Evidence map›Paper›PMID 37525060›Full record

ArticleClinical rheumatology2024

Assessment and comparison of probability scores to predict giant cell arteritis.

Chadi Sargi, Stephanie Ducharme-Benard, Valerie Benard, Rosalie-Selene Meunier, Carolyn Ross, Jean-Paul Makhzoum

Open access · hybridAbstract read
In one paragraph

Article in Clinical rheumatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
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  8. Multimodality imaging to assess diagnosis and evaluate complications of large vesselarteritis.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2024
    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 at 2 institutions in 1 country.

Chadi SargiDepartment of Medicine, Montreal Sacre-Coeur Hospital, University of Montreal, Montreal, QC, Canada.ORCID https://orcid.org/0000-0003-1445-6378
Stephanie Ducharme-BenardVasculitis Clinic, Department of Medicine, Montreal Sacre-Coeur Hospital, University of Montreal, Montreal, QC, Canada.
Valerie BenardVasculitis Clinic, Department of Medicine, Montreal Sacre-Coeur Hospital, University of Montreal, Montreal, QC, Canada.
Rosalie-Selene MeunierVasculitis Clinic, Department of Medicine, Montreal Sacre-Coeur Hospital, University of Montreal, Montreal, QC, Canada.
Carolyn RossVasculitis Clinic, Canadian Network for Research on Vasculitides (CanVasc), Department of Medicine, Montreal Sacre-Coeur Hospital, University of Montreal, Montreal, QC, Canada.ORCID https://orcid.org/0000-0002-2891-3245
Jean-Paul MakhzoumVasculitis Clinic, Canadian Network for Research on Vasculitides (CanVasc), Department of Medicine, Montreal Sacre-Coeur Hospital, University of Montreal, Montreal, QC, Canada. jean-paul.makhzoum@umontreal.ca.ORCID http://orcid.org/0000-0003-4523-8525
Université de Montréal · CAHôpital du Sacré-Cœur de Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

INTRODUCTION/

objectivesTo assess and compare the performance of the giant cell arteritis probability score (GCAPS), Ing score, Bhavsar-Khalidi score (BK score), color Doppler ultrasound (CDUS) halo count, and halo score, to predict a final diagnosis of giant cell arteritis (GCA).

methodA prospective cohort study was conducted from April to December 2021. Patients with suspected new-onset GCA referred to our quaternary CDUS clinic were included. Data required to calculate each clinical and CDUS probability score was systematically collected at the initial visit. Final diagnosis of GCA was confirmed clinically 6 months after the initial visit, by two blinded vasculitis specialists. Diagnostic accuracy and receiver operator characteristic (ROC) curves for each clinical and CDUS prediction scores were assessed.

resultsTwo hundred patients with suspected new-onset GCA were included: 58 with confirmed GCA and 142 without GCA. All patients with GCA satisfied the 2022 ACR/EULAR classification criteria. A total of 5/15 patients with GCA had a positive temporal artery biopsy. For clinical probability scores, the GCAPS showed the best sensitivity (Se, 0.983), whereas the BK score showed the best specificity (Sp, 0.711). As for CDUS, a halo count of 1 or more was found to have a Se of 0.966 and a Sp of 0.979. Combining concordant results of clinical and CDUS prediction scores showed excellent performance in predicting a final diagnosis of GCA.

conclusionUsing a combination of clinical score and CDUS halo count provided an accurate GCA prediction method which should be used in the setting of GCA Fast-Track clinics. Key Points • In this prospective cohort of participants with suspected GCA, 3 clinical prediction tools and 2 ultrasound scores were compared head-to-head to predict a final diagnosis of GCA. • For clinical prediction tools, the giant cell arteritis probability score (GCAPS) had the highest sensitivity, whereas the Bhavsar-Khalidi score (BK score) had the highest specificity. • Ultrasound halo count was both sensitive and specific in predicting GCA. • Combination of a clinical prediction tool such as the GCAPS, with ultrasound halo count, provides an accurate method to predict GCA.

Indexed as

Giant Cell ArteritisBiopsyHumansProbabilityProspective StudiesSensitivity and SpecificityTemporal ArteriesDiagnosisGiant cell arteritisProbabilityUltrasonography

Identifiers

PMID37525060
PMCPMC10774184
OpenAlexW4385407574

What OpenQuestion holds

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LicenceCC BY
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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.