Evidence map›Paper›PMID 42046065›Full record

SynthesisBMC pediatrics2026

Risk prediction models for central venous catheter-related complications in children: a systematic review.

Ruijuan Liu, Lu Li, Yansheng Peng, Liping Liao, Wenyu Huang, Yuan Li

Abstract readSystematic Review
In one paragraph

Synthesis in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Ruijuan LiuNursing Department, Affiliated Hospital of Zunyi Medical University, No. 149, Dalian Road, Huichuan District, Zunyi, Guizhou, 563003, P. R. China.
Lu LiNursing Department, Affiliated Hospital of Zunyi Medical University, No. 149, Dalian Road, Huichuan District, Zunyi, Guizhou, 563003, P. R. China.
Yansheng PengNursing Department, Affiliated Hospital of Zunyi Medical University, No. 149, Dalian Road, Huichuan District, Zunyi, Guizhou, 563003, P. R. China.
Liping LiaoNursing Department, Affiliated Hospital of Zunyi Medical University, No. 149, Dalian Road, Huichuan District, Zunyi, Guizhou, 563003, P. R. China.
Wenyu HuangNursing Department, Affiliated Hospital of Zunyi Medical University, No. 149, Dalian Road, Huichuan District, Zunyi, Guizhou, 563003, P. R. China.
Yuan LiNursing Department, Affiliated Hospital of Zunyi Medical University, No. 149, Dalian Road, Huichuan District, Zunyi, Guizhou, 563003, P. R. China. yuanli.zunyi@gmail.com.

Funding

Guizhou Nursing Association GZHLKY202403Zunyi Medical University Doctoral Research Start-up Fund Hospital No. (2024) 08
6 · The paper itself

Abstract

backgroundCentral venous catheters (CVCs) are widely used in pediatric care; however, their indwelling procedure can lead to severe complications such as catheter-associated infections and thrombosis. These complications significantly increase the suffering of pediatric patients, prolong hospitalization, and pose life-threatening risks. Although multiple risk prediction models have been developed to identify high-risk pediatric patients, a systematic and comprehensive evaluation of these models is still lacking.

objectiveWe systematically reviewed published risk prediction models for central venous catheter-related complications ( CLABSI and CRT ) in children, both domestically and internationally. The review assessed their predictive performance, validation status, and methodological quality, aiming to provide a basis for the selection of appropriate models in clinical practice.

methodsFollowing the PRISMA guidelines, a systematic search was conducted in databases including PubMed, Web of Science, Embase, Cochrane Library, CINAHL, CNKI, Wanfang, VIP, and CBM for relevant literature from their inception to December 31, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability using the PROBAST tool. A descriptive analysis was performed on the model construction methods, performance metrics, and validation status.

resultsA total of 15 studies were included in this analysis. Among them, three studies developed prediction models for CLABSI, all constructed using logistic regression(LR), with modeling AUCs ranging from 0.793 to 0.812; only one model underwent external validation. Twelve studies developed prediction models for CRT, employing diverse modeling methods (such as LR and machine learning). The modeling AUCs ranged from 0.74 to 0.957, of which four models underwent external validation (AUC 0.745–0.922). The PROBAST assessment indicated that most studies had a high risk of bias, primarily due to issues such as single-center retrospective design, highly subjective predictive factors, and inconsistent outcome evaluation criteria. The applicability of the models was generally satisfactory.

conclusionExisting risk prediction models for central venous catheter-related complications in children demonstrate potential in terms of discrimination. However, models specifically for CLABSI are limited in number and insufficiently validated. Both types of models commonly exhibit methodological flaws such as a high risk of bias. Currently, these models primarily serve as exploratory tools for risk screening and cannot yet be used as standalone evidence for clinical decision-making. Future efforts should focus on conducting multicenter prospective studies, standardizing diagnostic criteria and model development/validation procedures, and promoting the integration of models into clinical systems to enhance their reliability and clinical applicability.

Indexed as

Catheterization, Central VenousCatheter-Related InfectionsCentral Venous CathetersChildHumansPrediction AlgorithmsRisk AssessmentRisk FactorsCentral Venous CatheterChildrenCLABSICRTRisk Prediction ModelSystematic Review

Identifiers

PMID42046065
PMCPMC13255339

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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.