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Factors associated with rerupture of intracranial aneurysms after endovascular treatment: a retrospective review of 11 years experience at a single institution and review of the literature. <i>J Clin Neurosci<\/i> 2017; 44: 53\u201362.","DOI":"10.1016\/j.jocn.2017.06.033"},{"key":"5","doi-asserted-by":"crossref","unstructured":"5) Kim ST, Baek J, Lee W, et al. Causes of early rebleeding after coil embolization of ruptured cerebral aneurysms. <i>Clin Neurol Neurosurg<\/i> 2018; 174: 108\u2013116.","DOI":"10.1016\/j.clineuro.2018.09.006"},{"key":"6","doi-asserted-by":"crossref","unstructured":"6) Kocur D, Przyby\u0142ko N, Ba\u017cowski P, et al. Rupture during coiling of intracranial aneurysms: predictors and clinical outcome. <i>Clin Neurol Neurosurg<\/i> 2018; 165: 81\u201387.","DOI":"10.1016\/j.clineuro.2018.01.006"},{"key":"7","doi-asserted-by":"crossref","unstructured":"7) McDougall CG, Spetzler R, Zabramski J, et al. The barrow ruptured aneurysm trial: clinical article. <i>J Neurosurg<\/i> 2012; 116: 135\u2013144.","DOI":"10.3171\/2011.8.JNS101767"},{"key":"8","doi-asserted-by":"crossref","unstructured":"8) Wu TC, Tsui YK, Chen TY, et al. Rebleeding of aneurysmal subarachnoid hemorrhage in computed tomography angiography: risk factor, rebleeding pattern, and outcome analysis. <i>J Comput Assist Tomogr<\/i> 2012; 36: 103\u2013108.","DOI":"10.1097\/RCT.0b013e31823f2e57"},{"key":"9","doi-asserted-by":"crossref","unstructured":"9) Johnston SC, Dowd C, Higashida R, et al. Predictors of rehemorrhage after treatment of ruptured intracranial aneurysms: the Cerebral Aneurysm Rerupture After Treatment (CARAT) study. <i>Stroke<\/i> 2008; 39: 120\u2013125.","DOI":"10.1161\/STROKEAHA.107.495747"},{"key":"10","doi-asserted-by":"crossref","unstructured":"10) Sherif C, Gruber A, Schuster E, et al. 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Development and validation of machine learning prediction model for post-rehabilitation functional outcome after intracerebral hemorrhage. <i>Interdiscip Neurosurg<\/i> 2022; 29: 101560.","DOI":"10.1016\/j.inat.2022.101560"},{"key":"26","doi-asserted-by":"crossref","unstructured":"26) Chase BA, Krueger R, Pavelka L, et al. Multifactorial assessment of Parkinson\u2019s disease course and outcomes using trajectory modeling in a multiethnic, multisite cohort \u2013 extension of the LONG-PD study. <i>Front Aging Neurosci<\/i> 2023; 15: 1240971.","DOI":"10.3389\/fnagi.2023.1240971"},{"key":"27","doi-asserted-by":"crossref","unstructured":"27) Randell R, Wright JM, Alvarado N, et al. What supports and constrains the implementation of multifactorial falls risk assessment and tailored multifactorial falls prevention interventions in acute hospitals? Protocol for a realist review. <i>BMJ Open<\/i> 2021; 11: e049765.","DOI":"10.1136\/bmjopen-2021-049765"},{"key":"28","doi-asserted-by":"crossref","unstructured":"28) Singh P, Madanipour S, Fontalis A, et al. A systematic review and meta-analysis of trainee- versus consultant surgeon-performed elective total hip arthroplasty. <i>EFORT Open Rev<\/i> 2019; 4: 44\u201355.","DOI":"10.1302\/2058-5241.4.180034"},{"key":"29","doi-asserted-by":"crossref","unstructured":"29) Kauvar DS, Braswell A, Brown BD, et al. Influence of resident and attending surgeon seniority on operative performance in laparoscopic cholecystectomy. <i>J Surg Res<\/i> 2006; 132: 159\u2013163.","DOI":"10.1016\/j.jss.2005.11.578"},{"key":"30","doi-asserted-by":"crossref","unstructured":"30) Wilkiemeyer M, Pappas T, Giobbie-Hurder A, et al. 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