Multimodal physical therapy for a patient with hip osteoarthritis
Bibliographic record
Abstract
Rosa Garnatz A female patient with right symptomatic hip osteoarthritis (OA) was seen for physical therapy (PT) treatment during 10 visits at a university pro bono outpatient PT clinic.The examination and treatment were provided by a student physical therapist under the supervision of a licensed physical therapist.The patient was evaluated at the initial encounter with the Six-Minute Walk Test, Five-Times Sit-to-Stand Test, Nine-Step Stair Climbing Test, Western Ontario and McMaster Universities Osteoarthritis Index, as well as handheld dynamometry, goniometric measurements, the Numeric Pain Rating Scale, and American College of Rheumatology Criteria.An initial five-week plan of care was established.Main goals for the patient were to increase right hip strength and range of motion (ROM), to improve functional mobility and walking ability by reducing pain, to decrease disability due to hip OA, and to increase her ability to participate in recreational physical activities.Main interventions used were orthopedic manual therapy, bodyweight supported treadmill training, and therapeutic exercise with a corresponding home exercise program.viThe patient experienced a reduction in pain with activities; improved ROM, functional mobility, and walking ability; improved participation in recreational physical activities; and experienced a reduction in disability due to hip OA.The patient was discharged from PT with an individualized home exercise program to continue living at home.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".