Evidence map›Paper›PMID 35935776›Full record

ArticleFrontiers in medicine2022

Comparative analysis of neutrophil to lymphocyte ratio and derived neutrophil to lymphocyte ratio with respect to outcomes of in-hospital coronavirus disease 2019 patients: A retrospective study.

Muhammad Sohaib Asghar, Mohammed Akram, Farah Yasmin, Hala Najeeb, Unaiza Naeem, Mrunanjali Gaddam, Muhammad Saad Jafri, Muhammad Junaid Tahir, Iqra Yasin, Hamid Mahmood and 2 more

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Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

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11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Muhammad Sohaib AsgharDepartment of Internal Medicine, Dow University Hospital, Karachi, Pakistan.
Mohammed AkramDepartment of Internal Medicine, Liaquat National Hospital and Medical College, Karachi, Pakistan.
Farah YasminDepartment of Internal Medicine, Dow University of Health Sciences, Karachi, Pakistan.
Hala NajeebDepartment of Internal Medicine, Dow University of Health Sciences, Karachi, Pakistan.
Unaiza NaeemDepartment of Internal Medicine, Dow University of Health Sciences, Karachi, Pakistan.
Mrunanjali GaddamDepartment of Internal Medicine, The Brooklyn Hospital Center, Brooklyn, NY, United States.
Muhammad Saad JafriDepartment of Internal Medicine, Ziauddin University Hospital, Karachi, Pakistan.
Muhammad Junaid TahirDepartment of Internal Medicine, Lahore General Hospital, Lahore, Pakistan.
Iqra YasinDepartment of Internal Medicine, Liaquat National Hospital and Medical College, Karachi, Pakistan.
Hamid MahmoodDepartment of Internal Medicine, Lahore General Hospital, Lahore, Pakistan.
Qasim MehmoodDepartment of Internal Medicine, King Edward Medical University, Lahore, Pakistan.
Roy Rillera MarzoDepartment of Community Medicine, International Medical School, Management and Science University, Shah Alam, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction and objectives: In patients with coronavirus disease 2019 (COVID-19), several abnormal hematological biomarkers have been reported. The current study aimed to find out the association of neutrophil to lymphocyte ratio (NLR) and derived NLR (dNLR) with COVID-19. The objective was to compare the accuracy of both of these markers in predicting the severity of the disease. Materials and methods: The study was conducted in a single-center having patients with COVID-19 with a considerable hospital stay. NLR is easily calculated by dividing the absolute neutrophil count (ANC) with the absolute lymphocyte count (ALC) {ANC/ALC}, while dNLR is calculated by ANC divided by total leukocyte count minus ANC {ANC/(WBC-ANC)}. Medians and interquartile ranges (IQR) were represented by box plots. Multivariable logistic regression was performed obtaining an odds ratio (OR), 95% CI, and further adjusted to discover the independent predictors and risk factors associated with elevated NLR and dNLR. Results: A total of 1,000 patients with COVID-19 were included. The baseline NLR and dNLR were 5.00 (2.91-10.46) and 4.00 (2.33-6.14), respectively. A cut-off value of 4.23 for NLR and 2.63 for dNLR were set by receiver operating characteristic (ROC) analysis. Significant associations of NLR were obtained by binary logistic regression for dependent outcome variables as ICU stay ( Conclusion: Both markers are equally reliable and sensitive for predicting in-hospital outcomes of patients with COVID-19. Early detection and predictive analysis of these markers can allow physicians to risk assessment and prompt management of these patients.

Indexed as

COVID-19managementmarkerNLRseverity

Identifiers

PMID35935776
PMCPMC9354523

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