Low levels of maternal serum PAPP‐A in early pregnancy and the risk of adverse outcomes
Bibliographic record
Abstract
OBJECTIVES: To determine if low maternal serum level of pregnancy associated plasma protein A (PAPP-A) measured in early pregnancy can predict adverse pregnancy outcomes and to examine the gestational age (GA) sampling interval for these outcomes. METHODS: This was a nested case-control study from a prospective cohort of women recruited at <20 weeks of gestation in Halifax, NS. Cases (n=248) were defined as women who had a fetal loss or developed preeclampsia, severe pregnancy-induced hypertension (PIH), or small for gestational age infant (SGA). Controls (n=244) were frequency matched to cases by GA at the time of serum sampling (6 to <20 weeks GA). Participant information was obtained from questionnaires and medical chart reviews. RESULTS: Women with a low PAPP-A measure [ 0.4 MoM). However, performance as a screening test was poor [sensitivity=38.7%; specificity=81.6%; positive likelihood ratio (LR)=2.1; negative LR=0.75]. In the adjusted model, the 10- to 14-week GA period was the only time period where low PAPP-A was significantly associated with adverse outcomes. CONCLUSIONS: Women with a low PAPP-A early in their pregnancy have twice the risk of an adverse outcome, though PAPP-A as a one-time single marker test has limited value.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".