Evidence map›Paper›PMID 38393126›Full record

ArticleTropical medicine and infectious disease2024

Risk Screening Tools Could Potentially Miss HIV-Positive Individuals Who Seek Testing Services: A Secondary Program Data Analysis on the Performance Characteristics of an Adolescent and Adult HIV Risk Screening Tool in Uganda.

Marvin Lubega, Katherine Guerra, Megan Ginivan, Yewande Kamuntu, George Senyama, Andrew Musoke, Fiona Gambanga, Shaukat Khan, Geoffrey Taasi, Sylivia Nalubega and 1 more

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 98% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 2 institutions in 2 countries.

Marvin LubegaClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.ORCID 0000-0002-6039-1432
Katherine GuerraClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.
Megan GinivanClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.
Yewande KamuntuClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.
George SenyamaClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.
Andrew MusokeClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.ORCID 0009-0000-9110-6326
Fiona GambangaClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.ORCID 0009-0005-9339-3003
Shaukat KhanClinton Health Access Initiative-Uganda, Moyo Close, Kampala P.O. Box 2191, Uganda.ORCID 0000-0001-7247-4190
Geoffrey TaasiAIDS Control Program, Ministry of Health, Plot 6, Lourdel Road, Kampala P.O. Box 7272, Uganda.
Sylivia NalubegaInstitute of Applied Technology, Fatima College of Health Sciences, Ajman P.O. Box 3798, United Arab Emirates.
John Bosco Junior MatovuAIDS Control Program, Ministry of Health, Plot 6, Lourdel Road, Kampala P.O. Box 7272, Uganda.
Ministry of Health · UGUniversity of Nairobi · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improving HIV testing efficiency saves financial and material resources for health. We conducted a secondary data analysis of routinely collected HIV risk-screening program data in Uganda, from October to November 2019, to determine the performance characteristics of the adolescent and adult HIV risk screening tools in public health facilities. A total of 19,854 clients had been screened for HIV testing eligibility and tested for HIV. The overall positivity rate (cluster-weighted prevalence of HIV) among those screened was 4.5% (95% CI: 4.1-4.8) versus 3.71% (95% CI: 3.06-4.50) among those not screened. The sensitivity and specificity of the risk screening tool were 91% (95% CI: 89-93) and 25% (24.2-26), respectively. With screening, the number needed to test to identify one PLHIV was reduced from 27 to 22. Although risk screening would have led to a 24.5% (4825/19,704) reduction in testing volume, 9.3% (68/732) of PLHIV would have been missed and be misclassified as not eligible for testing. The cost saving per PLHIV identified was minimally reduced by 3% from USD 69 without screening to USD 66.9 with screening. Since the treatment-adjusted prevalence of HIV is dropping globally, overzealous use of risk screening tools to determine who to test or not carries the potential of missing PLHIV due to their limited specificity. We recommend the use of scientifically validated HIV risk screening tools, and a need to explore the use of HIV self-testing as a test for tirage to minimize misclassification of people who seek HIV testing services.

Indexed as

HIV risk screeningHIV risk screening toolsHIV testing cost analysisHIV testing servicesmisclassification

Identifiers

PMID38393126
PMCPMC10892028
OpenAlexW4391430910

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.