The effects and mechanisms of primiparity on the risk of pre‐eclampsia: a systematic review
Bibliographic record
Abstract
Pre-eclampsia has been dubbed as 'a disease of primiparity'. However, the effects and mechanisms of the association of primiparity with pre-eclampsia have not been clearly defined. We conducted a systematic review of studies evaluating the effect of primiparity on the risk of pre-eclampsia, and studies (published between January 1966 and July 2005) on the mechanisms underlying such an association. A total of 26 original studies were identified and a meta-analysis carried out for the risk of pre-eclampsia among primiparous vs. multiparous women. Variably (1.4-5.5 times) higher risks of pre-eclampsia were observed in primiparous women in all studies, with a summary odds ratio (OR) of 2.42 [95% CI 2.16, 2.71]. The adjusted ORs were larger than crude ORs in all but one study after various adjustments. Except for abundant epidemiological evidence in support of the immune maladaptation theory, only four original studies examined the actual mechanisms of such primiparity-associated risk. Two (small) studies suggested differences in immunological responses in the aetiology of pre-eclampsia in primiparous vs. multiparous women. Two recent studies indicated that differences in angiogenic factor profile or reactivity to insulin resistance in early pregnancy may explain the elevated pre-eclampsia risk in first pregnancies. In conclusion, primiparity is associated with approximately 2.4-fold elevated risk of pre-eclampsia. Although immune maladaptation is generally considered as the basis to explain such an elevated risk, few data are available on immune maladaptation parameters in primiparous vs. multiparous pregnancies. Available data are insufficient to interpret the mechanisms of such primiparity-associated excess risk of pre-eclampsia.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".