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Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

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dc.contributor.author김영대-
dc.contributor.author허지회-
dc.date.accessioned2021-04-29T17:36:40Z-
dc.date.available2021-04-29T17:36:40Z-
dc.date.issued2021-04-
dc.identifier.issn1474-4422-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/182433-
dc.description.abstractBackground: Balancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk. Methods: We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602. Findings: The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0·73 (95% CI 0·69-0·77) with a calibration slope of 0·94 (0·81-1·06) for the intracranial haemorrhage model and 0·63 (0·62-0·65) with a calibration slope of 0·97 (0·87-1·07) for the ischaemic stroke model. There was good agreement between predicted and observed risk for both models. Interpretation: The MICON risk scores, incorporating clinical variables and cerebral microbleeds, offer predictive value for the long-term risks of intracranial haemorrhage and ischaemic stroke in patients prescribed antithrombotic therapy for secondary stroke prevention; external validation is warranted. Funding: British Heart Foundation and Stroke Association.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherLancet Pub. Group-
dc.relation.isPartOfLANCET NEUROLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAdult-
dc.subject.MESHAged-
dc.subject.MESHFemale-
dc.subject.MESHFibrinolytic Agents / therapeutic use*-
dc.subject.MESHHumans-
dc.subject.MESHIntracranial Hemorrhages / etiology*-
dc.subject.MESHIschemic Attack, Transient / complications-
dc.subject.MESHIschemic Attack, Transient / diagnostic imaging-
dc.subject.MESHIschemic Attack, Transient / drug therapy-
dc.subject.MESHIschemic Stroke / complications*-
dc.subject.MESHIschemic Stroke / diagnostic imaging-
dc.subject.MESHIschemic Stroke / drug therapy*-
dc.subject.MESHMagnetic Resonance Imaging-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHRecurrence-
dc.subject.MESHRisk-
dc.titleDevelopment of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Neurology (신경과학교실)-
dc.contributor.googleauthorJonathan G Best-
dc.contributor.googleauthorGareth Ambler-
dc.contributor.googleauthorDuncan Wilson-
dc.contributor.googleauthorKeon-Joo Lee-
dc.contributor.googleauthorJae-Sung Lim-
dc.contributor.googleauthorMasayuki Shiozawa-
dc.contributor.googleauthorMasatoshi Koga-
dc.contributor.googleauthorLinxin Li-
dc.contributor.googleauthorCaroline Lovelock-
dc.contributor.googleauthorHugues Chabriat-
dc.contributor.googleauthorMichael Hennerici-
dc.contributor.googleauthorYuen Kwun Wong-
dc.contributor.googleauthorHenry Ka Fung Mak-
dc.contributor.googleauthorLuis Prats-Sanchez-
dc.contributor.googleauthorAlejandro Martínez-Domeño-
dc.contributor.googleauthorShigeru Inamura-
dc.contributor.googleauthorKazuhisa Yoshifuji-
dc.contributor.googleauthorEthem Murat Arsava-
dc.contributor.googleauthorSolveig Horstmann-
dc.contributor.googleauthorJan Purrucker-
dc.contributor.googleauthorBonnie Yin Ka Lam-
dc.contributor.googleauthorAdrian Wong-
dc.contributor.googleauthorYoung Dae Kim-
dc.contributor.googleauthorTae-Jin Song-
dc.contributor.googleauthorRobin Lemmens-
dc.contributor.googleauthorSebastian Eppinger-
dc.contributor.googleauthorThomas Gattringer-
dc.contributor.googleauthorEnder Uysal-
dc.contributor.googleauthorZeynep Tanriverdi-
dc.contributor.googleauthorNatan M Bornstein-
dc.contributor.googleauthorEinor Ben Assayag-
dc.contributor.googleauthorHen Hallevi-
dc.contributor.googleauthorJeremy Molad-
dc.contributor.googleauthorMasashi Nishihara-
dc.contributor.googleauthorJun Tanaka-
dc.contributor.googleauthorShelagh B Coutts-
dc.contributor.googleauthorAlexandros Polymeris-
dc.contributor.googleauthorBenjamin Wagner-
dc.contributor.googleauthorDavid J Seiffge-
dc.contributor.googleauthorPhilippe Lyrer-
dc.contributor.googleauthorAle Algra-
dc.contributor.googleauthorL Jaap Kappelle-
dc.contributor.googleauthorRustam Al-Shahi Salman-
dc.contributor.googleauthorHans R Jäger-
dc.contributor.googleauthorGregory Y H Lip-
dc.contributor.googleauthorUrs Fischer-
dc.contributor.googleauthorMarwan El-Koussy-
dc.contributor.googleauthorJean-Louis Mas-
dc.contributor.googleauthorLaurence Legrand-
dc.contributor.googleauthorChristopher Karayiannis-
dc.contributor.googleauthorThanh Phan-
dc.contributor.googleauthorSarah Gunkel-
dc.contributor.googleauthorNicolas Christ-
dc.contributor.googleauthorJill Abrigo-
dc.contributor.googleauthorThomas Leung-
dc.contributor.googleauthorWinnie Chu-
dc.contributor.googleauthorFrancesca Chappell-
dc.contributor.googleauthorStephen Makin-
dc.contributor.googleauthorDerek Hayden-
dc.contributor.googleauthorDavid J Williams-
dc.contributor.googleauthorWerner H Mess-
dc.contributor.googleauthorPaul J Nederkoorn-
dc.contributor.googleauthorCarmen Barbato-
dc.contributor.googleauthorSimone Browning-
dc.contributor.googleauthorKim Wiegertjes-
dc.contributor.googleauthorAnil M Tuladhar-
dc.contributor.googleauthorNoortje Maaijwee-
dc.contributor.googleauthorAnne Cristine Guevarra-
dc.contributor.googleauthorChathuri Yatawara-
dc.contributor.googleauthorAnne-Marie Mendyk-
dc.contributor.googleauthorChristine Delmaire-
dc.contributor.googleauthorSebastian Köhler-
dc.contributor.googleauthorRobert van Oostenbrugge-
dc.contributor.googleauthorYing Zhou-
dc.contributor.googleauthorChao Xu-
dc.contributor.googleauthorSaima Hilal-
dc.contributor.googleauthorBibek Gyanwali-
dc.contributor.googleauthorChristopher Chen-
dc.contributor.googleauthorMin Lou-
dc.contributor.googleauthorJulie Staals-
dc.contributor.googleauthorRégis Bordet-
dc.contributor.googleauthorNagaendran Kandiah-
dc.contributor.googleauthorFrank-Erik de Leeuw-
dc.contributor.googleauthorRobert Simister-
dc.contributor.googleauthorJeroen Hendrikse-
dc.contributor.googleauthorPeter J Kelly-
dc.contributor.googleauthorJoanna Wardlaw-
dc.contributor.googleauthorYannie Soo-
dc.contributor.googleauthorFelix Fluri-
dc.contributor.googleauthorVelandai Srikanth-
dc.contributor.googleauthorDavid Calvet-
dc.contributor.googleauthorSimon Jung-
dc.contributor.googleauthorVincent I H Kwa-
dc.contributor.googleauthorStefan T Engelter-
dc.contributor.googleauthorNils Peters-
dc.contributor.googleauthorEric E Smith-
dc.contributor.googleauthorHideo Hara-
dc.contributor.googleauthorYusuke Yakushiji-
dc.contributor.googleauthorDilek Necioglu Orken-
dc.contributor.googleauthorFranz Fazekas-
dc.contributor.googleauthorVincent Thijs-
dc.contributor.googleauthorJi Hoe Heo-
dc.contributor.googleauthorVincent Mok-
dc.contributor.googleauthorRoland Veltkamp-
dc.contributor.googleauthorHakan Ay-
dc.contributor.googleauthorToshio Imaizumi-
dc.contributor.googleauthorBeatriz Gomez-Anson-
dc.contributor.googleauthorKui Kai Lau-
dc.contributor.googleauthorEric Jouvent-
dc.contributor.googleauthorPeter M Rothwell-
dc.contributor.googleauthorKazunori Toyoda-
dc.contributor.googleauthorHee-Joon Bae-
dc.contributor.googleauthorJoan Marti-Fabregas-
dc.contributor.googleauthorDavid J Werring-
dc.identifier.doi10.1016/S1474-4422(21)00024-7-
dc.contributor.localIdA00702-
dc.contributor.localIdA04369-
dc.relation.journalcodeJ02153-
dc.identifier.eissn1474-4465-
dc.identifier.pmid33743239-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S1474442221000247-
dc.contributor.alternativeNameKim, Young Dae-
dc.contributor.affiliatedAuthor김영대-
dc.contributor.affiliatedAuthor허지회-
dc.citation.volume20-
dc.citation.number4-
dc.citation.startPage294-
dc.citation.endPage303-
dc.identifier.bibliographicCitationLANCET NEUROLOGY, Vol.20(4) : 294-303, 2021-04-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers

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