Dataset Information

The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients.

ABSTRACT:

Aim

To accumulate evidence that indicated the key role played by virus-triggered inflammation in the 2019-novel coronavirus disease (COVID-19) which emerged in Wuhan City and rapidly spread throughout China.

Methods

Age, neutrophil(NEU)-to-lymphocyte (LYM) ratio (NLR), lymphocyte-to-monocyte (MON) ratio, platelet-to-lymphocyte ratio (PLR), and C-reactive protein (CRP) of 93 patients with laboratory confirmed COVID-19 were investigated and compared. The receiver operating characteristic curve was applied to determine the thresholds for five bio-markers, and their prognostic values were assessed via the Kaplan-Meier curve and multivariate COX regression models.

Results

The median age was 46.4 years old, and 37cases were females. A total of 27.8% of patients had been to Wuhan, and 73.1% had contacted with people from Wuhan. Fever (83.8%) and cough (70.9%) were the two most common symptoms. Elevated NLR and age were significantly associated with illness severity. The binary logistic analysis identified elevated NLR (hazard risk [HR] 2.46, 95% confidence interval [CI] 1.98-4.57) and age (HR 2.52, 95% CI 1.65-4.83) as independent factors for poor clinical outcome of COVID-19. NLR exhibited the largest area under the curve at 0.841, with the highest specificity (63.6%) and sensitivity (88%).

Conclusions

Elevated age and NLR can be considered independent biomarkers for indicating poor clinical outcomes.

SUBMITTER: Yang AP

PROVIDER: S-EPMC7152924 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients.

Yang Ai-Ping AP Liu Jian-Ping JP Tao Wen-Qiang WQ Li Hui-Ming HM

International immunopharmacology 20200413

<h4>Aim</h4>To accumulate evidence that indicated the key role played by virus-triggered inflammation in the 2019-novel coronavirus disease (COVID-19) which emerged in Wuhan City and rapidly spread throughout China.<h4>Methods</h4>Age, neutrophil(NEU)-to-lymphocyte (LYM) ratio (NLR), lymphocyte-to-monocyte (MON) ratio, platelet-to-lymphocyte ratio (PLR), and C-reactive protein (CRP) of 93 patients with laboratory confirmed COVID-19 were investigated and compared. The receiver operating character ...[more]

PMID: 32304994

Similar Datasets

Project description:ObjectiveTo explore the validity of the neutrophil-to-lymphocyte ratio (NLR) combined with the platelet-to-lymphocyte ratio (PLR) in predicting the short-term prognosis of acute myocardial infarction (AMI).MethodsWe collected the data from a total of 3,246 clinical AMI patients hospitalized in the Second Affiliated Hospital of Dalian Medical University from December 2015 to December 2021. All patients underwent routine blood examination within 2 hours of admission. Outcome was defined as all-cause mortality during hospitalization. A total of 94 pairs of patients were generated by propensity score matching (PSM), and a combined NLR-based and PLR-based indicators was constructed according to receiver operating characteristic (ROC) curves and multivariate logistic regression analysis.ResultsWe finally generated 94 pairs of patients by PSM, and analyzed NLR and PLR in those patients using ROC curves, and converted NLR (optimal cut-off = 5.094) and PLR (optimal cut-off = 165.413) into binary variables according to optimal cut-offs, defined as NLR grouping (5.094 vs. > 5.094, ≤ 5.094 = 0, > 5.094 = 1) and PLR grouping (165.413 vs. > 165.413, ≤ 165.413 = 0, > 165.413 = 1). We constructed a combined indicator (NLR grouping + PLR grouping) based on the results of multivariate logistic regression. Combined indicator has four conditions [Y1 = 0.887 (NLR grouping = 0; PLR grouping = 0); Y2 = 0.949 (NLR grouping = 0; PLR grouping = 1); Y3 = 0.972 (NLR grouping = 1; PLR grouping = 0); and Y4 = 0.988 (NLR grouping = 1; PLR grouping = 1)]. Univariate logistic regression showed that the risk of in-hospital death was significantly increased when the combined indicator of patients was in Y3 (OR = 4.968, 95% CI 2.215-11.141, P < 0.0001) and Y4 (OR = 10.473, 95% CI 4.610-23.793, P < 0.0001). Combined indicator constructed by NLR grouping and PLR grouping can better predict the risk of in-hospital mortality in AMI patients and help clinical cardiologists to more finely care for and treat these high-risk groups to improve their short-term prognostic outcomes.

Dataset Information

The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients.

Aim

Methods

Results

Conclusions

Publications

The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets