Fetal heart rate monitoring during nocturnal polysomnography.
Bibliographic record
Abstract
STUDY OBJECTIVES: To evaluate the success rate of adding continuous electronic fetal heart rate monitoring (EFM) during full night polysomnography (PSG), in women with both gestational hypertension (GH) with uncomplicated singleton pregnancies. METHOD: As part of a larger study evaluating for the presence of sleep disordered breathing (SDB) in women with GH compared to women with uncomplicated pregnancies, continuous EFM was added to usual polysomnography. RESULTS: Forty-eight EFM studies (26 with GH and 22 with uncomplicated pregnancies) were evaluated. EFM studies were categorized by the percentage of time that interpretable tracings were obtained: < 25% of the time; 25-50% of the time; or > 50% of the time. We deemed > 50% of the time to be ideal, but under the test conditions 25-50% of the time to be acceptable. For women with GH, 71% of women had ideal or acceptable overnight EFM tracings compared to 82% for women with uncomplicated pregnancies. Of those women who were diagnosed with SDB, 77% had an acceptable or ideal EFM tracing. CONCLUSIONS: Adding EFM to conventional polysomnography is feasible and safe. It may prove an important adjunct as interest in sleep disorders of pregnancy continues to expand.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".