Evidence map›Paper›PMID 36387722›Full record

ArticleJournal of family medicine and primary care2022

Routine hematology parameters in COVID-19: A predictor of disease severity and mortality.

Rupali B Awale, Ashutosh Singh, Prabhaker Mishra, Prateek S Bais, Khare Vansh, Rafat Shamim, Tanmoy Ghatak, Zia Hashim, Devendra Gupta, Alok Nath and 3 more

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Rupali B AwaleDepartment of Laboratory Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Ashutosh SinghDepartment of Laboratory Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Prabhaker MishraDepartment of Biostatistics and Health Informatics, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Prateek S BaisDepartment of Anaesthesiology, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Khare VanshDepartment of Anaesthesiology, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Rafat ShamimDepartment of Anaesthesiology, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Tanmoy GhatakDepartment of Emergency Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Zia HashimDepartment of Pulmonary Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Devendra GuptaDepartment of Anesthesia, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Alok NathDepartment of Pulmonary Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Ratinder K SinghDepartment of Emergency Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Chandrakanta SinghDepartment of Emergency Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Shantanu PandeDepartment of Cardiovascular and Thoracic Surgery, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Our understanding of the pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still evolving and is limited for prognostication. The study was performed to predict severity and mortality based on hematology parameters in coronavirus disease (COVID-19). Material and Methods: The study was a single-center retrospective analysis of 240 patients with COVID-19. The hematological parameters were compared between different grades of severity. The receiver operating characteristics (ROC) curve along with the Classification and Regression Trees (CART) methods were used for the analysis. Result: The total leukocyte count, absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), and neutrophil-monocyte ratio (NMR) were increasing along with an increase in severity; while the absolute lymphocyte count and lymphocyte-monocyte ratio (LMR) were decreasing ( Conclusion: With the increase in severity there was an increase in the total leukocyte count and absolute neutrophil count while the absolute lymphocyte count decreased. On admission, the cut-off value of NLR >5.2, NMR >12.1, while LMR <2.4 may predict severity and mortality in COVID-19.

Indexed as

Complete blood countCOVID-19hematologylymphocyte-monocyte ratiomortalityneutrophil-lymphocyte ratiosevere disease

Identifiers

PMID36387722
PMCPMC9648217

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.