Improving identification of idiopathic intracranial hypertension patients in Swedish patient register.

Abstract

Idiopathic intracranial hypertension (IIH) is often misdiagnosed. This can cause problems if conducting register-based studies. The study purpose was to produce algorithms that better identify patients with correct diagnosis of IIH in the Swedish National Patient Register (NPR). Patients with ICD-10 code G93.2 for IIH registered in the NPR (2006-2013, Stockholm County) were included and diagnosis validated by medical record reviews. Patients were randomized into two groups: one used to produce the algorithm (n=105) and one for validation (n=102). We tested variables possible to extract from registries and used forward stepwise logistic regression which provided a predicted probability of correct diagnosis for each patient. We included 207 patients of which 135 had confirmed IIH. This gave a positive predictive value of 65.2% (CI: 58.4-71.4). The algorithm produced with variables extracted from registries, that is, age, number of times with diagnosis code G93.2 recorded (>2 times), and acetazolamide treatment, predicted the diagnosis correctly 88.2% (CI: 80.3-93.3) of the time. Excluding treatment data from the algorithm did not change the prediction notably, 86.3% (CI: 78.1-91.7). We produced two algorithms that with improved accuracy predict whether an IIH diagnosis in the NPR is correct. This can be a useful tool when performing register-based studies.