Management of Abnormal Uterine Bleeding in the Emergency Department Setting: Trends Over the Last 10 Years [10H]
Bibliographic record
Abstract
INTRODUCTION: Abnormal uterine bleeding is an issue facing many premenopausal women. Despite the risks of parenteral estrogen it continues to be first line treatment in clinical guidelines (AJOG 2016, American College of Obstetricians and Gynecologists 2013). We hypothesize that prescribing practices will demonstrate a decreased reliance on parenteral estrogen. METHODS: A retrospective chart review is underway to analyze emergency department charts for premenopausal women presenting to academic centers located in the Toronto area, between 2006 and 2016. 144 charts have been sampled from a proposed sample size of 6,412. Exclusion criteria included: postmenopausal bleeding, pregnancy related, malignancy or iatrogenic. RESULTS: The average patient in our pool was 37 years old (range 16-56). Hemoglobin at presentation ranged between 34 to 145 with 9.72% of patients requiring transfusion. The average length of stay was 5.18 hours. 50.69% of women did not receive tranexamic acid and NSAIDs were used only 6.25% of the time. OCP use occurred in only 4.86% of cases compared to 1.39% of women being treated with progestins. Parenteral estrogen was used in 2.08% of cases. Selective progesterone receptor modulators and GnRH agonists were never prescribed or utilized. Endometrial biopsy was performed in less than 1% of patients. CONCLUSION: Our data demonstrates that clinical practice guidelines are out of date. Parenteral estrogen is not being used as first line treatment. Despite average lengths of stay greater than 5 hours, endometrial biopsies are still not being performed for undiagnosed abnormal uterine bleeding. Revised guidelines and better utilization of newer medical therapies by physicians in the emergency setting are needed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".