Validity of Simple Algorithms to Identify Recurrence of Intracerebral Hemorrhage in Two Danish Nationwide Registries

Abstract

Purpose Danish registries could be an attractive resource for studies of recurrent intracerebral hemorrhage (re-ICH). We developed and validated algorithms to identify re-ICH in the Danish Stroke Registry (DSR) and the Danish National Patient Registry (DNPR). Patients and Methods Using multiple sources, we followed-up an inception cohort with verified first-ever spontaneous ICH (n = 2528) for their first re-ICH in 2009–2018 (study period). We used verified cases of re-ICH (n = 124) as the gold standard to assess the performance of register-based algorithms for identifying re-ICH. For each cohort member, we traced events of re-ICH (ICD-10-code I61) in the study period according to DSR and DNPR, respectively. For each registry, we tested algorithms with a blanking period (BP) – ie, a period immediately following the index ICH during which outcome events were ignored – of varying length (7 days–360 days). The algorithm with the shortest BP that returned a positive predictive value (PPV) of ≥80% was considered optimal. We also calculated negative predictive value (NPV), sensitivity, and specificity of each algorithm and [95% confidence intervals] for all proportions. Results The optimal algorithm for DSR (BP 30 days) had a PPV of 89.5% [82.2–94.0], NPV 98.8% [98.2–99.1], sensitivity 75.8% [67.6–82.5], and specificity 99.5% [99.2–99.7]. The optimal algorithm for DNPR (BP 120 days) had a PPV of 80.6% [71.7–87.2], NPV 98.1% [97.5–98.6], sensitivity 63.7% [55.0–71.6], and specificity 99.2% [98.8–99.5]. Conclusion Simple algorithms accurately identified re-ICH in DSR and DNPR. Compared with DNPR, DSR achieved higher PPV and sensitivity with a shorter BP. The proposed algorithms could facilitate valid use of DSR and DNPR for studies of re-ICH.