Accelerated menopausal changes as human disease model ‘FOCUM’ for the development of osteoarthritis and other degenerative disorders: protocol for a prospective cohort study
Bibliographic record
Abstract
INTRODUCTION: The incidence of degenerative disorders, including osteoarthritis (OA), increases rapidly in women after menopause. However, the influence of the menopause is still insufficiently investigated due to the slowness of menopausal transition. In this study, a novel human model is used in which it is expected that menopausal-related changes will occur faster. This is the Females discontinuing Oral Contraceptives Use at Menopausal age model. The ultimate aim is to link these changes to OA and other degenerative disorders, including cardiovascular diseases, diabetes, osteoporosis and tendinopathies. METHODS AND ANALYSIS: This is a pilot observational prospective cohort study with 2 years of follow-up. Fifty women aged 50-60 who use oral contraceptive (OC) and have the intention to stop are included. Measurements are performed once before stopping OC, and four times thereafter at 6 weeks, 6 months, 1 year and 2 years. At every time point, a questionnaire is filled in and a sample of blood is drawn. At the first and final time points, a physical examination, hand radiographs and a MRI scan of one knee are performed. The primary OA outcome is progression of the MRI Osteoarthritis Knee Score. Secondary OA outcomes are the development of clinical knee and hand OA, development of knee OA according to the MRI definition, and progression of radiographic features for hand OA. Principal component analysis will be used to assess which changes occur after stopping OC. Univariate and multivariate generalised estimating equation models will be used to test for associations between these components and OA. ETHICS AND DISSEMINATION: The study has been approved by the Medical Ethics Committee of the Erasmus MC University Medical Center Rotterdam (MEC-2019-0592). All participants must give informed consent before data collection. Results will be disseminated in national and international journals. TRIAL REGISTRATION NUMBER: NL70796.078.19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".