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Semin Arthritis Rheum. 2009 Feb;38(4):289-95. doi: 10.1016/j.semarthrit.2007.10.008. Epub 2007 Dec 31.

Feasibility of different capillaroscopic measures for identifying nailfold microvascular alterations.

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  • 1Department of Rheumatology, Istituto Gaetano Pini, University of Milan, Milan, Italy. francesca.ingegnoli@unimi.it

Abstract

OBJECTIVE:

To ascertain the most reliable and relevant capillaroscopic measurements of nailfold videocapillaroscopy (NVC) by analyzing their inter- and intraobserver agreement and predictive value.

METHODS:

We studied 217 subjects (110 with Raynaud's phenomenon under ongoing evaluation, and 107 with connective tissue diseases) by evaluating the number of capillaries, intercapillary distances, avascular areas, capillary disorganization, capillary loop length, capillary width, percentage of minor abnormalities (tortuous, crossed, or enlarged capillaries), and major abnormalities (giant, bushy, meandering, or branching capillaries), microhemorrhage, skin transparency, and subpapillary plexus visibility. Every finger of both hands was examined. All of the measurements were made by 2 observers under blinded conditions.

RESULTS:

A total of 877 nailfold images were analyzed. The number of capillaries/mm, interpeak distance, and avascular areas were poorly discriminant, with no statistical differences between their areas under the receiver operating characteristic curve; their reproducibility and repeatability were good, except for the intercapillary distance. Minor abnormalities were observed in 75% of the cases and major abnormalities in 34%; the inter- and intraobserver agreement concerning the major abnormalities was almost perfect. There was very good inter- and intraobserver agreement regarding the analysis of capillary disorganization and hemorrhages.

CONCLUSIONS:

This study shows that NVC can be useful in quantitatively and reproducibly recording various parameters. We suggest that combining the parameters showing the greatest reliability and prognostic value may be the best means of analyzing NVC images.

PMID:
18166220
[PubMed - indexed for MEDLINE]
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