Determination of fetal heart rate short‐term variation from umbilical artery Doppler waveforms
Bibliographic record
Abstract
OBJECTIVE: To evaluate the feasibility of using umbilical artery (UA) Doppler waveforms to measure fetal heart rate (FHR) short-term variation (STV) across gestation. METHODS: This was a prospective longitudinal study, conducted at two study sites, of 195 pregnancies considered low risk. Pulsed-wave Doppler of the UAs was performed at 4-weekly intervals, between 14 and 40 weeks of gestation, using a standardized imaging protocol. Up to 12 consecutive UA Doppler waveforms were analyzed using offline processing software. FHR STV was calculated using average R-R intervals extracted from the waveforms and baseline corrected for FHR. RESULTS: = 0.54; P < 0.0001). The STV ranged (median (interquartile range)) from 3.5 (2.9-4.1) ms at 14-20 weeks' gestation to 6.3 (4.8-7.7) ms at 34-40 weeks' gestation. The change in heart rate STV did not differ between study sites or individual sonographers. CONCLUSIONS: UA Doppler waveforms offer a robust and feasible method to derive STV of the FHR. It should be emphasized that the UA Doppler-derived STV is not interchangeable with measurements derived with computerized cardiotocography. Accordingly, further investigations are needed to validate associations with outcome, in order to determine the value of concurrent fetal cardiovascular and heart rate evaluations that are possible with the technique described here. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.
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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 | 0.009 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".