Endometrial Cryoablation for the Treatment of Heavy Menstrual Bleeding: 36-Month Outcomes from the CLARITY Study
Bibliographic record
Abstract
Study Objective: Cryotherapy Device (Channel Medsystems, Berkeley, CA) in premenopausal women with heavy menstrual bleeding due to benign causes who have completed childbearing. Methods: The prospective, multicenter, single-arm, open-label study had eight sites in the USA, one in Mexico, and two in Canada. Inclusion criteria included uterine sound ≤10 cm, endometrial cavity length 2.5 to 6.5 cm, age 25 to 50 years, a pictorial blood loss assessment chart score of ≥150, no submucosal myomata and/or uterine obstruction, distortion, or abnormality. A total of 242 subjects underwent a 2.5-minute cryoablation. Long-term follow-up visits were conducted at Month 24 and Month 36. Data collected included gynecological adverse events, description of last menstrual period, contraception status, self-report of pregnancy, medical or surgical interventions to treat abnormal uterine bleeding, satisfaction, recommendation, and quality of life (QoL). QoL outcomes were measured with the Menorrhagia Impact Questionnaire (MIQ) and the Premenstrual Symptoms Impact Survey (PMSIS™). Results: 201 subjects completed their Month 36 final study visit. Subject outcomes were comparable to those at Month 12. Eighty-nine percent of subjects reported amenorrhea, a lighter-than-normal, or normal period, 91% of subjects had no or slight limitations in MIQ measured activities, and 85% reported premenstrual symptoms at a low frequency. Eighty-five percent of the subjects were satisfied or very satisfied. The cumulative incidence of hysterectomy was 5% and reintervention was 8.7%. Forty-nine gynecologic adverse events (AE) were reported; one non-serious AE, postcoital bleeding, was reported as related to the procedure. No serious device-related or procedure-related AEs were reported. Conclusion: Study data demonstrate that the positive effects of Cerene Cryotherapy Device treatment are sustained through Month 36 and that the risks associated with the device and procedure are low (ClinicalTrials.gov; NCT02842736).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".