Prior mood disorder diagnoses do not relate to current mood disorder symptoms or patient-reported disease severity in rotator cuff patients
Bibliographic record
Abstract
BACKGROUND: Surgery for rotator cuff syndrome does not always produce symptom improvement. Biological factors may explain some symptoms, but mood disorder symptoms may also contribute. The purpose of this study is to examine the interaction between disease severity, prevalence of mood disorder diagnoses, and current mood disorder symptoms in preoperative rotator cuff patients. METHODS: A prospective cohort of patients aged 35-75 years with unilateral rotator cuff disease awaiting surgery participated. Demographics, psychiatric history, the Hospital Anxiety & Depression Scale, and the Western Ontario Rotator Cuff index were collected. Descriptive and univariate statistical testing was performed. RESULTS: Of 140 participants (75M:65W) aged 55 ± 8 years, 34 reported a prior diagnosis of a mood disorder. There was a moderate positive relationship between disease severity and current depression and anxiety scores. Women were more likely to carry a diagnosis of a mood disorder, but there were no differences in current symptom levels between genders. No differences were found in patient-reported outcome measure scores between patients with and without a mood disorder diagnosis. DISCUSSION: Current mood disorder symptoms were associated with greater disease severity, whereas the presence of a past mood disorder diagnosis was not. Awareness of this relationship may reduce bias about past mood disorder diagnoses during decision-making.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".