A Novel Approach of Intralesional Vasopressin using an Ovum Pickup Needle in Hysteroscopic Myomectomy
Bibliographic record
Abstract
The aim was to evaluate the efficacy of vasopressin injected into the center of submucosal myomas using an ovum pick up needle during hysteroscopic myomectomy.Design: Canadian task force II-2 clinical study Setting: Urban clinical research center,38 patients were enrolled in the study Materials and Methods: A retrospective Canadian Task Force II-2 clinical study design conducted on women aged 22-55 years in an urban clinical research center.38 symptomatic patients underwent hysteroscopic myomectomy after injection of dilute vasopressin (10U in 100mL Normal Saline).Around 5-8 mL was injected into the center of myomas using an ovum pick up needle, and the study was carried out between 2018-2021.Measured parameters were surgical operative time, and the secondary outcomes were related to fluid volume, visual clarity, and pregnancy outcome in patients with infertility. Results:The Wamsteker Grading System adopted by the European Society for Gynecological Endoscopy was used to classify the myomas.The mean time of myomectomy was 22 minutes (normal range: 15-40 minutes), with a median fluid deficit of 700 mL (normal range: 500-900mL); one patient had more than 1000 mL fluid deficit which was detected immediately and managed efficiently.This patient had the longest surgical operative time of 40 minutes with 10 multiple myomas between 1 and 4 cm in size.The diagnosis of the size, number, and grade of submucosal myomas was made by transvaginal ultrasound.In our study it was observed that the use of vasopressin injection during hysteroscopic myomectomy resulted in significantly reduced surgical operative time, minimal fluid deficit, lesser bleeding with a clear surgical field, and improved pregnancy outcome in infertility patients.Conclusion: Injection of vasopressin during hysteroscopic myomectomy was found to be effective in decreasing surgical operative time, improvement of visual clarity, thereby improving pregnancy outcomes in patients presenting with infertility.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".