Nailfold videocapillaroscopy abnormalities in autoimmune inflammatory myopathy subsets
Bibliographic record
Abstract
OBJECTIVES: Nailfold videocapillaroscopy (NVC) alterations have been described in autoimmune inflammatory myopathies (AIM). This study aimed to describe NVC abnormalities in AIM subsets using a clinico-sero-pathological approach. METHODS: We studied subjects from the Canadian Inflammatory Myopathy Study (CIMS), a prospective AIM cohort. NVC images were acquired using the DS MEDICA Videocap (×200 magnification). Capillary density was scored quantitatively and semi-quantitatively. Ectasias, giant capillaries, ramified capillaries and microhaemorrhages were scored as present or absent and with a standardized semi-quantitative scale (0 = none, 1=≤33%, 2 = 33-66% and 3=≥66% abnormal capillaries/total capillaries per mm). NVC patterns (i.e. scleroderma early/active/late, scleroderma-like, non-specific and normal) were described. NVC features and patterns were compared between AIM subsets. RESULTS: We included 99 AIM subjects: 41 dermatomyositis, 24 scleromyositis, 16 anti-synthetase syndrome, seven immune-mediated necrotizing myopathy, eight inclusion body myositis and three polymyositis. A total of 71% were female, and the median disease duration was 1 year [IQR; 0.4-2.8]. The most frequent NVC abnormality was decreased capillary density in dermatomyositis (95%), scleromyositis (92%) and anti-synthetase syndrome (87%). Qualitatively, 44% of subjects had abnormal NVC, 25% non-specific NVC abnormalities and 30% normal NVC. NVC patterns were not discriminant between dermatomyositis, scleromyositis and anti-synthetase syndrome. NVC abnormalities were absent in immune-mediated necrotizing myopathy, inclusion body myositis and polymyositis. CONCLUSION: Dermatomyositis, scleromyositis and anti-synthetase syndrome showed frequent NVC abnormalities, although no NVC pattern was associated with a particular subset in our study. However, NVC may help distinguish between these subsets and immune-mediated necrotizing myopathy, inclusion body myositis and polymyositis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".