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Record W2118600467 · doi:10.1186/1758-2652-8-2-72

A Population‐Based and Longitudinal Study of Sexual Behavior and Multidrug‐Resistant HIV Among Patients in Clinical Care

2006· article· en· W2118600467 on OpenAlexaff
Michael J. Kozal, K. Rivet Amico, Jennifer Chiarella, Deborah H. Cornman, William A. Fisher, Jeffrey D. Fisher, Gerald Friedland

Bibliographic record

VenueJournal of the International AIDS Society · 2006
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineHIV drug resistancePopulationDrug resistanceViral loadMultiple drug resistanceDrug classMen who have sex with menHuman immunodeficiency virus (HIV)DemographyDrugImmunologyPsychiatryEnvironmental healthAntiretroviral therapySyphilis

Abstract

fetched live from OpenAlex

BACKGROUND: Population-based and longitudinal information regarding sexual risk behavior among patients with multidrug resistant (MDR) HIV and their sexual partners is of great public health and clinical importance. OBJECTIVE: To characterize the HIV sexual risk behaviors of patients with and without drug-resistant HIV in the clinical care setting over time. MEASUREMENTS: 393 HIV-positive patients completed questionnaires of self-reported sexual risk behaviors at approximate 6-month intervals extending over 24 months. HIV viral load and genotypic drug resistance obtained during the same time points were matched to the behavioral data. Multidrug resistance was defined as having resistance to 2 or 3 antiretroviral (ARV) drug classes. RESULTS: In serial cross-sectional analyses, 393 patients (44% female and 79% heterosexual) contributed 919 matched behavioral and virologic results over the 24 months of data collection. Of these, 250 patients (64%) reported having sex during at least 1 survey period resulting in greater than 10,000 sexual events with more than 1000 partners. Unprotected sexual behavior was reported by 45% of sexually active patients, resulting in 34% of all sex events that exposed 29% of all partners. Of these patients with unprotected sexual events, 31% had HIV drug resistance--11.6% with resistance to 2 classes of ARVs (2-class), and 1.8% with 3-class ARV resistance at the time of a sexual risk event. Close to 1000 or 28% of all unprotected sexual events involved resistant strains (11% of these with resistance to 2 classes and 0.2% with 3-class resistance, exposing 20% of unprotected sexual partners to resistant HIV (8% to 2-class and 0.6% to 3-class resistance). In longitudinal analysis among the 78 patients who reported a cumulative total of 12 months of sexual history and had resistance testing, 38% reported engaging in unprotected sexual behavior. There was substantial and complex variation in the distribution of unprotected sexual events and in the detection of resistance over time. CONCLUSION: In this study of HIV sexual risk and resistance over time among HIV-infected patients in clinical care, a substantial proportion engaged in unprotected sex and had drug-resistant HIV, frequently exposing partners to 1- or 2-class resistant HIV strains. However, relatively few exposures involved 3-class resistance. The dynamics of sexual risk behavior and HIV drug resistance are complex and vary over time and urgently require both general and targeted interventions to reduce transmission of resistant HIV.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
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 head0.035
GPT teacher head0.378
Teacher spread0.344 · 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

Citations13
Published2006
Admission routes1
Has abstractyes

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