Capi-score: a quantitative algorithm for identifying disease patterns in nailfold videocapillaroscopy

Gracia Tello, Borja del Carmelo (Universidad de Zaragoza) ; Sáez Comet, Luis (Universidad de Zaragoza) ; Lledó, Gema ; Freire Dapena, Mayka ; Mesa, Miguel Antonio ; Martín-Cascón, Miguel ; Guillén del Castillo, Alfredo ; Martínez Robles, Elena ; Simeón-Aznar, Carmen Pilar ; Todolí Parra, Jose Antonio ; Varela, Diana Cristina ; Maldonado Vélez, Genessis ; Marín Ballvé, Adela (Universidad de Zaragoza) ; Aramburu Llorente, Jimena ; Pérez Abad, Laura ; Ramos Ibáñez, Eduardo

Resumen: Objectives
EULAR supports the use of nailfold videocapillaroscopy (NVC) for identifying disease patterns (DPs) associated with SSc and RP. Recently, EULAR proposed an easy-to-manage procedure, a so-called Fast Track algorithm, for differentiating SSc patterns from non-SSc patterns in NVC specimens. However, subjectivity among capillaroscopists remains a limitation. Our aim was to perform a software-based analysis of NVC peculiarities in a cohort of samples from SSc and RP patients and, subsequently, build a Fast Track–inspired algorithm for identifying DPs without the constraint of interobserver variability.

Methods
NVCs were examined by 9 capillaroscopists. Those NVCs whose DPs were consensually agreed upon (by ≥2 out of 3 interobservers) were subsequently analysed using in-house–developed software. The results for each variable were grouped according to the consensually agreed-upon DPs in order to identify useful hallmarks for categorizing them.

Results
A total of 851 NVCs (21 957 images) whose DPs had been consensually agreed upon were software-analysed. Appropriate cut-offs set for capillary density and percentage of abnormal and giant capillaries, tortuosities and haemorrhages allowed DP categorization and the development of the CAPI-score algorithm. This consisted of four rules: Rule 1, SSc vs non-SSc, accuracy 0.88; Rules 2 and 3, SSc-early vs SSc-active vs SSc-late, accuracy 0.82; Rule 4, non-SSc normal vs non-SSc non-specific, accuracy 0.73. Accuracy improved when the analysis was limited to NVCs whose DPs had achieved full consensus between the interobservers.

Conclusion
The CAPI-score algorithm may become a tool that is useful in assigning DPs by overcoming the limitations of subjectivity.

Idioma: Inglés

DOI: 10.1093/rheumatology/keae197

Año: 2024

Publicado en: Rheumatology (Oxford) 63, 12 (2024), 3315–3321
ISSN: 1462-0324

Factor impacto JCR: 4.4 (2024)

Categ. JCR: RHEUMATOLOGY rank: 9 / 58 = 0.155 (2024) - Q1 - T1

Factor impacto SCIMAGO: 1.721 - Rheumatology (Q1) - Pharmacology (medical) (Q1)

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Area Medicina (Dpto. Medicina, Psiqu. y Derm.)