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Blood parameters measured on admission as predictors of outcome for COVID-19; a prospective UK cohort study
Preprint
in English
| medRxiv
| ID: ppmedrxiv-20137935
ABSTRACT
IntroductionCOVID-19 has an unpredictable clinical course so prognostic biomarkers would be invaluable when triaging patients on admission to hospital. Many biomarkers have been suggested using large observational datasets but sample timing is crucial to ensure prognostic relevance. The DISCOVER study prospectively recruited patients with COVID-19 admitted to a UK hospital and analysed a panel of putative prognostic biomarkers on the admission blood sample to identify markers of poor outcome. MethodsConsecutive patients admitted to hospital with proven or clinicoradiological suspected COVID-19 were recruited. Admission bloods were extracted from the clinical laboratory. A panel of biomarkers (IL-6, suPAR, KL-6, Troponin, Ferritin, LDH, BNP, Procalcitonin) were performed in addition to routinely performed markers (CRP, neutrophils, lymphocytes, neutrophillymphocyte ratio). Age, NEWS score and CURB-65 were included as comparators. All biomarkers were tested in logistic regression against a composite outcome of non-invasive ventilation, intensive care admission, or death, with Area Under the Curve (AUC) figures calculated. Results155 patients had 28-day outcomes at the time of analysis. CRP (AUC 0.51, CI0.40-0.62), lymphocyte count (AUC 0.62, CI0.51-0.72), and other routine markers did not predict the primary outcome. IL-6 (AUC 0.78,0.65-0.89) and suPAR (AUC 0.77, CI 0.66-0.85) showed some promise, but simple clinical features alone such as NEWS score (AUC 0.74, 0.64-0.83) or age (AUC 0.70, 0.61-0.78) performed nearly as well. DiscussionAdmission blood biomarkers have only moderate predictive value for predicting COVID-19 outcomes, while simple clinical features such as age and NEWS score outperform many biomarkers. IL-6 and suPAR had the best performance, and further studies should validate these biomarkers in a prospective fashion.
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Full text:
Available
Collection:
Preprints
Database:
medRxiv
Type of study:
Cohort_studies
/
Observational study
/
Prognostic study
Language:
English
Year:
2020
Document type:
Preprint