Induced termination of pregnancy and low birthweight and preterm birth: a systematic review and meta‐analyses
Bibliographic record
Abstract
BACKGROUND: History of induced termination of pregnancy (I-TOP) is suggested as a precursor for infant being born low birthweight (LBW), preterm (PT) or small for gestational age (SGA). Infection, mechanical trauma to the cervix leading to cervical incompetence and scarred tissue following curettage are suspected mechanisms. OBJECTIVE: To systematically review the risk of an infant being born LBW/PT/SGA among women with history of I-TOP. SEARCH STRATEGY: Medline, Embase, CINAHL and bibliographies of identified articles were searched for English language studies. SELECTION CRITERIA: Studies reporting birth outcomes to mothers with or without history of induced abortion were included. DATA COLLECTION: and analyses Two reviewers independently collected data and assessed the quality of the studies for biases in sample selection, exposure assessment, confounder adjustment, analytical, outcome assessments and attrition. Meta-analyses were performed using random effect model and odds ratio (OR), weighted mean difference and 95% confidence interval (CI) were calculated. MAIN RESULTS: Thirty-seven studies of low-moderate risk of bias were included. A history of one I-TOP was associated with increased unadjusted odds of LBW (OR 1.35, 95% CI 1.20-1.52) and PT (OR 1.36, 95% CI 1.24-1.50), but not SGA (OR 0.87, 95% CI 0.69-1.09). A history of more than one I-TOP was associated with LBW (OR 1.72, 95% CI 1.45-2.04) and PT (OR 1.93, 95% CI 1.28-2.71). Meta-analyses of adjusted risk estimates confirmed these findings. CONCLUSIONS: A previous I-TOP is associated with a significantly increased risk of LBW and PT but not SGA. The risk increased as the number of I-TOP increased.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".