Evidence map›Paper›PMID 39329220›Full record

ArticleClinical transplantation2024

ChatGPT Solving Complex Kidney Transplant Cases: A Comparative Study With Human Respondents.

Michal A Mankowski, Ian S Jaffe, Jingzhi Xu, Sunjae Bae, Eric K Oermann, Yindalon Aphinyanaphongs, Mara A McAdams-DeMarco, Bonnie E Lonze, Babak J Orandi, Darren Stewart and 4 more

Abstract readComparative Study
In one paragraph

Article in Clinical transplantation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

14 authors.

Michal A MankowskiDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.
Ian S JaffeDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-7309-308X
Jingzhi XuDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.
Sunjae BaeDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-0098-8816
Eric K OermannDepartment of Neurosurgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-1876-5963
Yindalon AphinyanaphongsDepartment of Population Health, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0001-8605-5392
Mara A McAdams-DeMarcoDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-3013-925X
Bonnie E LonzeDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-0973-1657
Babak J OrandiDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0001-6026-7135
Darren StewartDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-6764-4842
Macey LevanDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-4239-1252
Allan MassieDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-5288-5125
Sommer GentryDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-4530-8917
Dorry L SegevDepartment of Surgery, NYU Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-1924-4801

Funding

Project-005UL1TR001445 · NCATS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BREDELLA, MIRIAM ANTOINETTE, HOCHMAN, JUDITH S · 2015 to 2025
$103.5M
Structural Racism, Resilience, and Premature Cognitive Aging in End-Stage Renal Disease - Revision - 5R01AG077888 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mara A. McAdams DeMarco · 2022 to 2026
$4.4M
Continuous allocation score design for guaranteeing equity and reducing discards in kidney and liver transplantationR01DK132395 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Allan B Massie · 2023 to 2026
$2.7M
Increasing Equity and Utility in Deceased Donor Kidney Allocation with HLA Molecular MatchingR01DK139240 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI LOREN GRAGERT, Michal A Mankowski · 2024 to 2026
$2.1M
Patient Oriented Research in Solid Organ TransplantationK24AI144954 · NIAID · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI SEGEV, DORRY L. · 2020 to 2024
$956k
Impact of climate change on cognitive and physical aging of older kidney transplant recipientsK02AG076883 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mara A. McAdams DeMarco · 2023 to 2026
$728k
National Institute of Allergy and Infectious Diseases R01DK132395NCATS NIH HHS UL1 TR001445NIAID NIH HHS K24 AI144954NIA NIH HHS K02 AG076883NIA NIH HHS R01 AG077888NIDDK NIH HHS R01 DK132395NIDDK NIH HHS R01 DK139240NIH HHS K02AG076883NIH HHS R01AG077888NIH HHS UL1TR001445
6 · The paper itself

Abstract

introductionChatGPT has shown the ability to answer clinical questions in general medicine but may be constrained by the specialized nature of kidney transplantation. Thus, it is important to explore how ChatGPT can be used in kidney transplantation and how its knowledge compares to human respondents.

methodsWe prompted ChatGPT versions 3.5, 4, and 4 Visual (4 V) with 12 multiple-choice questions related to six kidney transplant cases from 2013 to 2015 American Society of Nephrology (ASN) fellowship program quizzes. We compared the performance of ChatGPT with US nephrology fellowship program directors, nephrology fellows, and the audience of the ASN's annual Kidney Week meeting.

resultsOverall, ChatGPT 4 V correctly answered 10 out of 12 questions, showing a performance level comparable to nephrology fellows (group majority correctly answered 9 of 12 questions) and training program directors (11 of 12). This surpassed ChatGPT 4 (7 of 12 correct) and 3.5 (5 of 12). All three ChatGPT versions failed to correctly answer questions where the consensus among human respondents was low.

conclusionEach iterative version of ChatGPT performed better than the prior version, with version 4 V achieving performance on par with nephrology fellows and training program directors. While it shows promise in understanding and answering kidney transplantation questions, ChatGPT should be seen as a complementary tool to human expertise rather than a replacement.

Indexed as

Kidney TransplantationFellowships and ScholarshipsFemaleHumansKidney Failure, ChronicNephrologyPrognosisSurveys and Questionnairesartificial intelligenceChatGPTgenerative pretrained transformerkidney transplantationquiz

Identifiers

PMID39329220
PMCPMC11441623

What OpenQuestion holds

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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.