机器学习在高血压脑出血预后预测中的应用与展望

ISSN:2811-051X(P)

EISSN:2811-0781(O)

语言:中文

作者
何梦辉,卢忠胜
文章摘要
高血压脑出血属于神经外科常见的急危重症,有着高致残率以及高病死率的特性,精准的预后评估是制定个体化治疗方案以及优化医疗资源分配的关键前提条件,本文是要为高血压脑出血患者预后预测的临床研究和实践给予参考,推动机器学习模型从科研工具朝着临床决策支持系统进行转化。
文章关键词
高血压脑出血;预后预测;机器学习;传统模型;研究进展
参考文献
[1] VAN VALBURG M K, TERMORSHUIZEN F, GEERTS B F, et al. Predicting 30-day mortality in intensive care unit patients with ischaemic stroke or intracerebral haemorrhage [J]. European journal of anaesthesiology, 2024, 41(2): 136-45. [2] MAINALI S, DARSIE M E, SMETANA K S. Machine Learning in Action: Stroke Diagnosis and Outcome Prediction [J]. Frontiers in neurology, 2021, 12: 734345. [3] KATANO H, NISHIKAWAY, UCHIDA M, et al. Secular trends and features of thalamic hemorrhages compared with other hypertensive intracerebral hemorrhages: an 18-year single-center retrospective assessment [J]. Frontiers in neurology, 2023, 14: 1205091. [4] KASE C S, HANLEY D F. Intracerebral Hemorrhage: Advances in Emergency Care [J]. Neurologic clinics, 2021, 39(2): 405-18. [5] BRODERICK M, ROSIGNOLI L, LUNAGARIYAA, et al. Hypertension is a Leading Cause of Nontraumatic Intracerebral Hemorrhage in Young Adults [J]. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 2020, 29(5): 104719. [6] PURRUCKER J C, STEINER T. [Atypical intracerebral hemorrhage-etiology and acute management] [J]. Der Nervenarzt, 2019, 90(4): 423-41. [7] JIMéNEZ-RUIZ A, BECERRA-AGUIAR N N, AGUILAR-FUENTES V, et al. Expanding Diagnostic Workup for hypertensive Intracerebral hemorrhage: a retrospective LATAM cerebrovascular registry comparison [J]. Revista de investigacion clinica; organo del Hospital de Enfermedades de la Nutricion, 2024, 76(5): 213-22. [8] KLAVANSKY D, DAVIS N, LAY C. Emergency department management of acute intracerebral hemorrhage [J]. Emergency medicine practice, 2023, 25(Suppl 7): 1-41. [9] HALLER J T, WISS A L, MAY C C, et al. Acute Management of Hypertension Following Intracerebral Hemorrhage [J]. Critical care nursing quarterly, 2019, 42(2): 129-47. [10] ZHAO J, YUAN F, FU F, et al. Hypertension management in elderly with severe intracerebral hemorrhage [J]. Annals of clinical and translational neurology, 2021, 8(10): 2059-69. [11] SCHRAG M, KIRSHNER H. Management of Intracerebral Hemorrhage: JACC Focus Seminar [J]. Journal of the American College of Cardiology, 2020, 75(15): 1819-31. [12] MAGID-BERNSTEIN J, GIRARD R, POLSTER S, et al. Cerebral Hemorrhage: Pathophysiology, Treatment, and Future Directions [J]. Circulation research, 2022, 130(8): 1204-29. [13] WAN Y, HOLSTE K G, HUA Y, et al. Brain edema formation and therapy after intracerebral hemorrhage [J]. Neurobiology of disease,2023, 176: 105948. [14] KIRSHNER H, SCHRAG M. Management of Intracerebral Hemorrhage: Update and Future Therapies [J]. Current neurology and neuroscience reports, 2021, 21(10): 57. [15] DING W, GU Z, SONG D, et al. Development and validation of the hypertensive intracerebral hemorrhage prognosis models [J]. Medicine, 2018, 97(39): e12446. [16] ZHU Z Y, HAO L F, GAO L C, et al. Determinants of acute and subacute case-fatality in elderly patients with hypertensive intracerebral hemorrhage [J]. Heliyon, 2023, 9(10): e20781. [17] WANG S, WANG R, LI X, et al. A nomogram based on systemic inflammation response index and clinical risk factors for prediction of short-term prognosis of very elderly patients with hypertensive intracerebral hemorrhage [J]. Frontiers in medicine, 2025, 12: 1535443. [18] XIA Y, WANG R. Effect and prognosis of endoscopic intracranial hematoma removal and hematoma puncture and drainage in patients with hypertensive intracerebral hemorrhage [J]. Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques, 2024, 19(2): 266-73. [19] QIU M, SATO S, ZHENG D, et al. Admission Heart Rate Predicts Poor Outcomes in Acute Intracerebral Hemorrhage: The Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial Studies [J]. Stroke, 2016, 47(6): 1479-85. [20] WANG D, JIANG R, KANG K, et al. Association of severity and prognosis with elevated blood pressure and heart rate levels in patients with intracerebral hemorrhage [J]. BMC neurology, 2023, 23(1): 361. [21] ZHANG J, ZHANG N, LI X, et al. Retrospective analysis of prognostic factors in HICH patients after neuroendoscopic hematoma evacuation [J]. Scientific reports, 2024, 14(1): 29505. [22] SREEKRISHNAN A, DEARBORN J L, GREER D M, et al. Intracerebral Hemorrhage Location and Functional Outcomes of Patients: A Systematic Literature Review and Meta-Analysis [J]. Neurocritical care, 2016, 25(3): 384-91. [23] 王芙蓉.自发性大容积脑出血监测与治疗——中国专家共识[J].中华脑血管病杂志(电子版),2021,15(06):431. [24] LIANG S, TIAN X, GAO F, et al. Prognostic significance of the stress hyperglycemia ratio and admission blood glucose in diabetic and nondiabetic patients with spontaneous intracerebral hemorrhage [J]. Diabetology & metabolic syndrome, 2024, 16(1): 58. [25] GONG Y, WANG Y, CHEN D, et al. Predictive value of hyperglycemia on prognosis in spontaneous intracerebral hemorrhage patients [J]. Heliyon, 2023, 9(3): e14290. [26] 李思,王赛,张雨蓬,等.糖尿病/高血糖对脑出血预后的影响:动物实验 meta 分析[J].国际神经病学神经外科学杂志,2022,49(03):59-65. [27] TEASDALE G, JENNETT B. Assessment of coma and impaired consciousness. A practical scale [J]. Lancet (London, England), 1974, 2(7872): 81-4. [28] WONGVIBULSIN S, WU K C, ZEGER S L. Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis [J]. BMC medical research methodology, 2019, 20(1): 1. [29] ANGHELE A D, MARINA V, DRAGOMIR L, et al. Predicting Deep Venous Thrombosis Using Artificial Intelligence: A Clinical Data Approach [J]. Bioengineering (Basel, Switzerland), 2024, 11(11). [30] 王小曼,游一鸣,韩梦琦,等.基于机器学习模型对缺血性脑卒中住院期间死亡风险的预测[J].现代预防医学, 2024,51(19):3457-3462+3482. [31] MAO B, LING L, PAN Y, et al. Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit [J]. Scientific reports, 2024, 14(1): 14195. [32] 蒋小兵.基于机器学习的高血压脑出血血肿扩大因素分析及应用[D].西安医学院,2021. [33] LI Y, DU C, GE S, et al. Hematoma expansion prediction based on SMOTE and XGBoost algorithm [J]. BMC medical informatics and decision making, 2024, 24(1): 172.
Full Text:
DOI