Utility of applying a diagnostic algorithm in giant cell arteritis based on the level of clinical suspicion.

Utilidad de la aplicación de un algoritmo diagnóstico en la arteritis de células gigantes en función del grado de sospecha clínica.
18F-FDG-PET/CT 18F-FDG-PET/TC Arteritis de células gigantes Diagnosis Diagnóstico Ecografía Giant cell arteritis Imaging tests Pruebas de imagen Ultrasound

Journal

Medicina clinica
ISSN: 1578-8989
Titre abrégé: Med Clin (Barc)
Pays: Spain
ID NLM: 0376377

Informations de publication

Date de publication:
25 Jan 2024
Historique:
received: 14 09 2023
revised: 16 11 2023
accepted: 18 11 2023
medline: 27 1 2024
pubmed: 27 1 2024
entrez: 26 1 2024
Statut: aheadofprint

Résumé

To reach the diagnosis of giant cell arteritis (GCA), signs, symptoms, laboratory tests, imaging findings, and occasionally anatomopathological results from temporal artery biopsy are evaluated. This study describes the results of an algorithm analysis based on clinical and ultrasound evaluation of patients with suspected GCA, highlighting its diagnostic utility by contrasting its use in different clinical suspicion scenarios. Prospective multicenter study evaluating patients referred with suspected GCA through a preferential circuit (fast track), grouping them according to low or high clinical suspicion of GCA. Each of these scenarios is evaluated by biopsy and ultrasound for all patients, resulting in positive, indeterminate, or negative outcomes, yielding six possible groups. Potential areas of improvement are explored, emphasizing that, following a negative or indeterminate ultrasound, 18-FDG-PET-CT could be recommended. We analyze the results and application of a diagnostic algorithm, confirming its efficiency and applicability based on whether there is high or low clinical suspicion. Sixty-nine patients (41 in the high suspicion group and 28 in the low suspicion group). There were 41 new diagnoses of GCA: 35 in the high suspicion group and 6 in the low suspicion group. Using ultrasound alone, the initial algorithm has an overall diagnostic efficiency of 72.5%, which improves to 80.5% when including 18F-FDG-PET/CT. The negative predictive value of ultrasound in patients with low clinical suspicion is 84.6%, and the positive predictive value of ultrasound in patients with high suspicion is 100%, improving sensitivity from 57.1% to 80.8% with 18F-FDG-PET/CT in this scenario. Temporal artery biopsy was performed on all patients, with no differences in sensitivity or specificity compared to ultrasound. In cases where all three tests - ultrasound, biopsy, and 18F-FDG-PET/CT - are performed, sensitivity increases to 92.3% in patients with high clinical suspicion. In situations of high clinical suspicion, the algorithm provides sufficient information for the diagnosis of GCA if ultrasound is positive. A negative ultrasound is sufficient to rule out the diagnosis in the context of low clinical suspicion. 18-FDG-PET-CT may be useful in patients with high suspicion and negative or indeterminate ultrasound results.

Identifiants

pubmed: 38278759
pii: S0025-7753(23)00755-8
doi: 10.1016/j.medcli.2023.11.021
pii:
doi:

Types de publication

Journal Article

Langues

eng spa

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier España, S.L.U. All rights reserved.

Auteurs

Paula Estrada (P)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España. Electronic address: paulavestradaa@gmail.com.

Patricia Moya (P)

Servicio de Reumatología, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, España.

Javier Narváez (J)

Servicio de Reumatología, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, España.

Carmen Moragues (C)

Servicio de Reumatología, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, España.

Vanessa Navarro (V)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España.

Oscar Camacho (O)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España.

Daniel Roig (D)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España.

Dacia Cerdà (D)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España.

Sergi Heredia (S)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España.

Delia Reina (D)

Servicio de Reumatología,Complex Hospitalari Universitari Moisès Broggi, Sant Joan Despí, Universitat de Barcelona (UB), Barcelona, España.

Hèctor Corominas (H)

Servicio de Reumatología, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, España.

Classifications MeSH