Evidence map›Paper›PMID 39583098›Full record

ArticlePeerJ2024

Development and validation of a simple clinical nomogram for predicting infectious diseases in pediatric kidney transplantation recipients: a retrospective study.

Li Li, Meng Fu, Changshan Wang, Yuxin Pei, Lizhi Chen, Liping Rong, Yuanyuan Xu, Zhilang Lin, Yuanquan Qiu, Xiaoyun Jiang and 1 more

Abstract readValidation Study
In one paragraph

Article in PeerJ, 2024. 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

11 authors.

Li Li *Department of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Meng Fu *Department of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Changshan WangShenzhen Guangming District People's Hospital, Shenzhen, Guangdong, China.
Yuxin PeiDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Lizhi ChenDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Liping RongDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Yuanyuan XuDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Zhilang LinDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Yuanquan QiuDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Xiaoyun JiangDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Mengjie JiangDepartment of Pediatric Nephrology and Rheumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To construct and verify an easy-to-use nomogram for predicting the risk of infectious diseases in pediatric kidney transplant recipients. Clinical data of hospitalized pediatric kidney transplant recipients were retrospectively analyzed. Meaningful variables identified from the multivariate stepwise logistic regression analysis were used to construct the nomogram. Internal validation was performed using Bootstrap resampling 1,000 times. The nomogram was evaluated using calibration, decision and receiver operating characteristic (ROC) curves. A total of 297 pediatric kidney transplant recipients were included (164 infected, 133 non-infected). Multivariate stepwise regression analysis identified white blood cell count (WBC), lymphocyte to monocyte ratio (MLR), platelet to neutrophil ratio (PNR), red cell distribution width-standard deviation (RDW-SD), and albumin (ALB) as significant predictors of postoperative infection. The nomogram, based on the five indicators, showed strong discrimination ability (AUC = 0.756; 95% CI [0.702-0.811]), with a sensitivity of 88.0% and a specificity of 54.3%. The calibration curve and decision curve further demonstrated good consistency and clinical practicality between the predicted and actual values. WBC, MLR, PNR, RDW-SD, and ALB are effective indicators for predicting postoperative infection in pediatric kidney transplant recipients. The nomogram constructed from these indicators can effectively predict and evaluate the early risk of infection in these patients.

Indexed as

Kidney TransplantationNomogramsPostoperative ComplicationsAdolescentChildChild, PreschoolFemaleHumansInfectionsLeukocyte CountMaleRetrospective StudiesROC CurveChildrenInfectious diseaseKidney transplantationNomogramPrediction model

Identifiers

PMID39583098
PMCPMC11586046

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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.