Myopathy is a poor prognostic feature in systemic sclerosis: results from the Canadian Scleroderma Research Group (CSRG) cohort
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To determine the clinical impact of muscle involvement in a large systemic sclerosis (SSc) cohort. METHOD: Using the Canadian Scleroderma Research Group (CSRG) database, SSc patients with either elevated creatine kinase (CK) or a prior history of myositis/myopathy were identified. Regression and Kaplan-Meier analyses were performed to determine characteristics associated with muscle involvement in SSc and survival outcome. RESULTS: In 1145 patients with SSc, 5.6% had an elevated CK. This subset was more likely to be male (24.5% in elevated CK vs. 12.6% in normal CK, p < 0.013), younger (52 vs. 56 years, p < 0.045), have diffuse cutaneous SSc (dcSSc; 40.4% vs. 37.9%, p < 0.002), tendon friction rubs (30.0% vs. 13.4%, p < 0.001), and forced vital capacity (FVC) < 70% (23.9% vs. 13.1%, p < 0.039), be ribonucleoprotein (RNP) antibody positive (12.0% vs. 5.0%, p < 0.032), topoisomerase1 (topo1)-antibody positive (26.0% vs. 14.4%, p < 0.026), have a higher modified Rodnan skin score (MRSS; 16.14 vs. 9.81, p < 0.001), and a higher Health Assessment Questionnaire (HAQ) score (0.98 vs. 0.79, p < 0.011). Survival was reduced for patients with elevated CK (p < 0.025). Nearly 10% of patients in the CSRG cohort had a prior history of myositis/myopathy. This subset also had findings similar to those with elevated CK and increased mortality (p < 0.003). CONCLUSIONS: Muscle involvement in SSc has a poor prognosis impacting survival, especially in men with early dcSSc with topo1 and RNP autoantibodies and interstitial lung disease (ILD).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it