Evidence map›Paper›PMID 42265453›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026

An expert-led benchmark using common patient questions: evaluating large language models for adolescent idiopathic scoliosis education.

Cemre Aydin, Asli Beril Karakas, Anil Murat Ozturk, Figen Govsa, Mehmet Asim Ozer

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Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2026. 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. Review
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.

Cemre AydinDepartment of Orthopedics and Traumatology, Istanbul Bağcılar Education Research Hospital, 34200, Istanbul, Turkey.
Asli Beril KarakasDepartment of Anatomy, Faculty of Medicine, Kastamonu University, 37150, Kastamonu, Turkey. asliberilkarakas@gmail.com.
Anil Murat OzturkDepartment of Orthopedics and Traumatology, Faculty of Medicine, Ege University, 35040, Izmir, Turkey. amuratozturk@yahoo.com.
Figen GovsaDigital Imaging and 3D Modelling Laboratory, Department of Anatomy, Faculty of Medicine, Ege University, 35040, Izmir, Turkey.
Mehmet Asim OzerDigital Imaging and 3D Modelling Laboratory, Department of Anatomy, Faculty of Medicine, Ege University, 35040, Izmir, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIM/

backgroundLarge language models (LLMs) are increasingly used by patients to obtain medical information. Adolescent idiopathic scoliosis (AIS), a chronic condition requiring long-term monitoring and treatment decisions, generates substantial demand for reliable and understandable patient education. Although LLMs may function as accessible explanatory tools, their suitability for patient-oriented use remains uncertain. This study aimed to perform an expert-led, patient-centered evaluation of two widely accessible LLMs, Claude Sonnet 4.5 and GPT 5.2, focusing on their ability to deliver accurate, clear, and conceptually adequate responses to common AIS-related patient questions.

methodsA cross-sectional comparative design was used with 100 high-frequency patient questions covering ten clinical domains. Responses generated by both models using standardized zero-shot prompts were independently assessed by expert clinicians: factual accuracy by three raters (two orthopedic spine surgeons and one senior pediatric physiotherapist), and clarity and conceptual coverage by two raters (one surgeon and the physiotherapist). A structured evaluation framework examined three dichotomous dimensions relevant to patient education: factual accuracy, clarity and understandability, and conceptual coverage. Model performances were compared using McNemar's test, and inter-model agreement was assessed with Krippendorff's alpha.

resultsBoth models demonstrated equally high factual accuracy (91%). However, clarity was limited, with only one-third of responses rated as sufficiently understandable. A significant difference was observed in conceptual coverage, with Claude Sonnet 4.5 outperforming GPT 5.2 (46% vs. 29%, p = 0.012), particularly in domains requiring integrative explanations.

conclusionDespite strong factual accuracy, current LLMs show deficiencies in clarity and conceptual depth, limiting their reliability as standalone patient education tools for AIS. These findings highlight the necessity of clinician mediation and the importance of patient-centered evaluation criteria before clinical adoption. CLINICAL

trial registrationAs this study is not a clinical trial, clinical trial registration is not applicable.

Indexed as

Adolescent idiopathic scoliosisArtificial intelligenceClinical communicationHealth literacyLarge language modelsPatient education

Identifiers

PMID42265453

What OpenQuestion holds

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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.