Establishing a Human Chorionic Gonadotropin Cutoff to Guide Methotrexate Treatment of Ectopic Pregnancy: A Systematic Review
Bibliographic record
Abstract
Methotrexate is an established alternative to surgery for treating ectopic pregnancy. While lower levels of human chorionic gonadotropin (hCG) correlate with a decreased risk of treatment failure, there is as yet no agreement on an absolute hCG level that would be a relative contraindication to methotrexate therapy. The authors undertook a systematic MEDLINE search and encountered 5 observational studies, totaling 503 women, that purportedly documented increasing failure rates in conjunction with increasing hCG levels. All of these studies followed a single-dose methotrexate protocol. Failure rates increased with higher hCG levels, and a substantial, statistically significant increase in failures was evident when comparing patients whose initial hCG levels exceeded 5000 mIU/mL with those having lower baseline levels. The odds ratio (OR) was 5.45, with a 95% confidence interval (CI) of 3.04–9.78. Women whose initial serum hCG level ranged from 5000 to 4002 mIU/mL had a significantly higher failure rate than those whose initial serum concentrations were 2000–4999 mIU/mL (OR, 3.76; 95% CI, 1.16–12.33). Another way to express this is that, for every 10 treatments there will be 1 more failure if the serum hCG is 5000–4002 mIU/mL than if it is 2000–4999 mIU/mL. The difference in rates approximates 10%. There is little difference in failure rates between groups with cutoff values greater than 5000 mIU/mL because overall failure rates are increased for both groups. These findings dictate a cautious approach when planning single-dose methotrexate treatment for ectopic pregnancy when the initial serum hCG level exceeds 5000 mIU/mL. It is not clear whether the use of a 2-dose or multidose protocol would yield different results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".