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Record W2518955877 · doi:10.4187/respcare.04775

Cough Augmentation Techniques in the Critically Ill: A Canadian National Survey

2016· article· en· W2518955877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRespiratory Care · 2016
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsLondon Health Sciences CentreOttawa HospitalWest Park Healthcare CentreHealth Sciences CentreToronto East General HospitalUniversity of TorontoSunnybrook Health Science CentreWestern UniversitySt. Michael's Hospital
Fundersnot available
KeywordsMedicineCough reflexExsufflationLung volumesContraindicationMechanical ventilationPneumothoraxAnesthesiaLungInternal medicineAirwayInsufflationSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Critically ill mechanically ventilated patients experience impaired airway clearance due to ineffective cough and impaired secretion mobilization. Cough augmentation techniques, including mechanical insufflation-exsufflation (MI-E), manually assisted cough, and lung volume recruitment, improve cough efficiency. Our objective was to describe use, indications, contraindications, interfaces, settings, complications, and barriers to use across Canada. METHODS: An e-mail survey was sent to nominated local survey champions in eligible Canadian units (ICUs, weaning centers, and intermediate care units) with 4 telephone/e-mail reminders. RESULTS: The survey response rate was 157 of 238 (66%); 78 of 157 units (50%) used cough augmentation, with 50 (64%) using MI-E, 53 (68%) using manually assisted cough, and 62 (79%) using lung volume recruitment. Secretion clearance was the most common indication (MI-E, 92%; manually assisted cough, 88%; lung volume recruitment, 76%), although the most common units (44%) used it <50% of the time. Use during weaning from invasive (MI-E, 21%; manually assisted cough, 39%; lung volume recruitment, 3%) and noninvasive ventilation (MI-E, 21%; manually assisted cough, 33%; lung volume recruitment, 21%) was infrequent. The most common diagnoses were neuromuscular disease (97%) and spinal cord injury (83%). Pneumothorax was the most frequently identified absolute contraindication for MI-E (93%) and lung volume recruitment (83%); rib fracture was most frequently identified for manually assisted cough (69%). MI-E mean inspiratory pressure was 31 cm H2O, and expiratory pressure was -32 cm H2O. Mucus plugging requiring tracheostomy inner change was the most frequent complication for MI-E (23%), chest pain for manually assisted cough (36%), and hypotension for lung volume recruitment (17%). The most commonly cited barriers were lack of expertise (70%), knowledge (65%), and resources (52%). CONCLUSIONS: We found moderate adoption of cough augmentation techniques, particularly for secretion management. Lack of expertise and knowledge are potentially modifiable barriers addressed with educational interventions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.050
GPT teacher head0.338
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it