Validity of simple algorithms to identify recurrence of intracerebral hemorrhage in two danish nationwide registries

Purpose: Danish registries could be an attractive resource for studies of recurrent intracer-ebral 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.