Physical and Functional Clinical Profile of Older Adults in Specialized Geriatric Rehabilitation Care Services in Saguenay-Québec: A Retrospective Study at La Baie Hospital
Bibliographic record
Abstract
Musculoskeletal disorders, cardiovascular and neurological diseases were the most commonly debilitating conditions and risk factors associated with pain, mobility limitations, increased risk of falls and disability. Studies barely address the profile of older adults in care within a specialized geriatric rehabilitation service (SGRS) to provide subsidies for new actions within the public healthcare to reduce falls and improve management in health investments. This study aimed to establish a clinical physical and functional profile of the patients with neuromusculoskeletal and cognitive disorders and fallers in interventions within SGRS. From a retrospective study design, 127 medical records were compiled and analyzed to determine the physical and functional profile of older adults and differences according to sex, age groups and the benefits for local physical therapy intervention. The users were between 76 and 85 years of age, with diverse clinical diagnoses and debilitating conditions and impairments. A higher proportion presented gait and balance impairments and had two or more falls in 12 months. A significant effect for advanced age was observed. Overall, real benefits were reported with intervention for functional improvement, although the absence of a control group. These results have direct implications for a better understanding of a local SGRS and provide subsidies for developing new approaches for the assessment and treatment of older adults with high a risk of falls in order to reduce costs for the public health system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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".