Evidence map›Paper›PMID 36910481›Full record

ReviewFrontiers in medicine2023

Updates on the diagnosis and monitoring of giant cell arteritis.

Sara Monti, Valentin Sebastian Schäfer, Francesco Muratore, Carlo Salvarani, Carlomaurizio Montecucco, Raashid Luqmani

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. [RMD open · 2026
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  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Role and potential ofFrontiers in medicine · 2024
    Review
  13. Article
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sara MontiDepartment of Internal Medicine and Therapeutics, Università di Pavia, Pavia, Italy.
Valentin Sebastian SchäferClinic of Internal Medicine III, Department of Oncology, Hematology, Rheumatology and Clinical Immunology, University Hospital of Bonn, Bonn, Germany.
Francesco MuratoreRheumatology Unit, Azienda USL-IRCCS di Reggio Emilia, University of Modena and Reggio Emilia, Reggio Emilia, Italy.
Carlo SalvaraniRheumatology Unit, Azienda USL-IRCCS di Reggio Emilia, University of Modena and Reggio Emilia, Reggio Emilia, Italy.
Carlomaurizio MontecuccoDepartment of Internal Medicine and Therapeutics, Università di Pavia, Pavia, Italy.
Raashid LuqmaniRheumatology Department, Nuffield Orthopaedic Centre, University of Oxford, Oxford, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This mini-review offers a critical appraisal of the currently employed imaging or histopathological tools to diagnose and monitor giant cell arteritis (GCA). An overview of the most updated evidence and current application of color duplex ultrasonography (US), temporal artery biopsy (TAB), 18-fluorodeoxyglucose [18F] FDG-PET/CT, magnetic resonance imaging, and computed tomography angiography is provided. The main limitations of each tool, and the most relevant research developments are discussed. The review highlights the complementary value of the available modalities to ensure a correct diagnosis of GCA, and to provide valuable prognostic information. Novel evidence is accumulating to support the role of imaging, and particularly US, as a monitoring tool for the disease, opening new perspectives for the future management of large vessel vasculitis.

Indexed as

biopsydiagnosisgiant cell arteritisimagingmonitoring

Identifiers

PMID36910481
PMCPMC9995793

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.