Are psychosocial variables, sleep characteristics or central pain processing prognostic factors for outcome following rotator cuff repair? A protocol for a prospective longitudinal cohort study
Bibliographic record
Abstract
INTRODUCTION: Prognosis following surgical rotator cuff repair (RCR) is often established through the assessment of non-modifiable biomedical factors such as tear size. This understates the complex nature of recovery following RCR. There is a need to identify modifiable psychosocial and sleep-related variables, and to find out whether changes in central pain processing influence prognosis after RCR. This will improve our knowledge on how to optimise recovery, using a holistic rehabilitation approach. METHODS AND ANALYSIS: This longitudinal study will analyse 141 participants undergoing usual care for first time RCR. Data will be collected 1-21 days preoperatively (T1), then 11-14 weeks (T2) and 12-14 months (T3) postoperatively. We will use mixed-effects linear regression to assess relationships between potential prognostic factors and our primary and secondary outcome measures-the Western Ontario Rotator Cuff Index; the Constant-Murley Score; the Subjective Shoulder Value; Maximal Pain (Numeric Rating Scale); and Quality of Life (European Quality of Life, 5 dimensions, 5 levels). Potential prognostic factors include: four psychosocial variables; pain catastrophising, perceived stress, injury perceptions and patients' expectations for RCR; sleep; and four factors related to central pain processing (central sensitisation inventory, temporal summation, cold hyperalgesia and pressure pain threshold). Intercorrelations will be assessed to determine the strength of relationships between all potential prognostic indicators.Our aim is to explore whether modifiable psychosocial factors, sleep-related variables and altered central pain processing are associated with outcomes pre-RCR and post-RCR and to identify them as potential prognostic factors. ETHICS AND DISSEMINATION: The results of the study will be disseminated at conferences such as the European Pain Congress. One or more manuscripts will be published in a peer-reviewed SCI-ranked journal. Findings will be reported in accordance with the STROBE statement and PROGRESS framework. Ethical approval is granted by the Ethical commission of Canton of Zurich, Switzerland, No: ID_2018-02089 TRIAL REGISTRATION NUMBER: NCT04946149.
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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 | 0.058 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".