Modelling sequence of prior pregnancies on subsequent risk of very preterm birth
Bibliographic record
Abstract
The prevalence and intractability of preterm birth is known as is its association with reproductive history, but the relationship with sequence of pregnancies is not well studied. The data were from a population-based case-control study, conducted in Victoria, Australia. The study recruited women giving birth between April 2002 and April 2004 from 73 maternity hospitals. Detailed reproductive histories were collected by interview a few weeks after the birth. The cases were 603 women having a singleton birth between 20 and <32 weeks gestation (very preterm births including terminations of pregnancy). The controls were 796 randomly selected women from the population having a singleton birth of at least 37 completed weeks gestation. Unconditional logistic regression was used to assess the association of very preterm birth with sequence of pregnancies defined by their outcome (prior abortion - spontaneous or induced, and prior preterm or term birth) with adjustment for sociodemographic factors. The outcomes of each prior pregnancy, stratified by pregnancy order, and starting with the pregnancy immediately before the index or control pregnancy, were categorised as one of abortion, preterm birth or term birth. We showed that each of these prior pregnancy events was an independent risk of very preterm birth. This finding does not support the hypothesis of a neutralising effect of a term birth after an abortion on the subsequent risk for very preterm birth and is further evidence for the cumulative or increasing risk associated with increasing numbers of prior abortions or preterm births.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".