What is it about?
Background: Giant cell arteritis (GCA) is an autoimmune inflammation of the blood vessels in the elderly. GCA can be a difficult diagnosis especially when it does not present with typical symptoms, signs and abnormal bloodwork. Temporal artery biopsy is the conventional standard confirmatory test for giant cell arteritis (GCA), but is an invasive procedure. Ultrasound and MRI are other methods to investigate GCA. What we did: Mathematical prediction "formulas" for GCA were made using ten variables: age, gender, new onset headache, jaw muscle discomfort with chewing, temporal artery tenderness or pulselessness, vision loss, double vision, erythrocyte sedimentation rate, C-reactive protein and platelet levels. Using the data from 1,201 patients in whom the result of the biopsy was known, we developed a calculator that can estimate the risk of GCA prior to temporal artery biopsy, ultrasound or MRI. The link to the calculator is https://goo.gl/THCnuU
Photo by Josh Riemer on Unsplash
Why is it important?
Humans have difficulty assigning appropriate weights ("significance") to multiple patient variables. Although no mathematical model is infallible, the models can objectively determine the probability score for GCA with more accuracy than most clinicians. In addition to the pretest calculator there are posttest probability tables for ultrasound, MRI and a negative temporal artery biopsy.
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This page is a summary of: Neural network and logistic regression diagnostic prediction models for giant cell arteritis: development and validation, Clinical Ophthalmology, February 2019, Dove Medical Press,
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