Evidence map›Paper›PMID 23646162›Full record

ArticlePloS one2013

Challenges of diagnosing acute HIV-1 subtype C infection in African women: performance of a clinical algorithm and the need for point-of-care nucleic-acid based testing.

Koleka Mlisana, Magdalena Sobieszczyk, Lise Werner, Addi Feinstein, Francois van Loggerenberg, Nivashnee Naicker, Carolyn Williamson, Nigel Garrett

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. How can we better identify early HIV infections?Current opinion in HIV and AIDS · 2015
    Review
  10. 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

8 authors at 4 institutions in 2 countries.

Koleka MlisanaCentre for the AIDS Programme of Research in South Africa-CAPRISA, University of KwaZulu-Natal, Durban, South Africa. mlisanak@ukzn.ac.za
Magdalena Sobieszczyk
Lise Werner
Addi Feinstein
Francois van Loggerenberg
Nivashnee Naicker
Carolyn Williamson
Nigel Garrett
University of KwaZulu-Natal · ZACentre for the AIDS Programme of Research in South Africa · ZAColumbia University · USUniversity of Cape Town · ZA

Funding

The Viral Set Point in HIV-1 Subtype C InfectionU19AI051794 · NIAID · UNIVERSITY OF KWAZULU-NATAL · PI ABDOOL KARIM, SALIM S · 2002 to 2007
$22.5M
ENHANCING, TRAINING, RESEARCH CAPACITY AND EXPERTISE IN HIV CARE-ENTREER24TW008863 · FIC · UNIVERSITY OF KWAZULU-NATAL · PI BOBAT, RAZIYA, HAMMER, SCOTT M · 2010 to 2015
$8.6M
FIC NIH HHS R24 TW008863NIAID NIH HHS AI51794NIAID NIH HHS U19 AI051794
6 · The paper itself

Abstract

backgroundPrompt diagnosis of acute HIV infection (AHI) benefits the individual and provides opportunities for public health intervention. The aim of this study was to describe most common signs and symptoms of AHI, correlate these with early disease progression and develop a clinical algorithm to identify acute HIV cases in resource limited setting.

methods245 South African women at high-risk of HIV-1 were assessed for AHI and received monthly HIV-1 antibody and RNA testing. Signs and symptoms at first HIV-positive visit were compared to HIV-negative visits. Logistic regression identified clinical predictors of AHI. A model-based score was assigned to each predictor to create a risk score for every woman.

resultsTwenty-eight women seroconverted after a total of 390 person-years of follow-up with an HIV incidence of 7.2/100 person-years (95%CI 4.5-9.8). Fifty-seven percent reported ≥1 sign or symptom at the AHI visit. Factors predictive of AHI included age <25 years (OR = 3.2; 1.4-7.1), rash (OR = 6.1; 2.4-15.4), sore throat (OR = 2.7; 1.0-7.6), weight loss (OR = 4.4; 1.5-13.4), genital ulcers (OR = 8.0; 1.6-39.5) and vaginal discharge (OR = 5.4; 1.6-18.4). A risk score of 2 correctly predicted AHI in 50.0% of cases. The number of signs and symptoms correlated with higher HIV-1 RNA at diagnosis (r = 0.63; p<0.001).

conclusionsAccurate recognition of signs and symptoms of AHI is critical for early diagnosis of HIV infection. Our algorithm may assist in risk-stratifying individuals for AHI, especially in resource-limited settings where there is no routine testing for AHI. Independent validation of the algorithm on another cohort is needed to assess its utility further. Point-of-care antigen or viral load technology is required, however, to detect asymptomatic, antibody negative cases enabling early interventions and prevention of transmission.

Indexed as

AdultAlgorithmsCohort StudiesFemaleHIV-1HIV InfectionsHumansMass ScreeningMiddle AgedMolecular Diagnostic TechniquesPoint-of-Care SystemsReproducibility of ResultsRiskSouth AfricaYoung Adult

Identifiers

PMID23646162
PMCPMC3639937
OpenAlexW2126554222

What OpenQuestion holds

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LicenceCC BY
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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.