Quantitative Alterations of Capillary Diameter Have a Predictive Value for Development of the Capillaroscopic Systemic Sclerosis Pattern
Bibliographic record
Abstract
OBJECTIVE: To quantify earlier capillary diameter abnormalities, observed by nailfold videocapillaroscopy (NVC), in primary Raynaud phenomenon (PRP) subjects compared with RP subjects later evolved to systemic sclerosis (SSc)-associated secondary Raynaud phenomenon (SRP). METHODS: There were 6112 NVC images of 191 subjects analyzed at baseline and after a mean followup of 42.77 ± 35.80 months. We selected 48 patients affected by SRP and 143 matched controls confirmed with PRP. The diameter of the most dilated limbs (arterial, venous, and apical) was measured in 16 images per subject. Statistical analysis was performed using nonparametric tests. The threshold values for capillary diameters associated with the development of SSc-associated SRP were determined through receiver-operating characteristic curves. RESULTS: Mean capillary diameter values were significantly different for arterial, venous, and average diameters (mean value of arterial, venous, and apical) between patients with PRP and SRP (p < 0.0001). These alterations were found to be independent predictors for disease development (p = 0.015). Threshold values of 30 µm (area under the curve = 0.802, sensitivity/specificity = 0.85/0.63) to 31 µm were identified for average, arterial, and venous diameters, with a shortening effect on time to disease development. CONCLUSION: The study showed that capillary diameter is an independent predictor for development of SSc-associated SRP. Progression to SRP is unlikely for subjects affected by RP when average capillary diameter is under 30 μm. Subsequently, the execution of the qualitative/quantitative integrated analysis should be part of the NVC followup of RP subjects.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".