Use of endotracheal tubes in continuous aspiration of subglottic secretions: Knowledge and expertise of respiratory therapists and nurses
Bibliographic record
Abstract
Introduction: Ventilator-associated pneumonia (VAP) is a hospital acquired nosocomial infection that is commonly found in patients receiving mechanical ventilation. Continuous aspiration of subglottic secretions (CASS) is found to lower the incidence of VAP. The aim of this study was to assess respiratory therapists and nurses’ awareness and experiences about the Endotracheal Tubes (ETT) with CASS. Methodology: This is a cross-sectional study. Purposive sampling of 51 respiratory therapists and 51 nurses who were involved in taking care of critically ill patients in adult ICUs at King Abdul-Aziz Medical City, Riyadh were used. The questionnaire was related to the knowledge and experiences of respiratory therapists and nurses about the proper use of ETT with CASS. Results: The results suggest that the respiratory therapists were more knowledgeable in the use of ETT-CASS. However, both respiratory therapists and nurses had problems related to ETT design and materials. Most of these problems were related to cuff materials and its design, suctioning system and tubes, in addition to the availability of the equipment. Conclusion: This study presents a unique contribution to knowledge about the experiences of respiratory therapists and nurses who work in KAMC about the proper use of ETT-CASS. The results of this study showed that the use of ETT-CASS is yet to be popularly recognized. Thus, it should be acclaimed by further studies and promotion through formulation of updated protocols and educational programs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".