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Objectives. To analyse and compare 30-day mortality prognostic power of several biomarkers (C-reactive protein, procalcitonin, lactate and suPAR) in patients seen in emergency departments (ED) due to infections. Secondly, if these could improve the accuracy of systemic inflammatory response syndrome (SIRS) and quick Sepsis-related Organ Failure Assessment (qSOFA). Methods. A prospective, observational and analytical study was carried out on patients who were treated in an ED of one of the eight participating hospitals. An assessment was made of 32 independent variables that could influence mortality at 30 days. They covered epidemiological, comorbidity, functional, clinical and analytical factors. Results. The study included 347 consecutive patients, 54 (15.6%) of whom died within 30 days of visiting the ED. SUPAR has got the best biomarker area under the curve (AUC)-ROC to predict mortality at 30 days of 0.836 (95% CI: 0.765-0.907; P 10 ng/mL who had a sensitivity of 70% and a specificity of 86%. The score qSOFA ≥ 2 had AUC-ROC of 0.707 (95% CI: 0.621-0.793; P < .001) with sensitivity of 53% and a specificity of 89%. The mixed model (suPAR > 10 ng/mL plus qSOFA ≥ 2) has improved the AUC-ROC to 0.853 [95% CI: 0.790-0.916; P < .001] with the best prognostic performance: sensitivity of 39% and a specificity of 97% with a negative predictive value of 90%. Conclusions. suPAR showed better performance for 30-day mortality prognostic power from several biomarkers in the patients seen in ED due to infections. Score qSOFA has better performance that SRIS and the mixed model (qSOFA ≥ 2 plus suPAR > 10 ng/mL) increased the ability of qSOFA.

Objective To know the vascular age (VA) of a sample of general population included in the RICARTO study. Patients and method Epidemiological study of the general population aged ≥ 18 from the Health Area of Toledo, based on the health card database. VA was calculated from the absolute cardiovascular risk (CVR) estimated with the Framingham and SCORE equations (type 2 diabetes increased CVR in SCORE 2-fold in men and 4-fold in women). Patients with cardiovascular or renal disease were excluded. An ANCOVA analysis was conducted to adjust and compare the mean of VA by age and sex. Results 1,496 subjects (53.54% women) were analyzed. Mean (SD) age was 48.77 (14.89) years old and. Mean VA was 51.37 (19.13) with Framingham equation and 57.09 (17.63) years old with SCORE equation. VA was significantly higher in men, low education level, arterial hypertension, dyslipidemia, hypertriglyceridemia, diabetes mellitus, abdominal obesity, general obesity, smoking and in individuals with 5 CVR factors vs none (P 0.5) were found in non-diabetic vs diabetic people (1.58 Framingham; 2.44 SCORE), normotensive vs hypertensive subjects (1.64 Framingham; 1.19 SCORE), and non-dyslipidemia vs presence of dyslipidemia (0.95 Framingham; 0.66 SCORE). Conclusions VA of our sample is two and a half years older than chronological one with Framingham equation and more than eight years with SCORE equation. Control of CVR factors is the key to get a VA closer to real and to obtain a better cardiovascular health in the population.

Resumen Objetivos Conocer la edad vascular (EV) de una muestra de poblacion general del area sanitaria de Toledo incluida en el estudio RICARTO. Pacientes y metodo Estudio epidemiologico transversal realizado en poblacion general ≥ 18 anos, aleatorizada segun tarjeta sanitaria. La EV se calculo a partir del riesgo cardiovascular (RCV) absoluto estimado con las escalas de Framingham y SCORE (la presencia de diabetes mellitus duplico el RCV obtenido en varones y lo cuadruplico en mujeres). Se excluyeron los sujetos con patologia cardiovascular o renal. Se realizo ANCOVA para ajustar y comparar las medias de EV por edad y sexo. Resultados Se analizaron 1.496 individuos (53,54% mujeres), con una edad media (DE) de 48,77 (14,89) anos. La EV media fue 51,37 (19,13) anos con Framingham y 57,09 (17,63) anos con SCORE, resultando significativamente mayor en varones, nivel de estudios bajo, hipertension arterial, dislipidemia, hipertrigliceridemia, diabetes mellitus, obesidad abdominal, obesidad general, tabaquismo y en sujetos con 5 factores de RCV frente a ninguno (p 0,5) se hallaron entre no diabeticos y diabeticos (1,58 Framingham; 2,44 SCORE), normotensos e hipertensos (1,64 Framingham; 1,19 SCORE) y no dislipidemicos y dislipidemicos (0,95 Framingham; 0,66 SCORE). Conclusiones En nuestra muestra la EV es 2,5 anos superior a la cronologica con la ecuacion de Framingham y mas de 8 anos con la del SCORE. El control de los factores de RCV es clave para lograr una EV mas proxima a la real y lograr una mejor salud cardiovascular de la poblacion.

Coagulopathy is a key feature of COVID-19 and D-dimer has been reported as a predictor of severity. However, because D-dimer test results vary considerably among assays, resolving harmonization issues is fundamental to translate findings into clinical practice. In this retrospective multicenter study (BIOCOVID study), we aimed to analyze the value of harmonized D-dimer levels upon admission for the prediction of in-hospital mortality in COVID-19 patients. All-cause in-hospital mortality was defined as endpoint. For harmonization of D-dimer levels, we designed a model based on the transformation of method-specific regression lines to a reference regression line. The ability of D-dimer for prediction of death was explored by receiver operating characteristic curves analysis and the association with the endpoint by Cox regression analysis. Study population included 2663 patients. In-hospital mortality rate was 14.3%. Harmonized D-dimer upon admission yielded an area under the curve of 0.66, with an optimal cut-off value of 0.945 mg/L FEU. Patients with harmonized D-dimer >= 0.945 mg/L FEU had a higher mortality rate (22.4% vs. 9.2%; p < 0.001). D-dimer was an independent predictor of in-hospital mortality, with an adjusted hazard ratio of 1.709. This is the first study in which a harmonization approach was performed to assure comparability of D-dimer levels measured by different assays. Elevated D-dimer levels upon admission were associated with a greater risk of in-hospital mortality among COVID-19 patients, but had limited performance as prognostic test.

Identification of predictors for severe disease progression is key for risk stratification in COVID-19 patients. We aimed to describe the main characteristics and identify the early predictors for severe outcomes among hospitalized patients with COVID-19 in Spain. This was an observational, retrospective cohort study (BIOCOVID-Spain study) including COVID-19 patients admitted to 32 Spanish hospitals. Demographics, comorbidities and laboratory tests were collected. Outcome was in-hospital mortality. For analysis, laboratory tests values were previously adjusted to assure the comparability of results among participants. Cox regression was performed to identify predictors. Study population included 2873 hospitalized COVID-19 patients. Nine variables were independent predictors for in-hospital mortality, including creatinine (Hazard ratio [HR]:1.327; 95% Confidence Interval [CI]: 1.040-1.695, p = .023), troponin (HR: 2.150; 95% CI: 1.155-4.001; p = .016), platelet count (HR: 0.994; 95% CI: 0.989-0.998; p = .004) and C-reactive protein (HR: 1.037; 95% CI: 1.006-1.068; p = .019). This is the first multicenter study in which an effort was carried out to adjust the results of laboratory tests measured with different methodologies to guarantee their comparability. We reported a comprehensive information about characteristics in a large cohort of hospitalized COVID-19 patients, focusing on the analytical features. Our findings may help to identify patients early at a higher risk for an adverse outcome.

To know the vascular age (VA) of a sample of general population included in the RICARTO study.Epidemiological study of the general population aged ≥18 from the Health Area of Toledo, based on the health card database. VA was calculated from the absolute cardiovascular risk (CVR) estimated with the Framingham and SCORE equations (type2 diabetes increased CVR in SCORE 2-fold in men and 4-fold in women). Patients with cardiovascular or renal disease were excluded. An ANCOVA analysis was conducted to adjust and compare the mean of VA by age and sex.1,496 subjects (53.54% women) were analyzed. Mean (SD) age was 48.77 (14.89) years old and. Mean VA was 51.37 (19.13) with Framingham equation and 57.09 (17.63) years old with SCORE equation. VA was significantly higher in men, low education level, arterial hypertension, dyslipidemia, hypertriglyceridemia, diabetes mellitus, abdominal obesity, general obesity, smoking and in individuals with 5CVR factors vs none (P.001 in all). Higher differences (Cohen's D0.5) were found in non-diabetic vs diabetic people (1.58 Framingham; 2.44 SCORE), normotensive vs hypertensive subjects (1.64 Framingham; 1.19 SCORE), and non-dyslipidemia vs presence of dyslipidemia (0.95 Framingham; 0.66 SCORE).VA of our sample is two and a half years older than chronological one with Framingham equation and more than eight years with SCORE equation. Control of CVR factors is the key to get a VA closer to real and to obtain a better cardiovascular health in the population.

Re-accreditation consists in certifying the renewal of specific competencies of qualified professionals as mentioned in the health profession management law. The objective is to certify that the professional is qualified to perform a professional exercise in order to guarantee quality healthcare. The professional bodies and scientific societies should contribute by facilitating the continuing professional development, and the Health Administration should be responsible for guaranteeing the whole process.