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Record W7073672382

Gender differences in clinical, immunological, and virological outcomes in highly active antiretroviral-treated HIV–HCV coinfected patients

2010· article· en· W7073672382 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed Central · 2010
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAntiretroviral therapyHuman immunodeficiency virus (HIV)Confidence intervalSidaViral loadMortality rate
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: The influence of biological sex on human immunodeficiency virus (HIV) antiretroviral treatment outcome is not well described in HIV–hepatitis C (HCV) coinfection. METHODS: We assessed patients’ clinical outcomes of HIV–HCV coinfected patients initiating antiretroviral therapy attending the Ottawa Hospital Immunodeficiency Clinic from January 1996 to June 2008. RESULTS: We assessed 144 males and 39 females. Although similar in most baseline characteristics, the CD4 count was higher in females (375 vs 290 cells/μL). Fewer females initiated ritonavir-boosted regimens. The median duration on therapy before interruption or change was longer in males (10 versus 4 months) (odds ratio [OR] 1.40 95% confidence interval: 0.95–2.04; P = 0.09). HIV RNA suppression was frequent (74%) and mean CD4 count achieved robust (over 400 cells/μL) at 6 months, irrespective of sex. The primary reasons for therapy interruption in females and males included: gastrointestinal intolerance (25% vs 19%; P = 0.42); poor adherence (22% vs 15%; P = 0.31); neuropsychiatric symptoms (19% vs 5%; P = 0.003); and lost to follow-up (3% vs 13%; P = 0.08). Seven males (5%) and no females discontinued therapy for liver-specific complications. Death rate was higher in females (23% vs 7%; P = 0.003). CONCLUSION: There are subtle differences in the characteristics of female and male HIV–HCV coinfected patients that influence HIV treatment decisions. The reasons for treatment interruption and change differ by biological sex. This knowledge should be considered when starting HIV therapy and in efforts to improve treatment outcomes.

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)0.004
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 score0.018
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
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 integrity0.0000.001
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 head0.032
GPT teacher head0.273
Teacher spread0.241 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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