Use of Sedation and Neuromuscular Blockers in Critically Ill Adults Receiving High-Frequency Oscillatory Ventilation
Bibliographic record
Abstract
BACKGROUND: Nearly all patients receive sedation and neuromuscular blockers (NMBs) during high-frequency oscillatory ventilation (HFOV). OBJECTIVE: To describe analgo-sedation and NMB use prior to and during HFOV in adults with acute respiratory distress syndrome. METHODS: Retrospective single-center study of 131 consecutive adults whose care was managed with HFOV from 2002 to 2011. RESULTS: During the first 4 days of HFOV, 89% and 95% of patients received sedation and opioids, respectively. Upon HFOV initiation, 119 (90.8%) patients received fentanyl doses higher than 200 µg/h; of these, 48 also received more than 20 mg/h of midazolam. Analgo-sedation doses increased significantly over time such that doses were double by day 3. Factors independently associated with fentanyl doses higher than 200 µg/h were NMB ever used (OR 4.43; 95% CI 1.26-15.65, p = 0.02), pH less than 7.15 (OR 2.08; 95% CI 1.22-3.5, p = 0.007), worsening partial pressure of oxygen/fraction of inspired oxygen (OR 1.05; 95% CI 1.00-1.10, p = 0.04), and Acute Physiology and Chronic Health Evaluation (APACHE) II score (OR 0.87; 95% CI 0.79-0.97, p = 0.009). Deep sedation was commonly administered when NMBs were not being used, with 99.2% of sedation-agitation scores of 1 or 2. Eighty-six patients (65.6%) received NMBs and use was greatest on day 1 (59.5%). Train-of-Four was measured every hour for 53.4% of patients; 29.2% of the measurements were 0 of 4. NMB use declined over the 10-year study period. CONCLUSIONS: High analgo-sedation doses were associated with APACHE II scores, worsening gas exchange, and NMB use. Two thirds of patients received NMBs; use was highest on day 1 and subsequently declined. The percentage of patients who received NMB during HFOV in our study was lower than that previously reported. Future research should evaluate patient outcomes with and without use of NMBs, as well as the potential to manage patients with less sedation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".