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Record W2058400007 · doi:10.1177/154510970200100304

Can Structured Treatment Interruptions (STIs) Be Used as a Strategy to Decrease Total Drug Requirements and Toxicity in HIV Infection?

2002· review· en· W2058400007 on OpenAlexaff
Sharon Walmsley, Mona Loutfy

Bibliographic record

VenueJournal of the International Association of Physicians in AIDS Care · 2002
Typereview
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity Health NetworkToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineClinical trialRegimenSeroconversionHuman immunodeficiency virus (HIV)Intensive care medicinePopulationDrugDrug holidayAntiretroviral therapyViral loadInternal medicineImmunologyPharmacologyEnvironmental health

Abstract

fetched live from OpenAlex

Structured treatment interruptions (STIs) are a new strategy under investigation in clinical trials involving a number of different HIV-infected populations. These populations include patients with prolonged HIV RNA suppression who were treated in either seroconversion or later in disease, and patients with virologic failure despite HAART, prior to the initiation of a salvage regimen. The goals of STI vary in each of these groups. Until the results of clinical trials are available, the use of STIs must be considered experimental. There are a number of potential risks, including the loss of a significant number of CD4 cells with the development of opportunistic infections, rebound of HIV RNA, emergence of drug resistance, and reseeding of viral reservoirs. However, STIs also hold the promise for decreasing antiretroviral drug burden and toxicity, and improving quality of life. Given that much of the world's population infected with HIV does not have access to continuous HAART, the development of strategies that could decrease overall drug burden and cost is important. This paper provides an update of the recently published and presented studies on the use of STIs in various populations of HIV-infected patients. In particular, it discusses what is known and unknown about the relative risks and benefits of this approach, and what studies are ongoing. Lastly, it identifies how the use of STIs could decrease drug burden and toxicity in patients receiving therapy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.343
Teacher spread0.313 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations12
Published2002
Admission routes1
Has abstractyes

Explore more

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