Lung-protective ventilation decreases heart rate variability in a non-inflammatory porcine model
Bibliographic record
Abstract
Introduction: The effect of lung-protective mechanical ventilation (MV) on sympathetic/parasympathetic nervous system balance has not been demonstrated. We hypothesize that cyclical alveolar stretch during lung-protective MV progressively downregulates parasympathetic activity over the course of 50 hours. Heart rate variability (HRV) is an accepted method for measuring sympathetic/parasympathetic balance. Greater R-R interval (RRI) variance reflects a normal physiological state with parasympathetic predominance; lower RRI variance indicates sympathetic predominance, which correlates with high mortality and inflammation. Studying HRV during MV is important to better understand the inflammatory insult associated with MV. Methods: We ventilated eight human-size pigs using lung-protective MV for 50 hours. Ventilation parameters were set to achieve tidal volume 8ml/kg, plateau pressure <30 cmH2O, and PEEP of 5 mmHg. ECG data were analyzed over two periods after MV initiation; hours 0 to 6 (start) and hours 44 to hour 50 (end). Root mean square of the standard deviation of the R-R intervals (RMSSD) was chosen as the HRV time domain method of analysis. Results: A total of 407,762 RRIs were analyzed across the eight subjects; 213,301 at the start, 194,461 at the end (p=0.87). The median number of RRIs was 22,151 at the start, 22,152 at the end. RMSSD was 0.97 at the start, 0.82 at the end, with a statistically significant difference between start and end (p=0.015). Conclusion: Lung-protective MV for 50 hours results in a reduction in heart rate variability, indicating pro-inflammatory conditions with downregulation of the parasympathetic autonomic nervous system.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".