Patient characteristics, menopause symptoms, and care provided at an interdisciplinary menopause clinic: retrospective chart review
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to describe the characteristics, menopause symptoms, and treatment progressions in women cared for at an interdisciplinary menopause clinic. METHODS: We conducted a retrospective review of patient charts from women attending a multidisciplinary menopause clinic. Data collected from the charts included patient demographics, menopause symptoms, other concurrent medical conditions, and treatment recommendations. Data were entered into Research Electronic Data Capture database and analyzed descriptively. Generic symptom severity questionnaires were used to compare severity scores from initial to follow-up visits. RESULTS: Among the 198 women (mean age 52.1 y [±SD 6.3], 63.6% postmenopausal), the most common moderate/severe menopause symptoms were as follows: difficulty staying asleep or waking frequently (76.3%), tiredness (73.7%), and lack of interest in sex (60.1%). Women tended to have complex chronic medical conditions, with 54.5% suffering from four or more concurrent medical conditions. The majority of women (70.2%) were recommended various forms of hormone therapy. Women with a follow-up visit at 3 to 4 months reported a reduction in symptom severity. CONCLUSIONS: Our study addresses a gap in published information on patient characteristics and treatment in menopause-specific interdisciplinary clinics. The chart review highlights the variety of symptom experience and complexity of care faced in a menopause clinic. Rigorous prospective studies including standardized data collection and follow-up are needed to help guide clinicians in managing complex menopause patients.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".