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Record W2023728019 · doi:10.1097/qai.0b013e3181b065cf

Increased Risk of Genital Ulcer Disease in Women During the First Month After Initiating Antiretroviral Therapy

2009· article· en· W2023728019 on OpenAlexaff
Susan M. Graham, Linnet N. Masese, Ruth Gitau, D Mwakangalu, Walter Jaoko, J.O. Ndinya‐Achola, K Mandaliya, Norbert Peshu, JM Baeten, RS McClelland

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2009
Typearticle
Languageen
FieldMedicine
TopicSyphilis Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious Diseases
KeywordsMedicineGenital ulcerAntiretroviral therapySex organDiseaseSexually transmitted diseaseHuman immunodeficiency virus (HIV)Internal medicineImmunologyViral loadBiologySyphilis

Abstract

fetched live from OpenAlex

INTRODUCTION: Genital ulcer disease (GUD) is common in HIV-1-infected women, and a small number of studies have suggested increased GUD risk after antiretroviral therapy (ART) initiation. To better define this risk, we monitored 134 women at ART initiation and monthly thereafter. METHODS: Women were evaluated monthly for genital ulcers. Syphilis serology was tested quarterly, and chancroid culture was performed on ulcers that were felt to be clinically consistent with a diagnosis of chancroid. A logistic model with generalized estimating equations was used to analyze predictors of GUD from baseline until 6 months after ART initiation. RESULTS: During the study period, GUD occurred in 54 women (40.3%) at 85 visits (10.0%). GUD prevalence was 9.7% at baseline, increased to 16.7% at month 1 [adjusted odds ratio (aOR) 1.9 (1.0-3.6), P = 0.04], then decreased to 6.4% by month 6. History of GUD [aOR 3.8 (1.9-7.7), P < 0.001) and CD4 count <100 [aOR 1.8 (1.0-3.4), P = 0.06] were associated with increased risk of GUD after ART initiation. DISCUSSION: Women experience increased risk of GUD in the first month after ART initiation, particularly if they have low CD4 counts or a history of GUD.

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 score0.013
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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

Citations12
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJAIDS Journal of Acquired Immune Deficiency SyndromesSame topicSyphilis Diagnosis and TreatmentFrench-language works237,207