Adjuvants to Mechanical Ventilation for Acute Respiratory Failure. Adoption, De-adoption, and Factors Associated with Selection
Bibliographic record
Abstract
RATIONALE: Adoption and de-adoption of adjuvant strategies to mechanical ventilation for acute respiratory failure (ARF), and factors associated with their selection, have not been extensively evaluated. OBJECTIVES: To evaluate change in use of adjuvants to mechanical ventilation for ARF (2008-2013), the impact of landmark publications on adoption and de-adoption, and factors associated with use. METHODS: Changes in use of four adjuvants for ARF from 2008 to 2013, the impact of landmark publications on use, and factors associated with use were evaluated with the Premier Database. Extracorporeal membrane oxygenation (ECMO), inhaled nitric oxide, inhaled epoprostenol, and continuous neuromuscular blockading agents (cNMBAs) in adult mechanically ventilated patients were identified on the basis of International Classification of Diseases, Ninth Revision, Clinical Modification codes and billing data. MEASUREMENTS AND MAIN RESULTS: Among 514,913 patients with ARF, 11,567 (2.3%) were treated with at least one adjuvant. cNMBAs were the most frequently used adjuvants (n = 10,073, 2.1% in capable hospitals), followed by inhaled pulmonary vasodilators (n = 1,878, 1.0% in capable hospitals; 58% nitric oxide), and ECMO (n = 195, 0.2% in capable hospitals). There was an increase in ECMO and inhaled epoprostenol over time but no change in nitric oxide or cNMBAs. Segmented regression analysis was used to evaluate whether clinical practice was in accordance with emerging evidence from landmark studies. Using the relevant landmark publication dates, these analyses did not reveal any change in use over time after publication with the exception of inhaled epoprostenol-for which rates of growth decreased over time, possibly in response to the evidence. There was a significant amount of variability in patient and hospital factors associated with use with between adjuvants. CONCLUSIONS: Between 2008 and 2013, there was an increase in use of ECMO and inhaled epoprostenol, and no change in use of inhaled nitric oxide or continuous intravenous infusion of a neuromuscular blocking agent. There was considerable variability in patient and hospital factors associated with use across different adjuvants.
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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 | 0.015 | 0.097 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".