Evidence map›Paper›PMID 39866286›Full record

ArticleChina CDC weekly2025

Accuracy of the Self-Administered Rapid HIV Urine Test in a Real-World Setting and Individual Preferences for HIV Self-Testing - Guangzhou City, Guangdong Province, China, July 2020-February 2021.

Chunli Zhang, Mengdie Li, Yuzhou Gu, Yongheng Lu, Sha Chen, Zhongqi Liu, Yuantao Hao, Chun Hao

Abstract read
In one paragraph

Article in China CDC weekly, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

8 authors.

Chunli ZhangDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou City, Guangdong Province, China.
Mengdie LiSun Yat-Sen Global Health Institute, Institute of State Governance, Sun Yat-Sen University, Guangzhou City, Guangdong Province, China.
Yuzhou GuGuangzhou Center for Disease Control and Prevention, Guangzhou City, Guangdong Province, China.
Yongheng LuGuangzhou Lingnan Community Support Center, Guangzhou City, Guangdong Province, China.
Sha ChenWest China Hospital of Sichuan University, Chengdu City, Sichuan Province, China.
Zhongqi LiuDepartment of Quality Management Evaluation, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou City, Guangdong Province, China.
Yuantao HaoPeking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.
Chun HaoDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou City, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known about this topic?: Human immunodeficiency virus (HIV) self-testing serves as a crucial strategy for overcoming testing barriers, with urine-based self-testing emerging as a potential novel approach. What is added by this report?: In a real-world setting, this study demonstrated that the urine rapid test exhibited lower diagnostic accuracy compared to the blood rapid test. Study participants expressed stronger preferences for HIV self-testing methods utilizing finger prick samples, accompanied by standard written instructions and lower costs. What are the implications for public health practice?: Our findings indicate that rapid urine testing requires additional validation before widespread implementation. Future development efforts should prioritize user-friendly HIV self-testing approaches to enhance testing accessibility.

Indexed as

Discrete choice experimentHIV self-testingPreferenceRapid HIV test

Identifiers

PMID39866286
PMCPMC11754850

What OpenQuestion holds

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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.