Calculated plasma osmolality at hospital admission correlates well with eGFR and D-Dimer, a simple outcome predictor and guiding tool for management of severe COVID-19 patients.

AIMS: To evaluate calculated total plasma osmolality as a marker of outcome prediction, fluid and metabolic balance, thrombotic risk in severe COVID-19 patients. METHODS: Retrospective data of RT-PCR confirmed hospitalized severe COVID-19 patients (total: n = 175 patients, including diabetic subset: n = 102) were analyzed. Clinically applicable cut-offs were derived using receiver operating characteristic (ROC) curve analysis for calculated total osmolality, eGFR, and D-dimer, and their correlations were studied. RESULTS: Among 175 severe COVID-19 patients, a significant association with mortality was seen with respect to calculated total osmolality (p < 0.001), eGFR (p < 0.001), and D-dimer (p < 0.001). In the total cohort, applicable cut-offs based on ROC curve in predicting outcome were, for total osmolality 299 mosm/kg (area under the curve (AUC)-0.773, odds ratio (OR)-1.09), eGFR 61.5 ml/min/m2 (AUC-0.789, OR-0.96), D-dimer 5.13 (AUC-0.814, OR-2.65) respectively. In diabetic subset, the cut-offs for total osmolality were 298 mosm/kg (AUC-0.794, OR-1.12), eGFR 44.9 ml/min/m2 (AUC-0.774, OR-0.96) and D-dimer 1.59 (AUC-0.769, OR-1.52) respectively. CONCLUSIONS: Applicable cut-offs for calculated total plasma osmolality, eGFR, and D-dimer predicts clinical outcome in severe COVID-19 with and without diabetes. Correlation studies validated calculated total osmolality as a marker of the combined effect of fluid and metabolic imbalance, compromised renal function and hypercoagulability.

Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India.

BACKGROUND AND AIMS: COVID-19 pandemic has strained the health infrastructure globally, providing an opportunity to identify cost-effective biomarkers. We aimed to identify simple hematological prognostic markers in hospitalized severe COVID-19 patients with and without diabetes. METHODS: Retrospective study of RT-PCR confirmed hospitalized severe COVID-19 patients (total: n = 154 patients, including diabetic subset n = 57) were analyzed. Clinically applicable cut-offs were derived using receiver operating characteristic (ROC) curve analysis for total leucocyte count (TLC), absolute neutrophil count (ANC), neutrophil lymphocyte ratio (NLR), and derived neutrophil lymphocyte ratio (dNLR) in order to prognosticate the outcome. RESULTS: Among 154 severe COVID-19 patients, significant association with mortality was seen with respect to TLC(p < 0.001), ANC (p < 0.001), NLR(p < 0.001) and dNLR(p < 0.001). In the total cohort, applicable cut-offs based on ROC curve in predicting outcome were, for TLC 8950 cells/mm3 (area under curve (AUC)-0.764, odds ratio (OR)-7.53), ANC 7679 cells/mm3 (AUC-0.789, OR-8.14), NLR 5.13 (AUC-0.741, OR-4.77), dNLR 3.44 (AUC -0.741, OR-4.43) respectively.In diabetic subset, the cut-offs for TLC was 8950 cells/mm3 (AUC -0.762, OR-14.9), ANC 6510 cells/mm3 (AUC -0.773, OR-16.8), NLR 5.13(AUC -0.678, OR-6) and dNLR 3.25(AUC -0.685, OR-4.7) respectively. CONCLUSIONS: In severe COVID-19 patients irrespective of diabetes, a simple, applicable total leucocyte count cut-off, 8950 cells/mm3 , together with easily derived cut-offs for ANC, NLR, dNLR may serve as cost-effective prognosticators of clinical outcome. A normal TLC may be misleading in the intensive care and the above applicable cut-off for TLC serves as an early warning tool for high-risk identification and better in-hospital management. Even with similar or lower cut-offs, diabetics had a higher mortality.