Intracervical procedures and the risk of subsequent very preterm birth: a case–control study
Bibliographic record
Abstract
OBJECTIVE: To investigate the relation of prior intracervical procedures with very preterm birth. DESIGN: A population-based case-control study. SETTING: The study was conducted in Australia between 2002 and 2004. SAMPLE: Three hundred and forty-five women having a medically indicated and 236 having a spontaneous singleton birth between 20 and 31 weeks of gestation and 796 women selected randomly from all those giving birth at ≥37 weeks of gestation. METHODS: Interview data were analysed using logistic regression. MAIN OUTCOME MEASURE: Very preterm birth. RESULTS: Very preterm birth was significantly associated with having any intracervical procedure [adjusted odds ratio (AOR) 2.07; 95% confidence interval (CI) 1.6-2.7], in particular curettage associated with abortion (AOR 1.80; 95% CI 1.2-2.6). Assisted reproductive technology procedures were significantly associated with medically indicated very preterm birth (AOR 3.07; 95% CI 1.8-5.3) and treatments for precancerous cervical changes were significantly associated with spontaneous very preterm birth, as follows: conization/cone biopsy (AOR 3.33; 95% CI 1.8-6.2) and cauterization/ablation (AOR 2.27; 95% CI 1.4-3.8). Suction aspiration for abortion, abnormal Pap smear without treatment and abortion without instrumentation were not associated with very preterm birth. CONCLUSIONS: Intracervical procedures are associated with very preterm birth. Notably, curettage rather than any other procedure associated with abortion appears to be implicated in the risk. The introduction of infection during cervical procedures may be the common link with risks found. Changing clinical practice in the management of abortion and human papillomavirus vaccination may lead to lowering the risks of very preterm birth.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".