Methods of Assessing Nailfold Capillaroscopy Compared to Video Capillaroscopy in Patients with Systemic Sclerosis—A Critical Review of the Literature
Bibliographic record
Abstract
INTRODUCTION: Nailfolds of patients with systemic sclerosis (SSc) provide an opportunity to directly visualize microvascular remodeling in SSc. Nailfold video capillaroscopy (NVC) remains the gold standard for assessing nailfold capillaroscopy (NFC). However, access to NVC is limited by expense and expertise. This review aims to synthesize current research on other NFC devices compared to NVC. METHODS: The literature search included the primary research of adult patients with SSc as defined by the 2013 ACR/EULAR criteria. Methods of assessing NFC included stereomicroscopy/wide-field microscopy, ophthalmoscopy, dermatoscopy, smartphone devices, and digital USB microscopy. Primary outcomes included both qualitative (normal vs. abnormal nailfolds, overall pattern recognition, presence/absence of giant capillaries, hemorrhages, and abnormal morphology) and quantitative (capillary density and dimension) measures. RESULTS: The search yielded 471 studies, of which 9 were included. Five studies compared NVC to dermatoscopy, two compared it to widefield/stereomicroscopy, one to smartphone attachments, and one to USB microscopy. In dermatoscopy studies, NVC had a higher percentage of images that were interpretable (63-77% vs. 100%), classifiable (70% vs. 84%), or gradable (70% vs. 79.3%) across three studies. Dermatoscopy had a lower sensitivity (60.2% vs. 81.6%) and higher specificity (92.5% vs. 84.6%) compared to NVC. One stereomicroscopy study found a significant difference between methods in capillary density in limited cutaneous SSc, while another found correlations in all parameters between stereomicroscopy and NVC. One smartphone lens had good agreement with NVC on abnormal capillary morphology and density. USB microscopy was able to differentiate between SSc and healthy controls using mean capillary width but not by capillary density. DISCUSSION: A dermatoscope may serve as a more portable and affordable screening tool to identify a normal "scleroderma pattern", and images that need further corroboration by NVC. NFC parameters reported are heterogenous and the standardization of these parameters is important, especially in non-gold-standard devices.
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How this classification was reachedexpand
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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".