Haptoglobin phenotype and abnormal uterine artery Doppler in a racially diverse cohort
Bibliographic record
Abstract
OBJECTIVE: The anti-oxidant and proangiogenic protein haptoglobin (Hp) is believed to be important for implantation and pregnancy, although its specific role is not known. The three phenotypes (1-1, 2-1 and 2-2) differ in structure and function. Hp 2-2 is associated with increased vascular stiffness in other populations. We examined whether Hp phenotype is associated with abnormal uterine artery Doppler (UAD) in pregnancy. METHODS: We conducted a secondary analysis of a preeclampsia prediction cohort nested within a larger placebo-controlled randomized clinical trial of antioxidants for prevention of preeclampsia. We determined Hp phenotype in 2184 women who completed UAD assessments at 17 weeks gestation. Women with notching were re-evaluated for persistent notching at 24 weeks' gestation. Logistic regression was used to assess differences in UAD indices between phenotype groups. RESULTS: Hp phenotype did not significantly influence the odds of having any notch (p = 0.32), bilateral notches (p = 0.72), or a resistance index (p = 0.28) or pulsatility index (p = 0.67) above the 90th percentile at 17 weeks' gestation. Hp phenotype also did not influence the odds of persistent notching at 24 weeks (p = 0.25). CONCLUSIONS: Hp phenotype is not associated with abnormal UAD at 17 weeks' gestation or with persistent notching at 24 weeks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".