Manual Vacuum Aspiration and Dilatation & Curettage in First Trimester Miscarriages; Comparison of Efficacy
Bibliographic record
Abstract
Objective: To compare the efficacy of manual vacuum aspiration with dilatation and curettage in first trimester miscarriages. Study Design: Randomized control trial. Place and Duration of Study: Department of Obstetrics and Gynecology Unit “A”, Lady Reading Hospital, Peshawar. Patients were received through OPD and Emergency during the six months i.e from 1st Jan, 2015 till 30th June, 2015. Methodology: Women admitted in the department of Obstetrics and Gynecology Unit “A”, Lady Reading Hospital, Peshawar, who meet the inclusion and exclusion criteria, were included in the study by consecutive non probability sampling with random allocation by dividing them into two groups through lottery method. Patients in group A were treated by dilatation and curettage while the patients in group B were evacuated by manual vacuum aspiration. After the randomly allocated method of evacuation, the efficacy of the procedure was determined in terms of need for the evacuation by presence of retained products of conception on ultrasound done by specialist. Results: No substantial difference was found between patients subjected to D&C and to those subjected to MVA. Conclusion: MVA is as effective as D&C for the treatment of miscarriage. Keywords: Miscarriage, Abortion, Dilatation & Curettage, Manual Vacuum Aspiration, Retained products of conception.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".