Assessment of patient-ventilator breath contribution during neurally adjusted ventilatory assist in patients with acute respiratory failure
Bibliographic record
Abstract
INTRODUCTION: We previously showed in animals that the ratio of inspired tidal volume (Vtinsp) to inspiratory peak electrical activity of the diaphragm (EAdipk) can be used to quantify the respective patient and ventilator breath contributions (PVBCs) during neurally adjusted ventilatory assist (NAVA). The PVBC index has not been tested clinically. METHODS: We studied 12 intubated and mechanically ventilated patients with acute respiratory failure and measured EAdipk, airway (Paw) and inspiratory esophageal pressure (Pes) and Vtinsp. We applied 11 different NAVA levels, increasing them every 3 minutes in steps of 0.3 cm H₂O/μV from 0 to 3.0 cmH₂O/μV. At each NAVA level, one breath was non-assisted (NAVA level 0). PVBC indices were calculated by relating Vtinsp/EAdipk of the non-assisted breath to Vtinsp/EAdipk of the assisted breath(s) using one ((N1)PVBC) or the mean value of five preceding assisted breaths ((X5)PVBC). During assisted breaths, inspiratory changes in Pes (∆Pes) and transpulmonary (ΔPtp) pressures were used to calculate the relative contribution of patient to total inspiratory lung-distending pressures (ΔPes/ΔPtp). Matching of respiratory drive indices and squaring of the PVBC was evaluated for their effect on the correlation between PVBC and ΔPes/ΔPtp. Linear regression analysis and Bland-Altman analysis were applied to compare indices. RESULTS: Using an average of five assisted breaths prior to the non-assisted breath and squaring the PVBC ((X5)PVBC(2)) improved determination coefficients (P <0.05), adjusted the regression slope and intercept between PVBC and ΔPes/ΔPtp toward identity (P <0.05) and reduced bias (P <0.05). Matching EAdipk between non-assisted and assisted breaths within the range of 0.77 to 1.30 improved the relationship between (X5)PVBC(2) and ΔPes/ΔPtp (P <0.05) and abolished the need for EAdi normalization in the PVBC calculation (R(2) = 0.96; bias = 0.16 ± 0.06; precision = 0.33 ± 0.08 (mean and 95% confidence interval)). CONCLUSIONS: This clinical study confirms previous experimental results showing that the PVBC(2) predicts the contribution of the inspiratory muscles versus that of the ventilator during NAVA, when differences in effort (EAdi) between non-assisted and assisted breaths are limited. PVBC could help to quantify and standardize the adjustment of the level of assist, and hence reduce the risks of excessive ventilatory assist in patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT01663480. Registered 9 August 2012.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".