Trial reportPloS one2020
Development of stroke identification algorithm for claims data using the multicenter stroke registry database.
Trial report in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Risk of incident stroke and heart disease subtypes in a nationwide cohort of Korean radiation workers.Scandinavian journal of work, environment & health · 2025Article
- Accuracy of posthospitalization stroke detection following carotid revascularization in Medicare claims.Journal of vascular surgery · 2025Article
- Developing a national surveillance system for stroke and acute myocardial infarction using claims data in the Republic of Korea: a retrospective study.Osong public health and research perspectives · 2024Article
- Use of machine learning techniques for identifying ischemic stroke instead of the rule-based methods: a nationwide population-based study.European journal of medical research · 2024Article
- Incidence and case fatality of stroke in Korea, 2011-2020.Epidemiology and health · 2024Article
- Secondary use of routinely collected administrative health data for epidemiologic research: Answering research questions using data collected for a different purpose.International journal of population data science · 2024Article
- Network analysis of stroke systems of care in Korea.BMJ neurology open · 2024Article
- Weekend effect on 30-day mortality for ischemic and hemorrhagic stroke analyzed using severity index and staffing level.PloS one · 2023Article
- Analysis of medical service utilization for post-stroke sequelae in Korea between 2016 and 2018: a cross-sectional study.Scientific reports · 2022Observational
- Five-Year Risk of Acute Myocardial Infarction After Acute Ischemic Stroke in Korea.Journal of the American Heart Association · 2021Observational
- Incidence, Risk Factors, and Prediction of Myocardial Infarction and Stroke in Farmers: A Korean Nationwide Population-based Study.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2020Article
- Performance of ICD-10-CM Diagnosis Codes for Identifying Acute Ischemic Stroke in a National Health Insurance Claims Database.Clinical epidemiology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
35 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIdentifying 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.
methodsFrom 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.
resultsAltogether, 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.
conclusionsOur stroke identification algorithm may be useful to grasp stroke burden in Korea. However, further efforts to refine the algorithm are necessary.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.