Evidence map›Paper›PMID 38812633›Full record

ArticleTurkish journal of medical sciences2024

Evaluation of baseline F-18 FDG positron emission tomography in the diagnosis and assessment of giant cell arteritis.

Burak Ince, Emine Göknur Işik, Zeynep Gözde Özkan, Yasemin Yalçinkaya, Bahar Artim Esen, Ahmet Gül, Murat Inanç

Abstract read
In one paragraph

Article in Turkish journal of medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

7 authors.

Burak InceDivision of Rheumatology, Department of Internal Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0001-9813-2228
Emine Göknur IşikDepartment of Nuclear Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0002-3786-8052
Zeynep Gözde ÖzkanDepartment of Nuclear Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0003-0360-358X
Yasemin YalçinkayaDivision of Rheumatology, Department of Internal Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0001-9357-0456
Bahar Artim EsenDivision of Rheumatology, Department of Internal Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0002-5659-3955
Ahmet GülDivision of Rheumatology, Department of Internal Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0001-8219-3720
Murat InançDivision of Rheumatology, Department of Internal Medicine, İstanbul Faculty of Medicine, İstanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0002-6376-5583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/aim: The aim of this study is to evaluate the baseline F18-FDG PET/CT findings of individuals diagnosed with giant cell arteritis (GCA) and to explore its association with clinical findings and classification criteria. Materials and methods: We analysed data from patients who underwent F18-FDG PET/CT scans to investigate large vessel (LV) involvement between 2010 and 2019. Only patients with a clinical diagnosis of GCA and at least 6 months of follow-up were included. We compared initial clinical features and laboratory findings based on the presence of LV vasculitis on PET/CT and the maximum standard uptake value (SUVmax) of vascular territories. Results: Twenty-nine patients (median age at diagnosis: 70, F/M: 24/5) were included in the study. Among them, 21 patients (72.4%) presented with cranial symptoms, while 8 patients (27.5%) had isolated LV-GCA. Twenty-two patients (75.9%) met the ACR/EULAR 2022 GCA classification criteria. LV vasculitis was detected on PET/CT in 23 patients (79.3%). A positive correlation was observed between SUVmax in the thoracic aorta and both CRP and ESR levels (r = 0.50, p = 0.026 and r = 0.63, p = 0.002, respectively). PET/CT positive patients were found to be younger (p = 0.016) and more frequently female (p = 0.017). They also exhibited fewer headaches (56.5% vs. 100%, p = 0.04), experienced fewer flares during follow-up (p = 0.03), and had a lower cumulative glucocorticoid dose at the 6th month (p = 0.036). Comparison of PET/CT-positive patients (n = 23) based on the fulfilment of the ACR/EULAR 2022 classification criteria revealed that patients who met these criteria were older (p = 0.02) and had significantly lower CRP levels at diagnosis (p = 0.02). Conclusion: The performance of F18-FDG PET/CT in diagnosing LV involvement in GCA is favourable, and the severity of FDG uptake in the vessel wall correlates with the acute phase response. Patients with extracranial involvement on PET/CT exhibit distinct features, including a younger age and female predominance. Additionally, these patients appear to experience fewer relapses and require lower doses of glucocorticoids. However, the clinical significance of PET/CT in patients who met ACR/EULAR classification criteria, predominantly consisting of patients with ischemic cranial symptoms, could not be determined in our study.

Indexed as

Fluorodeoxyglucose F18Giant Cell ArteritisPositron Emission Tomography Computed TomographyAgedAged, 80 and overFemaleHumansMaleMiddle AgedRadiopharmaceuticalsRetrospective StudiesFluorodeoxyglucose F18RadiopharmaceuticalsGiant cell arteritislarge vessel vasculitispositron emission tomography

Identifiers

PMID38812633
PMCPMC11031169

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Registered trials

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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.