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Record W4200198804 · doi:10.1177/09564624211051615

Healthcare utilization among persons living with HIV in Manitoba, Canada, prior to HIV diagnosis: A case-control analysis

2021· article· en· W4200198804 on OpenAlexaffabout
Souradet Y. Shaw, Laurie Ireland, Leigh M. McClarty, Carla Loeppky, Jared Bullard, Paul Van Caeseele, Yoav Keynan, Ken Kasper, Stephen Moses, James Blanchard, Marissa Becker

Bibliographic record

VenueInternational Journal of STD & AIDS · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsManitoba HealthNine Circles Community Health CentreUniversity of ManitobaWinnipeg Regional Health Authority
FundersGilead Foundation
KeywordsMedicineHealth careOdds ratioPublic healthPopulationConfidence intervalCohortLogistic regressionFamily medicineMen who have sex with menPediatricsDemographyHuman immunodeficiency virus (HIV)SyphilisEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Understanding care patterns of persons living with HIV prior to diagnosis can inform prevention opportunities, earlier diagnosis, and engagement strategies. We examined healthcare utilization among HIV-positive individuals and compared them to HIV-negative controls. METHODS: Data were from a retrospective cohort from Manitoba, Canada. Participants included individuals living with HIV presenting to care between 2007 and 2011, and HIV-negative controls, matched (1:5) by age, sex, and region. Data from population-based administrative databases included physician visits, hospitalizations, drug dispensation, and chlamydia and gonorrhea testing. Diagnoses associated with physician visits were classified according to International Classification of Diseases chapters. Conditional logistic regression models were used to compare cases/controls, with adjusted odds ratios (AORs) and their 95% confidence intervals (95% CI) reported. RESULTS: A total of 193 cases and 965 controls were included. Physician visits and hospitalizations were higher for cases, compared to controls. In the 2 years prior to case date, cases were more likely to be diagnosed with "blood disorders" (AOR: 4.2, 95% CI: 2.0-9.0), be treated for mood disorders (AOR: 2.4, 95% CI: 1.6-3.4), and to have 1+ visits to a hospital (AOR: 2.2, 95% CI: 1.4-3.6). CONCLUSION: Opportunities exist for prevention, screening, and earlier diagnosis. There is a need for better integration of healthcare services with public health.

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)0.001
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 score0.730
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.322
Teacher spread0.296 · 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
Published2021
Admission routes2
Has abstractyes

Explore more

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