Evidence map›Paper›PMID 23743788›Full record

ReviewCurrent opinion in HIV and AIDS2013

What is needed to eliminate new pediatric HIV infections: the contribution of model-based analyses.

Katie Doherty, Andrea Ciaranello

Abstract readReview
In one paragraph

Review in Current opinion in HIV and AIDS, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Using Observational Data to Inform HIV Policy Change for Children and Youth.Journal of acquired immune deficiency syndromes (1999) · 2018
    Observational
  5. Article
  6. Article
  7. 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

2 authors at 1 institution in 1 country.

Katie DohertyThe Medical Practice Evaluation Center, Divisions of General Medicine bInfectious Disease, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. kdoherty6@partners.org
Andrea Ciaranello
Massachusetts General Hospital · US

Funding

LOC-IMPAACT Leadership GroupPharmacokinetics and Safety of Remdesivir for Treatment of COVID-19 in Pregnant Women in the USUM1AI068632 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI Jennifer Jao, Sharon A Nachman · 2011 to 2026
$278.1M
Statistical and Data Management Center-Pediatric,Adolescent, and Maternal CTGUM1AI068616 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Sean Scott Brummel, Marlene Ann Cooper · 2011 to 2026
$155.6M
International Maternal Pediatric Adolescent AIDS Clinical Trials (IMPAACT) GroupU01AI068632 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI JACKSON, J BROOKS · 2006 to 2010
$109.7M
LC - IMPAACT Leadership GroupUM1AI106716 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Grace M Aldrovandi · 2014 to 2026
$47.2M
Statistical/Data Management Center-Pediatric AIDS CTGU01AI041110 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI FENTON, TERRENCE · 1997 to 2006
$38.6M
Statistical and Data Management Center-Pediatric,Adolescent, and Maternal CTGU01AI068616 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI SHAPIRO, DAVID ERIC · 2006 to 2010
$38.6M
Optimizing HIV Care in Less Developed CountriesR01AI058736 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Kenneth Alan Freedberg, Emily Parker Hyle · 2004 to 2026
$21.5M
Optimizing Outcomes for HIV-Exposed and HIV-Infected Children in South AfricaK01AI078754 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI CIARANELLO, ANDREA LYNNE · 2009 to 2013
$685k
INTRACELLULAR PH PHYSIOLOGY IN MESANGIAL CELL GROWTHF32DK009001 · NIDDK · YALE UNIVERSITY · PI SINGH, SATISH K · 1993 to 1995
–
NIAID NIH HHS 5 U01 AI41110NIAID NIH HHS K01 AI078754NIAID NIH HHS R01 AI058736NIAID NIH HHS U01 AI041110NIAID NIH HHS U01 AI068616NIAID NIH HHS U01 AI068632NIAID NIH HHS UM1 AI068616NIAID NIH HHS UM1 AI068632NIAID NIH HHS UM1 AI106716NICHD NIH HHS HHSN267200800001CNIDDK NIH HHS HHSN267200800001GNIDDK NIH HHS N01-DK-9-001
6 · The paper itself

Abstract

purpose of reviewComputer simulation models can identify key clinical, operational, and economic interventions that will be needed to achieve the elimination of new pediatric HIV infections. In this review, we summarize recent findings from model-based analyses of strategies for prevention of mother-to-child HIV transmission (MTCT). RECENT

findingsIn order to achieve elimination of MTCT (eMTCT), model-based studies suggest that scale-up of services will be needed in several domains: uptake of services and retention in care (the PMTCT 'cascade'), interventions to prevent HIV infections in women and reduce unintended pregnancies (the 'four-pronged approach'), efforts to support medication adherence through long periods of pregnancy and breastfeeding, and strategies to make breastfeeding safer and/or shorter. Models also project the economic resources that will be needed to achieve these goals in the most efficient ways to allocate limited resources for eMTCT. Results suggest that currently recommended PMTCT regimens (WHO Option A, Option B, and Option B+) will be cost-effective in most settings. SUMMARY: Model-based results can guide future implementation science, by highlighting areas in which additional data are needed to make informed decisions and by outlining critical interventions that will be necessary in order to eliminate new pediatric HIV infections.

Indexed as

Anti-Retroviral AgentsComputer SimulationCosts and Cost AnalysisFamily Planning ServicesFemaleHIV InfectionsHumansInfant, NewbornInfectious Disease Transmission, VerticalMedication AdherencePerinatal CarePregnancyAnti-Retroviral Agents

Identifiers

PMID23743788
PMCPMC3799993
OpenAlexW2074339575

What OpenQuestion holds

Textmetadata
LicenceTDM
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.