Cardiorespiratory Physiotherapy around the Clock: Experience at a University Hospital
Bibliographic record
Abstract
Purpose: To document and describe the use of a hospital-wide, 24-hour cardiorespiratory physiotherapy service run by an intensive care unit (ICU) team of physiotherapists. Methods: We prospectively collected data on all non-ICU hospital patients who used the 24-hours-per-day cardiorespiratory physiotherapy service over a 1-year period between July 2013 and June 2014. The ICU physiotherapists documented the reason, origin of referral, time of call, and type and frequency of treatment of each patient. Results: Over the 1-year period, the ICU physiotherapists administered 2,192 out-of-hours cardiorespiratory physiotherapy treatments (n=685 patients) outside the ICU. Most referrals originated from the emergency department (25%), the cardiopulmonary transplant unit (20%), and the pulmonology department (16%). Referrals were from a physiotherapist in 49% of cases, from a nurse in 32%, and from a physician in 19%. Of these, 89% were made between 4:00 p.m. and 8:00 a.m., and sputum retention was the most frequent reason (86%). Conclusion: Although proving its cost effectiveness is difficult, organizing a 24-hours-per-day, 7-days-per-week cardiorespiratory physiotherapy service in a large hospital is feasible.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".