Sleep Disturbance and Anatomic Shoulder Arthroplasty
Bibliographic record
Abstract
Sleep disturbance is commonly encountered in patients with glenohumeral joint arthritis and can be a factor that drives patients to consider surgery. The prevalence of sleep disturbance before or after anatomic total shoulder arthroplasty has not been reported. The authors identified 232 eligible patients in a prospective shoulder arthroplasty registry following total shoulder arthroplasty for primary glenohumeral joint arthritis with 2- to 5-year follow-up. Sleep disturbance secondary to the affected shoulder was characterized preoperatively and postoperatively as no sleep disturbance, frequent sleep disturbance, or nightly sleep disturbance. A total of 211 patients (91%) reported sleep disturbance prior to surgery. Patients with nightly sleep disturbance had significantly worse (P<.05) Constant pain, Constant activity, and Western Ontario Osteoarthritis Shoulder index scores prior to surgery. Postoperatively, there was a significant improvement in the prevalence of sleep disturbance, with 186 patients (80%) reporting no sleep disturbance (P<.001). The no sleep disturbance group had significantly greater patient-reported outcome scores and range of motion following surgery compared with the other sleep disturbance groups for nearly all outcome measures (P≤.01). Patients have significant improvements in sleep after anatomic shoulder arthroplasty. There was a high prevalence of sleep disturbance preoperatively (211 patients, 91%) compared with postoperatively (46 patients, 20%). [Orthopedics. 2017; 40(3):e450-e454.].
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".