Introduction: Coronavirus disease 2019 (COVID-19) pandemic has caused unprecedented mortality and has stretched the health infrastructure thin worldwide, especially in low- and middle-income countries. There is a need to evaluate easily available biomarkers for their clinical relevance for poor outcomes in severe cases of COVID-19. It is also known that comorbidities affect these biomarkers with or without COVID-19. We aimed to unearth the influence of comorbidities on feasible hematological predictive markers for mortality in hospitalized severe COVID-19 patients. Materials and Methods: This is a retrospective study done on severe COVID-19 hospitalized patients, diagnosed with RT polymerase chain reaction (n = 205), were investigated. Comorbidities associated with the patients were tracked and scored according to Charlson comorbidity index (CCI). CCI score of zero was grouped in A, those with CCI score 1–4 into group B and those with CCI scores ≥ 5 into group C. Correlation between hematological parameters and CCI scores was analyzed using Pearson correlation coefficient. Optimal cut-off and odds ratio was derived from receiver operating characteristic (ROC) curve analysis. Results: Among the 205 severe COVID-19 patients age, C-reactive protein (CRP), neutrophil lymphocyte ratio (NLR), derived NLR (dNLR), absolute neutrophil count (ANC) and total leukocyte count (TLC) were found to be statistically significant independent risk factors for predicting COVID-19 mortality (p < 0.01). In group A, cut off for CRP was 51.5 mg/L (odds ratio [OR]: 26.7; area under curve [AUC]: 0.867), TLC was 11,850 cells/mm³ (OR: 11.7; AUC: 0.731), NLR was 11.76 (OR: 14.3; AUC: 0.756), dNLR was 5.77 (OR: 4.89; AUC: 0.659), ANC was 13,110 cells/mm³ (OR: 1.68; AUC: 0.553). In group B, cut off for CRP was 36.5 mg/L (OR: 32.1; AUC: 0.886), TLC was 11,077 cells/mm³ (OR: 12.1; AUC: 0.722), NLR was 8.27 (OR: 18.9; AUC: 0.827), dNLR was 3.79 (OR: 9.26; AUC: 0.727), ANC was 11,420 cells/mm³ (OR: 2.42; AUC: 0.564). In group C, cut-off for CRP was 23.7 mg/L (OR: 32.7; AUC: 0.904), TLC was 10,480 cells/mm³ (OR: 21.2; AUC: 0.651), NLR was 6.29 (OR: 23.5; AUC: 0.647), dNLR was 1.93 (OR: 20.8; AUC: 0.698), ANC was 6650 cells/mm³ (OR: 2.45; AUC: 0.564). Conclusions: In severe COVID-19 patients, CRP was the most reliable biomarker to predict mortality followed by NLR. Presence, type, and number of co-morbidities influence the levels of the biomarkers and the clinically relevant cut-offs associated with mortality.

BackgroundHealthcare systems worldwide are overwhelmed in the treatment of ever-increasing number of COVID 19 patients which has affected the management of non COVID 19 patients as well. We tested the adherence to Severe Acute Respiratory Illness (SARI) definition laid down by The Government of India for triaging of suspected COVID 19 cases, and the impact of this strategy on the non covid patients admitted to SARI ICU as suspected cases of covid 19 disease.MethodsA cross-sectional study was conducted to reflect the appropriateness and adherence of SARI definition in two tertiary care medical college hospitals in triaging COVID 19 suspect cases and assessed the challenges in admission, diagnosis and treatment of non COVID 19 diseases. The study involved 78 patients in two multidisciplinary units of medical college hospitals in the month of June – July 2020. Data related to demographics, severity of illness, advanced life supports required, delay in diagnosis, intervention and treatment of patients in SARI ICU due to suspect COVID 19 status was documented. ResultsAdherence to SARI definition for triaging COVID suspect cases was 19.2%. Respiratory symptoms amounted to 24% of presenting complaints. Despite hindrance in the diagnosis (17.9%) and treatment (12.8%), mortality among patients in SARI ICU was limited to 14.10%. The results were in-significant when checked for the various factors associated with mortality.ConclusionThe adherence to SARI definition while triaging COVID suspect cases to intensive care units was low among the clinicians. There were hindrances in the diagnosis and treatment of non COVID diseases due to COVID suspect status of the patient. However, treatment outcomes of these patients were comparable to critically ill population with similar disease severity scores suggesting that quality of care may not have been compromised despite the pandemic. Poor adherence to SARI definition while triaging might have led to economic implications on patients and healthcare systems but further studies are required to comment regarding the same.