Evidence map›Paper›PMID 41822876›Full record

ArticleFrontiers in medicine2026

PLR/SII/D-dimer iron triangle: a novel precision prediction strategy for

Minxuan Feng, Wenyan Li, Tao Ai, Yinghong Fan, Lei Zhang, Wanmin Xia, Cheng Xie

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 2026. 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. Review
  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

7 authors.

Minxuan FengDepartment of Respiratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Wenyan LiDepartment of Respiratory, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China.
Tao AiDepartment of Respiratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Yinghong FanDepartment of Respiratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Lei ZhangDepartment of Respiratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Wanmin XiaDepartment of Respiratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Cheng XieDepartment of Respiratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Plastic bronchitis (PB) is a life-threatening pulmonary infection disease, and the early recognition and diagnostic prediction of PB are currently not well established. This study aims to identify independent risk factors for PB and develop a clinically applicable predictive model to help clinicians make earlier and more accurate judgments about the potential occurrence of PB. Methods: This study included 132 hospitalized patients with lobar pneumonia caused by Results: The results of univariate analysis showed that N%, L%, NLR, PLR, CRP, PCT, SII, LDH, D-dimer, and the duration of macrolide antibiotic therapy were all independent risk factors for PB. It was also suggested that continued use of macrolides after two courses did not significantly reduce the occurrence of PB. The results of multivariate regression analysis indicated that a combined analysis of PLR, SII, and D-dimer had higher predictive value for PB occurrence. This was further supported by plotting ROC curves and establishing a triad model of these indicators to achieve simple data calculation for predicting PB in clinical practice. Conclusion: This study demonstrates that PLR, SII, and D-dimer are important indicators for predicting the occurrence of PB in children. The combined model of these three indicators is more sensitive and specific than the individual risk factors in predicting PB occurrence. Additionally, this model provides synergistic guidance for the duration of macrolide antibiotic therapy.

Indexed as

fiberoptic bronchoscopylobar pneumoniaplastic bronchitispredictive valuesystemic immune-inflammation index

Identifiers

PMID41822876
PMCPMC12977998

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.