Evidence map›Paper›PMID 42053898›Full record

ArticleIndian journal of pediatrics2026

A Clinically Ultrasound Fusion Visual Prediction Model for Childhood Irreducible Small-Bowel Intussusception.

Hongjia Qiang, Xin Li, Zhaozheng Ding, Xiangjie Li, Yuan Cao, Dongsheng Zhu

Abstract read
In one paragraph

Article in Indian journal of 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
–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

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.

Hongjia Qiang *Department of Pediatric Surgery, The First People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, 222000, Jiangsu Province, China.
Xin Li *Department of Pediatric Surgery, The First People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, 222000, Jiangsu Province, China.
Zhaozheng Ding *Department of Pediatric Surgery, The First People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, 222000, Jiangsu Province, China.
Xiangjie LiDepartment of Pediatric Surgery, The First People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, 222000, Jiangsu Province, China.
Yuan CaoDepartment of Pediatric Surgery, The First People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, 222000, Jiangsu Province, China.
Dongsheng ZhuDepartment of Pediatric Surgery, The First People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, 222000, Jiangsu Province, China. zhudongsheng@tmu.edu.cn.

Funding

Lianyungang City maternal and child health research project F202319
6 · The paper itself

Abstract

Small-bowel intussusception (SBI) is usually transient, but 10% require surgery. The authors developed a bedside nomogram using routine ultrasound to predict irreducible SBI in 484 children (47 irreducible, 9.7%). LASSO regression selected five predictors: bloody stool, intussusception diameter and length, bowel wall thickness, and Doppler flow grade. The nomogram demonstrated good discrimination (C-index 0.907, 95% CI 0.869–0.945) and favorable calibration. This bedside tool enables immediate risk stratification using routine ultrasound measurements, potentially reducing unnecessary surgical delays.

Indexed as

Intestine, SmallIntussusceptionChild, PreschoolFemaleHumansInfantMaleNomogramsUltrasonographyIntussusceptionIrreduciblePrediction modelSmall-bowelUltrasound

Identifiers

PMID42053898
PMCPMC13222187

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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.