Evidence map›Paper›PMID 41473917›Full record

ArticleFrontiers in pediatrics2025

Reliability of ChatGPT answers to common questions on developmental dysplasia of the hip as an information source for parents.

Klemens Vertesich, Joachim Ortmayr, Reinhard Windhager, Madeleine Willegger

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 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.

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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

4 authors.

Klemens VertesichDepartment of Orthopedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria.
Joachim OrtmayrDepartment of Orthopedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria.
Reinhard WindhagerDepartment of Orthopedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria.
Madeleine WilleggerDepartment of Orthopedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI), particularly AI-based large language models (LLM) like ChatGPT, is increasingly shaping how information is accessed, offering patients a new source for understanding complex medical conditions. Given the physical, emotional, and logistical challenges that parents are faced when their baby is diagnosed with developmental dysplasia of the hip (DDH), the demand for clear and accessible educational resources is high. This study aimed to evaluate the quality and reliability of ChatGPT's responses to frequently asked questions about DDH. Methods: This study assessed the quality of responses generated by the AI chatbot ChatGPT 4o to eight frequently asked questions about DDH, derived from real consultations in a pediatric orthopedic clinic Responses were generated during one interaction per question using a ChatGPT account not previously exposed to medical information. Responses were evaluated by two individual readers using a standardized rating system, comparing them to current literature, patient education resources, and consensus guidelines. Each response was categorized by its level of informational accuracy and completeness, and descriptive statistics were calculated to quantify performance. Results: ChatGPT 4o was able to generate structured responses to all eight parental questions. The responses were rated in 12.5% excellent, 25.0% satisfactory with minimal clarification, 50.0% satisfactory with moderate clarification, and 12.5% unsatisfactory due to missing or inaccurate information. Conclusion: ChatGPT provided satisfactory answers to questions about DDH and may serve as a useful supplementary information resource for parents. However, due to limitations in presenting detailed diagnostic and treatment pathways, it should be viewed as an adjunct to, not a replacement for, specialist medical consultation.

Indexed as

artificial intelligencedevelopmental dysplasia of the hiphip screeninginfant hiplarge language model

Identifiers

PMID41473917
PMCPMC12745415

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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.