = 1.04; 95% CI 1.02-1.05) and in-hospital (aOR = 1.08; 95% CI 1.05-1.10) and 30-day mortality (aOR = 1.07; 95% CI 1.04-1.09), and was associated with not being admitted to intensive care (aOR = 0.95; 95% CI 0.93-0.98). CONCLUSIONS: Older age is associated with less COVID-specific symptoms and more atypical symptoms, and poor short-term outcomes. Age has independent prognostic value and may help in shared decision-making in patients with confirmed COVID-19 infection.

Engineering Erg10 Thiolase from Saccharomyces cerevisiae as a Synthetic Toolkit for the Production of Branched-Chain Alcohols.

Thiolases catalyze the condensation of acyl-CoA thioesters through the Claisen condensation reaction. The best described enzymes usually yield linear condensation products. Using a combined computational/experimental approach, and guided by structural information, we have studied the potential of thiolases to synthesize branched compounds. We have identified a bulky residue located at the active site that blocks proper accommodation of substrates longer than acetyl-CoA. Amino acid replacements at such a position exert effects on the activity and product selectivity of the enzymes that are highly dependent on a protein scaffold. Among the set of five thiolases studied, Erg10 thiolase from Saccharomyces cerevisiae showed no acetyl-CoA/butyryl-CoA branched condensation activity, but variants at position F293 resulted the most active and selective biocatalysts for this reaction. This is the first time that a thiolase has been engineered to synthesize branched compounds. These novel enzymes enrich the toolbox of combinatorial (bio)chemistry, paving the way for manufacturing a variety of α-substituted synthons. As a proof of concept, we have engineered Clostridium's 1-butanol pathway to obtain 2-ethyl-1-butanol, an alcohol that is interesting as a branched model compound.