Nailfold Videocapillaroscopy in Systemic Sclerosis–related Pulmonary Arterial Hypertension: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: Pulmonary arterial hypertension (PAH) is one of the leading causes of death in systemic sclerosis (SSc). Current screening algorithms are hampered by low positive predictive values. Outcome measures that could add to performance characteristics would be welcome. We aim to evaluate the role of nailfold videocapillaroscopy (NVC) using standardized definitions, in SSc-related PAH (SSc-PAH). METHODS: A systematic review to identify original research papers documenting an association between NVC and right heart catheterization-defined SSc-PAH was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Subsequently, NVC characteristics were subdivided into quantitative (capillary density, dimension, morphology, and hemorrhages), semiquantitative, and qualitative assessment (NVC pattern), according to the definitions of the European League Against Rheumatism Study Group on Microcirculation in Rheumatic Diseases. RESULTS: The systematic search identified 316 unique search results, of which 5 were included in the final qualitative analysis. The occurrence of incident SSc-PAH unequivocally associated in 2 longitudinal studies with progressive capillary loss (p = 0.04 and p = 0.033) and the progression to a severe (active/late) NVC pattern (p = 0.05/0.01 and HR = 5.12, 95% CI 1.23-21.27). In 3 cross-sectional studies, SSc-PAH was found to be unequivocally inversely associated with capillary density (p = 0.001 and p < 0.05) and associated with the presence of a severe NVC pattern (p = 0.03 and p < 0.05). CONCLUSION: This is the first systematic literature review investigating the role of NVC in SSc-PAH using standardized description, to our knowledge. Unequivocal associations were found between (incident) SSc-PAH and capillary density and NVC pattern. Integration of NVC into current screening algorithms to boost their performance may be a future step.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".