A new haematocytometric index: Predicting severity and mortality risk value in COVID-19 patients

Abstract

Introduction Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection. Methods Clinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software. Results 97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0–30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886–0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group. Conclusion NLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.

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“…In fact, the neutrophil-to-lymphocyte ratio (NLR) is probably the most frequently cited severity predictor 21 . Similarly, neutrophil to monocyte ratio, which is highest in the healthy cluster, seems to be another potential candidate in recent studies 18 . Even though eosinophils appear to have a limited role in this kind of immune response, previous studies found eosinophils percentage to significantly decrease in SARS-CoV-19 compared to other causes of pneumonia, and its recovery to be parallel to CT-scan improvement and therefore eventually in patient groups with higher recovery rates 22 .…”

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“…Additionally, with a cutoff point of 4.4, NLR had a sensitivity of 78.5% and specificity of 68.2% for predicting severe disease. [42] A lower ALC is related to the risk of COVID-19 progression. The CALL score uses it as a variable for predicting pneumonia progression.…”

“…Additionally, with a cutoff point of 4.4, NLR had a sensitivity of 78.5% and specificity of 68.2% for predicting severe disease. [42]…”

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“…Complete cases were considered. The inclusion of variables in the final models were based on the following criteria: 1) significance in Kaplan-Meier and/or univariable analyses; 2) association with survival according to the previous studies [9][10][11][12][13][14]; 3) clinical knowledge.…”