Short interpregnancy intervals and adverse perinatal outcomes in high‐resource settings: An updated systematic review
Bibliographic record
Abstract
Abstract Background This systematic review summarises association between short interpregnancy intervals and adverse perinatal health outcomes in high‐resource settings to inform recommendations for healthy birth spacing for the United States. Methods Five databases and a previous systematic review were searched for relevant articles published between 1966 and 1 May 2017. We included studies meeting the following criteria: (a) reporting of perinatal health outcomes after a short interpregnancy interval since last livebirth; (b) conducted within a high‐resource setting; and (c) estimates were adjusted for maternal age and at least one socio‐economic factor. Results Nine good‐quality and 18 fair‐quality studies were identified. Interpregnancy intervals <6 months were associated with a clinically and statistically significant increased risk of adverse outcomes in studies of preterm birth (eg, aOR ≥ 1.20 in 10 of 14 studies); spontaneous preterm birth (eg, aOR ≥ 1.20 in one of two studies); small‐for‐gestational age (eg, aOR ≥ 1.20 in 5 of 11 studies); and infant mortality (eg, aOR ≥ 1.20 in four of four studies), while four studies of perinatal death showed no association. Interpregnancy intervals of 6‐11 and 12‐17 months generally had smaller point estimates and confidence intervals that included the null. Most studies were population‐based and few included adjustment for detailed measures of key confounders. Conclusions In high‐resource settings, there is some evidence showing interpregnancy intervals <6 months since last livebirth are associated with increased risks for preterm birth, small‐for‐gestational age and infant death; however, results were inconsistent. Additional research controlling for confounding would further inform recommendations for healthy birth spacing for the United States.
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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 | 0.009 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".