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Record W4416796103 · doi:10.1016/j.jogc.2025.103188

The Financial Toxicity of Endometriosis: Unseen Costs and Policy Gaps

2025· article· en· W4416796103 on OpenAlexaffvenueabout
Marfy Abousifein, Nicholas Leyland

Bibliographic record

VenueJournal of Obstetrics and Gynaecology Canada · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsThe Society of Obstetricians and Gynaecologists of CanadaMcMaster University
Fundersnot available
KeywordsFertilityHealth careFace (sociological concept)MEDLINEHealth policy

Abstract

fetched live from OpenAlex

Endometriosis affects 1 in 10 Canadians; however, its financial toxicity remains poorly understood. While universal health care covers physician and hospital services, patients face substantial out-of-pocket costs for medications, complementary therapies, fertility treatments, travel, and childcare. These burdens delay care, limit treatment, and worsen disparities. International evidence underscores the magnitude of these costs, but Canada lacks patient-level data to guide interventions. This commentary highlights manifestations of financial strain and calls for quantitative assessment and policy reform, including pharmacare, universal fertility coverage, and complementary therapy access, to ensure timely, comprehensive care nationwide.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.265
Threshold uncertainty score0.533

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.067
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.008
Scholarly communication0.0070.006
Open science0.0030.003
Research integrity0.0110.015
Insufficient payload (model declined to judge)0.0110.001

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 head0.275
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes3
Has abstractyes

Explore more

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