Test or No-Test: Comparison of Medication Abortion Outcomes and Adverse Events When Forgoing Ultrasound, Laboratory Testing, and Physical Examination
Bibliographic record
Abstract
OBJECTIVES: This study aimed to compare demographics and clinical outcomes between patients who did not undergo investigations and those who underwent investigations before receiving a prescription for medication abortion (MA) during the first 6 months of the COVID-19 pandemic. Outcomes include success rates, adverse events, pathways to completion, and loss to follow-up rates. METHODS: We conducted a retrospective medical record review of 1452 patients presenting for MA between 23 March 2020 and 30 September 2020. Descriptive statistics, 2 × 2 chi-square tests, and Fisher exact tests were used to compare characteristics and outcomes between groups. RESULTS: Of the 1307 patients who received a prescription, 895 (68.5%) were in the no-test group and 412 (31.5%) were in the test group. The success rate was 95.2%, with no significant difference between groups (94.0% and 95.8%, P = 0.194). Rates of adverse events were low, with 28 patients presenting for emergency department visits (2.1%), 62 having clinically significant retained products of conception (4.7%), 5 with heavy bleeding requiring treatment (0.4%), 16 with ongoing pregnancy (1.2%), and 3 requiring ectopic pregnancy management (0.2%). Completion of abortion was verified in 1034 patients (80.5%), and the loss to follow-up rate was 22.6%, with no difference between the groups (82.1% vs. 79.8%, P = 0.341; and 21.4% vs. 23.1%, P = 0.477; respectively). CONCLUSIONS: We found that clinical outcomes were consistent across the 2 groups, with high success rates and low adverse event rates. Our study contributes to the growing body of evidence that allows for individualized care implementing selective use of low- and no-test MA protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".