Evidence map›Paper›PMID 41116818›Full record

ArticleJournal of inflammation research2025

The Prognostic Value of Complete Blood Count-Derived Inflammatory Indicators for All-Cause Mortality in Type 2 Diabetes Mellitus: A Retrospective Cohort Study.

Bowen Li, Yue Xu, Huijing Zhu, Qingwei He, Qiaoxiang Yin, Mengdi Wu, Jing Zhang, Yan-Jie Cao

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Bowen Li *Graduate School, Hebei North University, Zhangjiakou, Hebei, People's Republic of China.ORCID 0009-0007-8696-2313
Yue Xu *Graduate School, Hebei North University, Zhangjiakou, Hebei, People's Republic of China.
Huijing Zhu *Graduate School, Hebei North University, Zhangjiakou, Hebei, People's Republic of China.
Qingwei HeCardiology Department, Air Force Medical Center, PLA, Beijing, People's Republic of China.ORCID 0009-0002-0392-8376
Qiaoxiang YinCardiology Department, Air Force Medical Center, PLA, Beijing, People's Republic of China.
Mengdi WuCardiology Department, Air Force Medical Center, PLA, Beijing, People's Republic of China.
Jing ZhangCardiology Department, Air Force Medical Center, PLA, Beijing, People's Republic of China.
Yan-Jie CaoCardiology Department, Air Force Medical Center, PLA, Beijing, People's Republic of China.ORCID 0000-0002-5756-1330

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Type 2 diabetes mellitus (T2DM) is closely associated with chronic inflammation. However, the value of low-cost, readily accessible complete blood count (CBC)-derived inflammatory indicators in predicting all-cause mortality among T2DM patients has not been fully evaluated. This study evaluated their predictive potential. Methods: This single-center retrospective cohort included 619 T2DM patients. Associations between nine inflammatory indicators and all-cause mortality were assessed using multivariable-adjusted Cox regression models. Time-dependent ROC curves, Kaplan-Meier (K-M) analysis, restricted cubic spline (RCS) models, and subgroup analyses evaluated predictive performance and stability. Results: Over a median follow-up of 1058 days, 137 deaths (22.1%) occurred. Patients in the highest quartile (Q4) of the systemic inflammation response index (SIRI, HR=2.486, 95% CI:1.291,4.788), neutrophil-to-lymphocyte ratio (NLR, HR=2.275, 95% CI:1.217,4.252), and neutrophil-monocyte to lymphocyte ratio (nMLR, HR=2.212, 95% CI:1.200,4.077) had significantly elevated mortality risk versus the lowest quartile (Q1) after adjustment (P for trend<0.01 for all). RCS confirmed significant positive linear associations (P for nonlinearity>0.05). Predictive ability attenuated over time per time-dependent ROC. Subgroup analyses demonstrated consistent associations across clinical subgroups (P for interaction>0.05). Conclusion: SIRI, NLR, and nMLR can independently predict all-cause mortality in T2DM patients and demonstrate stable performance across clinical subgroups. These low-cost, routinely tested biomarkers possess the potential to optimize risk stratification in resource-limited settings.

Indexed as

complete blood countdiabetesinflammatory biomarkersmortalityT2DM

Identifiers

PMID41116818
PMCPMC12535702

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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.