Evidence map›Paper›PMID 38313585›Full record

ArticlePlastic and reconstructive surgery. Global open2024

Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application.

Carter J Boyd, Kshipra Hemal, Thomas J Sorenson, Parth A Patel, Jonathan M Bekisz, Mihye Choi, Nolan S Karp

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Decision-making Tools for Postmastectomy Breast Reconstruction: A Scoping Review.Plastic and reconstructive surgery. Global open · 2025
    Article
  9. Enhancing patient education in breast surgery: artificial intelligence-powered guidance for mastopexy, augmentation, reduction, and reconstruction.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2025
    Article
  10. 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

7 authors.

Carter J BoydFrom the Hansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, N.Y.
Kshipra HemalFrom the Hansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, N.Y.
Thomas J SorensonFrom the Hansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, N.Y.
Parth A PatelWellstar Medical College of Georgia, Augusta, Ga.
Jonathan M BekiszFrom the Hansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, N.Y.
Mihye ChoiFrom the Hansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, N.Y.
Nolan S KarpFrom the Hansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, N.Y.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Given the dialogistic properties of ChatGPT, we hypothesized that this artificial intelligence (AI) function can be used as a self-service tool where clinical questions can be directly answered by AI. Our objective was to assess the content, accuracy, and accessibility of AI-generated content regarding common perioperative questions for reduction mammaplasty. Methods: ChatGPT (OpenAI, February Version, San Francisco, Calif.) was used to query 20 common patient concerns that arise in the perioperative period of a reduction mammaplasty. Searches were performed in duplicate for both a general term and a specific clinical question. Query outputs were analyzed both objectively and subjectively. Descriptive statistics, Results: From a total of 40 AI-generated outputs, mean word length was 191.8 words. Readability was at the thirteenth grade level. Regarding content, of all query outputs, 97.5% were on the appropriate topic. Medical advice was deemed to be reasonable in 100% of cases. General queries more frequently reported overarching background information, whereas specific queries more frequently reported prescriptive information ( Conclusions: Currently available AI tools, in their nascent form, can provide recommendations for common perioperative questions and concerns for reduction mammaplasty. With further calibration, AI interfaces may serve as a tool for fielding patient queries in the future; however, patients must always retain the ability to bypass technology and be able to contact their surgeon.

Identifiers

PMID38313585
PMCPMC10836902

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.