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Published on: February 8, 2019
The last classification of vasculitis
1Department of Rheumatology and Clinical Immunology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. c.g.m.kallenberg@int.umcg.nl
Insights
Classifying systemic vasculitis aids treatment and prognosis. A new algorithm combining existing criteria and patient data improves diagnostic accuracy for vasculitis, including antineutrophil-cytoplasmic-autoantibodies-associated vasculitis and polyarteritis nodosa.
Area of Science:
- Rheumatology
- Immunology
- Internal Medicine
Background:
- Systemic vasculitides encompass diverse conditions involving blood vessel inflammation.
- Accurate classification is crucial for homogeneous clinical characteristics, prognosis, and treatment response.
- Current classification systems, including American College of Rheumatology (ACR) criteria and Chapel Hill definitions, often lead to overlapping diagnoses, especially in small vessel vasculitis and polyarteritis nodosa (PAN).
Purpose of the Study:
- To evaluate a novel algorithm for classifying antineutrophil-cytoplasmic-autoantibodies-associated vasculitides and PAN.
- To assess the utility of integrating clinical data and serological findings into classification schemes.
- To propose a more unifying approach to classifying primary systemic vasculitides.
Main Methods:
- Development of a new algorithm incorporating Chapel Hill definitions and ACR criteria.
- Inclusion of clinical data and serological findings in the algorithm.
- Evaluation of the algorithm's performance in correctly classifying patients with vasculitis.
Main Results:
- The developed algorithm demonstrated usefulness in correctly classifying patients with antineutrophil-cytoplasmic-autoantibodies-associated vasculitides and PAN.
- The algorithm integrates key aspects of existing criteria with patient-specific data.
- Combining this algorithm with large vessel vasculitis definitions offers a more unified classification approach.
Conclusions:
- A novel algorithm integrating clinical and serological data improves classification accuracy for specific vasculitides.
- This approach addresses limitations of existing classification schemes, such as diagnostic overlap.
- Further application of this algorithm, alongside large vessel vasculitis definitions, may lead to a more unified system for primary systemic vasculitides.
Abstract:
Systemic vasculitides are a group of diverse conditions characterized by inflammation of the blood vessels. To obtain homogeneity in clinical characteristics, prognosis, and response to treatment, patients with vasculitis should be classified into defined disease categories. Many classification schemes have been proposed, but the American College of Rheumatology (ACR) criteria and the Chapel Hill definitions for the systemic vasculitides are most widely used. The ACR criteria for classifying a patient with vasculitis within a specific disease entity are useful in clinical practice; but, in many cases, their application results in overlapping diagnoses, particularly in patients with small vessel vasculitis and classical polyarteritis nodosa (PAN). The Chapel Hill definitions cannot be used as classification criteria in clinical practice. A recently developed algorithm for the antineutrophil-cytoplasmic-autoantibodies-associated vasculitides and PAN, based both on the Chapel Hill definitions and the ACR criteria and in which clinical data and serological findings are included, proved useful for correctly classifying patients. The use of this algorithm together with the definitions for the large vessel vasculitides may result in a more unifying approach to the classification of the primary systemic vasculitides.
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