Intratracheal Administration of Antimicrobial Agents in Mechanically Ventilated Adults: An International Survey on Delivery Practices and Safety
Bibliographic record
Abstract
BACKGROUND: Intratracheal antibiotic administration is increasingly used for treating respiratory infections. Limited information is available on delivery devices, techniques, and safety. METHODS: An online survey on intratracheal administration of anti-infective agents in mechanically ventilated adults was answered by health-care workers from 192 ICUs to assess the most commonly used devices, current delivery practices, and safety issues. We investigated whether ICU usage experience (≥3 y) impacted its performance. RESULTS: Intratracheal antibiotic administration was a current practice in 87 ICUs (45.3%), with 40 (46%) having experience with the technique (≥3 y). Sixty-six (78.6%) of 84 health-care workers reported avoiding intratracheal antibiotic administration due to an absence of evidence-based guidelines (78.6%). Jet nebulizers were the most commonly used devices for delivery, in 24 less experienced ICUs (27.6%) and in 18 (20.7%) experienced ICUs. Direct tracheal instillation (6; 6.9%) was still considered for drug prescription in 12 ICUs (6.9%). More experience resulted in neither greater adherence to measures improving the drug's delivery efficiency (93 measures in the experienced group; 27.9%) nor a greater adoption of measures to increase safety. Indeed, the expiratory filter was changed after each nebulization in only 2 experienced ICUs (6.9%), whereas 15 (51.7%) changed it daily instead. CONCLUSIONS: Intratracheal antibiotic administration is a common therapeutic modality in ICUs, but inadequate practices were widely encountered, independent of the level of experience with the technique. This suggests a need to develop standardization to reduce variability and improve safety and efficacy.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".