Do the Causes of Infertility Play a Direct Role in the Aetiology of Preterm Birth?
Bibliographic record
Abstract
BACKGROUND: It is well established that singletons born of assisted reproductive technology are at higher risk of preterm birth and other adverse outcomes. What remains unclear is whether the increased risk is attributable to the effects of the treatment alone or whether the underlying causes of infertility also play a role. The aim of this study was to examine whether any of the six categories of causes of infertility were associated with a direct effect on preterm birth using causal mediation analysis. METHODS: We assembled a hospital-based cohort of births delivered at a large tertiary care hospital in Montreal, Canada between 2001 and 2007. Causes of infertility were ascertained through a clinical database and medical chart abstraction. We employed marginal structural models (MSM) to estimate the controlled direct effect of each cause of infertility on preterm birth compared with couples without the cause under examination. RESULTS: The final study cohort comprised 18,598 singleton and twin pregnancies, including 1689 in couples with ascertained infertility. MSM results suggested no significant direct effect for any of the six categories of causes. However, power was limited in smaller subgroup analyses, and a possible direct effect for uterine abnormalities (e.g. fibroids and malformations) could not be ruled out. CONCLUSION: In this cohort, most of the increased risk of preterm birth appeared to be explained by maternal characteristics (such as age, body mass index, and education) and by assisted reproduction. If these findings are corroborated, physicians should consider these risks when counselling patients.
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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 | 0.003 | 0.008 |
| 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 | 0.000 |
| 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".