Practice Patterns of Canadian Physiotherapists Mobilizing Patients with External Ventricular Drains
Bibliographic record
Abstract
PURPOSE: To describe current mobilization practices of Canadian physiotherapists when treating patients with external ventricular drains (EVDs). METHODS: A quantitative, descriptive, cross-sectional study design using an online questionnaire via SurveyMonkey. An email invitation and questionnaire link was distributed in March 2010 to physiotherapists currently working with this patient population in Neurosurgical Centres across Canada. RESULTS: Respondents were 25 physiotherapists (21 full-time, 2 part-time, and 2 who did not disclose work status) working in 5 different provinces who treated ≥1 patient/month with an EVD (n=9). Slightly more than half of respondents had ≤10 years' clinical physiotherapy experience (n=14); the remainder had >10 years' experience (n=11). The majority of respondents indicated that they felt comfortable mobilizing patients with EVDs (n =19) and that it was safe to do so (n=20). Clinical experience (n=23) and safety concerns (n=25) were most commonly cited as guiding practice. More experienced physiotherapists were more likely to use out-of-bed mobilization practices. Regardless of experience, the majority of physiotherapists (20/25) ranked intracranial pressure (ICP) as the most important factor and saturation of oxygen (Spo2) as the least important factor to consider before mobilization. CONCLUSIONS: Canadian physiotherapists are mobilizing patients with EVDs, and the intensity level of their mobilization practices appears to be related to their experience level. Data from the current study may be used in developing future best-practice guidelines for the mobilization of patients with EVDs.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".