Giant cell arteritis: incidence and phenotypic distribution in Western Norway 2013-2020.

Objectives: There is an increasing awareness of the spectrum of phenotypes in giant cell arteritis (GCA). However, there is sparse evidence concerning the phenotypic distribution which may be influenced by both genetic background and the environment. We established a cohort of all GCA-patients in the Bergen Health Area (Western Norway), to describe the phenotypic distribution and whether phenotypes differ with regards to incidence and clinical features. Methods: This is a retrospective cohort study including all GCA-patients in the Bergen Health Area from 2013-2020. Data were collected by reviewing patient records, and patients considered clinically likely GCA were included if they fulfilled at least one set of classification criteria. Temporal artery biopsy (TAB) and imaging results were used to classify the patients according to phenotype. The phenotype "cranial GCA" was used for patients with a positive TAB or halo sign on temporal artery ultrasound. "Non-cranial GCA" was used for patients with positive findings on FDG-PET/CT, MRI-, or CT angiography, or wall thickening indicative of vasculitis on ultrasound of axillary arteries. Patients with features of both these phenotypes were labeled "mixed." Patients that could not be classified due to negative or absent examination results were labeled "unclassifiable". Results: 257 patients were included. The overall incidence of GCA was 20.7 per 100,000 persons aged 50 years or older. Overall, the cranial phenotype was dominant, although more than half of the patients under 60 years of age had the non-cranial phenotype. The diagnostic delay was twice as long for patients of non-cranial and mixed phenotype compared to those of cranial phenotype. Headache was the most common clinical feature (78% of patients). Characteristic clinic features occurred less frequently in patients of non-cranial phenotype compared to cranial phenotype. Conclusion: The overall incidence for GCA was comparable to earlier reports from this region. The cranial phenotype dominated although the non-cranial phenotype was more common in patients under 60 years of age. The diagnostic delay was longer in patients with the non-cranial versus cranial phenotype, indicating a need for examination of non-cranial arteries when suspecting GCA.

Survival and death causes of patients with giant cell arteritis in Western Norway 1972-2012: a retrospective cohort study.

BACKGROUND: Our objective was to determine the survival and causes of death in a large and well-characterized cohort of patients with giant cell arteritis (GCA). METHODS: This is a hospital-based, retrospective, observational cohort study including patients diagnosed with GCA in Western Norway during 1972-2012. Patients were identified through computerized hospital records using the International Classification of Diseases (ICD)-coding system. Medical records were reviewed. Patients were randomly assigned population controls matched on age, sex, and geography from the Central Population Registry of Norway (CPRN). Date and cause of death were obtained from the Norwegian Cause of Death Registry (NCoDR). The survival was analyzed using Kaplan-Meier methods with the Gehan-Breslow test and the causes of death using cumulative incidence and Cox models for competing risks. RESULTS: We identified 881 cases with a clinical diagnosis of GCA of which 792 fulfilled the American College of Rheumatology (ACR) 1990 classification criteria. Among those fulfilling the ACR criteria, 528 were also biopsy-verified. Cases were matched with 2577 population controls. A total of 490 (56%) GCA patients and 1517 (59%) controls died during the study period. We found no difference in the overall survival of GCA patients compared to controls, p = 0.413. The most frequent underlying causes of death in both groups were diseases of the circulatory system followed by cancer. GCA patients had increased risk of dying of circulatory disease (HR 1.31, 95% CI 1.13-1.51, p < 0.001) but lower risk of dying of cancer (HR 0.56, 95% CI 0.42-0.73, p < 0.001) compared to population controls. CONCLUSIONS: We found no difference in the overall survival of GCA patients compared to matched controls, but there were differences in the distribution of underlying death causes.

Correction to: Incidence of giant cell arteritis in Western Norway 1972-2012: a retrospective cohort study.

Following publication of the original article [1], the authors reported an error.

Incidence of giant cell arteritis in Western Norway 1972-2012: a retrospective cohort study.

BACKGROUND: Giant cell arteritis (GCA) is the most common systemic vasculitis in persons older than 50 years. The highest incidence rates of the disease have been reported in Scandinavian countries. Our objective was to determine the epidemiology of GCA in an expected high-incidence region during a 41-year period. METHODS: This is a hospital-based, retrospective, cohort study. Patients diagnosed with GCA in Bergen health area during 1972-2012 were identified through computerized hospital records (n = 1341). Clinical information was extracted from patients' medical journals, which were reviewed by a standardized method. We excluded patients if data were unavailable (n = 253), if the reviewing rheumatologist found GCA to be an implausible diagnosis (n = 207) or if the American College of Rheumatology (ACR) 1990 classification criteria for GCA were not fulfilled (n = 89). Descriptive methods were used to characterize the sample. Incidence was analyzed by graphical methods and Poisson regression. RESULTS: A total of 792 patients were included. The average annual cumulative incidence of GCA was 16.7 (95% CI 15.5-18.0) per 100,000 of the population ≥ 50 years old. The corresponding incidence for biopsy-verified GCA was 11.2 (95% CI 10.2-12.3). The annual cumulative incidence increased with time in the period 1972-1992 (relative risk (RR) 1.1, p < 0.001) but not in 1993-2012 (RR 1.0, p = 0.543). The incidence was higher in women compared to men (average annual incidence 37.7 (95% CI 35.8-39.6) vs. 14.3 (95% CI 13.2-15.5), p < 0.001) with women having a twofold to threefold higher incidence rate throughout the study period. Average annual incidence increased with age until the 7th decade of life in both sexes throughout the study period (2.8 (95% CI 2.3-3.3) for age <60, 15.5 (95% CI 14.4-16.8) for age 60-69, 34.5 (95% CI 32.8-36.4) for age 70-79 and 26.8 (95% CI 25.3-28.4) for age ≥80 years, p < 0.001 for all age adjustments). CONCLUSIONS: Our study confirms an incidence of GCA comparable to previous reports on Scandinavian populations. Our results show increasing incidence from 1972 through 1992, after which the incidence has levelled out.

Settings and artefacts relevant for Doppler ultrasound in large vessel vasculitis.

Ultrasound is used increasingly for diagnosing large vessel vasculitis (LVV). The application of Doppler in LVV is very different from in arthritic conditions. This paper aims to explain the most important Doppler parameters, including spectral Doppler, and how the settings differ from those used in arthritic conditions and provide recommendations for optimal adjustments. This is addressed through relevant Doppler physics, focusing, for example, on the Doppler shift equation and how angle correction ensures correctly displayed blood velocity. Recommendations for optimal settings are given, focusing especially on pulse repetition frequency (PRF), gain and Doppler frequency and how they impact on detection of flow. Doppler artefacts are inherent and may be affected by the adjustment of settings. The most important artefacts to be aware of, and to be able to eliminate or minimize, are random noise and blooming, aliasing and motion artefacts. Random noise and blooming artefacts can be eliminated by lowering the Doppler gain. Aliasing and motion artefacts occur when the PRF is set too low, and correct adjustment of the PRF is crucial. Some artefacts, like mirror and reverberation artefacts, cannot be eliminated and should therefore be recognised when they occur. The commonly encountered artefacts, their importance for image interpretation and how to adjust Doppler setting in order to eliminate or minimize them are explained thoroughly with imaging examples in this review.