Evidence map›Paper›PMID 41002642›Full record

ArticleJournal of cardiovascular development and disease2025

Association of Pan-Immune-Inflammation Value with All-Cause and Cardiovascular Mortality in Survivors of Myocardial Infarction: NHANES 2001-2018 Analysis.

Qingyi Liu, Wenling Yang, Ruiyu Zhang, Xiaopeng Guo, Yumiao Wei

Abstract read
In one paragraph

Article in Journal of cardiovascular development and disease, 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

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

1 citing paper in PubMed.

  1. 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

5 authors.

Qingyi LiuDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Wenling YangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Ruiyu ZhangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Xiaopeng GuoDepartment of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Yumiao WeiDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.

Funding

National Natural Science Foundation of China NO. 82202281National Natural Science Foundation of China NO. 82370348
6 · The paper itself

Abstract

backgroundInflammatory responses critically impact long-term outcomes in myocardial infarction (MI) survivors, yet few biomarkers comprehensively evaluate systemic immune-inflammatory status. This study assessed the prognostic utility of a novel marker-the pan-immune-inflammation value (PIV)-for predicting all-cause and cardiovascular mortality post-MI.

methodsUsing the National Health and Nutrition Examination Survey data (2001-2018), 1559 MI survivors were included. PIV was calculated as (neutrophils × platelets × monocytes)/lymphocytes. Weighted Cox models assessed the association between log-transformed PIV (LnPIV) and mortality. Restricted cubic spline (RCS) models explored non-linear dose-response relationships, and predictive performance was evaluated via time-dependent ROC analysis.

resultsOver a median 75-month follow-up, 675 deaths occurred. LnPIV showed significant non-linear associations with all-cause (

conclusionPIV demonstrates threshold-dependent mortality risk stratification in MI patients, particularly effective in high-inflammatory subgroups, offering a potential tool for personalized risk stratification.

Indexed as

all-cause mortalitycardiovascular mortalitymyocardial infarctionNHANESpan-immune-inflammation value

Identifiers

PMID41002642
PMCPMC12470339

What Socratic holds

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LicenceCC BY
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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 Socratic graph.