Evidence mapPaperPMID 40217197Full record

ArticleBMC pulmonary medicine2025

Association of eosinophil-to-monocyte ratio with asthma exacerbations in adults: a cross-sectional analysis of NHANES data.

Congyi Xie, Jinzhan Chen, Haiyan Chen, Ning Zhang

Abstract read
In one paragraph

Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Congyi XieDepartment of Pulmonary Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China.
Jinzhan ChenDepartment of Pulmonary Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China.
Haiyan ChenDepartment of Pulmonary Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China.
Ning ZhangDepartment of Pulmonary Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China. zhang.ning@zsxmhospital.com.ORCID http://orcid.org/0000-0002-0485-5028

Funding

Natural Science Foundation of Fujian Province 2023J011690
6 · The paper itself

Abstract

backgroundThe eosinophil-to-monocyte ratio (EMR) has emerged as a promising biomarker for assessing inflammation in various diseases, and this study aims to investigate its potential in predicting asthma exacerbations.

methodsThis cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) 1999-2020. A total of 4,738 adults were included in the analysis, and weighted analyses were performed to ensure a representative sample of the general population. The relationship between EMR and asthma exacerbation risk was assessed using multivariable logistic regression with progressively adjusted covariates across multiple models. Subgroup analyses were performed by stratifying key covariates to explore interactions. Restricted cubic spline (RCS) analysis was applied to evaluate non-linear relationships. Sensitivity analyses confirmed the robustness and reliability of the results.

resultsElevated EMR levels were significantly associated with an increased risk of asthma exacerbations (p < 0.001 in all models). In the highest EMR quartile (Q4), the odds ratio for exacerbation compared to the lowest quartile (Q1) was 1.54 (95% CI: 1.23, 1.93) in Model 1, increasing to 1.56 (95% CI: 1.24, 1.97) in Model 2 and 1.58 (95% CI: 1.24, 2.02) in Model 3, after further adjustments. Subgroup analyses showed consistent associations across various characteristics (all p for interaction > 0.05), while RCS analysis revealed a linear relationship without threshold effects (p for nonlinear > 0.05).

conclusionEMR demonstrates strong potential as a biomarker for predicting asthma exacerbations, with implications for personalized asthma management.

Indexed as

AsthmaEosinophilsMonocytesAdultAgedBiomarkersCross-Sectional StudiesDisease ProgressionFemaleHumansLeukocyte CountLogistic ModelsMaleMiddle AgedNutrition SurveysUnited StatesBiomarkersAsthmaBiomarkerEosinophil-to-monocyte ratio (EMR)ExacerbationNHANES

Identifiers

PMID40217197
PMCPMC11992703

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.