Evidence map›Paper›PMID 35734773›Full record

ArticleComputational and mathematical methods in medicine2022

Transmission and Drug Resistance Characteristics of Human Immunodeficiency Virus-1 Strain Using Medical Information Data Retrieval System.

Ning Wang, Hui Qi, Yong Deng, Weiwei Yu, Zhong Chen

Abstract read
In one paragraph

Article in Computational and mathematical methods 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Clinical Information Retrieval: A Literature Review.Journal of healthcare informatics research · 2024
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Ning WangDepartment of Infection and Immunology, The First Hospital of Changsha City, Changsha, 410000 Hunan, China.ORCID https://orcid.org/0000-0003-4007-7240
Hui QiDepartment of Infection and Immunology, The First Hospital of Changsha City, Changsha, 410000 Hunan, China.ORCID https://orcid.org/0000-0002-9742-2183
Yong DengDepartment of Infection and Immunology, The First Hospital of Changsha City, Changsha, 410000 Hunan, China.ORCID https://orcid.org/0000-0003-4016-5355
Weiwei YuPostgraduate School, Changsha Hospital Affiliated to Nanhua University, Changsha, 410000 Hunan, China.ORCID https://orcid.org/0000-0003-3380-5107
Zhong ChenDepartment of Infection and Immunology, The First Hospital of Changsha City, Changsha, 410000 Hunan, China.ORCID https://orcid.org/0000-0002-1246-0405

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was aimed at exploring the transmission and drug resistance characteristics of acquired immunodeficiency syndrome (AIDS) caused by human immunodeficiency virus-1 (HIV-1). The query expansion algorithm based on Candecomp Parafac (CP) decomposition was adopted to construct a data information retrieval system for semantic web and tensor decomposition. In the latent variable model based on tensor decomposition, the three elements in the triples generated feature vectors to calculate the training samples. The HIV patient data set was selected to evaluate the performance of the system, and then, the HIV gene resistance of 213 patients was retrospectively analyzed based on the electronic medical records. 43 cases showed failure of ribonucleic acid drug resistance, the ART virological failure rate was 24.43% (43/213), and one case was not reported. There was 1 case of RNA hemolysis that could not be detected. There were 50 resistant cases of nonnucleotide reverse transcriptase inhibitors (NNRTI), accounting for 29.94% (50/167), and there were 17 resistant cases of nucleotide reverse transcriptase inhibitors (NRTI), accounting for 10.18% (17/167) of all mutation cases. Among the HIV-1 strains, 19 cases failed the detection of drug resistance sites in the integrase region, and mutations in the integrase region were significantly more than those in the protease region. There were 12 types of HIV-1 strains with drug-resistant mutations. The fusion technical scheme constructed in this study showed excellent performance in medical information retrieval. In this study, the characteristics of HIV-1 of AIDS patients were analyzed from different directions, and effective treatment was performed for patients, so as to provide reference for clinical diagnosis of AIDS patients.

Indexed as

Acquired Immunodeficiency SyndromeAnti-HIV AgentsHIV-1HIV InfectionsDrug Resistance, ViralGenotypeHumansInformation Storage and RetrievalIntegrasesMutationRetrospective StudiesReverse Transcriptase InhibitorsAnti-HIV AgentsIntegrasesReverse Transcriptase Inhibitors

Identifiers

PMID35734773
PMCPMC9208953

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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.