Evidence mapPaperPMID 39931300Full record

ArticleFrontiers in public health2025

Advancing health equity: evaluating AI translations of kidney donor information for Spanish speakers.

Oscar A Garcia Valencia, Charat Thongprayoon, Caroline C Jadlowiec, Shennen A Mao, Napat Leeaphorn, Pooja Budhiraja, Nadeen Khoury, Justin H Pham, Iasmina M Craici, Maria L Gonzalez Suarez and 1 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
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 synthesis or guideline pooled it.

  1. Pooled it
  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

11 authors.

Oscar A Garcia ValenciaDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, United States.
Charat ThongprayoonDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, United States.
Caroline C JadlowiecDivision of Transplant Surgery, Department of Surgery, Mayo Clinic, Phoenix, AZ, United States.
Shennen A MaoDepartment of Transplant Surgery, Mayo Clinic, Jacksonville, FL, United States.
Napat LeeaphornDepartment of Transplant Surgery, Mayo Clinic, Jacksonville, FL, United States.
Pooja BudhirajaDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Phoenix, AZ, United States.
Nadeen KhouryDivision of Nephrology, Department of Medicine, Henry Ford Hospital, Detroit, MI, United States.
Justin H PhamDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, United States.
Iasmina M CraiciDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, United States.
Maria L Gonzalez SuarezDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, United States.
Wisit CheungpasitpornDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Health equity and access to essential medical information remain significant challenges, especially for the Spanish-speaking Hispanic population, which faces barriers in accessing living kidney donation opportunities. ChatGPT, an AI language model with sophisticated natural language processing capabilities, has been identified as a promising tool for translating critical health information into Spanish. This study aims to assess ChatGPT's translation efficacy to ensure the information provided is accurate and culturally relevant. Methods: Results: The mean linguistic accuracy scores were 4.89 ± 0.32 for GPT-3.5 and 5.00 ± 0.00 for GPT-4.0 ( Conclusion: ChatGPT 4.0 demonstrates strong potential to enhance health equity by improving Spanish-speaking Hispanic patients' access to LKD information through accurate and culturally sensitive translations. These findings highlight the role of AI in mitigating healthcare disparities and underscore the need for integrating AI-driven tools into healthcare systems. Future efforts should focus on developing accessible platforms and establishing guidelines to maximize AI's impact on equitable healthcare delivery and patient education.

Indexed as

Artificial IntelligenceHealth EquityKidney TransplantationLiving DonorsTranslationsAdultFemaleHispanic or LatinoHumansLanguageMaleMiddle AgedTranslatingartificial intelligenceChatGPTcultural competencyhealthcare communication barriershealth equitylanguage translation modelsliving kidney donationSpanish-speaking populations

Identifiers

PMID39931300
PMCPMC11808013

What Socratic 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 Socratic graph.