Longitudinal Characterization of Patient-Ventilator Asynchronies in Acute Hypoxemic Respiratory Failure
Bibliographic record
Abstract
Background: We sought to analyze the prevalence of patient-ventilator asynchronies in subjects with hypoxemic respiratory failure because of COVID-19 ARDS and their association with clinical outcomes. Methods: This was a two-center observational cohort study using prospectively collected real-world data. We included adult subjects with COVID-19 ARDS who required mechanical ventilation for more than 48 hours. We analyzed the prevalence, characteristics, and clusters of the following patient-ventilator asynchronies detected using dedicated software on continuous respiratory recordings obtained from ventilators over the duration of mechanical ventilation (Better Care, Sabadell, Spain): double triggering, ineffective efforts (IE), and reverse triggering with and without breath-stacking (BS). The outcome measures evaluated were duration of invasive mechanical ventilation, ICU stay, and ICU mortality. Results: We analyzed 82 subjects with COVID-19 ARDS. Over the complete duration of mechanical ventilation, the most frequent asynchronies and related clusters were reverse triggering without BS (0.72% of breaths [interquartile range (IQR), 0.17–3.07]) and 4.6 clusters/d [IQR, 2.0–8.1] and double triggering (0.44% of breaths [IQR, 0.19–0.80]) and 4.6 clusters/d [IQR, 2.1–7.3]. The use of neuromuscular blockers was associated with a lower prevalence of double triggering and IE, but reverse triggering was not significantly reduced. Double triggering significantly increased with longer mechanical ventilation time, whereas reverse trigger significantly decreased during this period. Double triggering and clusters of double triggering were independently associated with longer mechanical ventilation duration and better ICU survival, whereas clusters of reverse triggering with BS were associated with longer duration of mechanical ventilation and ICU stay. Conclusions: Reverse triggering was the most prevalent asynchrony in subjects with ARDS COVID-19, decreased over time, and was followed by double triggering. Survivors had a higher prevalence of double triggering and clusters of double triggering, mostly occurring during spontaneous modes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".