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DIAGNOSTIC DELAY FOR GIANT CELL ARTERITIS (GCA). A SYSTEMATIC REVIEW AND META-ANALYSIS

Prior, J. A.; Ranjbar, H.; Belcher, J.; Mackie, S.; Mallen, C. D.

Authors

H. Ranjbar

S. Mackie



Abstract

Background The diagnosis of giant cell arteritis (GCA) remains difficult, with patients often presenting with non-specific and atypical symptoms. Such ambiguity can lead to delays in the diagnosis of GCA, which in-turn may result in the patient experiencing preventable and life-altering outcomes, including blindness. Despite the seriousness of such diagnostic delay, the extent of this, though frequently highlighted, has seldom been the primary focus of GCA research. Without a clear understanding of the extent to which GCA diagnosis is delayed, it is difficult to quantify the current problem and how this may then impact on patient outcomes.

Objectives To determine the average time-period between the onset of GCA symptoms and receiving a GCA diagnosis.

Methods We conducted a systematic review and meta-analysis to identify research literature which has examined diagnostic delay of GCA and to determine the extent of this delay. Literature searches were conducted in the following bibliometric databases; MEDLINE, EMBASE, CINAHL, PsycInfo and ISI web of knowledge. A single reviewer (HR) initially performed a title screen; abstracts were then reviewed by two reviewers (HR & JP) and finally, two reviewers (JP & CM) assessed the remaining articles in full. Final article selection was based on pre-specified inclusion criteria and from these data on a multitude of factors was extracted. The primary outcome of interest was the “average number of weeks between onset of GCA symptoms and GCA diagnosis”, with other extracted data including; lead author, year of publication, sample size, gender, age, country, healthcare setting, method of GCA diagnosis and the definition of diagnostic delay. Where diagnostic delay was reported as “days” or “months”, data were converted to “weeks” to provide a standardised dataset for analysis. Standard deviations were also converted to standard errors (SE) for use in a meta-analysis. Random-effects meta-analysis was used to report the mean number of weeks (95% confidence interval (CI)) between symptom onset and GCA diagnosis.

Results 4,128 articles were initially identified, 185 were reviewed in full and 34 articles were included in the final systematic review. Of these, the average age ranged from 65.2 to 81.6 years and GCA samples from 31 articles were recruited from secondary care. GCA diagnosis was defined by a positive temporal artery biopsy in 25 articles, using the 1990 ACR criteria in 4 articles, with the remaining articles either using clinical judgement or not providing a definition. Delay was determined by the article reporting “how many days, weeks or months had occurred between GCA symptom onset and receiving a diagnosis of GCA”. 16 articles were included in the meta-analysis, resulting in a mean number of weeks between symptom onset and GCA diagnosis of 8.87 (95% CI 6.4 to 11.3) (I2 =95.8%, p<0.001).

Conclusions On average, patients experience approximately a 9-week delay between the onset of their symptoms and receiving a diagnosis of GCA. The reasons for this are yet to be understood, but could provide important insight and inform future strategies to improve outcomes for patients. Our research provides the current benchmark for diagnostic delay of GCA for which future efforts to reduce this problem can be measured against.

Journal Article Type Conference Paper
Online Publication Date Jul 15, 2016
Publication Date 2016-06
Deposit Date Aug 25, 2023
Journal ANNALS OF THE RHEUMATIC DISEASES
Print ISSN 0003-4967
Electronic ISSN 1468-2060
Publisher BMJ Publishing Group
Peer Reviewed Peer Reviewed
Volume 75
Issue S2
Pages 1092-1092
DOI https://doi.org/10.1136/annrheumdis-2016-eular.2639