Interpregnancy interval and gestation at the next birth—is there a racial difference?
Bibliographic record
Abstract
The association of short interpregnancy intervals (IPIs) with an increased rate of preterm birth in the next pregnancy has been known for 70 years or more (Eastman Am J Obstet Gynecol 1944;47:445–63). Rawlings et al. in 1995 reported that an IPI of <9 months in black women was significantly associated with a higher preterm birth rate, whereas the effect was only seen in white women when the IPI was <3 months (Rawlings N Engl J Med 1995;332:69–74). In the same journal in 1999, Zhu et al. reported that in a predominantly (90.1%) white/Hispanic population, most of the increased risk associated with a short IPI was in the first 6 months, with only a small fall thereafter, reaching a nadir at 18–23 months, following which it rose again (Zhu et al. N Engl J Med 1999;340:589–94). DeFranco et al. have defined a short IPI as <12 months, because the few pregnancies with an IPI of <6 months ‘did not allow for meaningful analysis of this subgroup’. This means that the majority of the women in their study—white—were at relatively low risk. However, more than a quarter of the women were black, and there are now considerable published data suggesting that black women have physiologically shorter pregnancies with their babies being more mature at birth (e.g. Balchin et al. Obstet Gynecol 2011;117:828–35), so making it more complicated to draw conclusions from data on gestational length in white and black women combined. More of the women with an IPI of <12 months in DeFranco's study were black (25.6%) than in the group with an IPI of ≥18 months (15.9%). Figure 2 in DeFranco's study shows in women with shorter IPIs a higher rate of births at each gestational age <37 weeks but a lower rate of births from 39 weeks onwards. However, the modal gestation is the same for each group, 40 weeks. This is surprising, if as the authors suggest there is ‘a shift of the distribution curve of cumulative births by week of gestation to the left’. A shift of the mode to the left in black women, consistent with more preterm and fewer post-term births, was indeed seen in the Balchin et al. study, and this is what one would expect if there was a physiological total population shift, rather than a pathological increase in preterm births. It may be that in DeFranco's study, the mode is dominated by white women at relatively low risk, while the increase in preterm births (and reduction in post-term births) is most pronounced in black women. Such nuances cannot be determined by multivariate logistic regression as by definition, such modelling incorporates adjustments for the included variables, which in this case, included racial group. See http://www.bjog.org/view/0/editorProfiles.html#psteer.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".