Prior Spontaneous or Induced Abortion Is a Risk Factor for Cervical Dysfunction in Pregnant Women: a Systematic Review and Meta-analysis
Bibliographic record
Abstract
A history of abortion is associated with cervical dysfunction during pregnancy, but there remains uncertainty about whether risk can be stratified by the abortion type, the abortion procedure, or number of previous abortions. The objective of this study was to verify the relationship between cervical dysfunction measures in pregnancies with and without a history of termination. Embase and Medline databases were searched from 01 January 1960 to 01 March 2022 resulting in a full-text review of 28 studies. The Newcastle-Ottawa Scale (NOS) was used to assess the quality and risk of bias for non-randomized studies. The meta-analysis consisted of 6 studies that met all inclusion and exclusion criteria and included a combined total of 2,513,044 pregnancies. Cervical dysfunction was defined as either cervical insufficiency/incompetence in 4 of the studies and as short cervix in the others. Results from a random-effects model using reported adjusted odds ratios (aOR) estimated an increase in the odds of 2.71 (95% CI 1.76, 4.16) for cervical dysfunction in the current pregnancy related to a history of induced or spontaneous abortion. Subgroup analyses with only induced abortions (surgical/medical) estimated an aOR of 2.54 (95% CI 1.41, 4.57), while studies limited to surgical abortions had an aOR of 4.08 (95% CI 2.84, 5.86). The risk of cervical dysfunction in the current pregnancy was also found to be dependent on the number of previous abortions. In this meta-analysis, a prior history of abortion, and specifically induced abortions, was associated with cervical dysfunction. The protocol was registered in PROSPERO (CRD42020209723).
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".