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Record W2898029178 · doi:10.2196/10807

Acute HIV Infection in Youth: Protocol for the Adolescent Trials Network 147 (ATN147) Comprehensive Adolescent Research and Engagement Studies (CARES) Study

2018· article· en· W2898029178 on OpenAlexvenueno aff
Karin Nielsen‐Saines, Kate L. Mitchell, Tara Kerin, Jasmine Fournier, Leslie Kozina, Brenda Andrews, Ruth Cortado, Robert Bolan, Risa Flynn, Mary Jane Rotheram‐Borus, Sue Ellen Abdalian, Yvonne J. Bryson

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of Mental HealthNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseAdolescent Medicine Trials Network for HIV/AIDS Interventions
KeywordsCartMedicineAntiretroviral therapyHuman immunodeficiency virus (HIV)Public healthTransmission (telecommunications)Clinical trialViral loadFamily medicinePsychiatryPediatricsInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Early treatment studies have shown that prompt treatment of HIV with combination antiretroviral therapy (cART) can limit the size of latent viral reservoirs, thereby providing clinical and public health benefits. Studies have demonstrated that adolescents have a greater capacity for immune reconstitution than adults. Nevertheless, adolescents who acquired HIV through sexual transmission have not been included in early treatment studies because of challenges in identification and adherence to cART. OBJECTIVE: This study aimed to identify and promptly treat with cART youth aged 12 to 24 years in Los Angeles and New Orleans who have acute, recent, or established HIV infection, as determined by Fiebig stages 1 to 6 determined by viral RNA polymerase chain reaction, p24 antigen presence, and HIV-1 antigen Western blot. The protocol recommends treatment on the day of diagnosis when feasible. Surveillance and dedicated behavioral strategies are used to retain them in care and optimize adherence. Through serial follow-up, HIV biomarkers and response to antiretroviral therapy (ART) are assessed. The study aims to assess viral dynamics, decay and persistence of viral reservoirs over time, and correlate these data with the duration of viral suppression. METHODS: A total of 72 youth (36 acutely infected and 36 treatment naïve controls) are enrolled across clinical sites using a current community-based strategy and direct referrals. Youth are prescribed ART according to the standard of care HIV-1 management guidelines and followed for a period of 2 years. Assessments are conducted at specific time points throughout these 2 years of follow-up for monitoring of adherence to ART, viral load, magnitude of HIV reservoirs, and presence of coinfections. RESULTS: The study began enrolling youth in July 2017 across study sites in Los Angeles and New Orleans. As of September 30, 2018, a total of 37 youth were enrolled, 12 with recently acquired, 16 with established HIV infection as determined by Fiebig staging, and 9 pending determination of Fiebig status. Recruitment and enrollment are ongoing. CONCLUSIONS: We hypothesize that the size of the HIV reservoir and immune activation markers will be different across groups treated with cART, that is, those with acute or recent HIV infection and those with established infection. Adolescents treated early who are virally suppressed will have diminished HIV reservoirs than those with established infection. These youth may be potential candidates for a possible HIV vaccine and additional HIV remission intervention trials. Our study will inform future studies of viral remission strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/10807.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.047
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.047
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.036
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0300.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.739
GPT teacher head0.671
Teacher spread0.068 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2018
Admission routes1
Has abstractyes

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