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Record W1998200336 · doi:10.1155/2012/595762

Cost-Effectiveness of Antiretroviral Therapy for Multidrug-Resistant HIV: Past, Present, and Future

2012· article· en· W1998200336 on OpenAlexaff
Marianne Harris, Bohdan Nosyk, Richard Harrigan, Viviane D. Lima, Calvin Cohen, Julio Montaner

Bibliographic record

VenueAIDS Research and Treatment · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsAIDS VancouverUniversity of British ColumbiaProvidence Health Care
Fundersnot available
KeywordsEnfuvirtideEtravirineDarunavirMedicineRaltegravirTolerabilityMaravirocIntensive care medicineAntiretroviral therapyHuman immunodeficiency virus (HIV)Viral loadPharmacologyVirologyImmunologyAdverse effect

Abstract

fetched live from OpenAlex

In the early years of the highly active antiretroviral therapy (HAART) era, HIV with resistance to two or more agents in different antiretroviral classes posed a significant clinical challenge. Multidrug-resistant (MDR) HIV was an important cause of treatment failure, morbidity, and mortality. Treatment options at the time were limited; multiple drug regimens with or without enfuvirtide were used with some success but proved to be difficult to sustain for reasons of tolerability, toxicity, and cost. Starting in 2006, data began to emerge supporting the use of new drugs from the original antiretroviral classes (tipranavir, darunavir, and etravirine) and drugs from new classes (raltegravir and maraviroc) for the treatment of MDR HIV. Their availability has enabled patients with MDR HIV to achieve full and durable viral suppression with more compact and cost-effective regimens including at least two and often three fully active agents. The emergence of drug-resistant HIV is expected to continue to become less frequent in the future, driven by improvements in the convenience, tolerability, efficacy, and durability of first-line HAART regimens. To continue this trend, the optimal rollout of HAART in both rich and resource-limited settings will require careful planning and strategic use of antiretroviral drugs and monitoring technologies.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.095
GPT teacher head0.397
Teacher spread0.302 · 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 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

Citations11
Published2012
Admission routes1
Has abstractyes

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