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

DOI

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.2020.3050KEY 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.

Date Submitted: 2021-11-25

Modified: 2020-04-23

Identifier
DOI https://doi.org/10.17026/dans-xvs-b7sa
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-xvs-b7sa
Provenance
Creator K.S.M. van der Geest ORCID logo
Publisher DANS Data Station Life Sciences
Contributor K.S.M. van der Geest; M. Sandovici (University of Groningen, University Medical Center Groningen); E. Brouwer (University of Groningen, University Medical Center Groningen); S.L. Mackie (University of Leeds, Leeds Teaching Hospitals NHS)
Publication Year 2021
Rights CC-BY-NC-4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by-nc/4.0
OpenAccess true
Contact K.S.M. van der Geest (University of Groningen, University Medical Center Groningen)
Representation
Resource Type Dataset
Format text/csv; application/x-stata-14; application/zip; application/vnd.oasis.opendocument.spreadsheet
Size 21151; 36707; 26526; 10526
Version 2.0
Discipline Life Sciences; Medicine