Background: Most outcome-predictive models for COVID-19 patients use hospital admission data, offering a spontaneous mortality risk estimation. We aimed to elaborate on a tool that could be applied repeatedly, thus being more suitable for these patients' rapidly changing clinical course.
Methods: In this prospective study, we evaluated 560 samples derived from 156 patients hospitalized for COVID-19 in a single center. Age >61 years, male sex, comorbidities >2, need for intensive care unit admission, lactate dehydrogenase (LDH) >408 U/L, Neutrophil/Lymphocyte Ratio (NLR) >17, C-reactive protein (CRP) >10 mg/dl, and D-dimers >3,200 ng/ml were incorporated in an eight-scale score (MaD-CLINYC) after optimal scaling, ridge regression, and bootstrapping, which was documented to correlate with outcome independently of one or more samples analyzed, day from admission at sampling, and need for delivery. Validation process was performed over 574 samples derived from three centers.
Results: The developing and the validation cohort Area under Curve (AUC) was 0.90 (95 % Confidence Interval: 0.82-0.98) and 0.91 (0.88-0.94), respectively (p =0.822). A MaD-CLINYC score ≥4 had 75 % sensitivity and 81 % specificity to predict fatal outcome.
Conclusions: MaD-CLINYC score is a powerful, feasible, easy-to-use, dynamic tool to assess the risk of the outcome, thus assisting clinicians in close monitoring and timely decisions in COVID-19 hospitalized patients. HIPPOKRATIA 2021, 25 (3):119-125.
Keywords: C-reactive protein; COVID-19; CRP; Coronavirus disease 2019; D-dimers; LDH; NLR; Neutrophil/Lymphocyte Ratio; intensive care unit; lactate dehydrogenase; mortality.
Copyright 2021, Hippokratio General Hospital of Thessaloniki.