Emergency department presentations and hospital admissions for patients with biopsy-positive giant cell arteritis in South Australia

Background/Aims: Giant cell arteritis (GCA) causes significant morbidity from disease burden and treatment complications, yet Australian data on healthcare utilisation are lacking. This study quantified healthcare utilisation among patients with biopsy-proven GCA in South Australia (SA) by examining rates and causes of hospitalisation and emergency department (ED) presentation, temporal trends, length of stay, and cumulative comorbidity burden.

Methods: Patients aged ≥50 years with positive temporal artery biopsy were identified from the SA GCA Registry (1992–2022). ED presentations and hospital admissions (2001–2022) were obtained using the SA-NT Data-linkage framework, and compared against controls (4:1) from the same sociodemographic distribution. Recurrent event Andersen-Gill time-to-event models estimated Hazard Ratios (HR). Cumulative Elixhauser comorbidity scores were determined at last visit as a surrogate for patients’ overall health status.

Results: 435 GCA patients and 2124 controls were included. Both ED presentations and hospital admissions were increased in GCA patients compared to controls (HR 1.74 (95%CI 1.48, 2.03) and HR 1.73 (95%CI 1.14, 2.61)), with events highest within 12 months of GCA diagnosis. Mean length of stay was equivalent. GCA patients more often had a principal admission diagnosis of infection (HR 1.53, 95%CI 1.12, 2.09), cerebrovascular disease (HR 1.99, 95%CI 1.17, 3.36), osteoporosis/osteoporotic fracture (HR 4.0, 95%CI 1.06, 15.08), pulmonary embolus (HR 4.35, 95%CI 1.53, 12.27), diverticulitis (HR 4.74, 95%CI 1.12, 2.09), and atherosclerosis (HR 9.73, 95%CI 3.22, 29.4). Comorbidity index suggested no difference between GCA patients and controls (age-adjusted mean difference =-0.1, p = 0.59).

Conclusion: This is the first Australian study to determine the significant burden of GCA, particularly in the 12 months following diagnosis. Improved understanding of healthcare utilisation will enable appropriate resource allocation and research prioritisation to improve patient outcomes.