Combined use of the neutrophil-to-lymphocyte ratio and CRP to predict 7-day disease severity in 84 hospitalized patients with COVID-19 pneumonia: a retrospective cohort study

Abstract

Background: Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide from Wuhan. An easy-to-use index capable of the early identification of inpatients who are at risk of becoming critically ill is urgently needed in clinical practice. Hence, the aim of this study was to explore an easy-to-use nomogram and a model to triage patients into risk categories to determine the likelihood of developing a critical illness. Methods: A retrospective cohort study was conducted. We extracted data from 84 patients with laboratoryconfirmed COVID-19 from one designated hospital. The primary endpoint was the development of severe/ critical illness within 7 days after admission. Predictive factors of this endpoint were selected by LASSO Cox regression model. A nomogram was developed based on selected variables. The predictive performance of the derived nomogram was evaluated by calibration curves and decision curves. Additionally, the predictive performances of individual and combined variables under study were evaluated by receiver operating characteristic curves. The developed model was also tested in a separate validation set with 71 laboratoryconfirmed COVID-19 patients. Results: None of the 84 inpatients were lost to follow-up in this retrospective study. The primary endpoint occurred in 23 inpatients (27.4%). The neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were selected as the final prognostic factors. A nomogram was developed based on the NLR and CRP. The calibration curve and decision curve indicated that the constructed nomogram model was clinically useful.The AUCs for the NLR, CRP and Combined Index in both training set and validation sets were 0.685 (95%

Acute Ischemic Stroke in COVID-19: A Case-Based Systematic Review

“…In this study, there is a trend that patients with good outcomes have lower NLR, CRP, and serum ferritin compared to patients who died or remained critically ill. NLR has been shown to have a good predictive value in assessing patients who are likely to have severe SARS-CoV2 infection (30,(93)(94)(95)(96). In particular, it has been proposed that patients who are older and have NLR values of more than 3 are likely to require intensive care (27).…”

Predictive values of neutrophil-to-lymphocyte ratio on disease severity and mortality in COVID-19 patients: a systematic review and meta-analysis

“…The remaining 42 studies were further scrutinized by reading the full text. Finally, only 19 studies were included in this meta-analysis, of which 9 reported the predictive value on disease severity [26][27][28][29][30][31][32][33][34], 6 reported the predictive value on mortality [35][36][37][38][39][40], and 4 reported the predictive value on both disease severity and mortality [41][42][43][44].…”

A descriptive study of random forest algorithm for predicting COVID-19 patients outcome

“…By 26 June 2020, COVID-19 had affected 213 countries, with over 9,621,470 confirmed cases and 487,295 deaths worldwide (COVID-19 CoV—Update , accessed 26 June 2020). The least absolute shrinkage and selection operator (LASSO) regression has been used to identify the important factors of severity transition in COVID-19 patients ( Liu et al, 2020 ), and critically ill patients exhibited respiratory failure, acute respiratory distress syndrome, heart failure, and septic shock, which increased the mortality of COVID-19 patients ( Zhou et al, 2020 ).…”