Fetal Heart Rate Variability Following An Acute Bout Of Maternal Exercise During Pregnancy
Bibliographic record
Abstract
PURPOSE: It is well known that the fetal environment influences the development of the fetus’ nervous system. For example, pregnant mothers who regularly engage in aerobic exercise give birth to babies with greater brain maturity (May et al. 2014; LeMoyne et al. 2013). This suggests that the autonomic nervous system of the fetus may be stimulated while the mother is exercising. The purpose of this study was to examine fetal cardiac-autonomic function following an acute bout of maternal exercise. METHODS: Electrocardiograms were placed on a group of 10 pregnant women in order to detect fetal cardiovascular activity. Participants then completed 30-minutes of cycling at 50% of their maximum oxygen consumption. Fetal Heart Rate (HR) and Heart Rate Variability (HRV) were analyzed for 5 minutes before the start of exercise and for a period of 10 minutes immediately after the exercise session. RESULTS: A series of one-way repeated measure ANOVAs revealed that spectral power of fetal HR was significantly greater immediately following exercise cessation, as indicated by increased absolute power at very-low (VLF), low (LF), intermediate (intF) and high frequencies (HF) (ps<0.05). Furthermore, fetal HRV was significantly greater immediately following exercise cessation, as indicated by an increase in the standard deviation of beat-to-beat intervals (SDNN/NN) and root mean square standard deviation (RMSSD/NN) (ps<0.05). These modifications returned to pre-exercise baseline within 10 minutes of exercise cessation. CONCLUSIONS: An acute bout of exercise during pregnancy leads to significant alterations in multiple fetal HRV parameters, suggesting a modification in fetal cardiac-autonomic activity. The current findings add to our knowledge regarding the influence of maternal exercise on fetal cardiac-autonomic function, reaffirming the benefit of maternal exercise on fetal health.
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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 | 0.000 | 0.002 |
| 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".