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.

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)