Evidence map›Paper›PMID 36401819›Full record

ArticleInternational journal of rheumatic diseases2023

Utility of biomarkers and temporal artery biopsy length for investigating giant cell arteritis in Western Australia.

Isabella S Atlas, Stephen M Colley, Mark A Chia

Open access · hybridAbstract read
In one paragraph

Article in International journal of rheumatic diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

3 authors at 2 institutions in 2 countries.

Isabella S AtlasSir Charles Gairdner Hospital, Perth, Australia.ORCID https://orcid.org/0000-0002-0135-9029
Stephen M ColleyFremantle Hospital, Perth, Australia.
Mark A ChiaFremantle Hospital, Perth, Australia.ORCID https://orcid.org/0000-0003-0339-5186
Fremantle Hospital · AUSir Charles Gairdner Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo explore demographic characteristics, biopsy length, and blood biomarker performance in an Australian cohort of patients who have undergone temporal artery biopsy (TAB) for giant cell arteritis (GCA).

methodsWe extracted data on biopsies performed for GCA between January 2016 and December 2020 at public hospitals in Perth. Sensitivity, specificity, and area under the curve (AUC) were calculated for blood results. We evaluated the proportion of biopsies with post-fixation length less than 15 mm and explored several length associations.

resultsWe retrospectively reviewed biopsies of 360 patients (65.8% female, mean age 72.1 years). Biopsy-positive patients were older (6.0 years, P < 0.01), and had higher C-reactive protein (CRP) (44.5 mg/L, P < 0.01), erythrocyte sedimentation rate (ESR) (18.9 mm/h, P < 0.01), and platelets (86.8 × 10

conclusionESR and CRP are helpful preliminary investigations, especially in identifying low-risk patients, but their specificity is limited. Smaller centers had a higher proportion of biopsies with sub-optimal length. Considering the importance of biopsy length for TAB diagnostic value, reviewing biopsy data may assist services in developing improvement strategies.

Indexed as

Giant Cell ArteritisAgedAustraliaBiomarkersBiopsyC-Reactive ProteinFemaleHumansMaleRetrospective StudiesTemporal ArteriesWestern AustraliaBiomarkersC-Reactive ProteinbiopsyC-reactive proteinepidemiologyerythrocyte sedimentation rategiant cell arteritisinflammatory markers

Identifiers

PMID36401819
PMCPMC10098702
OpenAlexW4309409242

What OpenQuestion holds

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LicenceCC BY
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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.