Corrigendum: Prediction model of immunosuppressive medication non-adherence for renal transplant patients based on machine learning technology.

Xiao Zhu, Bo Peng, QiFeng Yi, Jia Liu, Jin Yan

Abstract readPublished Erratum

In one paragraph

Article in Frontiers in medicine, 2022. 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

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

1 citing paper in PubMed.

Association between negative emotional states, self-regulation skills, and immunosuppressive medication adherence in liver or kidney transplant recipients: a cross-sectional study.BMC public health · 2025
Article

4 · The record

Corrections and comments

Erratum for
Prediction Model of Immunosuppressive Medication Non-adherence for Renal Transplant Patients Based on Machine Learning Technology.2022

5 · Who and what money

Authors and funding

5 authors.

Xiao ZhuNursing Department of Third Xiangya Hospital of Central South University, Changsha, China.

Bo PengResearch Center of Chinese Health Ministry on Transplantation Medicine Engineering and Technology, The Third Xiangya Hospital, Central South University, Changsha, China.

QiFeng YiNursing School of Central South University, Changsha, China.

Jia LiuNursing School of Central South University, Changsha, China.

Jin YanNursing School of Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

[This corrects the article DOI: 10.3389/fmed.2022.796424.].

Indexed as

immunosuppressive medicationmachine learning technologynon-adherenceprediction modelrenal transplant patients

Identifiers

PMID36017011

DOI10.3389/fmed.2022.964157

PMCPMC9398454

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.