ArticleRMD open2026
Comparison of four clinical risk prediction models for the diagnosis of giant cell arteritis: results from the ongoing PREDICT-GCA study.
Article in RMD open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe potential role of structured clinical pretest probability assessment in the diagnostic workup of giant cell arteritis (GCA) is not well defined. PATIENTS AND
methodsWe applied four clinical prediction rules to patients enrolled in the ongoing prospective PREDICT GCA study. All patients underwent temporal artery biopsy in addition to the detailed clinical and sonographic workup. The final diagnosis was based on the 6 months follow-up and ambiguous cases were judged by an independent expert panel. The diagnostic accuracy of the four models was determined using 2×2 contingency tables and receiver operating characteristic analysis. Patients with and without discordant results in different scoring systems were compared using univariate significance tests.
resultsSeventy patients were analysed. The highest diagnostic accuracy (area under the curve (AUC) 0.84) and the highest negative predictive value (NPV, 86.7%) were provided by the Ing
conclusionClinical prediction models for the diagnosis of GCA differ in their diagnostic accuracy. Clinically relevant discordances of individual risk prediction are common. TRIAL REGISTRATION NUMBER: DRKS00031293.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.