THE INVESTIGATION OF RADIOLOGICAL FINDINGS AND UPPER EXTREMITY FUNCTIONS IN DIFFERENT AGE PATIENTS WITH DEGENERATIVE ROTATOR CUFF TEARS
Bibliographic record
Abstract
Clinical outcomes and upper extremity functions are deteriorated over time in degenerative rotator cuff tear (dRCT). Therefore, evaluation of the radiological and clinical parameters in cases with dRCT will guide to choose a proper treatment. This article is a case-control study which investigates the effects of age related changes on degree of anatomic abnormalities in individuals with dRCT and the influence of these parameters on upper extremity functions (UEF). 20 healthy participants and 43 symptomatic patients with dRCT participated in this study. The healthy group and patient group were divided into 2 categories based on their ages and degree of abnormalities. UEF was determined with Western Ontario Rotator Cuff Index (WORC) and 9 Hole Peg Test (9PEG). Number of tendons, tear size, humeral head migration>7mm (Mig>7mm), humeral cysts, presence of retraction (PR) and muscle atrophy (MA) were evaluated with MRI. Mean age of the patients with severe radiological parameters was 10 years older than those with mild abnormalities. Mean age of the patients with mild degree abnormalities was cumulated about 50 years whereas those with severe degree abnormalities were around 64 years. Mean age of the patients with Mig>7mm, involvement of more than 2 tendons, PR and MA were significantly older (p 0.05). In relatively elderly cases or for the ones with symptomatic dRCT more than 10 years, all radiological components of dRCT are expected to be already in severe degree. Therefore, radiological, objective and subjective assessment modalities should be utilized in examination of the cases with dRCT.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".