Evidence map›Paper›PMID 41950349›Full record

ArticleJMIR medical informatics2026

Exploring the Role of AI in Managing Treatment Recommendations for Lymphedema: International, Multidisciplinary, Multiprofessional Survey Study of Trust, Reliability, and Impact on Decision-Making.

Adriano Fabi, Caroline E Egli, Séverin R Wendelspiess, Sebastian Griewing, Yvonne Haas, Laura De Pellegrin, Dirk J Schaefer, Shan S Qiu, Yves Harder, Elisabeth A Kappos

Abstract read
In one paragraph

Article in JMIR medical informatics, 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. 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

10 authors.

Adriano Fabi *Department of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Basel, Spitalstrasse 21, Basel, 4031, Switzerland, 41 613286254.ORCID 0009-0003-2605-7398
Caroline E Egli *Department of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Basel, Spitalstrasse 21, Basel, 4031, Switzerland, 41 613286254.ORCID 0000-0001-5333-7078
Séverin R WendelspiessDepartment of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Basel, Spitalstrasse 21, Basel, 4031, Switzerland, 41 613286254.ORCID 0009-0008-6441-0128
Sebastian GriewingInstitute for Digital Medicine, Philipps University of Marburg, Marburg, Germany.ORCID 0000-0001-5355-8903
Yvonne HaasDepartment of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Basel, Spitalstrasse 21, Basel, 4031, Switzerland, 41 613286254.ORCID 0009-0001-4940-452X
Laura De PellegrinDepartment of Plastic and Hand Surgery, University Hospital of Bern, Bern, Switzerland.ORCID 0009-0004-6010-7886
Dirk J SchaeferDepartment of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Basel, Spitalstrasse 21, Basel, 4031, Switzerland, 41 613286254.ORCID 0000-0002-9619-8650
Shan S QiuDepartment of Plastic and Reconstructive Surgery, Maastricht University Medical Centre, Maastricht, The Netherlands.ORCID 0000-0002-0616-9566
Yves HarderDepartment of Plastic, Reconstructive and Aesthetic Surgery and Hand Surgery, University Hospital of Lausanne (CHUV), Lausanne, Switzerland.ORCID 0000-0002-2557-249X
Elisabeth A KapposDepartment of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Basel, Spitalstrasse 21, Basel, 4031, Switzerland, 41 613286254.ORCID 0000-0003-4057-1951

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Upper and lower extremity lymphedema is a chronic, progressive condition that significantly impairs the quality of life of affected patients. Despite the recently established effectiveness of physical therapy and supermicrosurgical interventions, current guidelines frequently lag behind emerging evidence and commonly do not offer stage-specific treatment algorithms. This gap in evidence-based guidance may prompt clinicians with limited experience to seek support from large language models such as ChatGPT. Objective: Given the potential of artificial intelligence to rapidly integrate emerging research, this study evaluated how clinicians from different professional backgrounds rate the quality and reliability of personalized lymphedema management recommendations generated by ChatGPT. Methods: In this exploratory cross-sectional study, ChatGPT generated treatment recommendations for 6 standardized lymphedema case scenarios. An international panel of 67 participants (resident doctors, board-certified specialists, physiotherapists, and advanced practice nurses) from 34 institutions across 11 countries assessed the recommendations using a modified DISCERN questionnaire with a 9-point agreement scale ranging from 1 (completely disagree) to 9 (completely agree). Ratings were summarized as pooled means with variability measures and compared across clinician groups (residents vs board-certified physicians vs physiotherapists or advanced practice nurses) using group comparison testing. Results: ChatGPT was rated most favorably for diagnostic accuracy and treatment relevance, with higher ratings among residents than board-certified physicians. Residents assigned significantly lower scores for source indication, source currency, and communication of uncertainty. Between-group differences were observed across multiple DISCERN items, consistent with systematically more critical appraisal by experienced specialists. Participants reported moderate to high trust and willingness to consider ChatGPT as a supplementary resource, with more favorable perceptions among younger respondents. Conclusions: Clinicians perceived ChatGPT as potentially useful for preliminary orientation and educational support in lymphedema management, especially for less experienced users. Despite not being blinded, lower ratings in evidence transparency and uncertainty communication, particularly among experienced specialists, suggest that current artificial intelligence outputs should not be used as stand-alone guidance. Future work should test clinically integrated, citation-grounded workflows in prospective settings and evaluate whether they improve decision quality and efficiency.

Indexed as

Artificial IntelligenceLymphedemaTrustAdultCross-Sectional StudiesFemaleGenerative Artificial IntelligenceHumansLarge Language ModelsMaleReproducibility of ResultsSurveys and QuestionnairesAIartificial intelligenceChatGPTdecision-makingdigital healthlarge language modelslymphedemapersonalized medicine

Identifiers

PMID41950349
PMCPMC13060743

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.