Dataset belonging to 'Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis'

This dataset contains data underlying Table 2 and Table 3 in the following study:

van der Geest KSM, Sandovici M, Brouwer E, Mackie SL. Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis. JAMA Intern Med. 2020;180(10):1295–1304. doi:10.1001/jamainternmed.2020.3050

KEY POINTS OF THE AFOREMENTIONED STUDY: Question: In patients with suspected giant cell arteritis, which clinical and laboratory findings can help to identify the disease?

Findings: This systematic review and meta-analysis of 68 unique diagnostic cohort studies (14 037 unique patients) identified combinations of symptoms, physical signs, and laboratory tests that were informative with regard to the presence or absence of giant cell arteritis, but no single feature taken alone. Headache and scalp tenderness were poorly informative in this population.

Meaning: These findings suggest that in patients with suspected giant cell arteritis, no single clinical or laboratory feature is sufficient to rule in or rule out the disease; therefore, additional investigations (vascular imaging and/or temporal artery biopsy) are required.

Identifier
DOI https://doi.org/10.17026/dans-xvs-b7sa
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-8t-6tb6
Related Identifier https://doi.org/10.1001/jamainternmed.2020.3050
Related Identifier https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2769372?utm_campaign=articlePDF&utm_medium=articlePDFlink&utm_source=articlePDF&utm_content=jamainternmed.2020.3050
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:228409
Provenance
Creator van der Geest, K.S.M. ORCID logo
Publisher Data Archiving and Networked Services (DANS)
Contributor Sandovici, M.; Brouwer, E.; Mackie, S.L.; van der Geest, K.S.M.; MD PhD K.S.M. van der Geest (University of Groningen, University Medical Center Groningen); MD PhD M. Sandovici (University of Groningen, University Medical Center Groningen); MD PhD E. Brouwer (University of Groningen, University Medical Center Groningen); MD PhD S.L. Mackie (University of Leeds, Leeds Teaching Hospitals NHS)
Publication Year 2021
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/licenses/by-nc/4.0/; http://creativecommons.org/licenses/by-nc/4.0/
OpenAccess true
Representation
Language English
Resource Type Dataset
Format Stata Dataset (.dta); Microsoft Excel (.csv); application/x-cmdi+xml
Discipline Life Sciences; Medicine