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BACKGROUND:Identifying acute ischemic stroke (AIS) among potential stroke cases is crucial for stroke research based on claims data. However, the accuracy of using the diagnostic codes of the International Classification of Diseases 10th revision was less than expected. METHODS:From the National Health Insurance Service (NHIS) claims data, stroke cases admitted to the hospitals participating in the multicenter stroke registry (Clinical Research Collaboration for Stroke in Korea, CRCS-K) during the study period with principal or additional diagnosis codes of I60-I64 on the 10th revision of International Classification of Diseases were extracted. The datasets were randomly divided into development and validation sets with a ratio of 7:3. A stroke identification algorithm using the claims data was developed and validated through the linkage between the extracted datasets and the registry database. RESULTS:Altogether, 40,443 potential cases were extracted from the NHIS claims data, of which 31.7% were certified as AIS through linkage with the CRCS-K database. We selected 17 key identifiers from the claims data and developed 37 conditions through combinations of those key identifiers. The key identifiers comprised brain CT, MRI, use of tissue plasminogen activator, endovascular treatment, carotid endarterectomy or stenting, antithrombotics, anticoagulants, etc. The sensitivity, specificity, and diagnostic accuracy of the algorithm were 81.2%, 82.9%, and 82.4% in the development set, and 80.2%, 82.0%, and 81.4% in the validation set, respectively. CONCLUSIONS:Our stroke identification algorithm may be useful to grasp stroke burden in Korea. However, further efforts to refine the algorithm are necessary.

Measuring blood pressure (BP) at home and remote monitoring can improve the patient's adherence to BP control and vascular outcomes. This study evaluated the feasibility of a trial regarding the effects of an intensive mobile BP management strategy versus usual care in acute ischemic stroke patients. A feasibility-testing, randomized, open-labeled controlled trial was conducted. Remote BP measurement, data transmission, storage, and centralized monitoring system were organized through a Bluetooth-equipped sphygmomanometer paired to the participants' smartphones. Participants were randomized equally into intensive management (behavioral intensification to measure BP at home by texting, direct telephone call, or breakthrough visit) and control (usual care) groups. The primary feasibility outcomes were: 1) recruitment time for the pre-specified number of participants, 2) retention of participants, 3) frequency of breakthrough visit calls, 4) response to breakthrough visit call, and 5) proportions satisfying BP measurement criteria. Sixty participants were randomly assigned to the intensive management (n = 31) and control (n = 29) groups, of which 57 participants were included in the primary analysis with comparable baseline characteristics. Recruitment time from the first to the last participant was 350 days, and 95% of randomized participants completed the final visit (intensive, 94%; control, 98%). Eight breakthrough visit calls were made to 7 participants (23%), with complete and immediate responses within 3 ± 4 days. The median of half-day blocks fulfilling the BP measurement criteria per patient were 91% in the intensive group and 83% in the control group (difference, 12.2; 95% confidence interval, 2.2-22.2). No adverse events related to the trial procedures were reported. The intensive monitoring, including remote BP measurement, data transfer, and centralized monitoring system, engaged with behavioral intensification was feasible if the patients complied with the intervention. However, the device utilized would need further improvement prior to a large trial.