Evidence map›Paper›PMID 41757812›Full record

ArticleJournal of global health2026

C-reactive protein predicts respiratory failure in chronic obstructive pulmonary disease: a cohort analysis from the UK Biobank.

Boyan Zhang, Zhongshang Dai, Qi Jiang, Rui Zhao, Yan Chen

Abstract read
In one paragraph

Article in Journal of global health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

5 authors.

Boyan Zhang *The Second Xiangya Hospital of Central South University, Department of Respiratory and Critical Care Medicine, Changsha, China.
Zhongshang Dai *The Second Xiangya Hospital of Central South University, Department of Infectious Diseases, Changsha, China.
Qi JiangThe Second Xiangya Hospital of Central South University, Department of Respiratory and Critical Care Medicine, Changsha, China.
Rui ZhaoThe Second Xiangya Hospital of Central South University, Department of Respiratory and Critical Care Medicine, Changsha, China.
Yan ChenThe Second Xiangya Hospital of Central South University, Department of Respiratory and Critical Care Medicine, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Respiratory failure (RF) is the leading cause of death in chronic obstructive pulmonary disease (COPD), yet reliable biomarkers for early risk stratification remain unclear. Circulating C-reactive protein (CRP) reflects systemic inflammation, but its prognostic value for incident RF in COPD is controversial. Methods: A total of 38 933 patients from the UK Biobank with the ratio of Forced Expiratory Volume in 1 second to Forced Vital Capacity (FEV Results: Kaplan-Meier curves showed statistically significant differences in RF across all subgroups throughout the entire follow-up period. Additionally, significant differences were observed between groups concerning all-cause mortality and COPD-induced mortality as well. The Cox proportional hazards model demonstrated a clear dose-response relationship between CRP concentration and RF, even after adjustment for several clinical covariates and systemic inflammation index. Conclusions: Serum CRP concentration may forecast a high risk of incident RF in patients with COPD, indicating further research on the threshold.

Indexed as

C-Reactive ProteinPulmonary Disease, Chronic ObstructiveRespiratory InsufficiencyAgedBiomarkersCohort StudiesFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisUK BiobankUnited KingdomBiomarkersC-Reactive Protein

Identifiers

PMID41757812
PMCPMC12947716

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Registered trials

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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.