Evidence map›Paper›PMID 40634989›Full record

ArticleBMC medical ethics2025

Construction and validation of a predictive model for the acceptance of kidney xenotransplantation among patients awaiting kidney transplantation: a cross-sectional study from China.

Shujun Yang, Hao Wei, Haihong Yang, Jiang Peng, Panfeng Shang, Shengkun Sun

Abstract readValidation Study
In one paragraph

Article in BMC medical ethics, 2025. 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

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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

6 authors.

Shujun Yang *Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, 730030, China.
Hao Wei *Department of Urology, Affiliated Hospital of Qingdao University, Qingdao, 730030, China.
Haihong Yang *Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, 730030, China.
Jiang PengInstitute of Orthopaedic Research, Department of Orthopaedic Medicine, Fourth Medical Centre, General Hospital of the People's Liberation Army, Beijing, 10000, China.
Panfeng ShangDepartment of Urology, The Second Hospital of Lanzhou University, Lanzhou, 730030, China. shangpf@lzu.edu.cn.
Shengkun SunDepartment of Urology, Third Medical Centre, General Hospital of the People's Liberation Army, Beijing, 10000, China. sunshengkun@301hospital.com.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKidney xenotransplantation (KXTx) has the potential to address the shortage of kidney donations. To construct and validate a predictive model for the willingness to receive KXTx, data were collected from Chinese patients awaiting kidney transplantation.

methodsThe data were collected from 539 questionnaires from June 20, 2023, to April 3, 2024. A random allocation method was used to conduct univariate analysis and multiple logistic regression analysis to explore the factors that affect KXTx acceptance. A prediction model was constructed in the form of a nomogram, and the accuracy of the prediction model was evaluated using multiple methods.

resultsThe results of multivariate logistic regression revealed that medical insurance (No vs. Yes, odds ratio [OR] 3.10, 95% confidence interval [CI] 1.52-6.12), religion (no belief as the reference group; Atheist: OR 2.56, 95% CI 1.26-5.33; Buddhism: OR 2.03, 95% CI 0.78-4.89; Taoism: OR 2.33, 95% CI 0.72-6.77; Islam: OR 5.78, 95% CI 1.38-21.10; Catholicism: OR 4.52, 95% CI 0.74-22.7; Christianity: OR 7.69, 95% CI 0.36-66.5; Other: OR 0.93, 95% CI 0.05-5.26), and knowing about KXTx (No vs. Yes, OR 3.39, 95% CI 1.89-6.08) were independent risk factors for KXTx acceptance. A nomogram was constructed based on the abovementioned factors, and the area under the curve was 0.717. The calibration curves decision curve analysis also revealed good performance. Additionally, previous research has shown that KXTx-related risk factors are the primary concern for these patients.

conclusionThis study constructed a predictive model for the acceptance of KXTx among patients awaiting kidney transplantation. This model has significance for studying the acceptance and attitudes of this population.

Indexed as

Kidney TransplantationPatient Acceptance of Health CareTransplantation, HeterologousAdultChinaCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedNomogramsReligionSurveys and QuestionnairesTissue and Organ ProcurementAttitudesKidney xenotransplantationNomogram

Identifiers

PMID40634989
PMCPMC12243268

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.