Reproducibility and Utility of the 6-minute Walk Test in Systemic Sclerosis
Bibliographic record
Abstract
Objective. To assess the reproducibility and the utility of the 6-minute walk test (6MWT) in systemic sclerosis (SSc). Methods. All patients with SSc who underwent at least two 6MWT within a minimum 3-month interval plus simultaneous routine clinical, biological, and functional evaluations were consecutively enrolled in this observational study over 6 years. Following American Thoracic Society guidelines, each 6MWT was repeated twice to assess the 6-minute walk distance (6MWD) reproducibility, with the highest value being reported for subsequent analysis. Results. Among 56 (38 female) included patients aged 46 ± SD 12.7 years, with 17 ± 10 modified Rodnan skin score (mRSS) and 1 ± 0.8 Scleroderma Health Assessment Questionnaire (SHAQ) at first referral, 277 6MWT evaluations (5 ± 3.9 6MWT per patient) were performed over 23 ± 22.5 months followup. Meanwhile, 8 deaths (87.5% SSc-related) occurred. The mean 6MWD absolute value was 457 ± 117 m with a 4 ± 2.2 mean Borg dyspnea score. The 6MWD intraclass correlation coefficient was 0.996 (95% CI 0.995–0.999, p < 0.0001). In multivariate linear regression analysis, these factors were independently associated with a lower 6MWD: sex (R2 = 0.47, p < 0.0001), mRSS (R2 = 0.47, p = 0.008), tendon friction rub (R2 = 0.47, p = 0.003), SHAQ (R2 = 0.47, p = 0.02), muscle disability score (R2 = 0.47, p = 0.03), DLCO% (R2 = 0.47, p = 0.0008), and left ventricular ejection fraction (R2 = 0.47, p = 0.006). The 6MWD at first referral was an independent predictor for the overall mortality (HR 0.99, 95% CI 0.988–0.999) and the SSc-related mortality (HR 0.99, 95% CI 0.988–0.999). Conclusion. We show strong reproducibility for the 6MWD and confirm the 6MWT utility to assess the overall prognosis of patients with SSc.
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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 | 0.010 | 0.035 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".