Sequential measurement of the neurosensory retina in hypertensive disorders of pregnancy: a model of microvascular injury in hypertensive emergency
Bibliographic record
Abstract
Optical coherence tomography of the eye suggests the retina thins in normal pregnancy. Our objectives were to confirm and extend these observations to women with hypertensive disorders of pregnancy (HDP). Maternal demographics, clinical/laboratory findings and measurements of macular thickness were repeatedly collected at gestational ages <20 weeks, 20-weeks to delivery, at delivery and postpartum. The primary outcome was the change in macular thickness from non-pregnant dimensions in women with incident HDP compared to non-hypertensive pregnant controls. Secondary outcomes were the relationship(s) between mean arterial pressure (MAP) and macular response. Data show macular thicknesses diminished at <20 weeks gestation in each of 27 pregnancies ending in HDP (mean 3.94 µm; 95% CI 4.66, 3.21) and 11 controls (mean 3.92 µm; 5.05, 2.79; P < 0.001 versus non-pregnant dimensions in both; P = 0.983 HDP versus controls). This thinning response continued to delivery in all controls and in 7 women with HDP superimposed on chronic hypertension. Macular thinning was lost after 20 weeks gestation in the other 20 women with HDP. MAP at loss of macular thinning in women without prior hypertension (n = 12) was identical to MAP at enrollment. However, mean MAP subsequently rose 19 mmHg (15, 22) leading to de novo HDP in all 12 women. Loss of thinning leading to a rise in MAP was also observed in 8 of 15 women with HDP superimposed on chronic hypertension. We conclude the macula thins in most women in early pregnancy. Those who lose this early macular thinning response often develop blood pressure elevations leading to HDP.
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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 | 0.001 |
| 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 | 0.000 | 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".