Analysis of common biomarkers in capillary blood in routine clinical laboratory. Preanalytical and analytical comparison with venous blood.

OBJECTIVES: Remote self-collected capillary blood samples have been proposed as alternative to venous blood samples as an aid in telemedicine. The aim of this work is to compare the preanalytical and analytical performance of these two types of samples and to study the stability of common measurands in capillary blood. METHODS: Capillary and venous blood samples were collected in parallel from 296 patients in serum tubes to analyze 22 common biochemistry magnitudes after centrifugation and in EDTA tubes to analyze 15 hematologic magnitudes. Quality of the preanalytical process was assessed applying the model of quality indicator. 24 h stability at room temperature was studied by obtaining paired capillary samples. A questionnaire of assessment was conducted. RESULTS: Mean hemolysis index was higher in capillary samples compared to venous blood samples (p<0.001). Regression analysis and difference analysis showed no bias for all studied biochemistry parameters and hematologic parameters, except mean corpuscular volume (MCV), between capillary and venous blood samples. Regarding sample stability, percentage deviation was higher than the corresponding minimum analytical performance specification for ferritin, vitamin D, hematocrit, MCV, mean corpuscular hemoglobin concentration, platelets distribution wide, mean platelet volume and basophils. Finger pricking was perceived as less painful (p<0.05) than venipuncture in participants who undergo more than one blood test per year. CONCLUSIONS: Capillary blood can be used as an alternative to venous blood for the studied parameters in automated common clinical analyzers. Cautious should be taken if samples are not analyzed within 24 h from the collection.

Poder pronóstico de mortalidad a corto plazo delreceptor soluble activador del plasminógeno tipo uroquinasa (suPAR) en los pacientes atendidos en urgencias por infección / Prognostic power of soluble urokinase plasminogen activator receptor (suPAR) for short-term mortality in patients seen in Emergency Departments due to infections

Objetivos. Analizar y comparar el poder predictivo de mortalidad a 30 días de varios biomarcadores (proteína C reactiva, procalcitonina, lactato y suPAR) en los pacientes que acuden al servicio de urgencias (SU) por un episodio de infección. Y, secundariamente, si estos mejoran la capacidad pronóstica de los criterios de sepsis (síndrome de respuesta inflamatoria sistémica-SRIS- y del quick Sepsis-related Organ Failure Assessment –qSOFA-). Métodos. Estudio observacional, prospectivo y analítico. Se incluyó consecutivamente a pacientes atendidos en un SU por un proceso infeccioso. Se analizaron 32 variables independientes (epidemiológicas, de comorbilidad, funcionales, clínicas y analíticas) que pudieran influir en la mortalidad a corto plazo (30 días). Resultados. Se incluyó a 347 pacientes, de los que 54 (15,6%) habían fallecido a los 30 días tras su consulta en el SU. El suPAR es el biomarcador que consigue la mayor área bajo la curva (ABC)-ROC para predecir mortalidad a los 30 días de 0,836 [IC 95%: 0,765-0,907; p< 0,001] con sensibilidad de 53% y especificidad de 89%. El modelo combinado (suPAR > 10 ng/ml con qSOFA ≥ 2) mejora el ABC-ROC a 0,853 [IC 95%: 0,790-0,916; p<0,001] y ofrece el mejor rendimiento pronóstico con una sensibilidad de 39%, especificidad del 97% y un valor predictivo negativo de 90%. Conclusiones. En los pacientes que acuden al SU por un episodio de infección, suPAR presenta una capacidad pronóstica de mortalidad a los 30 días superior al resto de biomarcadores, la qSOFA obtiene mayor rendimiento que los criterios de SRIS, y el modelo combinado qSOFA ≥ 2 con suPAR > 10 ng/ mL mejora el poder predictivo de qSOFA. (AU)

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 < .001) with a cut-off > 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. (AU)