The predictive value of 18 and 22 week uterine artery Doppler in patients with low first trimester maternal serum PAPP‐A
Bibliographic record
Abstract
OBJECTIVE: To determine if the addition of uterine artery (UA) Doppler pulsatility index (PI) at 18 and 22 weeks of gestation improves the predictive accuracy of low first trimester pregnancy associated plasma protein A (PAPP-A) in the detection of adverse obstetrical outcomes. METHODS: This was a prospective interventional study. All women undergoing first trimester combined screening (FTS) at a single center, with a low maternal serum PAPP-A level (<0.4 MoM), were included. Patients underwent bilateral UA Doppler assessments at 18 and 22 weeks of gestation. A positive test was defined as a mean PI > 1.45. Primary outcomes were obtained from chart review, and logistic regression analysis was used to compare outcomes with positive and negative tests. Positive and negative predictive value, specificity and sensitivity were calculated. RESULTS: Between January and October 2007, 5359 women completed FTS. Among the low PAPP-A group (n = 289), 18 week UA Doppler was a significant predictor of low birth weight (OR = 2.28, p = 0.04) while 22 week UA Doppler significantly predicted preterm birth (OR = 12.6, p = 0.001), small for gestational age (OR = 8.24, p = 0.001) and low birth weight (OR = 2.28, p = 0.04). Test characteristics suggested improved positive and negative predictive value for Doppler at 22 versus 18 weeks for these outcomes. CONCLUSIONS: UA Doppler at 22 weeks is a useful adjunct in patients with low PAPP-A. However, a negative Doppler does not rule out all adverse outcomes and clinical judgment is advised in the management of these patients.
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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 | 0.011 |
| 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".