Comment on: The association between pre‐eclampsia and neonatal complications in relation to gestational age
Bibliographic record
Abstract
We read Ulfsdottir et al.'s1 article on pre-eclampsia and risk of adverse neonatal outcomes at different gestational ages with great interest. The authors analysed a cohort of 805 591 singletons, including 34 145 (4.2%) newborns exposed to pre-eclampsia and 46 586 (5.8%) that were born pre-term. The authors stratified their population to examine pre-term newborns separately from term newborns. While they found that pre-eclampsia was strongly associated with neonatal morbidity at term, pre-eclampsia was not as great a risk factor for morbidity pre-term. The findings suggest that pre-eclampsia is less worrisome when neonates are delivered before term. Among births at 22–31 weeks, pre-eclampsia was associated with only a 23% greater risk of resuscitation compared with no pre-eclampsia, while at term, the risk of resuscitation was 94% greater. Other results suggest that birth before term could even be protective. Among births at 22–31 weeks, pre-eclampsia was associated with a 53% lower risk of having an Apgar score below 7 compared with no pre-eclampsia, whereas among term births, pre-eclampsia was associated with a 66% greater risk of this outcome. Based on these findings, it may be tempting to recommend delivering infants early when pre-eclampsia presents before 37 weeks. However, there is a possibility of bias as the data were stratified by gestational age. Neonates exposed to pre-eclampsia who were born at 22–31 weeks were compared with unexposed neonates who were also born extremely premature. The comparison group is not representative of normal foetuses because other severe complications requiring delivery were likely present. These complications could potentially be more dangerous to the foetus than pre-eclampsia. As a result, pre-eclampsia may appear less harmful or even paradoxically protective against neonatal morbidity in pre-term newborns. Paradoxical findings before term may be a sign of collider stratification bias, a widely recognised problem in perinatal epidemiology.2 When gestational age is an intermediate variable, restricting the study population to pre-term births can distort the association between prenatal exposures and neonatal outcomes.2 The protective effect of pre-eclampsia on cerebral palsy among pre-term children is a well-established example of collider bias.2 The birthweight paradox is another example, where maternal smoking is seemingly protective against mortality among low birthweight infants.2 Methods are available to prevent collider bias, including avoiding stratification and adjustment or using a foetuses-at-risk approach.3 The foetuses-at-risk approach relies on using ongoing pregnancies in the analysis, rather than only pregnancies that are delivered early.3 Ulfsdottir et al.'s1 study is important and reinforces the harmful impact of pre-eclampsia on neonatal morbidity at term. However, the results for pre-term newborns should be interpreted with caution as stratification can inadvertently attenuate or lead to protective associations between pre-eclampsia and morbidity. Future studies of prenatal exposures should be mindful of collider bias when gestational age is an intermediate and data are stratified by pre-term birth. Nathalie Auger: Conceptualization; writing – review and editing. Méloë Maigné: Conceptualization; writing – original draft. Émilie Brousseau: Conceptualization; writing – original draft. The authors declare no conflicts of interest.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".