Obstructive sleep apnoea and its association with gestational hypertension
Bibliographic record
Abstract
Hypertension develops in 10% of pregnancies. Snoring, a marker of obstructive sleep apnoea, is a newly identified risk factor for gestational hypertension. Moreover, obstructive sleep apnoea is an independent risk factor for incident hypertension in the non-pregnant population. The aim of the present study was to test the hypothesis that obstructive sleep apnoea is associated with new onset of hypertension among pregnant females. A case-control study was performed involving 17 pregnant females with gestational hypertension and 33 pregnant females without hypertension. Subjects were frequency-matched for gestational age and recruited in a tertiary obstetrical centre. Obstructive sleep apnoea was ascertained by polysomnography and defined by an apnoea/hypopnoea index (AHI) of >or=15 events x h(-1), without requirement for desaturation. The mean+/-sd AHI for normotensive pregnant females was 18.2+/-12.2 events x h(-1) compared with 38.6+/-36.7 events x h(-1) for females with hypertensive pregnancies. The crude odds ratio for the presence of obstructive sleep apnoea given the presence of gestational hypertension was 5.6. The odds ratio was 7.5 (95% confidence interval 3.5-16.2), based on a logistic regression model with adjustment for maternal age, gestational age, pre-pregnancy body mass index, prior pregnancies, and previous live births. In conclusion, gestational hypertension appears to be strongly associated with the presence of obstructive sleep apnoea.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".