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Record W4415449855 · doi:10.1210/jendso/bvaf149.1909

MON-177 Pathways To Care For Those With Polycystic Ovary Syndrome: Development Of An Algorithm For Patients And Primary Care To Improve Health Care Management

2025· article· en· W4415449855 on OpenAlexaffabout
Donna F. Vine, Mahua Ghosh, Sarah Chambers, P. Beckles, L. Sadiq, Maria Kupreeva, Laurie Mereu, A. Achi, Tarek Motan, C. LeJour, Beate C. Sydora, Julie Robison

Bibliographic record

VenueJournal of the Endocrine Society · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsAlberta Health ServicesUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsPolycystic ovaryCare pathwaySpecialtyHealth carePrimary careClinical pathwayCharter

Abstract

fetched live from OpenAlex

Abstract Disclosure: D.F. Vine: None. M. Ghosh: None. S. Chambers: None. P. Beckles: None. L. Sadiq: None. M. Kupreeva: None. L. Mereu: None. A. Achi: None. T. Motan: None. C. Lejour: None. B. Sydora: None. J. Robison: None. OBJECTIVE: Polycystic Ovary Syndrome (PCOS) is the most common metabolic-endocrine disorder impacting 15% of females across the lifespan. Despite its high prevalence, those with PCOS in Alberta, Canada have expressed concerns about their health care including prolonged time for diagnosis, insufficient patient information, and lack of management support. Health care providers in Alberta have expressed the need for direction to integrate care of those with PCOS and appropriately address their complex health needs. Our project was to develop an evidence-based primary care clinical pathway to guide providers with diagnosis and management of PCOS, and a patient pathway to educate and guide patients on their health care journey with PCOS. METHODS: In collaboration with the Alberta Health Services Provincial Pathways Unit (AHS PPU) we followed the five phases in the Pathway Development Toolkit; i) Co-define, ii) Co-Design, iii) Validate, iv) Implement, and v) Sustain. A co-design team was established with patient-partners and health care providers including family physicians, researchers, dietitians, endocrinologists and obstetrician-gynecologists. The algorithm pathway was developed using recommendations from the evidence-based literature, the International Guidelines for Assessment and Management of PCOS (2023) and provincial resources. A project charter was co-defined to develop a pathway that did not need additional resources, was usable to primary care providers, supported by specialty care providers, supported patient self-management and shared decision making, and addressed the challenges related to managing PCOS and co-morbidities identified by patients and health care providers. RESULTS: Two pathway-of-care documents were generated: one for patients and one for primary care physicians. The pathway algorithms with expanded detail for patients and primary care physicians were developed based on serial consultation with the co-design team. The algorithms were refined by stepwise iteration and review to meet the project charter outcomes. CONCLUSIONS: The pathway development reflects a patient-centered collaborative multidisciplinary team approach to support primary care providers and those affected by PCOS to improve their health care journey. While the pathway algorithms were developed for provincial use in Alberta, we envision a wider use in Canada, and that it can adapted for use in other countries to establish models of care for improving primary care in those affected by PCOS. Presentation: Monday, July 14, 2025

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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 designOther design
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

Citations0
Published2025
Admission routes2
Has abstractyes

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