MétaCan
Menu
Back to cohort
Record W2008700853 · doi:10.1086/321902

Effect of Cessation of Highly Active Antiretroviral Therapy during a Discordant Response: Implications for Scheduled Therapeutic Interruptions

2001· article· en· W2008700853 on OpenAlexafffund
Nanci Hawley‐Foss, Georgina Mbisa, Julian J. Lum, André A. Pilon, Jonathan B. Angel, Gary Garber, Andrew D. Badley

Bibliographic record

VenueClinical Infectious Diseases · 2001
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersMedical Research CouncilMedical Research Council CanadaOntario HIV Treatment Network
KeywordsMedicineViremiaAntiretroviral therapyViral loadInternal medicineObservational studyPharmacotherapyImmunologyRetrospective cohort studyOncologyIntensive care medicineHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Although treatment with combination antiretroviral therapy leads to a reduction in the level of plasma viremia and an improvement in CD4 T cell count for most patients, for a minority of patients, an improvement in CD4 T cell count occurs despite the failure of treatment to suppress viral replication. Recent reports suggest that these discordant improvements in CD4 T cell count may last for months to years and are associated with improved clinical outcomes. In a retrospective observational study, we evaluated the effect of therapy cessation on 8 patients with discordant immunologic responses to therapy and found that improved CD4 T cell responses are dependent upon ongoing drug pressure. If antiretroviral agents that are likely to resuppress the virus are not available, we suggest that patients continue the therapy associated with immunologic improvement to maximize the clinical benefit of the discordant response.

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)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.406
Teacher spread0.365 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueClinical Infectious DiseasesSame topicHIV Research and TreatmentFrench-language works237,207