Evidence map›Paper›PMID 28051896›Full record

ArticleAIDS patient care and STDs2017

Optimizing the Timing of HIV Screening as Part of Routine Medical Care.

Matthew R Golden, James P Hughes, Julia C Dombrowski

Open access · greenAbstract read
In one paragraph

Article in AIDS patient care and STDs, 2017. 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
0.3field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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 1 country.

Matthew R Golden1 Division of Infectious Diseases, Department of Medicine, University of Washington , Seattle, Washington.
James P Hughes3 Department of Biostatistics, University of Washington , Seattle, Washington.
Julia C Dombrowski1 Division of Infectious Diseases, Department of Medicine, University of Washington , Seattle, Washington.
Public Health – Seattle & King County · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

US federal guidelines recommend that medical providers test all adolescents and adults for HIV infection at least once before the age of 64. The wide age range included in these guidelines may limit their utility and impact. We created an arithmetic model to estimate how HIV screening at different ages would impact the total number of years of undiagnosed HIV infection in the population and the number of persons developing clinical manifestations of HIV/AIDS. Our base case model assumed that age of infection in the screened population was the same as the estimated age of infection among all persons diagnosed with HIV in the United States in 2010. We parameterized a second model assuming age of infection was similar to the younger age distribution observed in African Americans. In the base case model, the number of years of undiagnosed HIV infection and number of persons with clinical manifestations of HIV/AIDS were both minimized by screening at age 34. If age of infection was similar to that estimated to occur among African Americans, testing at age 24 and 27 would minimize the number of years of undiagnosed infection and clinical cases, respectively. For both parameterization scenarios, testing between the ages of 21 and 38 resulted in outcomes within 10% of the model's estimated optimal age for screening. Focusing HIV screening on a narrower age range than is currently recommended may improve the impact of routine HIV screening efforts.

Indexed as

AIDS SerodiagnosisMass ScreeningModels, TheoreticalAdolescentAdultBlack or African AmericanFemaleHIV InfectionsHumansMalePopulation SurveillanceSerologic TestsUnited StatesYoung AdultHIVmathematical modelscreening

Identifiers

PMID28051896
PMCPMC5220561
OpenAlexW2594674179

What OpenQuestion holds

Textmetadata
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.