Evidence map›Paper›PMID 41059476›Full record

ArticleFrontiers in pediatrics2025

Risk factors for mortality and development of a predictive model in pediatric sepsis.

Caizhen Wang, Lijie Feng, Xiaohui Yang, Pan Wang, Yuan Chen

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

5 authors.

Caizhen WangPediatric Intensive Care Unit, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Lijie FengPediatric Intensive Care Unit, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Xiaohui YangPediatric Intensive Care Unit, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Pan WangPediatric Intensive Care Unit, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yuan ChenPediatric Intensive Care Unit, The Second Hospital of Hebei Medical University, Shijiazhuang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the clinical characteristics and risk factors associated with mortality in pediatric sepsis patients, and to establish a predictive model for early identification of high-risk children. Methods: A retrospective cohort study was conducted including 143 pediatric sepsis cases admitted to the Pediatric Intensive Care Unit of the Second Hospital of Hebei Medical University from January 2020 to December 2024. Clinical data, laboratory indicators, and treatment history were collected. Univariate and multivariate logistic regression analyses were performed to identify risk factors for mortality. A nomogram model was constructed based on significant predictors, and its predictive performance was evaluated by receiver operating characteristic (ROC) curve analysis. Results: Among the 143 cases, 121 survived and 22 died. Significant differences were observed between the survival and death groups in lymphocyte count, platelet count, albumin, D-dimer, liver function tests (ALT, TBIL), CALLY index, and pre-admission glucocorticoid use ( Conclusion: Platelet count, D-dimer level, and CALLY index are valuable indicators for assessing prognosis in pediatric sepsis and can aid in early risk stratification. The established nomogram provides a useful tool for clinical decision-making to improve outcomes in high-risk pediatric sepsis patients. Further multicenter prospective studies are warranted to validate and refine these findings.

Indexed as

albuminCALLY indexchildrenmortality risk factorssepsis

Identifiers

PMID41059476
PMCPMC12497786

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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.