Use of Preparatory Stability Exercises with Chronic Obstructive Pulmonary Disease Patients (COPD) to Prevent Iatrogenic Injuries during Rehabilitation
Bibliographic record
Abstract
Background: The increasing incidence of injuries sustained by clients during pulmonary rehabilitation, created a need to develop a prevention strategy. A pre-pulmonary rehabilitation stability exercise class was created based on best practice principles from the orthopaedic literature. It has been discussed in the literature that patients who have COPD have poor stability strategies based on the dominance of the need to drive the respiratory system. If successful, it was felt that this program would decrease the incidence of injury, decrease length stay and help to optimize outcomes. Methods: Six months of data recording the incidence and severity of injuries from participants in the pulmonary rehabilitation program was collected in order to obtain comparative statistics and demonstrate the need for this program. A literature review was performed to determine the risk of injury in this population. In a 6 month period, 17% of COPD clients admitted to the Rehabilitation Centre for pulmonary rehabilitation have had musculoskeletal issues that proved a significant enough barrier to rehabilitation to require treatment or pulmonary rehabilitation modification. Wait list clients for pulmonary rehabilitation were assessed using the PSFS, NPRS, the 6-minute walk test, the Active Straight Leg Raise, Sitting Arm Lift and the non-stop walk test. Clients participated in six one-hour group exercise sessions. The exercises included neck stabilizers, pelvic floor muscles, trunk stabilizers, and scapular stabilizers derived from published literature. Results: Clients were re-evaluated using the same outcome tools as well as noting any injuries sustained and capacity to participate. This data was compared with historical data. Conclusion: The data will help With patient selection for participation in the exercise class as well as refinement of the outcome tools and exercise protocol. This project illustrates the opportunities that exist to share and transfer knowledge from one area of physiotherapy expertise to another to meet the needs of practice. It is essential that this integrated approach to treatment be fostered by clinicians, educators and researchers alike to improve the overall outcomes for the clients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".