Harmonized D-dimer levels upon admission for prognosis of COVID-19 severity: Results from a Spanish multicenter registry (BIOCOVID-Spain study).

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.

Edad vascular de una muestra de población general del área sanitaria de Toledo (España). Estudio RICARTO / Vascular age in a sample of general population of the sanitary area of Toledo (Spain). RICARTO study

Objetivos: Conocer la edad vascular (EV) de una muestra de población general del área sanitaria de Toledo incluida en el estudio RICARTO.Pacientes y métodoEstudio epidemiológico transversal realizado en población general ≥18 años, aleatorizada según tarjeta sanitaria. La EV se calculó a partir del riesgo cardiovascular (RCV) absoluto estimado con las escalas de Framingham y SCORE (la presencia de diabetes mellitus duplicó el RCV obtenido en varones y lo cuadruplicó en mujeres). Se excluyeron los sujetos con patología cardiovascular o renal. Se realizó ANCOVA para ajustar y comparar las medias de EV por edad y sexo.ResultadosSe analizaron 1.496 individuos (53,54% mujeres), con una edad media (DE) de 48,77 (14,89) años. La EV media fue 51,37 (19,13) años con Framingham y 57,09 (17,63) años con SCORE, resultando significativamente mayor en varones, nivel de estudios bajo, hipertensión arterial, dislipidemia, hipertrigliceridemia, diabetes mellitus, obesidad abdominal, obesidad general, tabaquismo y en sujetos con 5 factores de RCV frente a ninguno (p<0,001 en todos). Las mayores diferencias (D de Cohen >0,5) se hallaron entre no diabéticos y diabéticos (1,58 Framingham; 2,44 SCORE), normotensos e hipertensos (1,64 Framingham; 1,19 SCORE) y no dislipidémicos y dislipidémicos (0,95 Framingham; 0,66 SCORE).ConclusionesEn nuestra muestra la EV es 2,5años superior a la cronológica con la ecuación de Framingham y más de 8años con la del SCORE. El control de los factores de RCV es clave para lograr una EV más próxima a la real y lograr una mejor salud cardiovascular de la población. (AU)

Objective: To know the vascular age (VA) of a sample of general population included in the RICARTO study.Patients and methodEpidemiological 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.Results1,496 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 D >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).ConclusionsVA 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. (AU)

Characteristics and laboratory findings on admission to the emergency department among 2873 hospitalized patients with COVID-19: the impact of adjusted laboratory tests in multicenter studies. A multicenter study in Spain (BIOCOVID-Spain study).

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.

[Vascular age in a sample of general population of the sanitary area of Toledo (Spain). RICARTO study]. / Edad vascular de una muestra de población general del área sanitaria de Toledo (España). Estudio RICARTO.

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 (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. 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 5CVR factors vs none (P<.001 in all). Higher differences (Cohen's D >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.

Cuidado con la biotina: un problema creciente en la práctica clínica / Awareness of biotin: A growing problem in clinical practice

No disponible

La Asociación Española de Biopatología Médica-Medicina del Laboratorio aclara conceptos sobre recertificación y registro profesionales / The Spanish Association of Medical Biopathology-Laboratory Medicine clarifies concepts related with recertification as well as with professional registration

No disponible

Herramientas para la evaluación de las competencias profesionales / Toolkit for professional competencies assessment of Medicine Laboratory specialists

No disponible

Recertificación de los especialistas en Análisis Clínicos y Bioquímica Clínica / Re-accreditation of specialists in Clinical Analysis and Clinical Biochemistry

La recertificación consiste en certificar la renovación de las competencias específicas de los profesionales titulados referidos en la ley de ordenación de las profesiones sanitarias. El objetivo es certificar que el profesional esté cualificado para realizar un ejercicio profesional con el fin de garantizar una asistencia sanitaria de calidad. Las organizaciones colegiales profesionales y las sociedades científicas deben contribuir a facilitar el camino del desarrollo profesional y a la Administración sanitaria le corresponde ser valedora y garante en todo el proceso (AU)

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 (AU)