MULTI-DIMENSIONAL EVALUATION OF THE PRESENCE OF SARCOPENIA IN PATIENTS WITH KNEE OSTEOARTHRITIS
Bibliographic record
Abstract
Aim: In this study, we evaluated the presence of sarcopenia multidimensionally in patients with knee osteoarthritis (OA) using clinical, ultrasonographic and biochemical parameters, and in this respect, it was aimed to investigate the relation between OA and sarcopenia and to identify the most practical, easily accessible and inexpensive method for investigating sarcopenia.Materials and methods: 102 patients with clinical and radiological diagnosis of knee osteoarthritis and 33 healthy control subjects were included in the study. The detailed musculoskeletal system examination of the patients included in the study was carried out by a single physician, and blood sample tests were recorded .Dual-X-ray absorptiometry (DEXA) is used to measure Body composition parameters and muscle mass measurements, isometric muscle strength evaluations, handgrip strength and gait speeds for diagnosis of sarcopenia. Short-form -36 (SF-36) The Nutritional Assessment-short form (MNA), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the International Physical Assessment Questionnaire Short Form (IPAQ-SF) and the Center for Epidemiologic Studies Depression Scale (CES-D scale) were administered to every patient as outcome measures.Results: Body composition parameter results showed that sarcopenic patients had statistically lower values as fat mass, lean body mass and skeletal muscle index (p <0.001, p= 0.001, p <0.001, respectively) than those of non-sarcopenic and control group. It was determined that body composition values measured with DEXA, ultrasonographic measures, isokinetic muscle strength assessment, handgrip strength and gait speed had predictive values for sarcopenia. Conclusion: We found that patients with sarcopenic OA were older, weaker, undernourished, and restricted in their level of physical activity in the study in which we identified sarcopenia as approximately 12% in patients with osteoarthritis. Among the methods of determining sarcopenia, ultrasound becomes prominent with its practical, cheap and easily accessible features. We think that our results will increase the awareness of the presence of sarcopenia in OA patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".