Sampling rate of heart rate variability impacts the ability to detect acidemia in ovine fetuses near-term
Bibliographic record
Abstract
BACKGROUND: To evaluate the impact of sampling rate on the predictive capability of continuous fetal heart rate (FHR) variability (fHRV) monitoring for detecting fetal acidemia during labor, we tested the performance of the root mean square of successive differences (RMSSD) in R-R intervals from the ECG when acquired with the sampling rate of 4 Hz currently available in FHR monitors, in comparison to the gold standard of 1000 Hz. METHODS: Near-term ovine fetuses (N = 9) were chronically prepared with precordial electrodes for recording ECG, vascular catheters for blood sampling, and an umbilical cord occluder. For 1 min every 2.5 min, animals underwent mild partial umbilical cord occlusions (UCO) × 1 h, moderate partial UCO × 1 h, then complete UCO × 2 h, or until arterial pH reached <7.00. Arterial blood samples were drawn at baseline and every 20 min during the UCO series. RMSSD was calculated continuously in 5 min windows using an automated, standardized system (CIMVA.com). RESULTS are presented as mean ± SEM with significance assumed for p < 0.05. RESULTS: Repetitive UCO resulted in pH decreasing from 7.35 ± 0.01 to 7.00 ± 0.03. In all nine animals, RMSSD increased from 16.7 ± 1.0 ms at baseline to 44.4 ± 2.3 ms, 70 ± 15 min prior to reaching the pH nadir when sampled at 1000 Hz. When sampled at 4 Hz, RMSSD at baseline measured 36.1 ± 6.0 ms and showed no significant increase during the UCO series until the pH nadir was reached. Consequently, early detection of severe hypoxic-acidemia would have been missed in all fetuses. CONCLUSION: RMSSD as a measure of fHRV when calculated from FHR sampled at 1000 Hz allowed for the early detection of worsening hypoxic-acidemia in each fetus. However, when calculated at the low sampling rate of 4 Hz used clinically, RMSSD remained unchanged until terminally when the nadir pH was reached. For early detection of fetal acidemia during labor, more sensitive means of acquiring FHR are therefore recommended than currently deployed, e.g., trans-abdominal fetal ECG.
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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 | 0.003 |
| 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) | 0.000 | 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".