Evidence map›Paper›PMID 41800207›Full record

ArticlePlastic and reconstructive surgery. Global open2025

Novel Breast Reconstruction Generative Pretrained Transformer Promotes Decisional Confidence and Clinical Efficiency.

Puja M Jagasia, Kazimir Bagdady, Meryl Pearl D Franco, Joshua K DeYoung, Megan E Fracol

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2025. 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

5 authors.

Puja M JagasiaFrom the Division of Plastic Surgery, Northwestern Memorial Hospital, Chicago, IL.
Kazimir BagdadyFrom the Division of Plastic Surgery, Northwestern Memorial Hospital, Chicago, IL.
Meryl Pearl D FrancoFrom the Division of Plastic Surgery, Northwestern Memorial Hospital, Chicago, IL.
Joshua K DeYoungFrom the Division of Plastic Surgery, Northwestern Memorial Hospital, Chicago, IL.
Megan E FracolFrom the Division of Plastic Surgery, Northwestern Memorial Hospital, Chicago, IL.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients undergoing breast reconstruction face many decisions. A generative pretrained transformer (GPT) tool was custom built to assist patients at their initial reconstructive consultation. Twenty patients undergoing immediate breast reconstruction were enrolled, and 10 were randomized to interact with this GPT for 10 minutes at most before seeing the surgeon who was blinded. Patients then completed the 4-item abbreviated Decisional Conflict Scale SURE survey, the 12-item preoperative Consumer Assessment of Healthcare Providers and Systems survey, and a 3-item GPT-specific survey. Patients spent an average of 6.79 minutes asking an average of 6.5 questions, which were most commonly about recovery (34%), autologous reconstruction (23%), and complications (17%). With a 100% response rate (20 of 20), patients in the GPT cohort experienced less decisional conflict (Decisional Conflict Scale SURE-GPT: 3.9 versus control: 3.1,

Identifiers

PMID41800207
PMCPMC12962575

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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.