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Record W4290600442 · doi:10.3390/jpm12081294

Prevalence of Physical Health, Mental Health, and Disability Comorbidities among Women Living with HIV in Canada

2022· article· en· W4290600442 on OpenAlexafffundabout
Emily Heer, Angela Kaida, Nadia O’Brien, Bluma Kleiner, Alie Pierre, Danielle Rouleau, Ann N. Burchell, Lashanda Skerritt, Karène Proulx‐Boucher, Valerie Nicholson, Mona Loutfy, Alexandra de Pokomandy

Bibliographic record

VenueJournal of Personalized Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsWomen's College HospitalUniversity of TorontoSt. Michael's HospitalMcGill University Health CentreSimon Fraser UniversityCentre Hospitalier de l’Université de MontréalMcGill University
FundersCanadian Institutes of Health Research
KeywordsMedicineComorbidityMental healthCohortAnxietyDepression (economics)Body mass indexPsychiatryObesityHealth careGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Life expectancy for people living with HIV has increased, but management of HIV is now more complex due to comorbidities. This study aimed to measure the prevalence of comorbidities among women living with HIV in Canada. We conducted a cross-sectional analysis using data from the 18-months survey (2014−2016) of the Canadian HIV Women’s Sexual and Reproductive Health Cohort Study (CHIWOS). Self-report of diagnosed conditions was used to measure lifetime prevalence of chronic physical conditions, current mental health conditions, and disabilities. We examined frequency of overlapping conditions and prevalence stratified by gender identity, ethnicity, and age. Among 1039 participants, 70.1% reported a physical health diagnosis, 57.4% reported a current mental health diagnosis, 19.9% reported a disability, and 47.1% reported both physical and mental health comorbidities. The most prevalent comorbidities were depression (32.3%), anxiety (29.5%), obesity (26.7%, defined as body mass index >30 kg/m2), asthma/chronic obstructive pulmonary disease (23.3%), sleep disorder (22.0%), drug addiction (21.9%), and arthritis/osteoarthritis (20.9%). These results highlight the complexity of HIV care and the important prevalence of comorbidities. Personalized health care that integrates care and prevention of all comorbidities with HIV, with attention to social determinants of health, is necessary to optimize health and well-being of women living with 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 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 score0.132
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.299
Teacher spread0.283 · 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

Citations15
Published2022
Admission routes3
Has abstractyes

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