Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio

Giant cell arteritis (GCA) is a primary granulomatous systemic vasculitis involving the aorta and its main branches that affects people aged over 50 years with a genetic predisposition. Its main phenotypes are cranial and extracranial involvement, with or without symptoms of polymyalgia rheumatica....

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Autores principales:	Wolff C,Verónica, Paolinelli G,Paola, Guevara H,David Ladrón De
Lenguaje:	Spanish / Castilian
Publicado:	Sociedad Médica de Santiago 2020
Materias:	Giant Cell Arteritis Multidetector Computed Tomography Positron-Emission Tomography Ultrasonography
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0034-98872020001101619
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spelling	oai:scielo:S0034-988720200011016192021-04-04Arteritis de células gigantes: actualización y proposición de un algoritmo de estudioWolff C,VerónicaPaolinelli G,PaolaGuevara H,David Ladrón De Giant Cell Arteritis Multidetector Computed Tomography Positron-Emission Tomography Ultrasonography Giant cell arteritis (GCA) is a primary granulomatous systemic vasculitis involving the aorta and its main branches that affects people aged over 50 years with a genetic predisposition. Its main phenotypes are cranial and extracranial involvement, with or without symptoms of polymyalgia rheumatica. These phenotypes can overlap. The extracranial form can be oligosymptomatic and must be sought directly. The main complications of the disease are ischemia of essential territories such as the optic nerve or cerebral circulation, and aneurysmal dilations of the aorta and its large branches. Clinicians must be aware of all the presentation forms of the disease, to start a timely treatment and avoid potentially serious or fatal consequences. To date, the diagnosis of GCA is based on clinical and pathological criteria, with the temporal artery biopsy as the “gold standard” for diagnosis, although its sensitivity is variable. This can lead to an underdiagnosis in patients with negative biopsies or predominant extra-cranial symptoms. The emergence of new and valuable imaging tools substantially improved the timely diagnosis, mainly in subclinical and oligosymptomatic forms. Among them we highlight ultrasonography of the temporal and axillary arteries, Computed Tomography Angiography, Magnetic Resonance Angiography, and PET-CT. These imaging techniques are complementary, and their use is highly recommended. GCA treatment is based on steroidal therapy, often associated with a corticosteroid-sparing immunosuppressive agent. The follow-up is eminently clinical.info:eu-repo/semantics/openAccessSociedad Médica de SantiagoRevista médica de Chile v.148 n.11 20202020-11-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0034-98872020001101619es10.4067/S0034-98872020001101619
institution	Scielo Chile
collection	Scielo Chile
language	Spanish / Castilian
topic	Giant Cell Arteritis Multidetector Computed Tomography Positron-Emission Tomography Ultrasonography
spellingShingle	Giant Cell Arteritis Multidetector Computed Tomography Positron-Emission Tomography Ultrasonography Wolff C,Verónica Paolinelli G,Paola Guevara H,David Ladrón De Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
description	Giant cell arteritis (GCA) is a primary granulomatous systemic vasculitis involving the aorta and its main branches that affects people aged over 50 years with a genetic predisposition. Its main phenotypes are cranial and extracranial involvement, with or without symptoms of polymyalgia rheumatica. These phenotypes can overlap. The extracranial form can be oligosymptomatic and must be sought directly. The main complications of the disease are ischemia of essential territories such as the optic nerve or cerebral circulation, and aneurysmal dilations of the aorta and its large branches. Clinicians must be aware of all the presentation forms of the disease, to start a timely treatment and avoid potentially serious or fatal consequences. To date, the diagnosis of GCA is based on clinical and pathological criteria, with the temporal artery biopsy as the “gold standard” for diagnosis, although its sensitivity is variable. This can lead to an underdiagnosis in patients with negative biopsies or predominant extra-cranial symptoms. The emergence of new and valuable imaging tools substantially improved the timely diagnosis, mainly in subclinical and oligosymptomatic forms. Among them we highlight ultrasonography of the temporal and axillary arteries, Computed Tomography Angiography, Magnetic Resonance Angiography, and PET-CT. These imaging techniques are complementary, and their use is highly recommended. GCA treatment is based on steroidal therapy, often associated with a corticosteroid-sparing immunosuppressive agent. The follow-up is eminently clinical.
author	Wolff C,Verónica Paolinelli G,Paola Guevara H,David Ladrón De
author_facet	Wolff C,Verónica Paolinelli G,Paola Guevara H,David Ladrón De
author_sort	Wolff C,Verónica
title	Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
title_short	Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
title_full	Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
title_fullStr	Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
title_full_unstemmed	Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
title_sort	arteritis de células gigantes: actualización y proposición de un algoritmo de estudio
publisher	Sociedad Médica de Santiago
publishDate	2020
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0034-98872020001101619
work_keys_str_mv	AT wolffcveronica arteritisdecelulasgigantesactualizacionyproposiciondeunalgoritmodeestudio AT paolinelligpaola arteritisdecelulasgigantesactualizacionyproposiciondeunalgoritmodeestudio AT guevarahdavidladronde arteritisdecelulasgigantesactualizacionyproposiciondeunalgoritmodeestudio
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Arteritis de células gigantes: actualización y proposición de un algoritmo de estudio

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