Haptoglobin phenotype, pre‐eclampsia, and response to supplementation with vitamins<scp>C</scp>and<scp>E</scp>in pregnant women with type‐1 diabetes
Bibliographic record
Abstract
OBJECTIVE: The phenotype of the antioxidant and pro-angiogenic protein haptoglobin (Hp) predicts cardiovascular disease risk and treatment response to antioxidant vitamins in individuals with diabetes. Our objective was to determine whether Hp phenotype influences pre-eclampsia risk, or the efficacy of vitamins C and E in preventing pre-eclampsia, in women with type-1 diabetes. DESIGN: This is a secondary analysis of a randomised controlled trial in which women with diabetes received daily vitamins C and E, or placebo, from 8 to 22 weeks of gestation until delivery. SETTING: Twenty-five antenatal metabolic clinics across the UK (in north-west England, Scotland, and Northern Ireland). POPULATION: Pregnant women with type-1 diabetes. METHODS: Hp phenotype was determined in white women who completed the study and had plasma samples available (n = 685). MAIN OUTCOME MEASURE: Pre-eclampsia. RESULTS: Compared with Hp 2-1, Hp 1-1 (OR 0.59, 95% CI 0.30-1.16) and Hp 2-2 (OR 0.93, 95% CI 0.60-1.45) were not associated with significantly decreased pre-eclampsia risk after adjusting for treatment group and HbA1c at randomisation. Our study was not powered to detect an interaction between Hp phenotype and treatment response; however, our preliminary analysis suggests that vitamins C and E did not prevent pre-eclampsia in women of any Hp phenotype (Hp 1-1, OR 0.77, 95% CI 0.22-2.71; Hp 2-1, OR 0.81, 95% CI 0.46-1.43; Hp 2-2, 0.67, 95% CI 0.34-1.33), after adjusting for HbA1c at randomisation. CONCLUSIONS: The Hp phenotype did not significantly affect pre-eclampsia risk in women with type-1 diabetes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".