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Yum KS, Chung JW, Ha SY, Park KY, Shin DI, Park HK, Cho YJ, Hong KS, Kim JG, Lee SJ, Kim JT, Seo WK, Bang OY, Kim GM, Lee M, Kim D, Sunwoo L, Bae HJ, Ryu WS, Kim BJ. A multicenter validation and calibration of automated software package for detecting anterior circulation large vessel occlusion on CT angiography. BMC Neurol 2025; 25:100. [PMID: 40065263 PMCID: PMC11892136 DOI: 10.1186/s12883-025-04107-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Accepted: 02/25/2025] [Indexed: 03/14/2025] Open
Abstract
PURPOSE To validate JLK-LVO, a software detecting large vessel occlusion (LVO) on computed tomography angiography (CTA), within a multicenter dataset. METHODS From 2021 to 2023, we enrolled patients with ischemic stroke who underwent CTA within 24-hour of onset at six university hospitals for validation and calibration datasets and at another university hospital for an independent dataset for testing model calibration. The diagnostic performance was evaluated using area under the curve (AUC), sensitivity, and specificity across the entire study population and specifically in patients with isolated middle cerebral artery (MCA)-M2 occlusion. We calibrated LVO probabilities using logistic regression and by grouping LVO probabilities based on observed frequency. RESULTS After excluding 168 patients, 796 remained; the mean (SD) age was 68.9 (13.7) years, and 57.7% were men. LVO was present in 193 (24.3%) of patients, and the median interval from last-known-well to CTA was 5.7 h (IQR 2.5-12.1 h). The software achieved an AUC of 0.944 (95% CI 0.926-0.960), with a sensitivity of 89.6% (84.5-93.6%) and a specificity of 90.4% (87.7-92.6%). In isolated MCA-M2 occlusion, the AUROC was 0.880 (95% CI 0.824-0.921). Due to sparse data between 20 and 60% of LVO probabilities, recategorization into unlikely (0-20% LVO scores), less likely (20-60%), possible (60-90%), and suggestive (90-100%) provided a reliable estimation of LVO compared with mathematical calibration. The category of LVO probabilities was associated with follow-up infarct volumes and functional outcome. CONCLUSION In this multicenter study, we proved the clinical efficacy of the software in detecting LVO on CTA.
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Affiliation(s)
- Kyu Sun Yum
- Department of Neurology, College of Medicine, Chungbuk National University Hospital, Chungbuk National University, Cheongju, Republic of Korea
| | - Jong-Won Chung
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Sue Young Ha
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kwang-Yeol Park
- Department of Neurology, Chung-Ang University College of Medicine, Chung-Ang University Hospital, Seoul, Republic of Korea
| | - Dong-Ick Shin
- Department of Neurology, College of Medicine, Chungbuk National University Hospital, Chungbuk National University, Cheongju, Republic of Korea
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Jae Guk Kim
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Soo Joo Lee
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Woo-Keun Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Oh Young Bang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Gyeong-Moon Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Myungjae Lee
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea
| | - Dongmin Kim
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea
| | - Leonard Sunwoo
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Seongnam, Republic of Korea
- Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea.
| | - Beom Joon Kim
- Department of Neurology, Seoul National University College of Medicine, Seongnam, Republic of Korea.
- Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
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Kim JG, Ha SY, Kang YR, Hong H, Kim D, Lee M, Sunwoo L, Ryu WS, Kim JT. Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study. J Neurointerv Surg 2024:jnis-2024-022254. [PMID: 39304193 DOI: 10.1136/jnis-2024-022254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Accepted: 09/06/2024] [Indexed: 09/22/2024]
Abstract
BACKGROUND To evaluate the stand-alone efficacy and improvements in diagnostic accuracy of early-career physicians of the artificial intelligence (AI) software to detect large vessel occlusion (LVO) in CT angiography (CTA). METHODS This multicenter study included 595 ischemic stroke patients from January 2021 to September 2023. Standard references and LVO locations were determined by consensus among three experts. The efficacy of the AI software was benchmarked against standard references, and its impact on the diagnostic accuracy of four residents involved in stroke care was assessed. The area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity of the software and readers with versus without AI assistance were calculated. RESULTS Among the 595 patients (mean age 68.5±13.4 years, 56% male), 275 (46.2%) had LVO. The median time interval from the last known well time to the CTA was 46.0 hours (IQR 11.8-64.4). For LVO detection, the software demonstrated a sensitivity of 0.858 (95% CI 0.811 to 0.897) and a specificity of 0.969 (95% CI 0.943 to 0.985). In subjects whose symptom onset to imaging was within 24 hours (n=195), the software exhibited an AUROC of 0.973 (95% CI 0.939 to 0.991), a sensitivity of 0.890 (95% CI 0.817 to 0.936), and a specificity of 0.965 (95% CI 0.902 to 0.991). Reading with AI assistance improved sensitivity by 4.0% (2.17 to 5.84%) and AUROC by 0.024 (0.015 to 0.033) (all P<0.001) compared with readings without AI assistance. CONCLUSIONS The AI software demonstrated a high detection rate for LVO. In addition, the software improved diagnostic accuracy of early-career physicians in detecting LVO, streamlining stroke workflow in the emergency room.
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Affiliation(s)
- Jae Guk Kim
- Department of Neurology, Daejeon Eulji University Hospital, Daejeon, Daejeon, Korea
| | - Sue Young Ha
- Artificial Intelligence Research Center, JLK Inc, Seoul, Korea
| | - You-Ri Kang
- Department of Neurology, Chonnam National University Medical School, Gwangju, Korea
| | - Hotak Hong
- Artificial Intelligence Research Center, JLK Inc, Seoul, Korea
| | - Dongmin Kim
- Artificial Intelligence Research Center, JLK Inc, Seoul, Korea
| | - Myungjae Lee
- Artificial Intelligence Research Center, JLK Inc, Seoul, Korea
| | - Leonard Sunwoo
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc, Seoul, Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Medical School, Gwangju, Korea
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Han JH, Ha SY, Lee H, Park GH, Hong H, Kim D, Kim JG, Kim JT, Sunwoo L, Kim CK, Ryu WS. Automated identification of thrombectomy amenable vessel occlusion on computed tomography angiography using deep learning. Front Neurol 2024; 15:1442025. [PMID: 39119560 PMCID: PMC11306064 DOI: 10.3389/fneur.2024.1442025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Accepted: 07/10/2024] [Indexed: 08/10/2024] Open
Abstract
Introduction We developed and externally validated a fully automated algorithm using deep learning to detect large vessel occlusion (LVO) in computed tomography angiography (CTA). Method A total of 2,045 patients with acute ischemic stroke who underwent CTA were included in the development of our model. We validated the algorithm using two separate external datasets: one with 64 patients (external 1) and another with 313 patients (external 2), with ischemic stroke. In the context of current clinical practice, thrombectomy amenable vessel occlusion (TAVO) was defined as an occlusion in the intracranial internal carotid artery (ICA), or in the M1 or M2 segment of the middle cerebral artery (MCA). We employed the U-Net for vessel segmentation on the maximum intensity projection images, followed by the application of the EfficientNetV2 to predict TAVO. The algorithm's diagnostic performance was evaluated by calculating the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results The mean age in the training and validation dataset was 68.7 ± 12.6; 56.3% of participants were men, and 18.0% had TAVO. The algorithm achieved AUC of 0.950 (95% CI, 0.915-0.971) in the internal test. For the external datasets 1 and 2, the AUCs were 0.970 (0.897-0.997) and 0.971 (0.924-0.990), respectively. With a fixed sensitivity of 0.900, the specificities and PPVs for the internal test, external test 1, and external test 2 were 0.891, 0.796, and 0.930, and 0.665, 0.583, and 0.667, respectively. The algorithm demonstrated a sensitivity and specificity of approximately 0.95 in both internal and external datasets, specifically for cases involving intracranial ICA or M1-MCA occlusion. However, the diagnostic performance was somewhat reduced for isolated M2-MCA occlusion; the AUC for the internal and combined external datasets were 0.903 (0.812-0.944) and 0.916 (0.816-0.963), respectively. Conclusion We developed and externally validated a fully automated algorithm that identifies TAVO. Further research is needed to evaluate its effectiveness in real-world clinical settings. This validated algorithm has the potential to assist early-career physicians, thereby streamlining the treatment process for patients who can benefit from endovascular treatment.
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Affiliation(s)
- Jung Hoon Han
- Department of Neurology, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Sue Young Ha
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Hoyeon Lee
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Gi-Hun Park
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Hotak Hong
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Dongmin Kim
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Jae Guk Kim
- Department of Neurology, Eulji University Hospital, Daejeon, Republic of Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Leonard Sunwoo
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Chi Kyung Kim
- Department of Neurology, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
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Chung I, Bae HJ, Kim BJ, Kim JY, Han MK, Kim J, Jung C, Kang J. Interactive Direct Interhospital Transfer Network System for Acute Stroke in South Korea. J Clin Neurol 2023; 19:125-130. [PMID: 36647229 PMCID: PMC9982181 DOI: 10.3988/jcn.2022.0158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/30/2022] [Accepted: 07/30/2022] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND AND PURPOSE Interhospital transfer is an essential practical component of regional stroke care systems. To establish an effective stroke transfer network in South Korea, an interactive transfer system was constructed, and its workflow metrics were observed. METHODS In March 2019, a direct transfer system between primary stroke hospitals (PSHs) and comprehensive regional stroke centers (CSCs) was established to standardize the clinical pathway of imaging, recanalization therapy, transfer decisions, and exclusive transfer linkage systems in the two types of centers. In an active case, the time metrics from arrival at PSH ("door") to imaging was measured, and intravenous thrombolysis (IVT) and endovascular treatment (EVT) were used to assess the differences in clinical situations. RESULTS The direct transfer system was used by 27 patients. They stayed at the PSH for a median duration of 72 min (interquartile range [IQR], 38-114 min), with a median times of 15 and 58 min for imaging and subsequent processing, respectively. The door-to-needle median times of subjects treated with IVT at PSHs (n=5) and CSCs (n=2) were 21 min (IQR, 20.0-22.0 min) and 137.5 min (IQR, 125.3-149.8 min), respectively. EVT was performed on seven subjects (25.9%) at CSCs, which took a median duration of 175 min; 77 min at the PSH, 48 min for transportation, and 50 min at the CSC. Before EVT, bridging IVT at the PSH did not significantly affect the door-to-puncture time (127 min vs. 143.5 min, p=0.86). CONCLUSIONS The direct and interactive transfer system is feasible in real-world practice in South Korea and presents merits in reducing the treatment delay by sharing information during transfer.
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Affiliation(s)
- Inyoung Chung
- Department of Neurology, H PLUS YANGJI Hospital, Seoul, Korea.,Department of Neurology, Gyeonggi Provincial Medical Center Icheon Hospital, Icheon, Korea
| | - Hee-Joon Bae
- Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University, Seongnam, Korea
| | - Beom Joon Kim
- Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University, Seongnam, Korea
| | - Jun Yup Kim
- Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University, Seongnam, Korea
| | - Moon-Ku Han
- Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University, Seongnam, Korea
| | - Jinhwi Kim
- Department of Emergency Medicine, Gyeonggi Provincial Medical Center Icheon Hospital, Icheon, Korea
| | - Cheolkyu Jung
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jihoon Kang
- Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University, Seongnam, Korea.
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Kim DH, Moon SJ, Lee J, Cha JK, Kim MH, Park JS, Ban B, Kang J, Kim BJ, Kim WS, Yoon CH, Lee H, Kim S, Kang EK, Her AY, Yoon CW, Rha JH, Woo SI, Lee WK, Jung HY, Lee JH, Park HS, Hwang YH, Kim K, Kim RB, Choi NC, Hwang J, Park HW, Park KS, Yi S, Cho JY, Kim NH, Choi KH, Kim J, Han JY, Choi JC, Kim SY, Choi JH, Kim J, Sohn MK, Choi SW, Shin DI, Lee SY, Bae JW, Lee KS, Bae HJ. Comparison of Factors Associated With Direct Versus Transferred-in Admission to Government-Designated Regional Centers Between Acute Ischemic Stroke and Myocardial Infarction in Korea. J Korean Med Sci 2022; 37:e305. [PMID: 36325609 PMCID: PMC9623032 DOI: 10.3346/jkms.2022.37.e305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 08/29/2022] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND There has been no comparison of the determinants of admission route between acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We examined whether factors associated with direct versus transferred-in admission to regional cardiocerebrovascular centers (RCVCs) differed between AIS and AMI. METHODS Using a nationwide RCVC registry, we identified consecutive patients presenting with AMI and AIS between July 2016 and December 2018. We explored factors associated with direct admission to RCVCs in patients with AIS and AMI and examined whether those associations differed between AIS and AMI, including interaction terms between each factor and disease type in multivariable models. To explore the influence of emergency medical service (EMS) paramedics on hospital selection, stratified analyses according to use of EMS were also performed. RESULTS Among the 17,897 and 8,927 AIS and AMI patients, 66.6% and 48.2% were directly admitted to RCVCs, respectively. Multivariable analysis showed that previous coronary heart disease, prehospital awareness, higher education level, and EMS use increased the odds of direct admission to RCVCs, but the odds ratio (OR) was different between AIS and AMI (for the first 3 factors, AMI > AIS; for EMS use, AMI < AIS). EMS use was the single most important factor for both AIS and AMI (OR, 4.72 vs. 3.90). Hypertension and hyperlipidemia increased, while living alone decreased the odds of direct admission only in AMI; additionally, age (65-74 years), previous stroke, and presentation during non-working hours increased the odds only in AIS. EMS use weakened the associations between direct admission and most factors in both AIS and AMI. CONCLUSIONS Various patient factors were differentially associated with direct admission to RCVCs between AIS and AMI. Public education for symptom awareness and use of EMS is essential in optimizing the transportation and hospitalization of patients with AMI and AIS.
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Affiliation(s)
- Dae-Hyun Kim
- Busan Regional Cardiocerebrovascular Disease Center, Dong-A University Hospital, Busan, Korea
| | - Seok-Joo Moon
- Department of Biostatistics, Korea University College of Medicine, Seoul, Korea
| | - Juneyoung Lee
- Department of Biostatistics, Korea University College of Medicine, Seoul, Korea
| | - Jae-Kwan Cha
- Busan Regional Cardiocerebrovascular Disease Center, Dong-A University Hospital, Busan, Korea
| | - Moo Hyun Kim
- Busan Regional Cardiocerebrovascular Disease Center, Dong-A University Hospital, Busan, Korea
| | - Jong-Sung Park
- Busan Regional Cardiocerebrovascular Disease Center, Dong-A University Hospital, Busan, Korea
| | - Byeolnim Ban
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jihoon Kang
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Beom Joon Kim
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Won-Seok Kim
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Chang-Hwan Yoon
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Heeyoung Lee
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Seongheon Kim
- Gangwon Regional Cardiocerebrovascular Disease Center, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Eun Kyoung Kang
- Gangwon Regional Cardiocerebrovascular Disease Center, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Ae-Young Her
- Gangwon Regional Cardiocerebrovascular Disease Center, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Cindy W Yoon
- Incheon Regional Cardiocerebrovascular Disease Center, Inha University College of Medicine, Incheon, Korea
| | - Joung-Ho Rha
- Incheon Regional Cardiocerebrovascular Disease Center, Inha University College of Medicine, Incheon, Korea
| | - Seong-Ill Woo
- Incheon Regional Cardiocerebrovascular Disease Center, Inha University College of Medicine, Incheon, Korea
| | - Won Kyung Lee
- Incheon Regional Cardiocerebrovascular Disease Center, Inha University College of Medicine, Incheon, Korea
| | - Han-Young Jung
- Incheon Regional Cardiocerebrovascular Disease Center, Inha University College of Medicine, Incheon, Korea
| | - Jang Hoon Lee
- Daegu-Gyeongbuk Regional Cardiocerebrovascular Disease Center, Kyungpook National University Hospital, Daegu, Korea
| | - Hun Sik Park
- Daegu-Gyeongbuk Regional Cardiocerebrovascular Disease Center, Kyungpook National University Hospital, Daegu, Korea
| | - Yang-Ha Hwang
- Daegu-Gyeongbuk Regional Cardiocerebrovascular Disease Center, Kyungpook National University Hospital, Daegu, Korea
| | - Keonyeop Kim
- Daegu-Gyeongbuk Regional Cardiocerebrovascular Disease Center, Kyungpook National University Hospital, Daegu, Korea
| | - Rock Bum Kim
- Gyeongnam Regional Cardiocerebrovascular Disease Center, Gyeongsang National University Hospital, Gyeongsang National University School of Medicine, Jinju, Korea
| | - Nack-Cheon Choi
- Gyeongnam Regional Cardiocerebrovascular Disease Center, Gyeongsang National University Hospital, Gyeongsang National University School of Medicine, Jinju, Korea
| | - Jinyong Hwang
- Gyeongnam Regional Cardiocerebrovascular Disease Center, Gyeongsang National University Hospital, Gyeongsang National University School of Medicine, Jinju, Korea
| | - Hyun-Woong Park
- Gyeongnam Regional Cardiocerebrovascular Disease Center, Gyeongsang National University Hospital, Gyeongsang National University School of Medicine, Jinju, Korea
| | - Ki Soo Park
- Gyeongnam Regional Cardiocerebrovascular Disease Center, Gyeongsang National University Hospital, Gyeongsang National University School of Medicine, Jinju, Korea
| | - SangHak Yi
- Jeonbuk Regional Cardiocerebrovascular Center, Wonkwang University Hospital, Iksan, Korea
| | - Jae Young Cho
- Jeonbuk Regional Cardiocerebrovascular Center, Wonkwang University Hospital, Iksan, Korea
| | - Nam-Ho Kim
- Jeonbuk Regional Cardiocerebrovascular Center, Wonkwang University Hospital, Iksan, Korea
| | - Kang-Ho Choi
- Gwangju-Jeonnam Regional Cardiocerebrovascular Disease Center, Chonnam National University Medical School and Hospital, Gwangju, Korea
| | - Juhan Kim
- Gwangju-Jeonnam Regional Cardiocerebrovascular Disease Center, Chonnam National University Medical School and Hospital, Gwangju, Korea
| | - Jae-Young Han
- Gwangju-Jeonnam Regional Cardiocerebrovascular Disease Center, Chonnam National University Medical School and Hospital, Gwangju, Korea
| | - Jay Chol Choi
- Jeju Regional Cardiocerebrovascular Disease Center, Jeju National University Hospital, Jeju, Korea
| | - Song-Yi Kim
- Jeju Regional Cardiocerebrovascular Disease Center, Jeju National University Hospital, Jeju, Korea
| | - Joon-Hyouk Choi
- Jeju Regional Cardiocerebrovascular Disease Center, Jeju National University Hospital, Jeju, Korea
| | - Jei Kim
- Daejeon-Chungnam Regional Cardiocerebrovascular Disease Center, Hospital and College of Medicine, Chungnam National University, Daejeon, Korea
| | - Min Kyun Sohn
- Daejeon-Chungnam Regional Cardiocerebrovascular Disease Center, Hospital and College of Medicine, Chungnam National University, Daejeon, Korea
| | - Si Wan Choi
- Daejeon-Chungnam Regional Cardiocerebrovascular Disease Center, Hospital and College of Medicine, Chungnam National University, Daejeon, Korea
| | - Dong-Ick Shin
- Chungbuk Regional Cardiocerebrovascular Disease Center, Chungbuk National University and Hospital, Cheongju, Korea
| | - Sang Yeub Lee
- Chungbuk Regional Cardiocerebrovascular Disease Center, Chungbuk National University and Hospital, Cheongju, Korea
| | - Jang-Whan Bae
- Chungbuk Regional Cardiocerebrovascular Disease Center, Chungbuk National University and Hospital, Cheongju, Korea
| | - Kun Sei Lee
- Department of Preventive Medicine, School of Medicine, Konkuk University, Seoul, Korea
| | - Hee-Joon Bae
- Gyeonggi Regional Cardiocerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
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Kim JY, Kang J, Kim BJ, Kim SE, Kim DY, Lee KJ, Park HK, Cho YJ, Park JM, Lee KB, Cha JK, Lee JS, Lee J, Yang KH, Hong OR, Shin JH, Park JH, Gorelick PB, Bae HJ. Annual Case Volume and One-Year Mortality for Endovascular Treatment in Acute Ischemic Stroke. J Korean Med Sci 2022; 37:e270. [PMID: 36123959 PMCID: PMC9485065 DOI: 10.3346/jkms.2022.37.e270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 07/21/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The association between endovascular treatment (EVT) case volume per hospital and clinical outcomes has been reported, but the exact volume threshold has not been determined. This study aimed to examine the case volume threshold in this context. METHODS National audit data on the quality of acute stroke care in patients admitted via emergency department, within 7 days of onset, in hospitals that treated ≥ 10 stroke cases during the audit period were analyzed. Ischemic stroke cases treated with EVT during the last three audits (2013, 2014, and 2016) were selected for the analysis. Annual EVT case volume per hospital was estimated and analyzed as a continuous and a categorical variable (in quartiles). The primary outcome measure was 1-year mortality as a surrogate of 3-month functional outcome. As post-hoc sensitivity analysis, replication of the study results was examined using the 2018 audit data. RESULTS We analyzed 1,746 ischemic stroke cases treated with EVT in 120 acute care hospitals. The median annual EVT case volume was 12.0 cases per hospital, and mortality rates at 1 month, 3 months, and 1 year were 12.7%, 16.6%, and 23.3%, respectively. Q3 and Q4 had 33% lower odds of 1-year mortality than Q1. Adjustments were made for predetermined confounders. Annual EVT case volume cut-off value for 1-year mortality was 15 cases per year (P < 0.02). The same cut-off value was replicated in the sensitivity analysis. CONCLUSION Annual EVT case volume was associated with 1-year mortality. The volume threshold per hospital was 15 cases per year.
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Affiliation(s)
- Jun Yup Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jihoon Kang
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Seong-Eun Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Do Yeon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Keon-Joo Lee
- Department of Neurology, Korea University Guro Hospital, Seoul, Korea
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu, Korea
| | - Kyung Bok Lee
- Department of Neurology, Soonchunhyang University Hospital, Soonchunhyang University College of Medicine, Seoul, Korea
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Dong-A University College of Medicine, Busan, Korea
| | - Ji Sung Lee
- Clinical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea
| | - Juneyoung Lee
- Department of Biostatistics, Korea University College of Medicine, Seoul, Korea
| | - Ki Hwa Yang
- Health Insurance Review and Assessment Service, Wonju, Korea
| | - Ock Ran Hong
- Health Insurance Review and Assessment Service, Wonju, Korea
| | - Ji Hyeon Shin
- Health Insurance Review and Assessment Service, Wonju, Korea
| | - Jung Hyun Park
- Department of Neurology, Gyeonggi Provincial Medical Center Icheon Hospital, Icheon, Korea
| | - Philip B Gorelick
- Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
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Kwon DH, Jang SH, Park H, Sohn SI, Hong JH. Emergency Cervical Carotid Artery Stenting After Intravenous Thrombolysis in Patients With Hyperacute Ischemic Stroke. J Korean Med Sci 2022; 37:e156. [PMID: 35578588 PMCID: PMC9110268 DOI: 10.3346/jkms.2022.37.e156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 04/15/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Intravenous recombinant tissue plasminogen activator (IV rtPA) is the mainstay of treatment for acute ischemic stroke to recanalize thrombosed intracranial vessels within 4.5 hours. Emergency carotid artery stenting for the treatment of acute stroke due to steno-occlusion of the proximal internal carotid artery (ICA) can improve symptoms, prevent neurological deterioration, and reduce recurrent stroke risk. The feasibility and safety of the combination therapy of IV rtPA and urgent carotid artery stenting have not been established. METHODS From November 2005 to October 2020, we retrospectively assessed patients who had undergone emergent carotid artery stenting after IV rtPA for hyperacute ischemic stroke due to steno-occlusive proximal ICA lesion. Hemorrhagic transformation, successful recanalization, modified Rankin Scale (mRS) score at 90 days, and stent patency at 3 and 12 months or longer were evaluated. Favorable outcome was defined as a 90-days mRS score of ≤ 2. RESULTS Nineteen patients with hyperacute stroke had undergone emergent carotid artery stenting after IV rtPA therapy. Their median age was 70 (67.5-73.5) years (94.7% men). Among 15 patients with an additional intracranial occlusion after flow restoration in the proximal ICA, a modified TICI grade ≥ 2b was achieved in 11 patients (73.3%). Hemorrhagic transformation occurred in five patients (26.3%); mortality rate was 5.7%. Eleven patients (57.9%) had favorable outcomes at 90 days. Stent patients (94.1%) maintained stent patency for ≥ 12 months. CONCLUSION We showed that emergent carotid artery stenting after IV rtPA therapy for hyperacute stroke caused by atherosclerotic proximal ICA steno-occlusion was feasible and safe.
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Affiliation(s)
- Doo Hyuk Kwon
- Department of Neurology, Yeungnam University College of Medicine, Daegu, Korea
- Department of Neurology, Keimyung University School of Medicine, Daegu, Korea
| | - Seong Hwa Jang
- Department of Neurology, Keimyung University School of Medicine, Daegu, Korea
| | - Hyungjong Park
- Department of Neurology, Keimyung University School of Medicine, Daegu, Korea
| | - Sung-Il Sohn
- Department of Neurology, Keimyung University School of Medicine, Daegu, Korea
| | - Jeong-Ho Hong
- Department of Neurology, Keimyung University School of Medicine, Daegu, Korea.
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Park D, Jeong E, Lee SY, Kim M, Hong DY, Kwon HD, Kim MC. Behavioral and Disease-Related Characteristics of Patients with Acute Stroke during the Coronavirus Disease Pandemic. Healthcare (Basel) 2022; 10:healthcare10040604. [PMID: 35455782 PMCID: PMC9026943 DOI: 10.3390/healthcare10040604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 11/16/2022] Open
Abstract
This study aimed to evaluate the behavioral and disease-related characteristics of patients with acute stroke during the Coronavirus disease (COVID-19) pandemic. This retrospective study was conducted using the Korean Stroke Registry database from a single cerebrovascular specialty hospital. We categorized the COVID-19 pandemic (February 2020 to June 2021) into three waves according to the number of COVID-19 cases recorded and the subjective fear index of the general population and matched them with the corresponding pre-COVID-19 (January 2019 to January 2020) periods. The total number of acute stroke hospitalizations during the pre-COVID-19 and COVID-19 periods was 402 and 379, respectively. The number of acute stroke hospitalizations recorded during the regional outbreak of COVID-19 was higher than that recorded during the corresponding pre-COVID-19 period (97 vs. 80). Length of hospital stay was significantly longer during the COVID-19 pandemic than during the pre-COVID-19 period (11.1 and 8.5 days, respectively; p = 0.003). There were no significant differences in the time from onset to hospital arrival, rate of acute intravenous/intra-arterial (IV/IA) treatments, and door-to-IV/IA times between the pre-COVID-19 and COVID-19 periods. This study suggests that specialty hospitals can effectively maintain the quality of healthcare through the management of acute time-dependent diseases, even during pandemics.
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Affiliation(s)
- Dougho Park
- Department of Rehabilitation Medicine, Pohang Stroke and Spine Hospital, Pohang 37659, Korea;
| | - Eunhwan Jeong
- Department of Neurology, Pohang Stroke and Spine Hospital, Pohang 37659, Korea; (E.J.); (S.Y.L.)
| | - Su Yun Lee
- Department of Neurology, Pohang Stroke and Spine Hospital, Pohang 37659, Korea; (E.J.); (S.Y.L.)
| | - Mansu Kim
- Department of Neurosurgery, Pohang Stroke and Spine Hospital, Pohang 37659, Korea; (M.K.); (D.Y.H.); (H.D.K.)
| | - Dae Young Hong
- Department of Neurosurgery, Pohang Stroke and Spine Hospital, Pohang 37659, Korea; (M.K.); (D.Y.H.); (H.D.K.)
| | - Heum Dai Kwon
- Department of Neurosurgery, Pohang Stroke and Spine Hospital, Pohang 37659, Korea; (M.K.); (D.Y.H.); (H.D.K.)
| | - Mun-Chul Kim
- Department of Neurosurgery, Pohang Stroke and Spine Hospital, Pohang 37659, Korea; (M.K.); (D.Y.H.); (H.D.K.)
- Correspondence:
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9
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The effects of socioeconomic and geographic factors on chronic phase long-term survival after stroke in South Korea. Sci Rep 2022; 12:4327. [PMID: 35289331 PMCID: PMC8921252 DOI: 10.1038/s41598-022-08025-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 02/23/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractThe stroke incidence has increased rapidly in South Korea, calling for a national-wide system for long-term stroke management. We investigated the effects of socioeconomic status (SES) and geographic factors on chronic phase survival after stroke. We retrospectively enrolled 6994 patients who experienced a stroke event in 2009 from the Korean National Health Insurance database. We followed them up from 24 to 120 months after stroke onset. The endpoint was all-cause mortality. We defined SES using a medical-aid group and four groups divided by health insurance premium quartiles. Geographic factors were defined using Model 1 (capital, metropolitan, city, and county) and Model 2 (with or without university hospitals). The higher the insurance premium, the higher the survival rate tended to be (P < 0.001). The patient survival rate was highest in the capital city and lowest at the county level (P < 0.001). Regions with a university hospital(s) showed a higher survival rate (P = 0.006). Cox regression revealed that the medical-aid group was identified as an independent risk factor for chronic phase mortality. Further, NHIP level had a more significant effect than geographic factors on chronic stroke mortality. From these results, long-term nationwide efforts to reduce inter-regional as well as SES discrepancies affecting stroke management are needed.
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10
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Sex and Economic Disparity Related to Reperfusion Therapies for Patients with Acute Ischemic Stroke in South Korea across a 10-Year Period: A Nationwide Population-Based Study Using the National Health Insurance Database. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19053050. [PMID: 35270741 PMCID: PMC8910261 DOI: 10.3390/ijerph19053050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 02/25/2022] [Accepted: 03/03/2022] [Indexed: 12/10/2022]
Abstract
A complete enumeration study was conducted to evaluate trends related to reperfusion therapies (intravenous thrombolysis (IVT) and endovascular treatment (EVT)) in acute ischemic stroke (AIS) in South Korea, according to sex, economic status, and age, over a 10-year period retrospectively, using the National Health Information Database (NHIS-2020-1-481). This study included AIS patients aged ≥20 years who were hospitalized in a general hospital or tertiary hospital for ≥4 days and underwent brain imaging during the same period. Study participants were classified by sex, economic status (Medical Aid beneficiaries and National Health Insurance beneficiaries) and age (20-44, 45-64, 65-79, and ≥80 years). Women showed a significantly lower OR (Odds ratio) than men in IVT (OR: 0.75; 95% CI: 0.73-0.77), EVT (OR: 0.96; 95% CI: 0.93-0.99), and any therapy (OR: 0.82; 95% CI: 0.80-0.84). The Medical Aid beneficiaries showed significantly lower OR in IVT (OR 0.91, 95% CI 0.88-0.95), EVT (OR 0.93, 95% CI 0.89-0.98), and either therapy (OR 0.92, 95% CI 0.90-0.95) than the National Health Insurance beneficiaries. This study showed sex and economic disparity related to reperfusion therapies in patients with AIS in Korea.
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11
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Choi JC, Kim JG, Kang CH, Bae HJ, Kang J, Lee SJ, Park JM, Park TH, Cho YJ, Lee KB, Lee J, Kim DE, Cha JK, Kim JT, Lee BC, Lee JS, Kim AS. Effect of Transport Time on the Use of Reperfusion Therapy for Patients with Acute Ischemic Stroke in Korea. J Korean Med Sci 2021; 36:e77. [PMID: 33754510 PMCID: PMC7985286 DOI: 10.3346/jkms.2021.36.e77] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Accepted: 01/11/2021] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND We investigated the association between geographic proximity to hospitals and the administration rate of reperfusion therapy for acute ischemic stroke. METHODS We identified patients with acute ischemic stroke who visited the hospital within 12 hours of symptom onset from a prospective nationwide multicenter stroke registry. Reperfusion therapy was classified as intravenous thrombolysis (IVT), endovascular therapy (EVT), or combined therapy. The association between the proportion of patients who were treated with reperfusion therapy and the ground transport time was evaluated using a spline regression analysis adjusted for patient-level characteristics. We also estimated the proportion of Korean population that lived within each 30-minute incremental service area from 67 stroke centers accredited by the Korean Stroke Society. RESULTS Of 12,172 patients (mean age, 68 ± 13 years; men, 59.7%) who met the eligibility criteria, 96.5% lived within 90 minutes of ground transport time from the admitting hospital. The proportion of patients treated with IVT decreased significantly when stroke patients lived beyond 90 minutes of the transport time (P = 0.006). The proportion treated with EVT also showed a similar trend with the transport time. Based on the residential area, 98.4% of Korean population was accessible to 67 stroke centers within 90 minutes. CONCLUSION The use of reperfusion therapy for acute stroke decreased when patients lived beyond 90 minutes of the ground transport time from the hospital. More than 95% of the South Korean population was accessible to 67 stroke centers within 90 minutes of the ground transport time.
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Affiliation(s)
- Jay Chol Choi
- Department of Neurology, Jeju National University Hospital, Jeju National University College of Medicine, Jeju, Korea
- Institute of Medical Science, Jeju National University, Jeju, Korea.
| | - Joong Goo Kim
- Department of Neurology, Jeju National University Hospital, Jeju National University College of Medicine, Jeju, Korea
| | - Chul Hoo Kang
- Department of Neurology, Jeju National University Hospital, Jeju National University College of Medicine, Jeju, Korea
| | - Hee Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jihoon Kang
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Soo Joo Lee
- Department of Neurology, Eulji University Hospital, Daejeon, Korea
| | - Jong Moo Park
- Department of Neurology, Eulji General Hospital, Eulji University, Seoul, Korea
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Seoul, Korea
| | - Yong Jin Cho
- Department of Neurology, Ilsan Paik Hospital, Inje University, Goyang, Korea
| | - Kyung Bok Lee
- Department of Neurology, Soonchunhyang University College of Medicine, Seoul, Korea
| | - Jun Lee
- Department of Neurology, Yeungnam University Hospital, Daegu, Korea
| | - Dong Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
| | - Jae Kwan Cha
- Department of Neurology, Dong-A University College of Medicine, Busan, Korea
| | - Joon Tae Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Byung Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea
| | - Ji Sung Lee
- Clinical Research Center, Asan Medical Center, Seoul, Korea
| | - Anthony S Kim
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
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