Evidence map›Paper›PMID 34079385›Full record

ArticleHIV/AIDS (Auckland, N.Z.)2021

Clustering of HIV Patients in Ethiopia.

Wondimu Biressaw, Habtamu Tilaye, Dessie Melese

Open access · goldAbstract read
In one paragraph

Article in HIV/AIDS (Auckland, N.Z.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 7 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

3 authors at 2 institutions in 2 countries.

Wondimu BiressawBenishangul-Gumuz, Wombera Sineor Secondary and Preparatory School, Benishangul, Ethiopia.
Habtamu TilayeUniversity of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, Ethiopia.
Dessie MeleseUniversity of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, Ethiopia.ORCID 0000-0002-5621-6252
University of Gondar · ETSaint Joseph Seminary College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAmong the many worldwide health problems, HIV/AIDS has caused severe health problems in several countries. The problem is also widely seen in Ethiopia. The general objective of the study is to cluster HIV patients and to find out the factors that mostly affect the prevalence of HIV within a group (cluster) and between groups (clusters) of HIV patients.

methodsThe study is made based on the 2016 Ethiopian Demographic Health Survey (EDHS) which was collected by the Central Statistical Agency (CSA) of Ethiopia, and the survey collected a total of 26,753 samples, of which 14,785 were women and 11,968 were men and the age group was between 15 and 49 years for both. Binary logistic regression, principal component analysis, cluster analysis, and ANOVA were applied to analyze the data.

resultsThe result from binary logistic regression reveals that 15 factors such as ever heard of AIDS, region, water not available for at least a day in the last 2 weeks, has a radio, family members wash their hands, location of the source of water, everything completed to water to make it harmless to drink, food cooked in the house/separate house/outside, has a mobile telephone, has a table, type of place of residence, highest education level attained, current marital status, sex of household members, and age of household members are all significant factors that affect HIV status.

conclusionUsing these significant variables, 12 principal components are identified which describe 78% of the variation in the data. The result of HIV patients are clustered into 3 clusters and determine the status of HIV levels. Mainly, cluster 2 accounts for 50% of HIV patients whereas cluster 3 and 1 accounts for 40% and 10%, respectively.

Indexed as

cluster analysisEthiopian Demographic Health Survey; EDHSHIV patientsprincipal component analysis

Identifiers

PMID34079385
PMCPMC8164663
OpenAlexW3165356376

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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.