科目
Help ?

IGMIN: あなたがここにいてくれて嬉しいです. お願いクリック '新しいクエリを作成してください' 当ウェブサイトへの初めてのご訪問で、さらに情報が必要な場合は.

すでに私たちのネットワークのメンバーで、すでに提出した質問に関する進展を追跡する必要がある場合は, クリック '私のクエリに連れて行ってください.'

科学、技術、工学、医学（STEM）分野に焦点を当てています | ISSN: 2995-8067  G o o g l e  Scholar

logo image

IgMin Research | マルチディシプリナリーオープンアクセスジャーナルは、科学、技術、工学、医学（STEM）の広範な分野における研究と知識の進展に貢献することを目的とした権威ある多分野のジャーナルです.

31 of 152
Enforcement and Enlargement of the Saccharomyces cerevisiae Endoplasmic Reticulum through Artificial Evocation of the Unfolded Protein Response
Masaki Monguchi and Yukio Kimata
33 of 152
On the Governing Equations for Velocity and Shear Stress of some Magnetohydrodynamic Motions of Rate-type Fluids and their Applications
Constantin Fetecau
Abstract

要約 at IgMin Research

私たちの使命は、学際的な対話を促進し、広範な科学領域にわたる知識の進展を加速することです.

Biology Group Mini Review 記事ID: igmin143

The Model for Clinical, Laboratory, and Genetic Prediction of Recurrent Ischemic Stroke against the Background of Laboratory Aspirin Resistance using Machine Learning

Molecular Biology
Anastasia V Anisimova 1 ,
Sergey S Galkin * 1 ,
Anastasia S Gunchenko 1 ,
Tatyana V Nasedkina 2 and
Igor V Vorobiev 2
Affiliation

Affiliation

    Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, Moscow, Russia

    Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, Moscow, Russia

    Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, Moscow, Russia

    Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, Moscow, Russia

    Engelhardt Institute of Molecular Biology RAS, Moscow, Russia

    Engelhardt Institute of Molecular Biology RAS, Moscow, Russia

DOI10.61927/igmin143 全文HTML 全文PDF この記事を引用する
DOI10.61927/igmin143 全文HTML 全文PDF この記事を引用する

要約

The aim of the study was to determine the incidence of laboratory aspirin resistance; and to study the associations of genetic markers and clinical and laboratory parameters (including parameters of the platelet hemostasis) in patients with non-cardioembolic ischemic stroke using machine learning methods to assess the prognosis of recurrent ischemic strokes. Clinical and laboratory data (including induced platelet aggregation) were analyzed from 296 patients with ischemic stroke who were treated in the stroke center of City Clinical Hospital No. 1 named after. N.I. Pirogov. The frequencies of polymorphic variants of the ITGB3, GPIba, TBXA2R, ITGA2, PLA2G7, HMOX1, PTGS1, PTGS2, ADRA2A, ABCB1, PEAR1 genes and intergenic region 9p21.3) in patients with non-cardioembolic ischemic stroke, which were identified using hydrogel biochip technology, were determined. Using the developed machine learning model, additional clinical and genetic factors influencing the development of laboratory aspirin resistance and recurrent ischemic stroke were studied. In the future, the identified factors can be used for differentiated prevention of recurrent ischemic strokes.

数字

NIHSS scores at admission and discharge. Figure 1: NIHSS scores at admission and discharge....
Biological microchip for genetic marker analysis. Figure 2: Biological microchip for genetic marker analysis....
Machine learning pipeline. Figure 3: Machine learning pipeline....
Feature importance ranking obtained using SHAP values. Variables are listed in order of significance from top to bottom along the y-axis. Each dot represents a patient, and its color indicates the value of the corresponding variable. The position of the points on the x-axis represents SHAP values indicating changes in log odds, and the probability of success can be extracted from this value. Figure 4: Feature importance ranking obtained using SHAP val...
Receiver Operating Characteristic (ROC) Curve. Figure 5: Receiver Operating Characteristic (ROC) Curve....

参考文献

    1. Anisimova AV, Gunchenko AS, Ikonnikova AY, Galkin SS, Avdonina MA, Nasedkina TV. Kliniko-geneticheskiĭ analiz faktorov riska razvitiia ostroĭ i khronicheskoĭ ishemii golovnogo mozga [A clinical and genetic analysis of risk factors for the development of acute and chronic cerebral ischemia]. Zh Nevrol Psikhiatr Im S S Korsakova. 2019;119(3. Vyp. 2):62-67. Russian. doi: 10.17116/jnevro201911903262. PMID: 31184626.
    2. Anisimova AV, Gunchenko AS, Avdonina MA, Ikonnikova AU, Nasedkina TV. Clinical features and genetic risk factors in the development of ischemic stroke. Ural Medical Journal. 2017; T. 153: 9.
    3. Anisimova AV, Gendlin GE, Borisov SN. [Prevention of stroke in patients with atrial fibrillation: a role of modern anticoagulants]. Zh Nevrol Psikhiatr Im S S Korsakova. 2013;113(9 Pt 2):62-9. Russian. PMID: 24107898.
    4. Galkin SS, Gunchenko AS, Abdukhalikova Z, Yutskova EV, Anisimova AV. Dinamika pokazatelei trombotsitarnogo gemostaza u patsientov s kardioembolicheskim insul'tom [Dynamics of platelet hemostasis indices in patients with cardioembolic stroke against the background of atrial fibrillation]. Zh Nevrol Psikhiatr Im S S Korsakova. 2021;121(12. Vyp. 2):62-68. Russian. doi: 10.17116/jnevro202112112262. PMID: 35044128.
    5. Storozhakov GI, Gendlin GE, Anisimova AV, Melekhov AV, Ostrovskaya YI. Taktika antigipertenzivnoĭ terapii u patsientov s gipertonicheskim krizom, oslozhnennym gemorragicheskim insul'tom [Tactics of antihypertensive therapy in patients with hypertonic crisis complicated with hemorrhagic stroke]. Zh Nevrol Psikhiatr Im S S Korsakova. 2015;115(3 Pt 2):12-19. Russian. doi: 10.17116/jnevro2015115312-19. PMID: 26120992.
    6. Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh EE 3rd. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993 Jan;24(1):35-41. doi: 10.1161/01.str.24.1.35. PMID: 7678184.
    7. Saini V, Guada L, Yavagal DR. Global Epidemiology of Stroke and Access to Acute Ischemic Stroke Interventions. Neurology. 2021 Nov 16;97(20 Suppl 2):S6-S16. doi: 10.1212/WNL.0000000000012781. PMID: 34785599.
    8. Potter TBH, Tannous J, Vahidy FS. A Contemporary Review of Epidemiology, Risk Factors, Etiology, and Outcomes of Premature Stroke. Curr Atheroscler Rep. 2022 Dec;24(12):939-948. doi: 10.1007/s11883-022-01067-x. Epub 2022 Nov 14. PMID: 36374365; PMCID: PMC9660017.
    9. Feigin VL, Brainin M, Norrving B, Martins S, Sacco RL, Hacke W, Fisher M, Pandian J, Lindsay P. World Stroke Organization (WSO): Global Stroke Fact Sheet 2022. Int J Stroke. 2022 Jan;17(1):18-29. doi: 10.1177/17474930211065917. Erratum in: Int J Stroke. 2022 Apr;17(4):478. PMID: 34986727.
    10. Pohl M, Hesszenberger D, Kapus K, Meszaros J, Feher A, Varadi I, Pusch G, Fejes E, Tibold A, Feher G. Ischemic stroke mimics: A comprehensive review. J Clin Neurosci. 2021 Nov;93:174-182. doi: 10.1016/j.jocn.2021.09.025. Epub 2021 Sep 20. PMID: 34656244.
    11. Zheng S, Yao B. Impact of risk factors for recurrence after the first ischemic stroke in adults: A systematic review and meta-analysis. J Clin Neurosci. 2019 Feb;60:24-30. doi: 10.1016/j.jocn.2018.10.026. Epub 2018 Oct 16. PMID: 30340974.
    12. Fernández-Cadenas I, Mendióroz M, Giralt D, Nafria C, Garcia E, Carrera C, Gallego-Fabrega C, Domingues-Montanari S, Delgado P, Ribó M, Castellanos M, Martínez S, Freijo M, Jiménez-Conde J, Rubiera M, Alvarez-Sabín J, Molina CA, Font MA, Grau Olivares M, Palomeras E, Perez de la Ossa N, Martinez-Zabaleta M, Masjuan J, Moniche F, Canovas D, Piñana C, Purroy F, Cocho D, Navas I, Tejero C, Aymerich N, Cullell N, Muiño E, Serena J, Rubio F, Davalos A, Roquer J, Arenillas JF, Martí-Fábregas J, Keene K, Chen WM, Worrall B, Sale M, Arboix A, Krupinski J, Montaner J; GRECOS Study Group. GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke. Stroke. 2017 May;48(5):1147-1153. doi: 10.1161/STROKEAHA.116.014322. Epub 2017 Apr 14. PMID: 28411264; PMCID: PMC5473776.
    13. Pezzini A, Grassi M, Del Zotto E, Lodigiani C, Ferrazzi P, Spalloni A, Patella R, Giossi A, Volonghi I, Iacoviello L, Magoni M, Rota LL, Rasura M, Padovani A. Common genetic markers and prediction of recurrent events after ischemic stroke in young adults. Neurology. 2009 Sep 1;73(9):717-23. doi: 10.1212/WNL.0b013e3181b59aaf. PMID: 19720979.
    14. Ding L, Liu Y, Meng X, Jiang Y, Lin J, Cheng S, Xu Z, Zhao X, Li H, Wang Y, Li Z. Biomarker and genomic analyses reveal molecular signatures of non-cardioembolic ischemic stroke. Signal Transduct Target Ther. 2023 May 30;8(1):222. doi: 10.1038/s41392-023-01465-w. PMID: 37248226; PMCID: PMC10227023.
    15. Dash P, Singh VK, Gautam D, Pathak A, Kumar A, Mishra SP, Dash D, Mishra VN, Joshi D, Chaurasia RN. Aspirin resistance and blood biomarkers in predicting ischemic stroke recurrence: An exploratory study. Brain Circ. 2022 Mar 21;8(1):31-37. doi: 10.4103/bc.bc_75_21. PMID: 35372727; PMCID: PMC8973447.
    16. Parsa-Kondelaji M, Mansouritorghabeh H. Aspirin and clopidogrel resistance; a neglected gap in stroke and cardiovascular practice in Iran: a systematic review and meta-analysis. Thromb J. 2023 Jul 27;21(1):79. doi: 10.1186/s12959-023-00522-2. PMID: 37501091; PMCID: PMC10373335.
    17. Ross S, Krebs K, Paré G, Milani L. Pharmacogenomics in Stroke and Cardiovascular Disease: State of the Art. Stroke. 2023 Jan;54(1):270-278. doi: 10.1161/STROKEAHA.122.037717. Epub 2022 Nov 3. PMID: 36325912.
    18. Morton M, Kubiak-Balcerewicz K, Sarnowska A, Fiszer U. Biochemical aspirin resistance in acute stroke patients and its association with clinical factors: a prospective pilot study. Folia Neuropathol. 2021;59(3):271-275. doi: 10.5114/fn.2021.109434. PMID: 34628792.
    19. Wang H, Yuan J, Wang Y, Chen J. To study the mechanism of panax notoginseng in the treatment of aspirin resistance in the secondary prevention of stroke based on TLR4/MyD88/NF-κB signaling pathway: A study protocol. Medicine (Baltimore). 2022 Dec 16;101(50):e31919. doi: 10.1097/MD.0000000000031919. PMID: 36550905; PMCID: PMC9771212.
    20. Venketasubramanian N, Agustin SJ, Padilla JL, Yumul MP, Sum C, Lee SH, Ponnudurai K, Gan RN. Comparison of Different Laboratory Tests to Identify "Aspirin Resistance" and Risk of Vascular Events among Ischaemic Stroke Patients: A Double-Blind Study. J Cardiovasc Dev Dis. 2022 May 12;9(5):156. doi: 10.3390/jcdd9050156. PMID: 35621867; PMCID: PMC9145610.
    21. Li Z, Dong W, Yang D, Sun L, He X, Hu H, Zhang J, Wang C, Li Y, Zhao M, Kong Y, Wang Y. Body weight, CYP2C19, and P2Y12 receptor polymorphisms relate to clopidogrel resistance in a cohort of Chinese ischemic stroke patients with aspirin intolerance. Eur J Clin Pharmacol. 2020 Nov;76(11):1517-1527. doi: 10.1007/s00228-020-02946-5. Epub 2020 Jul 6. PMID: 32632713.
    22. Wiśniewski A, Filipska K, Sikora J, Kozera G. Aspirin Resistance Affects Medium-Term Recurrent Vascular Events after Cerebrovascular Incidents: A Three-Year Follow-up Study. Brain Sci. 2020 Mar 19;10(3):179. doi: 10.3390/brainsci10030179. PMID: 32204465; PMCID: PMC7139350.
    23. Alhazzani A, Venkatachalapathy P, Padhilahouse S, Sellappan M, Munisamy M, Sekaran M, Kumar A. Biomarkers for Antiplatelet Therapies in Acute Ischemic Stroke: A Clinical Review. Front Neurol. 2021 Jun 10;12:667234. doi: 10.3389/fneur.2021.667234. PMID: 34177775; PMCID: PMC8222621.
    24. Silva GFD, Lopes BM, Moser V, Ferreira LE. Impact of pharmacogenetics on aspirin resistance: a systematic review. Arq Neuropsiquiatr. 2023 Jan;81(1):62-73. doi: 10.1055/s-0042-1758445. Epub 2023 Mar 14. PMID: 36918009; PMCID: PMC10014202.
    25. Dorogush Veronika A, Ershov V, Gulin A. CatBoost: Gradient boosting with categorical features support. ArXiv. 2018; arXiv: 1810.11363.
    26. Lundberg Scott M, Lee S. A unified approach to interpreting model predictions. Adv. Neural Inf. Process. Syst. 2017; 30: 4768-4777.

ソーシャルアイコン

Page Navigation

タイトルと著者 要約 数字 参考文献 類似の記事
研究を公開する

私たちは、科学、技術、工学、医学に関する幅広い種類の記事を編集上の偏見なく公開しています。

提出する

見る 原稿のガイドライン 追加 論文処理料

IgMin 科目を探索する
Biology Medicine Engineering

現在トレンドになっている記事はどれですか？

トップ10の記事をクリック

クイックリンク

原稿を提出する
IgMinリサーチを購読する

発表された記事、号のリリース、ジャーナル活動の最新情報についてのお知らせを受け取るために、メールアドレスを入力してください。

研究論文
  1. Problem of Surface Waves on Water in Higher School Laboratory Workshop
  2. DNA Genetics and UHPLC-Q-TOF-MS Analysis of Phytochemicals for Asparagus racemosus Roots
  3. Solar Energy Resource Potentials of the City of Arkadag
  4. Designing a Compact High-precision Positioner with Large Stroke Capability for Nanoindentation Devices
  5. Efficient Room Temperature Ethanol Vapor Sensing by Unique Fractal Features of Tin Oxide
  6. A Comprehensive Methodology for Assessing the Business Reputation of Industrial and Production Personnel
もっと読む
グーグルスカラー
welcome Image

Google Scholarは2004年11月にベータ版が発表され、幅広い学術領域を航海する学術ナビゲーターとして機能します。それは査読付きジャーナル、書籍、会議論文、論文、博士論文、プレプリント、要約、技術報告書、裁判所の意見、特許をカバーしています。 IgMin の記事を検索