Shoulder mobility and strength impairments in patients with rotator cuff related shoulder pain: a systematic review and meta analysis
Bibliographic record
Abstract
Background The methods previously proposed in the literature to assess patients with rotator cuff related shoulder pain, based on special orthopedic tests to precisely identify the structure causing the shoulder symptoms have been recently challenged. This opens the possibility of a different way of physical examination. Objective To analyze the differences in shoulder range of motion, strength and thoracic kyphosis between rotator cuff related shoulder pain patients and an asymptomatic group. Method The protocol of the present research was registered in the International Prospective Register of Systematic Review (PROSPERO) (registration number CRD42021258924). Database search of observational studies was conducted in MEDLINE, EMBASE, WOS and CINHAL until July 2023, which assessed shoulder or neck neuro-musculoskeletal non-invasive physical examination compared to an asymptomatic group. Two investigators assessed eligibility and study quality. The Newcastle Ottawa Scale was used to evaluate the methodology quality. Results Eight studies ( N = 604) were selected for the quantitative analysis. Meta-analysis showed statistical differences with large effect for shoulder flexion (I2 = 91.7%, p < 0.01, HG = −1.30), external rotation (I2 = 83.2%, p < 0.01, HG = −1.16) and internal rotation range of motion (I2 = 0%, p < 0.01, HG = −1.32). Regarding to shoulder strength; only internal rotation strength showed statistical differences with small effect (I2 = 42.8%, p < 0.05, HG = −0.3). Conclusions There is moderate to strong evidence that patients with rotator cuff related shoulder pain present less shoulder flexion, internal and external rotation range of motion and less internal rotation strength than asymptomatic individuals.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".