Ectopic Pregnancy: An Analysis of Prevalence and Clinical Magnitude
Bibliographic record
Abstract
Objective: To determine the prevalence and clinical manifestations and symptoms associated with ectopic pregnancy Methodology: This retrospective observational study was done at Pessi Hospital, I-12, Islamabad with collaboration of different Hospitals for the data collection. From October 2021 to September 2022. Patients of reproductive age presenting with symptoms suggestive of ectopic pregnancy and confirmed through diagnostic tests such as ultrasound, serum beta-hCG levels, or surgical findings were included. After taking demographic information including age, parity, gravidity, and reproductive history is collected for each patient, clinical data related to ectopic pregnancy diagnosis were recorded. Descriptive statistics are employed to summarize demographic characteristics, prevalence rates, and clinical pattern of ectopic pregnancy cases. Results: Overall prevalence of ectopic pregnancy was found 1.4%. Overall mean age of the women was 33.39+5.48 years. Family history was positive among 36.1% of the cases. In terms to the clinical presentation of patients with ectopic pregnancy, pain and bleeding were most common clinical features, 91.80% and 79.40% respectively, followed by shock 4.5% and 18.0% had others multiple clinical features and 5.8% were asymptomatic. Conclusion: In conclusion, ectopic pregnancy was observed at a rate of 1.4%, indicating its continued significance as a health concern. Pain and bleeding were observed to the most common clinical features.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".