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2. Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study

Author

Park, Eunjeong, Lee, Kijeong, Han, Taehwa, and Nam, Hyo Suk

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundSubtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess the symptoms. In the clinical environment, diagnoses and decisions are based on clinical grading methods, including the National Institutes of Health Stroke Scale (NIHSS) score or the Medical Research Council (MRC) score, which have been used to measure motor weakness. Objective grading in various environments is necessitated for consistent agreement among patients, caregivers, paramedics, and medical staff to facilitate rapid diagnoses and dispatches to appropriate medical centers. ObjectiveIn this study, we aimed to develop an autonomous grading system for stroke patients. We investigated the feasibility of our new system to assess motor weakness and grade NIHSS and MRC scores of 4 limbs, similar to the clinical examinations performed by medical staff. MethodsWe implemented an automatic grading system composed of a measuring unit with wearable sensors and a grading unit with optimized machine learning. Inertial sensors were attached to measure subtle weaknesses caused by paralysis of upper and lower limbs. We collected 60 instances of data with kinematic features of motor disorders from neurological examination and demographic information of stroke patients with NIHSS 0 or 1 and MRC 7, 8, or 9 grades in a stroke unit. Training data with 240 instances were generated using a synthetic minority oversampling technique to complement the imbalanced number of data between classes and low number of training data. We trained 2 representative machine learning algorithms, an ensemble and a support vector machine (SVM), to implement auto-NIHSS and auto-MRC grading. The optimized algorithms performed a 5-fold cross-validation and were searched by Bayes optimization in 30 trials. The trained model was tested with the 60 original hold-out instances for performance evaluation in accuracy, sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). ResultsThe proposed system can grade NIHSS scores with an accuracy of 83.3% and an AUC of 0.912 using an optimized ensemble algorithm, and it can grade with an accuracy of 80.0% and an AUC of 0.860 using an optimized SVM algorithm. The auto-MRC grading achieved an accuracy of 76.7% and a mean AUC of 0.870 in SVM classification and an accuracy of 78.3% and a mean AUC of 0.877 in ensemble classification. ConclusionsThe automatic grading system quantifies proximal weakness in real time and assesses symptoms through automatic grading. The pilot outcomes demonstrated the feasibility of remote monitoring of motor weakness caused by stroke. The system can facilitate consistent grading with instant assessment and expedite dispatches to appropriate hospitals and treatment initiation by sharing auto-MRC and auto-NIHSS scores between prehospital and hospital responses as an objective observation.

Published
2020
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9. Effectiveness of endovascular treatment for in-hospital stroke vs. community-onset stroke: a propensity score-matched analysis

Author

Jung, Jae Wook, Kim, Kwang Hyun, Yun, Jaeseob, Nam, Hyo Suk, Heo, Ji Hoe, Baik, Minyoul, Yoo, Joonsang, Kim, Jinkwon, Park, Hyungjong, Sohn, Sung-Il, Hong, Jeong-Ho, Kim, Byung Moon, Kim, Dong Joon, Heo, JoonNyung, Bang, Oh Young, Seo, Woo-Keun, Chung, Jong-Won, Lee, Kyung-Yul, Jung, Yo Han, Lee, Hye Sun, Ahn, Seong Hwan, Shin, Dong Hoon, Choi, Hye-Yeon, Cho, Han-Jin, Baek, Jang-Hyun, Kim, Gyu Sik, Seo, Kwon-Duk, Kim, Seo Hyun, Song, Tae-Jin, Han, Sang Won, Park, Joong Hyun, Choi, Jin Kyo, and Kim, Young Dae

Published
2024
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14. More Than 50 Percent Reduction in LDL Cholesterol in Patients With Target LDL <70 mg/dL After a Stroke

Author

Amarenco, Pierre, Lavallée, Philippa C., Kim, Jong S., Labreuche, Julien, Charles, Hugo, Giroud, Maurice, Lee, Byung-Chul, Mahagne, Marie-Hélène, Meseguer, Elena, Nighoghossian, Norbert, Steg, Philippe Gabriel, Vicaut, Éric, Bruckert, Eric, Kim, Jong S, Touboul, Pierre-Jean, Leys, Didier, Béjot, Yannick, Pico, Fernando, Touzé, Emmanuel, Ducrocq, Gregory, Abtan, Jérémy, Varenne, Olivier, Touboul, Pierre-Jean, Kemmel, Agnes, Syana, Fausta, Ledra, Manele, Nagasara, Tharani, Ledjeroud, Mervette, Samia, Bahous, Hadia, Hafirassou, Hazare, Benyoub, Jaghouni, Ikrame El, Yelles, Nessima, Zemouri, Sofia, Ladjeroud, Mervette, Kerai, Salim, In, YunJeong, Hobeanu, Cristina, Guidoux, Celine, Cabrejo, Lucie, Lapergue, Bertrand, Sabben, Candice, Gonzalez-Valcarcel, Jaime, Rigual, Ricardo, Sirimarco, Gaia, Martin-Bechet, Anna, Viedma, Elena, Avram, Ioan, Samson, Yves, Rosso, Charlotte, Crozier, Sophie, Leder, Sara, Léger, Anne, Deltour, Sandrine, Mutlu, Gurkan, Yger, Marion, Zavanone, Chiara, Baronnet, Flore, Pires, Christine, Lapergue, Bertrand, Wang, Adrien, Evrard, Serge, Tchikviladze, Maya, Bourdain, Frédéric, Lopez, Delphine, Pico, Fernando, de la Tour, Laetitia Bayon, Chadenat, Marie-Laure, Duong, Duc Long, Genty, Solène, Hirel, Catherine, Mutlu, Gurkan, Nifle, Chantal, Servan, Jérôme, Stanciu, Daniela, Sudacevschi, Veronica, Tir, Mélissa, Troussière, Anne-Cécile, Yeung, Jennifer, Zeghoudi, Anne-Céline, Tidafi-Bayou, Ikram, Lachaud, Sylvain, Cho, Tae-Hee, Mechtouff, Laura, Ritzenthaller, Thomas, Derex, Laurent, Albanesi, Carlo, Ong, Elodie, Benoit, Amandine, Berhoune, Nadia, Felix, Sandra, Esteban-Mader, Maud, Sibon, Igor, Kazadi, Annabelle, Rouanet, François, Renou, Pauline, Debruxelles, Sabrina, Poli, Mathilde, Sagnier, Sharmila, Mas, Jean-Louis, Domigo, Valérie, Lamy, Catherine, Bodiguel, Eric, Grimaud, Jérôme, Bohotin, Valentin, Obadia, Michael, Sabben, Candice, Morvan, Erwan, Rodier, Gilles, Vadot, Wilfried, Hénon, Hilde, Cordonnier, Charlotte, Dumont, Frédéric, Bodenant, Marie, Lucas, Christian, Moulin, Solène, Dequatre, Nelly, Alamowitch, Sonia, Muresan, Jean-Paul, Drouet, Thomas, Gallea, Magalie, Dalloz, Marie-Amélie, Delorme, Stephen, Yger, Marion, Béjot, Yannick, Loisel, Philippe, Bonnin, Carine, Bernigal, Virginie, Osseby, Guy Victor, Hervieu-BègueMarsac, Marie, Garnier, Pierre, Accassat, Sandrine, Epinat, Magali, Varvat, Jérôme, Marinescu, Doïna, Triquenot-Bagan, Aude, Ozkul- Wermester, Ozlem, Philippeau, Frédéric, Olaru, Angel, Vieillart, Anne, Lannuzel, Annie, Demoly, Alice, Wolff, Valérie, Diaconu, Mihaela, Bataillard, Marc, Montoro, Francisco Macian, Faugeras, Frédéric, Gimenez, Laeticia, Abdallah-Lebeau, Françoise, Timsit, Serge, Viakhireva-Dovganyuk, Irina, Tirel-Badets, Anne, Merrien, François-Mathias, Goas, Philippe, Rouhart, François, Jourdain, Aurore, Guillon, Benoit, Hérissson, Fanny, Sevin-Allouet, Mathieu, Nasr, Nathalie, Olivot, Jean-Marc, Lecluse, Alderic, Marc, Guillaume, Touzé, Emmanuel, de la Sayette, Vincent, Apoil, Marion, Lin, Li, Cogez, Julien, Guettier, Sophie, Godefroy, Olivier, Lamy, Chantal, Bugnicourt, Jean-Marc, Taurin, Grégory, Mérienne, Marc, Gere, Julien, Chessak, Anne-Marie, Habet, Tarik, Ferrier, Anna, Bourgois, Nathalie, Minier, Dominique, Caillier-Minier, Marie, Contégal- Callier, Fabienne, Vion, Philippe, Vaschalde, Yvan, Amrani, Mohammed El, Emilie, Zuber, Mathieu, Bruandet, Marie, Join- Lambert, Claire, Garcia, Pierre-Yves, Serre, Isabelle, Faucheux, Jean-Marc, Radji, Fatia, Leca-Radu, Elena, Debroucker, Thomas, Cumurcuc, Rodica, Cakmak, Serkan, Peysson, Stéphane, Ellie, Emmanuel, Bernady, Patricia, Moulin, Thierry, Montiel, Paola, Revenco, Eugeniu, Decavel, Pierre, Medeiros, Elisabeth, Bouveret, Myriam, Louchart, Pierre, Vaduva, Claudia, Couvreur, Grégory, Sartori, Eric, Carpentier, Alnajar, Levasseur, Michèle, Louchart, Pierre, Faucheux, Jean-Marc, Neau, Philippe, Vandamme, Xavier, Meresse, Isabelle, Stantescu, Bataillard, Marc, Ozsancak, Canan, Beauvais, Katell, Auzou, Pascal, Amevigbe, Joséphine, Vuillemet, Francis, Dugay-Arentz, Marie-Hélène, Carelli, Gabriela, Martinez, Mikel, Maillet-Vioud, Marcel, Escaillas, Jean-Pierre, Chapuis, Stéphane, Tardy, Jean, Manchon, Eric, Varnet, Olivier, Kim, Yong-Jae, Chang, Yoonkyung, Song, Tae-Jin, Kim, Jong Sung, Han, Jung-Hoon, Noh, Kyung Chul, Lee, Eun-Jae, Kang, Dong-Wha, Kwon, Sun Uck, Kwon, Boseoung, Park, Seongho, Lee, Dongwhane, Kwon, Hyuk Sung, Jeong, Daeun, Lee, MinHwan, Kim, Joonggoo, Lee, Hanbin, Nam, Hyo Jung, Lee, Sang Hun, Kim, Bum Joon, Cha, Jae-kwan, Kim, DaeHyun, Kim, Rae Young, Sohn, Sang Wuk, Shim, Dong-Hyun, Lee, Hyungjin, Nah, Hyun-Wook, Sung, Sang Min, Lee, Kyung Bok, Yoon Lee, Jeong, Yoon, Jee Eun, Kim, Eung-Gyu, Seo, Jung Hwa, Kim, Yong-Won, Hwang, Yangha, Park, Man Seok, Kim, Joon-Tae, Choi, Kang-Ho, Nam, Hyo Suk, Heo, Ji Hoe, Kim, Young Dae, Hwang, In Gun, Park, Hyung Jong, Kim, Kyoung Sub, Baek, Jang Hyun, Song, Dong Beom, Yoo, Joon Sang, Park, Jong-Moo, Kwon, Ohyun, Lee, Woong-Woo, Lee, Jung-Ju, Kang, Kyusik, Kim, Byung Kun, Lim, Jae-Sung, Oh, Mi Sun, Yu, Kyung-Ho, Hong, Bora, Jang, Mihoon, Jang, Seyoung, Jin, Jung Eun, Kim, Jei, Jeong, Hye Seon, Hong, Keun Sik, Park, Hong Kyun, Cho, Yong Jin, Bang, Oh Young, Seo, Woo-Keun, and Chung, Jongwon

Published
2023
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15. Cancer Prediction With Machine Learning of Thrombi From Thrombectomy in Stroke: Multicenter Development and Validation

Author

Heo, JoonNyung, Lee, Hyungwoo, Seog, Young, Kim, Sungeun, Baek, Jang-Hyun, Park, Hyungjong, Seo, Kwon-Duk, Kim, Gyu Sik, Cho, Han-Jin, Baik, Minyoul, Yoo, Joonsang, Kim, Jinkwon, Lee, Jun, Chang, Yoonkyung, Song, Tae-Jin, Seo, Jung Hwa, Ahn, Seong Hwan, Lee, Heow Won, Kwon, Il, Park, Eunjeong, Kim, Byung Moon, Kim, Dong Joon, Kim, Young Dae, and Nam, Hyo Suk

Published
2023
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17. Functional Outcomes Associated With Blood Pressure Decrease After Endovascular Thrombectomy

Author

Jung, Jae Wook, primary, Kim, Kwang Hyun, additional, Yun, Jaeseob, additional, Kim, Young Dae, additional, Heo, JoonNyung, additional, Lee, Hyungwoo, additional, Choi, Jin Kyo, additional, Lee, Il Hyung, additional, Lim, In Hwan, additional, Hong, Soon-Ho, additional, Kim, Byung Moon, additional, Kim, Dong Joon, additional, Shin, Na Young, additional, Cho, Bang-Hoon, additional, Ahn, Seong Hwan, additional, Park, Hyungjong, additional, Sohn, Sung-Il, additional, Hong, Jeong-Ho, additional, Song, Tae-Jin, additional, Chang, Yoonkyung, additional, Kim, Gyu Sik, additional, Seo, Kwon-Duk, additional, Lee, Kijeong, additional, Chang, Jun Young, additional, Seo, Jung Hwa, additional, Lee, Sukyoon, additional, Baek, Jang-Hyun, additional, Cho, Han-Jin, additional, Shin, Dong Hoon, additional, Kim, Jinkwon, additional, Yoo, Joonsang, additional, Baik, Minyoul, additional, Lee, Kyung-Yul, additional, Jung, Yo Han, additional, Hwang, Yang-Ha, additional, Kim, Chi Kyung, additional, Kim, Jae Guk, additional, Lee, Chan Joo, additional, Park, Sungha, additional, Jeon, Soyoung, additional, Lee, Hye Sun, additional, Kwon, Sun U., additional, Bang, Oh Young, additional, Heo, Ji Hoe, additional, and Nam, Hyo Suk, additional

Published
2024
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18. Arterial Stiffness Predicts the Outcome of Endovascular Treatment in Patients with Acute Ischemic Stroke.

Author

Han, Minho, Joo, Haram, Lee, Hyungwoo, Heo, JoonNyung, Jung, Jae Wook, Kim, Young Dae, Park, Eunjeong, and Nam, Hyo Suk

Subjects
PULSE wave analysis, STROKE patients, ISCHEMIC stroke, ARTERIAL diseases, LOGISTIC regression analysis, ANKLE brachial index
Abstract

Background: The association between arterial stiffness and outcome after endovascular treatment (EVT) is unknown. This study investigated whether arterial stiffness predicts post-EVT outcome in patients with acute ischemic stroke. Methods: This retrospective and observational cohort study included consecutive patients treated with EVT for acute ischemic stroke from June 2020 to November 2022. Arterial stiffness was assessed by brachial–ankle pulse wave velocity. Poor functional outcome was defined as a modified Rankin Scale score ≥3 at 3 months. Results: The mean age of patients included in this study was 71.9 ± 11.8 years, and 57.3% were men. Poor functional outcome was present in 46.8%. Multivariable logistic regression analysis showed that arterial stiffness was independently associated with poor functional outcome (odds ratio 8.640, 95% confidence interval [CI] 1.581–47.228) after adjusting for age, initial stroke severity, hypertension, atrial fibrillation, device pass number, and successful recanalization. A nomogram based on the multivariable statistic model showed a better prediction of poor functional outcome compared to classic risk factor models without arterial stiffness (net reclassification improvement 0.529, 95% CI 0.186–0.873; integrated discrimination improvement 0.046, 95% CI 0.009–0.083). Conclusions: We found that arterial stiffness was an independent predictor of poor functional outcome in patients treated with EVT following acute ischemic stroke. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Comorbidity index for predicting mortality at 6 months after reperfusion therapy

Author

Nam, Hyo Suk, Kim, Young Dae, Yoo, Joonsang, Park, Hyungjong, Kim, Byung Moon, Bang, Oh Young, Kim, Hyeon Chang, Han, Euna, Kim, Dong Joon, Heo, Joonyung, Kim, Minyoung, Choi, Jin Kyo, Lee, Kyung-Yul, Lee, Hye Sun, Shin, Dong Hoon, Choi, Hye-Yeon, Sohn, Sung-Il, Hong, Jeong-Ho, Lee, Jong Yun, Baek, Jang-Hyun, Kim, Gyu Sik, Seo, Woo-Keun, Chung, Jong-Won, Kim, Seo Hyun, Song, Tae-Jin, Han, Sang Won, Park, Joong Hyun, Kim, Jinkwon, Jung, Yo Han, Cho, Han-Jin, Ahn, Seong Hwan, Lee, Sung Ik, Seo, Kwon-Duk, and Heo, Ji Hoe

Published
2021
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35. Association between substantia nigra degeneration and functional outcome in patients with basal ganglia infarction.

Author

Lee, Hyungwoo, Lee, Kijeong, Kim, Young Dae, Nam, Hyo Suk, Lee, Hye Sun, Cho, Sunghee, and Heo, Ji Hoe

Subjects
CEREBRAL infarction, SUBSTANTIA nigra, BASAL ganglia, STROKE patients, DIFFUSION magnetic resonance imaging, INFARCTION
Abstract

Background and purpose: Cerebral infarction in the basal ganglia may cause secondary and delayed neuronal degeneration in the substantia nigra (SN). However, the clinical significance of SN degeneration remains poorly understood. Methods: This retrospective observational study included patients with acute ischemic stroke in the basal ganglia on initial diffusion‐weighted imaging who underwent follow‐up diffusion‐weighted imaging between 4 and 30 days after symptom onset. SN degeneration was defined as a hyperintensity lesion in the SN observed on diffusion‐weighted imaging. We compared functional outcomes at 3 months between patients with and without SN degeneration. A poor outcome was defined as a score of 3–6 (functional dependence or death) on the modified Rankin Scale. Results: Of 350 patients with basal ganglia infarction (median age = 74.0 years, 53.7% male), 125 (35.7%) had SN degeneration. The proportion of functional dependence or death was 79.2% (99/125 patients) in patients with SN degeneration, which was significantly higher than that in those without SN degeneration (56.4%, 127/225 patients, p < 0.001). SN degeneration was more frequent in patients with functional dependence or death (99/226 patients, 43.8%) than in those with functional independence (26/124 patients, 21.0%, p < 0.001). Multivariable logistic regression analysis showed a significant association between SN degeneration and functional dependence or death (odds ratio = 2.91, 95% confidence interval = 1.17–7.21, p = 0.021). Conclusions: The study showed that patients with degeneration of SN were associated with functional dependence or death at 3 months, suggesting that secondary degeneration is a predictor of poor stroke outcomes and a potential therapeutic target. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Benefit of Targeting a LDL (Low-Density Lipoprotein) Cholesterol <70 mg/dL During 5 Years After Ischemic Stroke

Author

Amarenco, Pierre, Kim, Jong S., Labreuche, Julien, Charles, Hugo, Giroud, Maurice, Lee, Byung-Chul, Mahagne, Marie-Hélène, Nighoghossian, Norbert, Gabriel Steg, Philippe, Vicaut, Éric, Bruckert, Eric, Touboul, Pierre-Jean, Leys, Didier, Béjot, Yannick, Lavallée, Philippa, Pico, Fernando, Touzé, Emmanuel, Ducrocq, Gregory, Abtan, Jérémy, Varenne, Olivier, Touboul, Pierre-Jean, Kemmel, Agnes, Syana, Fausta, Ledra, Manele, Nagasara, Tharani, Ledjeroud, Mervette, Samia, Bahous, Hadia, Hafirassou, Hazare, Benyoub, El Jaghouni, Ikrame, Yelles, Nessima, Zemouri, Sofia, Ladjeroud, Mervette, Kerai, Salim, In, Yun Jeong, Meseguer, Elena, Lavallée, Philippa C, Hobeanu, Cristina, Guidoux, Celine, Cabrejo, Lucie, Lapergue, Bertrand, Sabben, Candice, Gonzalez-Valcarcel, Jaime, Rigual, Ricardo, Sirimarco, Gaia, Martin-Bechet, Anna, Viedma, Elena, Avram, Ioan, Samson, Yves, Rosso, Charlotte, Crozier, Sophie, Leder, Sara, Léger, Anne, Deltour, Sandrine, Mutlu, Gurkan, Yger, Marion, Zavanone, Chiara, Baronnet, Flore, Pires, Christine, Lapergue, Bertrand, Wang, Adrien, Evrard, Serge, Tchikviladze, Maya, Bourdain, Frédéric, Lopez, Delphine, Pico, Fernando, de la Tour, Laetitia Bayon, Chadenat, Marie-Laure, Duong, Duc Long, Genty, Solène, Hirel, Catherine, Mutlu, Gurkan, Nifle, Chantal, Servan, Jérôme, Stanciu, Daniela, Sudacevschi, Veronica, Tir, Mélissa, Troussière, Anne-Cécile, Yeung, Jennifer, Zeghoudi, Anne-Céline, Tidafi-Bayou, Ikram, Lachaud, Sylvain, Cho, Tae-Hee, Mechtouff, Laura, Ritzenthaller, Thomas, Derex, Laurent, Albanesi, Carlo, Ong, Elodie, Benoit, Amandine, Berhoune, Nadia, Felix, Sandra, Esteban-Mader, Maud, Sibon, Igor, Kazadi, Annabelle, Rouanet, François, Renou, Pauline, Debruxelles, Sabrina, Poli, Mathilde, Sagnier, Sharmila, Mas, Jean-Louis, Domigo, Valérie, Lamy, Catherine, Bodiguel, Eric, Grimaud, Jérôme, Bohotin, Valentin, Obadia, Michael, Sabben, Candice, Morvan, Erwan, Rodier, Gilles, Vadot, Wilfried, Hénon, Hilde, Cordonnier, Charlotte, Dumont, Frédéric, Bodenant, Marie, Lucas, Christian, Moulin, Solène, Dequatre, Nelly, Alamowitch, Sonia, Muresan, Jean-Paul, Drouet, Thomas, Gallea, Magalie, Dalloz, Marie-Amélie, Delorme, Stephen, Yger, Marion, Béjot, Yannick, Loisel, Philippe, Bonnin, Carine, Bernigal, Virginie, Osseby, Guy Victor, Marsac, Marie Hervieu-Bègue, Garnier, Pierre, Accassat, Sandrine, Epinat, Magali, Varvat, Jérôme, Marinescu, Doïna, Triquenot-Bagan, Aude, Ozkul-Wermester, Ozlem, Philippeau, Frédéric, Olaru, Angel, Vieillart, Anne, Lannuzel, Annie, Demoly, Alice, Wolff, Valérie, Diaconu, Mihaela, Bataillard, Marc, Montoro, Francisco Macian, Faugeras, Frédéric, Gimenez, Laeticia, Abdallah-Lebeau, Françoise, Timsit, Serge, Viakhireva-Dovganyuk, Irina, Tirel-Badets, Anne, Merrien, François-Mathias, Goas, Philippe, Rouhart, François, Jourdain, Aurore, Guillon, Benoit, Hérissson, Fanny, Sevin-Allouet, Mathieu, Nasr, Nathalie, Olivot, Jean-Marc, Lecluse, Alderic, Marc, Guillaume, Touzé, Emmanuel, de la Sayette, Vincent, Apoil, Marion, Lin, Li, Cogez, Julien, Guettier, Sophie, Godefroy, Olivier, Lamy, Chantal, Bugnicourt, Jean-Marc, Taurin, Grégory, Mérienne, Marc, Gere, Julien, Chessak, Anne-Marie, Habet, Tarik, Ferrier, Anna, Bourgois, Nathalie, Minier, Dominique, Caillier-Minier, Marie, Contégal-Callier, Fabienne, Vion, Philippe, Vaschalde, Yvan, El Amrani, Emilie, Mohammed, Zuber, Mathieu, Bruandet, Marie, Join-Lambert, Claire, Garcia, Pierre-Yves, Serre, Isabelle, Faucheux, Jean-Marc, Radji, Fatia, Leca-Radu, Elena, Debroucker, Thomas, Cumurcuc, Rodica, Cakmak, Serkan, Peysson, Stéphane, Ellie, Emmanuel, Bernady, Patricia, Moulin, Thierry, Montiel, Paola, Revenco, Eugeniu, Decavel, Pierre, Medeiros, Elisabeth, Bouveret, Myriam, Louchart, Pierre, Vaduva, Claudia, Couvreur, Grégory, Sartori, Eric, Alnajar-Carpentier, Eric, Levasseur, Michèle, Louchart, Pierre, Neau, Jean-Philippe, Vandamme, Xavier, Meresse, Isabelle, Stantescu, Bataillard, Marc, Ozsancak, Canan, Beauvais, Katell, Auzou, Pascal, Amevigbe, Joséphine, Vuillemet, Francis, Dugay-Arentz, Marie-Hélène, Carelli, Gabriela, Martinez, Mikel, Maillet-Vioud, Marcel, Escaillas, Jean-Pierre, Chapuis, Stéphane, Tardy, Jean, Manchon, Eric, Varnet, Olivier, Kim, Yong-Jae, Chang, Yoonkyung, Song, Tae-Jin, Han, Jung-Hoon, Noh, Kyung Chul, Lee, Eun-Jae, Kang, Dong-Wha, Kwon, Sun Uck, Kwon, Boseoung, Park, Seongho, Lee, Dongwhane, Kwon, Hyuk Sung, Jeong, Daeun, Lee, MinHwan, Kim, Joonggoo, Lee, Hanbin, Nam, Hyo Jung, Lee, Sang Hun, Kim, Bum Joon, Cha, Jae-kwan, Kim, DaeHyun, Young Kim, Rae, Sohn, Sang Wuk, Shim, Dong-Hyun, Lee, Hyungjin, Nah, Hyun-Wook, Sung, Sang Min, Lee, Kyung Bok, Lee, Jeong Yoon, Yoon, Jee Eun, Kim, Eung-Gyu, Seo, Jung Hwa, Kim, Yong-Won, Hwang, Yangha, Park, Man Seok, Kim, Joon-Tae, Choi, Kang-Ho, Nam, Hyo Suk, Heo, Ji Hoe, Kim, Young Dae, Hwang, In Gun, Park, Hyung Jong, Kim, Kyoung Sub, Baek, Jang Hyun, Song, Dong Beom, Yoo, Joon Sang, Park, Jong-Moo, Kwon, Ohyun, Lee, Woong-Woo, Lee, Jung-Ju, Kang, Kyusik, Kim, Byung Kun, Lim, Jae-Sung, Oh, Mi Sun, Yu, Kyung-Ho, Hong, Bora, Jang, Mihoon, Jang, Seyoung, Jin, Jung Eun, Kim, Jei, Jeong, Hye Seon, Hong, Keun Sik, Park, Hong Kyun, Cho, Yong Jin, Bang, Oh Young, Seo, Woo-Keun, and Chung, Jongwon

Published
2020
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37. Cilostazol Versus Aspirin in Ischemic Stroke Patients With High-Risk Cerebral Hemorrhage: Subgroup Analysis of the PICASSO Trial

Author

Kim, Bum Joon, Kwon, Sun U., Park, Joung-Ho, Kim, Yong-Jae, Hong, Keun-Sik, Wong, Lawrence K.S., Yu, Sungwook, Hwang, Yang-Ha, Lee, Ji Sung, Lee, Juneyoung, Rha, Jong-Ho, Heo, Sung Hyuk, Ahn, Seong Hwan, Seo, Woo-Keun, Park, Jong-Moo, Lee, Ju-Hun, Kwon, Jee-Hyun, Sohn, Sung-Il, Jung, Jin-Man, Navarro, Jose C., Kim, Hahn Young, Kim, Eung-Gyu, Kim, Seongheon, Cha, Jae-Kwan, Park, Man-Seok, Nam, Hyo Suk, and Kang, Dong-Wha

Published
2020
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39. Balloon Guide Catheter Is Beneficial in Endovascular Treatment Regardless of Mechanical Recanalization Modality

Author

Baek, Jang-Hyun, Kim, Byung Moon, Kang, Dong-Hun, Heo, Ji Hoe, Nam, Hyo Suk, Kim, Young Dae, Hwang, Yang-Ha, Kim, Yong-Won, Kim, Yong-Sun, Kim, Dong Joon, Kwak, Hyo Sung, Roh, Hong Gee, Lee, Young-Jun, Kim, Sang Heum, Baik, Seung Kug, Jeon, Pyoung, Yoo, Joonsang, Suh, Sang Hyun, Kim, Byungjun, Kim, Jin Woo, Suh, Sangil, and Jeon, Hong-Jun

Published
2019
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40. Corrigendum: Clinical implications of atrial fibrillatioN detection using wearabLE devices in patients with cryptogenic stroke (CANDLE-AF) trial: Design and rationale

Author

Jung, Sodam, primary, Lee, Hye Ah, additional, Kang, In Sook, additional, Shin, Sang Hoon, additional, Chang, Yoonkyung, additional, Shin, Dong Woo, additional, Park, Mooseok, additional, Kim, Young Dae, additional, Nam, Hyo Suk, additional, Heo, Ji Hoe, additional, Kim, Tae-Hoon, additional, Yu, Hee Tae, additional, Lee, Jung Myung, additional, Heo, Sung Hyuk, additional, Woo, Ho Geol, additional, Park, Jin-Kyu, additional, Ro, Seung-Y., additional, Kim, Chi Kyung, additional, Lee, Young-Soo, additional, Do, Jin Kuk, additional, Kim, Dong-Hyeok, additional, Song, Tae-Jin, additional, and Park, Junbeom, additional

Published
2023
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41. Moderate-Intensity Rosuvastatin Plus Ezetimibe Versus High-Intensity Rosuvastatin for Target Low-Density Lipoprotein Cholesterol Goal Achievement in Patients With Recent Ischemic Stroke: A Randomized Controlled Trial

Author

Hong, Keun-Sik, primary, Bang, Oh Young, additional, Park, Jong-Ho, additional, Jung, Jin-Man, additional, Lee, Sang-Hun, additional, Song, Tae-Jin, additional, Nam, Hyo Suk, additional, Park, Hee-Kwon, additional, Jung, Keun-Hwa, additional, Heo, Sung Hyuk, additional, Koo, Jaseong, additional, Yu, Kyung-Ho, additional, Park, Kwang-Yeol, additional, Kim, Chi Kyung, additional, Park, Hong-Kyun, additional, Lee, Jiyoon, additional, Lee, Juneyoung, additional, and Seo, Woo-Keun, additional

Published
2023
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48. Intensive vs Conventional Blood Pressure Lowering After Endovascular Thrombectomy in Acute Ischemic Stroke: The OPTIMAL-BP Randomized Clinical Trial.

Author

Nam, Hyo Suk, Kim, Young Dae, Heo, JoonNyung, Lee, Hyungwoo, Jung, Jae Wook, Choi, Jin Kyo, Lee, Il Hyung, Lim, In Hwan, Hong, Soon-Ho, Baik, Minyoul, Kim, Byung Moon, Kim, Dong Joon, Shin, Na-Young, Cho, Bang-Hoon, Ahn, Seong Hwan, Park, Hyungjong, Sohn, Sung-Il, Hong, Jeong-Ho, Song, Tae-Jin, and Chang, Yoonkyung

Subjects
*THROMBOLYTIC therapy, *ISCHEMIC stroke, *ENDOVASCULAR surgery, *BLOOD pressure, *STROKE patients, *SYSTOLIC blood pressure
Abstract

Key Points: Question: Does early intensive blood pressure management improve outcomes after successful reperfusion with endovascular thrombectomy in acute ischemic stroke? Findings: In this randomized clinical trial that included 306 patients, 39.4% of patients with intensive blood pressure management (systolic blood pressure target <140 mm Hg) and 54.4% of those with conventional blood pressure management (systolic blood pressure target 140-180 mm Hg) achieved functional independence (modified Rankin Scale score ≤2) at 3 months; this represented a significant difference. Meaning: Intensive blood pressure lowering during the first 24 hours after successful reperfusion may be harmful in patients with acute ischemic stroke who have undergone endovascular thrombectomy. Importance: Optimal blood pressure (BP) control after successful reperfusion with endovascular thrombectomy (EVT) for patients with acute ischemic stroke is unclear. Objective: To determine whether intensive BP management during the first 24 hours after successful reperfusion leads to better clinical outcomes than conventional BP management in patients who underwent EVT. Design, Setting, and Participants: Multicenter, randomized, open-label trial with a blinded end-point evaluation, conducted across 19 stroke centers in South Korea from June 2020 to November 2022 (final follow-up, March 8, 2023). It included 306 patients with large vessel occlusion acute ischemic stroke treated with EVT and with a modified Thrombolysis in Cerebral Infarction score of 2b or greater (partial or complete reperfusion). Interventions: Participants were randomly assigned to receive intensive BP management (systolic BP target <140 mm Hg; n = 155) or conventional management (systolic BP target 140-180 mm Hg; n = 150) for 24 hours after enrollment. Main Outcomes and Measures: The primary outcome was functional independence at 3 months (modified Rankin Scale score of 0-2). The primary safety outcomes were symptomatic intracerebral hemorrhage within 36 hours and death related to the index stroke within 3 months. Results: The trial was terminated early based on the recommendation of the data and safety monitoring board, which noted safety concerns. Among 306 randomized patients, 305 were confirmed eligible and 302 (99.0%) completed the trial (mean age, 73.0 years; 122 women [40.4%]). The intensive management group had a lower proportion achieving functional independence (39.4%) than the conventional management group (54.4%), with a significant risk difference (−15.1% [95% CI, −26.2% to −3.9%]) and adjusted odds ratio (0.56 [95% CI, 0.33-0.96]; P =.03). Rates of symptomatic intracerebral hemorrhage were 9.0% in the intensive group and 8.1% in the conventional group (risk difference, 1.0% [95% CI, −5.3% to 7.3%]; adjusted odds ratio, 1.10 [95% CI, 0.48-2.53]; P =.82). Death related to the index stroke within 3 months occurred in 7.7% of the intensive group and 5.4% of the conventional group (risk difference, 2.3% [95% CI, −3.3% to 7.9%]; adjusted odds ratio, 1.73 [95% CI, 0.61-4.92]; P =.31). Conclusions and Relevance: Among patients who achieved successful reperfusion with EVT for acute ischemic stroke with large vessel occlusion, intensive BP management for 24 hours led to a lower likelihood of functional independence at 3 months compared with conventional BP management. These results suggest that intensive BP management should be avoided after successful EVT in acute ischemic stroke. Trial Registration: ClinicalTrials.gov Identifier: NCT04205305 This randomized trial assesses the effect of intensive blood pressure management vs conventional management on functional independence at 3 months among patients with large vessel occlusion acute ischemic stroke treated with endovascular thrombectomy. [ABSTRACT FROM AUTHOR]

Published
2023
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49. d ‐Dimer Level After Endovascular Treatment Can Help Predict Outcome of Acute Ischemic Stroke

Author

Nam, Hyo Suk, primary, Kim, Young Dae, additional, Yoo, Joonsang, additional, Park, Hyungjong, additional, Kim, Byung Moon, additional, Bang, Oh Young, additional, Kim, Hyeon Chang, additional, Han, Euna, additional, Kim, Dong Joon, additional, Lee, Il Hyung, additional, Lee, Hyungwoo, additional, Choi, Jin Kyo, additional, Lee, Kyung‐Yul, additional, Lee, Hye Sun, additional, Shin, Dong Hoon, additional, Choi, Hye‐Yeon, additional, Sohn, Sung‐Il, additional, Hong, Jeong‐Ho, additional, Lee, Jong Yun, additional, Baek, Jang‐Hyun, additional, Kim, Gyu Sik, additional, Seo, Woo‐Keun, additional, Chung, Jong‐Won, additional, Kim, Seo Hyun, additional, Song, Tae‐Jin, additional, Han, Sang Won, additional, Park, Joong Hyun, additional, Kim, Jinkwon, additional, Jung, Yo Han, additional, Cho, Han‐Jin, additional, Ahn, Seong Hwan, additional, Seo, Kwon‐Duk, additional, Lee, Kee Ook, additional, Song, Jaewoo, additional, and Heo, Ji Hoe, additional

Published
2023
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