Evidence map›Paper›PMID 42890638›Full record

ArticleTanaffos2025

Predicting COPD Severity by Red Cell Distribution Width as a Potential Marker.

Fateme Mohammadzade, Mohammad Yousefi, Amirali Moodi Ghalibaf, Mostafa Kamandi, Farid Poursadegh, Fariba Rezaeetalab, Sepide Hejazi, Mahnaz Mozdourian

Abstract read
In one paragraph

Article in Tanaffos, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Fateme MohammadzadeDepartment Of Internal Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Mohammad YousefiStudent Research Committee, Birjand University of Medical Sciences, Birjand, Iran.
Amirali Moodi GhalibafStudent Research Committee, Birjand University of Medical Sciences, Birjand, Iran.
Mostafa KamandiDepartment Of Internal Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Farid PoursadeghLung Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Fariba RezaeetalabLung Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Sepide HejaziLung Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Mahnaz MozdourianLung Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a condition of the lower airways and lungs with stable inflammation and alterations in the structure of small airways. There are some biomarkers linked to acute exacerbations of COPD (AECOPD). Red cell distribution width (RDW) is one of these biomarkers. To investigate the correlation between RDW and the severity of COPD, and to assess its relationship with the stage of airway obstruction in spirometry among COPD patients. Materials and Methods: In an 18-month retrospective study, a total of 255 participants were enrolled, including 170 patients with COPD (85 with stable COPD and 85 with acute exacerbations of COPD) and 85 age- and sex-matched healthy individuals. Demographic factors and blood laboratory tests were conducted for each group. The COPD groups had their COPD severity, spirometry parameters, and inflammation indices recorded and then compared. Results: RDW levels are increased in COPD patients (p<0.001). However, no statistically significant relationships between RDW values and CAT scores or mMRC grades were observed. Our analysis revealed that spirometry parameters and RDW levels are negatively correlated (p<0.05). Additionally, the RDW parameter has a positive and significant correlation with PCO Conclusion: Our findings indicate that RDW could serve as a potential predictor of COPD conditions, especially in spirometry parameters.

Indexed as

Acute exacerbationBiomarkerChronic obstructive pulmonary disease (COPD)Red cell distribution width (RDW)

Identifiers

PMID42890638
PMCPMC13672039

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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.