Evidence map›Paper›PMID 40073613›Full record

ArticleClinics (Sao Paulo, Brazil)2025

Routinely available inflammation biomarkers to predict stroke and mortality in atrial fibrillation.

Long Wu, Zhiquan Yuan, Yuhong Zeng, Lanqing Yang, Qin Hu, Huan Zhang, Chengying Li, Yanxiu Chen, Zhihui Zhang, Li Zhong and 2 more

Abstract read
In one paragraph

Article in Clinics (Sao Paulo, Brazil), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Long WuDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Zhiquan YuanDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Yuhong ZengDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Lanqing YangDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Qin HuDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Huan ZhangDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Chengying LiDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Yanxiu ChenDepartment of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Army Medical University (Third Military Medical University), PR China.
Zhihui ZhangDepartment of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Army Medical University (Third Military Medical University), PR China.
Li ZhongDepartment of Cardiology, Third Affiliated Hospital of Chongqing Medical University, PR China.
Yafei LiDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Na WuEvidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China. Electronic address: cqwuna@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to assess the predictive value of 7 routinely available inflammation biomarkers for stroke and all-cause mortality in 229 non-valvular AF patients. METHODS AND

resultsC-reactive protein, Albumin (ALB), d-dimer, fibrinogen, the number of platelets, lymphocytes, monocyte and neutrophils were measured. The Multivariable Cox proportional hazard model was used to assess the predictive value of the inflammation biomarkers for stroke and all-cause mortality, the c-statistic, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) were calculated. Lymphocyte Monocyte Ratio (LMR) was the most informative biomarker for predicting stroke, and adding LMR to the CHA

conclusionsAdding routinely available inflammatory biomarkers to the CHA

Indexed as

Atrial FibrillationInflammationStrokeAgedAged, 80 and overBiomarkersC-Reactive ProteinFemaleFibrin Fibrinogen Degradation ProductsFibrinogenHumansMaleMiddle AgedPredictive Value of TestsProportional Hazards ModelsRisk AssessmentBiomarkersC-Reactive ProteinFibrin Fibrinogen Degradation Productsfibrin fragment DFibrinogenSerum AlbuminAtrial fibrillationCHA(2)DS(2)-VAScInflammation biomarkerMortalityStroke

Identifiers

PMID40073613
PMCPMC11950969

What OpenQuestion holds

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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.