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Record W2089274669 · doi:10.1258/ijsa.2011.010483

Factors associated with repeat visits among clients attending a clinic for sexually transmitted infections in Kisumu, Kenya

2011· article· en· W2089274669 on OpenAlexaff
Elizabeth L. Pultorak, Elijah Odoyo‐June, J Hayombe, Felix Opiyo, Wycliffe Odongo, J A Ogollah, Stephen Moses, Robin L. Bailey, Supriya D. Mehta

Bibliographic record

VenueInternational Journal of STD & AIDS · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Allergy and Infectious Diseases
KeywordsMedicineSexually transmitted diseaseFamily medicineOptometryHuman immunodeficiency virus (HIV)Syphilis

Abstract

fetched live from OpenAlex

To identify factors associated with repeat visits among patients attending a clinic for sexually transmitted infections (STIs) in Kisumu, Kenya, we examined records of clinic visits from March 2009 to May 2010. Multivariable logistic regression identified factors associated with repeat visits occurring >30 days after the initial visit. Among 1473 clients (1296 single-visit individuals versus 177 individuals with repeat visits), the median age was 24 years, 67% were men and 8.6% self-reported being HIV-positive. In adjusted analyses, men with repeat visits were more likely to report ≥ 2 recent sexual partners (adjusted odds ratio [aOR] = 1.60) and being HIV-positive (aOR = 2.35). They were less likely to have been referred from other health facilities (aOR = 0.14) and more likely to have urethral discharge at their initial visit (aOR = 2.46). Among women, repeat visits were associated with vaginal discharge (aOR = 2.22), but attending the clinic with a partner was protective (aOR = 0.38). The association between sexual risk, HIV positivity and repeat visits among male clients highlights the need to focus intervention efforts on this group. For women, attending with a partner may reflect a decreased risk of re-infection if both partners are treated and counselled together.

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)0.001
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 score0.010
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.075
GPT teacher head0.374
Teacher spread0.299 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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