← Capillary.io team publications
Publications by other researchers
Explore how other research groups use Capillary.io in clinical and population studies. This collection includes applications and evaluations of the software, with links to the original publications.
Research articles, clinical reports and letters documenting the use of Capillary.io or its algorithms.
Stroke. 2026;57(10):e483–e484.
Examines the relationship between nailfold capillary abnormalities and cerebral small vessel disease burden in 289 older adults from the Atahualpa cohort in Ecuador.
The corresponding preprint explicitly documents analysis with Capillary.io. This publication extends work in the same cohort as the white matter hyperintensities study listed below.
Clinical and Translational Medicine. 2026;16(9):e70789.
University of Michigan researchers used Capillary.io to detect, classify and quantify nailfold capillary features in juvenile myositis and comparison groups. The paper cites publications on the software.
ACR Open Rheumatology. 2026;8(8):e90106.
An Australian study of nicotinamide supplementation in Raynaud phenomenon. Nailfold images were assessed with Capillary.io, and the methods cite the CAPI-Detect publication.
Journal of Primary Care & Community Health. 2026;17:21501319261473346.
A population study of 306 older adults in Ecuador examining oily fish intake and microvascular integrity. Methods explicitly name Capillary.io for automated image analysis, followed by expert review.
Arthritis & Rheumatology. 2026;78(7):1557–1558.
A single-patient report using CAPI-Detect on Capillary.io for serial capillaroscopy in anti–Mi-2 dermatomyositis. It describes microvascular improvement occurring later than clinical remission and cites the platform's algorithms.
Rheumatology. 2026;65(7):keag319.
A clinical vignette using and citing CAPI-Detect in primary acrocyanosis. Two structures flagged as giant capillaries were identified as false positives on expert review, illustrating the importance of reviewing automated findings.
Journal of Stroke and Cerebrovascular Diseases. 2026;35:108633.
A study of 289 older adults in Ecuador combining nailfold capillaroscopy with brain MRI. Automated analysis used Capillary.io to quantify capillary abnormalities; the methods name the platform and link to its website.
Mediterranean Journal of Rheumatology. 2025;36(2).
A case report on navicular algodystrophy and microvascular abnormalities. Capillaroscopy was assessed using Capillary.io and its CAPI-Detect algorithm alongside expert interpretation; the paper cites CAPI-Detect.
ACR Open Rheumatology. 2025;7(1):e11784.
A case report describing a scleroderma-like capillaroscopic pattern without an underlying connective tissue disease. It explicitly uses Capillary.io and cites CAPI-Score.
A published correction updates an apical-diameter measurement in Figure 1.
Conference reports of research using or evaluating Capillary.io, published as abstracts.
ACR Convergence 2026. Abstract 1686. Arthritis & Rheumatology. 2026;78(suppl 9).
A two-center evaluation comparing Capillary.io with expert capillary density assessment in 50 participants. It reports moderate overall agreement and very poor agreement at severely reduced density, and concludes that the measurements are not interchangeable with high precision.
Abstract published online for the ACR Convergence session dated 9 November 2026.
EULAR 2026. Abstract POS0155.
Researchers in Varna, Bulgaria, compare automated capillaroscopy using Capillary.io with expert assessment in connective tissue diseases. The abstract reports preliminary diagnostic accuracy results.
ACR Convergence 2025. Abstract 2158. Arthritis & Rheumatology. 2025;77(suppl 9).
A UCSF and UC Berkeley study examining nailfold capillary changes in juvenile dermatomyositis. Capillary.io measured capillary limb widths and apical diameters, followed by manual review.
ACR Convergence 2025. Abstract 0252. Arthritis & Rheumatology. 2025;77(suppl 9).
A Colombian study of 136 patients with autoimmune rheumatic diseases. Images acquired with Smart G-Scope were processed using Capillary.io to characterize capillaroscopic patterns.
Manuscripts shared before peer review. The version linked here is a preprint.
SSRN. 2026. doi:10.2139/ssrn.7008573.
A study of 51 women with antiphospholipid syndrome using Capillary.io to assess capillaroscopic patterns and quantitative metrics, and their relationships with antibody profiles, vascular events and obstetric morbidity.