Depression in patients with systemic sclerosis: A systematic review of the evidence
Bibliographic record
Abstract
OBJECTIVE: To assess the prevalence, course, and predictors of depression in patients with systemic sclerosis (SSc). METHODS: We conducted a comprehensive search in November 2006 of MEDLINE, PsycINFO, and CINAHL databases to identify original research studies published in any language that used a structured interview or validated questionnaire to assess major depressive disorder or clinically significant symptoms of depression in patients with SSc. The search was augmented by hand searching 26 selected journals through December 2006 and references from identified articles and reviews. Studies were excluded if only an abstract was provided or if depression was not measured by a validated method. RESULTS: No studies used a structured clinical interview to assess the prevalence of major depressive disorder. The prevalence of clinically significant depressive symptoms was 51-65% based on 2 studies that used a Beck Depression Inventory (BDI) score >or=10 and 46-56% based on 2 studies that used a BDI score >or=11. These rates and those reported in 4 other studies that used different assessment tools (36-43%) were consistently high compared with other medical patient groups assessed with the same instruments and cutoffs. Methodologic issues limited the ability to draw strong conclusions from studies of predictors. CONCLUSION: Symptoms of depression are common among patients with SSc. The high rates reported across studies suggest that routine screening is recommended. There is a need for studies that examine depression at different time points from the diagnosis of SSc and that systematically investigate factors associated with high levels of depressive symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".