Evidence map›Paper›PMID 38125421›Full record

ArticleHeliyon2023

Characteristics of the different HIV-1 risk populations based on the genetic transmission network of the newly diagnosed HIV cases in Jiangsu, Eastern China.

Ying Zhou, Jing Lu, Zhi Zhang, Qi Sun, Xiaoqin Xu, Haiyang Hu

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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 at 1 institution in 1 country.

Ying ZhouInstitute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
Jing LuInstitute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
Zhi ZhangInstitute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
Qi SunInstitute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
Xiaoqin XuInstitute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
Haiyang HuInstitute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
Jiangsu Provincial Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The HIV-1 prevalence has been steadily increasing in Jiangsu, China. HIV-1 genetic transmission network can be used to explore the transmission kinetics and precision intervention in high-risk populations. Thus, we generated an HIV-1 genetic transmission network, explored key risk populations based on different risk factors and found out the risk factors for HIV-1 prevention and control among the newly-diagnosed HIV-1 cases from 2017 to 2018. Method: We amplified the HIV-1 Results: We obtained 3362 sequences with the Conclusion: The HIV-1 genetic transmission network is adept at discovering undiagnosed HIV-infected cases and linking all diagnosed cases for determination of risk infections. Therefore we should pay more attention to these risk infections with further investigation and intervention, helping to achieve the goal of 95 % use combination prevention from the World Health Organization, and push to end AIDS epidemic.

Indexed as

Genetic transmission networkHIV-1Newly-diagnosedRisk population

Identifiers

PMID38125421
PMCPMC10730745
OpenAlexW4389100788

What OpenQuestion 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 OpenQuestion graph.