Effect of Education on Discriminability of Montreal Cognitive Assessment Compared to Mini-Mental State Examination.

Background and Purpose: The Montreal Cognitive Assessment (MoCA) has been known as a screening test for detecting mild cognitive impairment (MCI) better than Mini-Mental State Examination (MMSE). However, in previous domestic studies, no significant difference was found in the discriminability between MoCA and MMSE. Researchers have suggested that this might be because older Koreans are less educated than older Westerners. This study was conducted to examine the effect of education on the discriminability of MoCA compared to the MMSE. Methods: Participants were 123 cognitively normal elderly, 118 with vascular MCI, 108 with amnestic MCI, 121 with vascular dementia, and 113 with dementia of the Alzheimer's type. The Korean-MoCA (K-MoCA) and Korean-MMSE (K-MMSE) were administered. Multiple regression analyses and receiver operating characteristic (ROC) curve analyses were performed. Results: In all participants, education significantly affected both K-MoCA and K-MMSE scores along with age. The effect of education was re-examined by subgroup analysis after dividing subjects according to the level of education. Effect of education on K-MoCA and K-MMSE was only shown in the group with <9 years of education. ROC curve analyses revealed that the discriminability of K-MoCA to differentiate between vascular MCI and normal elderly was significantly higher than that of K-MMSE. When re-examining subgroups divided by education level, however, this higher discriminability of K-MoCA disappeared in the group with <9 years of education. Conclusions: These results indicate no difference in discriminating cognitive deficits between K-MoCA and K-MMSE in Korean elderly with <9 years of education.

Validity of the Montreal Cognitive Assessment (MoCA) Index Scores: a Comparison with the Cognitive Domain Scores of the Seoul Neuropsychological Screening Battery (SNSB).

BACKGROUND AND PURPOSE: A new approach was proposed to score the Montreal Cognitive Assessment (MoCA) index scores for 6 cognitive domains: orientation (OIS), attention (AIS), language (LIS), visuospatial function (VIS), memory (MIS), and executive function (EIS). This study investigated whether the MoCA index scores represent the functions of each cognitive domain by examining the correlations with the corresponding cognitive domain scores derived from conventional neuropsychological tests included in the Seoul Neuropsychological Screening Battery, 2nd Edition (SNSB-II). METHODS: The participants were 104 amnestic mild cognitive impairment (aMCI), 74 vascular mild cognitive impairment (VaMCI), 73 dementia of the Alzheimer's type (DAT), and 41 vascular dementia (VaD) patients. All participants were administered the Korean-MoCA and SNSB-II. RESULTS: Like the MoCA total score, the MoCA-OIS, MoCA-VIS, and MoCA-MIS showed differences between aMCI and AD groups and between VaMCI and VaD groups. The MoCA-AIS, MoCA-LIS, and MoCA-EIS showed significant differences between VaMCI and VaD groups, but no difference between aMCI and DAT groups. In the aMCI and VaMCI groups, all index scores of the MoCA showed significant correlations with the corresponding cognitive domain scores of the SNSB-II. Except for MoCA-MIS, the MoCA-AIS, MoCA-LIS, MoCA-VIS, and MoCA-EIS also showed significant correlations with the corresponding domain scores of the SNSB-II in the DAT and VaD groups. CONCLUSIONS: These results indicate that all MoCA index scores, except for MoCA-MIS, which does not reflect the severity of memory impairment in dementia patients, provide highly valid information on the function of each cognitive domain in patients with mild cognitive impairment and dementia.

Three-month modified Rankin Scale as a determinant of 5-year cumulative costs after ischemic stroke: An analysis of 11,136 patients in Korea.

OBJECTIVE: Stroke is a devastating and costly disease; however, there is a paucity of information on long-term costs and on how they differ according to 3-month modified Rankin scale (mRS) score, which is a primary outcome variable in acute stroke intervention trials. METHODS: We analyzed a prospective multicenter stroke registry (Clinical Research Collaboration for Stroke in Korea) database through linkage with claims data from the National Health Insurance Service with follow-up to December 2016. Healthcare expenditures were converted into daily cost individually, and annual and cumulative costs up to 5 years were estimated and compared according to the 3-month mRS score. RESULTS: Between January 2011 and November 2013, 11,136 patients were enrolled in the study. The mean age was 68 years, and 58% were men. The median follow-up period was 3.9 years (range 0-5 years). Mean cumulative cost over 5 years was $117,576 (US dollars [USD]); the cost in the first year after stroke was the highest ($38,152 USD), which increased markedly from the cost a year before stroke ($8,718 USD). The mean 5-year cumulative costs differed significantly according to the 3-month mRS score (p < 0.001); the costs for a 3-month mRS score of 0 or 5 were $53,578 and $257,486 USD, respectively. Three-month mRS score was an independent determinant of long-term costs after stroke. CONCLUSIONS: We show that 3-month mRS score plays an important role in the prediction of long-term costs after stroke. Such estimates relating to 3-month mRS categories may be valuable when undertaking health economic evaluations related to stroke care.

Development of stroke identification algorithm for claims data using the multicenter stroke registry database.

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.

Building Linked Big Data for Stroke in Korea: Linkage of Stroke Registry and National Health Insurance Claims Data.

BACKGROUND: Linkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases. METHODS: Acute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006-2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA. RESULTS: Of 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1-7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable. CONCLUSION: We could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.

Years of optimum health lost due to complications after acute ischemic stroke: disability-adjusted life-years analysis.

BACKGROUND AND PURPOSE: Complications after stroke increase disability or death. The disability-adjusted life-year (DALY) metric, developed by the World Health Organization to measure the global burden of disease, integrates both mortality and disability. Widely used in population-level data analyses, it has not been applied to individual patient-level data captured in outcome registries. METHODS: We analyzed patient-level data from the outcome registry of 1254 consecutive patients with acute ischemic stroke enrolled between September 1, 2004, and August 31, 2005, in South Korea. For each subject, we calculated DALY lost due to the qualifying stroke and then analyzed additional DALY lost due to complications after stroke. RESULTS: For 1233 patients with available 3-month outcomes, the average DALY lost due to the index stroke was 3.82 (95% CI, 3.68 to 3.96). Any complications, neurological complications, and medical complications occurred in 34.0%, 20.8%, and 24.0%, respectively. The additional DALYs lost associated with any, neurological, and medical complications were 2.11 (95% CI, 1.78 to 2.44), 2.15 (95% CI, 1.72 to 2.59), and 1.99 (95% CI, 1.59 to 2.40), respectively. Patients with 1 complication had 1.52 (95% CI, 1.15 to 1.89) additional DALY lost, and those with >or=2 complications had 2.69 (95% CI, 2.18 to 3.20) additional DALY lost. CONCLUSIONS: Early poststroke complications deprive patients of approximately 2 years of optimum health. Greater numbers of complications are associated with greater loss of healthy life-years. DALY analysis quantifies the burden of poststroke complications with a uniform metric potentially useful for health system planners.