Démanteler l’islamophobie genrée en médecine
Bibliographic record
Abstract
OBJECTIVE: Patients with systemic sclerosis (SSc) may develop psychological problems in addition to physiologic symptoms. We investigated whether demographic and clinical factors are associated with comorbid depression. METHODS: From a university hospital9s rheumatology clinic, 72 SSc patients who completed 3 questionnaires [Center for Epidemiologic Studies Depression (CES-D) scale, an abbreviated version of a functional status instrument, the Scleroderma Health Assessment Questionnaire (SHAQ), and the Gastrointestinal Quality of Life Index (GIQLI)] during an examination were recruited into the study. Correlations among scores on the 3 questionnaires [including upper and lower gastrointestinal (GI) tract subscales of the GIQLI] were calculated, and associations between CES-D scores and a variety of demographic and clinical characteristics were examined using stepwise linear regression. RESULTS: Higher CES-D scores (i.e., more depression symptoms) were significantly correlated with upper (r = -0.48, p < 0.0001) and lower (r = -0.41, p < 0.001) GI tract dysfunction and worse overall functional status (r = 0.51, p < 0.0001). Stepwise regression indicated that higher levels of depression were independently associated with lower levels of education (p < 0.01), worse upper GI tract functioning (p = 0.019), worse functional status (p = 0.34), current corticosteroid use (p = 0.061), and cardiac involvement (p = 0.086). CONCLUSION: Decreased functional status and abnormal GI functioning are significantly correlated with depression among patients with SSc. Other demographic and clinical indicators are also associated with depression.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".