Effect of Thermotherapy on Clinical Outcomes among Patients with Osteoarthritis
Bibliographic record
Abstract
Background: The most common and crippling type of arthritis is osteoarthritis (OA), which is characterized as a degenerative disorder targeting synovial joints. Patients with osteoarthritis frequently lament a dull aching pain that worsens with movements. When physical agents as heat therapy are used properly, they can combat unpleasant conditions. Aim: This study was carried out to determine the effect of thermotherapy on Clinical Outcomes among Patients with Osteoarthritis. Design: A quasi-experimental research design (pre-post study/control) was used to achieve the study's aim Setting: The study was conducted in the orthopedic outpatient department of the shebin EL-Kom Teaching Hospital and Menoufia University Hospital, Menoufia Governorate, Egypt. Sample: 80 adults with unilaterally knee osteoarthritis were chosen as a convenient sample. Three different tools were used to collect data. Tool I: structured interview questionnaire. Tool II: Lysholm Knee Scoring Scale (LKSC). Tool II1: The Western Ontario and McMaster Universities Arthritis Index. Results: The mean pain and stiffness scores were 13.62±2.10 and 5.40±0.92 respectively among the study group and 13.52±2.01 and 5.50±0.87 respectively among the control group, which were highly significantly decreased among the study group than the control group with P value = <0.001. Conclusions: A distinct effect of thermotherapy on knee osteoarthritis was observed in a form of decreasing pain, stiffness, and improving physical functions. Recommendation: Superficial heat therapy should be included in managing patients with osteoarthritis to relieve pain, stiffness and improve physical function. Moreover, replication of the study with a larger probability sample must be considered in the development of future research to allow for greater generalization of the results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".