Evidence map›Paper›PMID 22742573›Full record

ArticleBMC infectious diseases2012

Mean CD4 cell count changes in patients failing a first-line antiretroviral therapy in resource-limited settings.

Alexandra Calmy, Eric Balestre, Fabrice Bonnet, Andrew Boulle, Eduardo Sprinz, Robin Wood, Eric Delaporte, Eugène Messou, James McIntyre, Kamal Marhoum El Filali and 10 more

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

5 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Implementation of HIV and Tuberculosis Diagnostics: The Importance of Context.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2015
    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

20 authors at 13 institutions in 8 countries.

Alexandra CalmyHIV Unit, Geneva University Hospital, Geneva, Switzerland. acalmy@gmail.com
Eric Balestre
Fabrice Bonnet
Andrew Boulle
Eduardo Sprinz
Robin Wood
Eric Delaporte
Eugène Messou
James McIntyre
Kamal Marhoum El Filali
Mauro Schechter
N Kumarasamy
David Bangsberg
Patrick McPhail
Stefaan Van Der Borght
Carlos Zala
Matthias Egger
Rodolphe Thiébaut
François Dabis
T-LINC of IeDEA Collaboration (Asia, South America, East, Southern and West Africa)
Bordeaux Population Health · FRCentre Hospitalier Universitaire Ibn Rochd · MAHeineken (Netherlands) · NLHelen Joseph Hospital · ZAHospital de Clínicas de Porto Alegre · BRInstitut de Recherche pour le Développement · FRPerinatal HIV Research Unit · ZASociété de Développement des Forêts · CIUniversité de Bordeaux · FRUniversity Hospital of Geneva · CHUniversity of Bern · CHUniversity of Cape Town · ZAYR Gaitonde Centre for AIDS Research and Education · IN

Funding

The impact of HIV viral diversity and cellular immunity on HIV pathogenesisP30AI060354 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI ROBERT A. PARKER · 2004 to 2026
$94.4M
Observational Antiretroviral Studies In Southern Africa (OASIS) CollaborationU01AI069924 · NIAID · UNIVERSITAT BERN · PI Cleophas Chimbetete, Mary-Ann Davies · 2006 to 2026
$55.9M
The Asia-Pacific HIV Research CollaborationU01AI069907 · NIAID · FOUNDATION FOR AIDS RESEARCH · PI ANNETTE H SOHN · 2006 to 2026
$44.8M
WADA (West Africa Database on Antiretroviral Therapy) CollaborationU01AI069919 · NIAID · UNIVERSITY OF BORDEAUX II · PI Didier Koumavi Ekouevi, Antoine Jaquet · 2006 to 2026
$29.9M
TB PREVENTION AND HIV IN THE HOMELESS--AN INTERVENTIONR01MH054907 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BANGSBERG, DAVID ROY · 1995 to 2014
$20.7M
NIAID NIH HHS P30 AI060354NIAID NIH HHS U01 AI069907NIAID NIH HHS U01 AI069919NIAID NIH HHS U01 AI069924NIMH NIH HHS R01 MH054907
6 · The paper itself

Abstract

backgroundChanges in CD4 cell counts are poorly documented in individuals with low or moderate-level viremia while on antiretroviral treatment (ART) in resource-limited settings. We assessed the impact of on-going HIV-RNA replication on CD4 cell count slopes in patients treated with a first-line combination ART.

methodNaïve patients on a first-line ART regimen with at least two measures of HIV-RNA available after ART initiation were included in the study. The relationships between mean CD4 cell count change and HIV-RNA at 6 and 12 months after ART initiation (M6 and M12) were assessed by linear mixed models adjusted for gender, age, clinical stage and year of starting ART.

results3,338 patients were included (14 cohorts, 64% female) and the group had the following characteristics: a median follow-up time of 1.6 years, a median age of 34 years, and a median CD4 cell count at ART initiation of 107 cells/μL. All patients with suppressed HIV-RNA at M12 had a continuous increase in CD4 cell count up to 18 months after treatment initiation. By contrast, any degree of HIV-RNA replication both at M6 and M12 was associated with a flat or a decreasing CD4 cell count slope. Multivariable analysis using HIV-RNA thresholds of 10,000 and 5,000 copies confirmed the significant effect of HIV-RNA on CD4 cell counts both at M6 and M12.

conclusionIn routinely monitored patients on an NNRTI-based first-line ART, on-going low-level HIV-RNA replication was associated with a poor immune outcome in patients who had detectable levels of the virus after one year of ART.

Indexed as

CD4 Lymphocyte CountAdultAnti-HIV AgentsFemaleHIV InfectionsHumansMaleRNA, ViralAnti-HIV AgentsRNA, Viral

Identifiers

PMID22742573
PMCPMC3573925
OpenAlexW2134600698

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.