Evidence map›Paper›PMID 39210407›Full record

SynthesisJournal of orthopaedic surgery and research2024

The diagnostic value of artificial intelligence-assisted imaging for developmental dysplasia of the hip: a systematic review and meta-analysis.

Min Chen, Ruyi Cai, Aixia Zhang, Xia Chi, Jun Qian

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Journal of orthopaedic surgery and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 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

11 citing papers in PubMed, 2 syntheses or guidelines 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.

Min Chen *Department of the Child Health Department, Women's Hospital of Nanjing Medical University, (Nanjing Women and Children's Healthcare Hospital), Nanjing, Jiangsu, 21000, China.
Ruyi Cai *Department of the Child Health Department, Women's Hospital of Nanjing Medical University, (Nanjing Women and Children's Healthcare Hospital), Nanjing, Jiangsu, 21000, China.
Aixia ZhangDepartment of the Child Health Department, Women's Hospital of Nanjing Medical University, (Nanjing Women and Children's Healthcare Hospital), Nanjing, Jiangsu, 21000, China.
Xia ChiDepartment of the Child Health Department, Women's Hospital of Nanjing Medical University, (Nanjing Women and Children's Healthcare Hospital), Nanjing, Jiangsu, 21000, China.
Jun QianDepartment of the Child Health Department, Women's Hospital of Nanjing Medical University, (Nanjing Women and Children's Healthcare Hospital), Nanjing, Jiangsu, 21000, China. 466711076@qq.com.

Funding

Research fund project of Jiangsu Maternal and Child Health Association FYX202212
6 · The paper itself

Abstract

objectiveTo clarify the efficacy of artificial intelligence (AI)-assisted imaging in the diagnosis of developmental dysplasia of the hip (DDH) through a meta-analysis.

methodsRelevant literature on AI for early DDH diagnosis was searched in PubMed, Web of Science, Embase, and The Cochrane Library databases until April 4, 2024. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of included studies. Revman5.4 and StataSE-64 software were used to calculate the combined sensitivity, specificity, AUC value, and DOC value of AI-assisted imaging for DDH diagnosis.

resultsThe meta-analysis included 13 studies (6 prospective and 7 retrospective) with 28 AI models and a total of 10,673 samples. The summary sensitivity, specificity, AUC value, and DOC value were 99.0% (95% CI: 97.0-100.0%), 94.0% (95% CI: 89.0-96.0%), 99.0% (95% CI: 98.0-100.0%), and 1342 (95% CI: 469-3842), respectively.

conclusionAI-assisted imaging demonstrates high diagnostic efficacy for DDH detection, improving the accuracy of early DDH imaging examination. More prospective studies are needed to further confirm the value of AI-assisted imaging for early DDH diagnosis.

Indexed as

Artificial IntelligenceDevelopmental Dysplasia of the HipHip Dislocation, CongenitalHumansInfantProspective StudiesSensitivity and SpecificityArtificial intelligenceDevelopmental dysplasia of the hipDiagnostic valueMeta-analysis

Identifiers

PMID39210407
PMCPMC11360681

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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.