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

Mie Micheelsen Jensen; Stine Munk Hald; Line Marie Buch Kristensen; Nils Jensen Boe; Frederik Severin Gråe Harbo; David Gaist

doi:10.2147/CLEP.S333624

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

Clin Epidemiol. 2021 Oct 9:13:949-958. doi: 10.2147/CLEP.S333624. eCollection 2021.

Authors

Mie Micheelsen Jensen¹, Stine Munk Hald^{1

2}, Line Marie Buch Kristensen¹, Nils Jensen Boe^{1

2}, Frederik Severin Gråe Harbo³, David Gaist^{1

2

4}

Affiliations

¹ Department of Neurology, Odense University Hospital, Odense, Denmark.
² Neurology Research Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
³ Department of Radiology, Odense University Hospital, Odense, Denmark.
⁴ Open Patient Data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark.

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.

Keywords: epidemiology; intracerebral hemorrhage; recurrent stroke; register-based research; stroke; validity.

Grants and funding

The project received funding from the Novo Nordisk Foundation (grant no. NNF20OC0064637). The funding source had no role in the study design; the collection, analysis, and interpretation of data; the writing of the article; or the decision to submit the article for publication.