Bätjer, Emma Luise (2025) Inter- Hospital Variability in the Giant Cell Arteritis Probability Score Performance – A Two Centre Study. thesis, Medicine.
Full text available on request.Abstract
Background: Giant Cell Arteritis (GCA) needs to be diagnosed and treated at an early stage to help prevent serious complications. The GCA probability score (GCAPS) was developed by Laskou et al. as a clinical tool to stratify risk in patients with suspected GCA, but its utility in Dutch healthcare settings needs further assessment. Objective: We aim to evaluate the performance of the modified GCAPS as a pre-test risk stratification tool for GCA across different hospital settings in the Netherlands and to determine the diagnostic accuracy of various imaging modalities. Methods: We conducted a two-centre retrospective cohort study at the University Medical Centre Groningen (UMCG) and Ziekenhuisgroup Twente (ZGT) Almelo, including 269 patients with suspected GCA. Final diagnosis was determined by rheumatologist expert opinion six months after presentation. Diagnostic performance of imaging modalities was evaluated using sensitivity and specificity. GCAPS validation was performed using ROC curve analysis with calculation of Youden's index for optimal cutoff determination. Results: The modified GCAPS demonstrated strong overall discriminative ability (Area under the receiver operating characteristic curve: 0.828, 95% CI: 0.777–0.879) for predicting GCA diagnosis. Each one-unit increase in the continuous GCAPS score was associated with a 41% increase in the odds of GCA diagnosis. However, we observed substantial variability in GCAPS performance between the two hospitals, suggesting context-specific factors may influence its diagnostic utility. Conclusion: The GCAPS shows promise as a risk stratification tool for GCA in Dutch healthcare settings, though its performance varies between institutions. These findings highlight the importance of local validation before widespread implementation and suggest that contextspecific factors should be considered when using GCAPS to guide clinical decision-making in GCA diagnosis.
| Item Type: | Thesis (UNSPECIFIED) |
|---|---|
| Supervisor name: | Brouwer, Dr. E. |
| Faculty: | Medical Sciences |
| Date Deposited: | 20 Jan 2026 14:13 |
| Last Modified: | 20 Jan 2026 14:13 |
| URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/3881 |
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