Derivation of a Prediction Rule for Unfavorable Outcome after Ischemic Stroke in the Chinese Population

被引:2
|
作者
Mao, Haifeng [1 ]
Wu, Qianyi [2 ,3 ]
Lin, Peiyi [1 ]
Mo, Junrong [1 ]
Jiang, Huilin [1 ]
Lin, Shaopeng [1 ]
Rainer, Timothy H. [4 ]
Chen, Xiaohui [1 ]
机构
[1] Guangzhou Med Univ, Emergency Dept, Affiliated Hosp 2, Guangzhou, Guangdong, Peoples R China
[2] Guangzhou Med Univ, Affiliated Hosp 2, Inst Neurosci, Guangzhou, Guangdong, Peoples R China
[3] Guangzhou Med Univ, Affiliated Hosp 2, Dept Neurol, Guangzhou, Guangdong, Peoples R China
[4] Cardiff Univ, Inst Mol & Expt Med, Welsh Heart Res Inst, Sch Med, Cardiff, S Glam, Wales
关键词
prognosis; ischemic stroke; NIHSS; emergency department; decision curve analysis; ATRIAL-FIBRILLATION; NUTRITIONAL-STATUS; POOR OUTCOMES; URIC-ACID; BILIRUBIN; SCALE; RISK; PREALBUMIN; DISABILITY; MORTALITY;
D O I
10.1016/j.jstrokecerebrovasdis.2018.09.025
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: Efficient assessment of patients after ischemic stroke has important reference value for doctors to choose appropriate treatment for patients. Our study aimed to develop a new prognostic model for predicting outcomes 3 months after ischemic stroke among Chinese Population. Methods: A prospective observational cohort study among ischemic stroke patients presenting to Emergency Department in the Second Affiliated Hospital of Guangzhou Medical University was conducted from May 2012 to June 2013. Demographic data of ischemic stroke patients, assessment of NIHSS and laboratory results were collected. Based on 3-month modified Rankin Scale (mRS) ischemic stroke patients were divided into either favorable outcome (mRS: 0-2) or unfavorable outcome groups (mRS: 3-6). The variables closely associated with prognosis of ischemic stroke were selected to develop the new prognostic model (NAAP) consisted of 4 parameters: NIHSS, age, atrial fibrillation, and prealbumin. The prognostic value of the modified prognostic model was then compared with NIHSS alone. Results: A total of 454 patients with suspected stroke were recruited. One hundred eighty-six patients with ischemic stroke were included in the final analysis. A new prognostic model, NAAP was developed. The area under curve (AUC) of NAAP was .861 (95%confidence interval: .803-.907), whilst the AUC of NIHSS was .783 (95%CI: .717-.840), (P = .0048). Decision curve analysis showed that NAAP had a higher net benefit for threshold probabilities of 65% for predictive risk of poor outcomes. Conclusions: The modified prognostic model, NAAP may be a better prognostic tool for predicting 3-month unfavorable outcomes for ischemic stroke than NIHSS alone.
引用
收藏
页码:133 / 141
页数:9
相关论文
共 50 条
  • [21] Can HRV Predict Prolonged Hospitalization and Favorable or Unfavorable Short-Term Outcome in Patients with Acute Ischemic Stroke?
    Aftyka, Joanna
    Staszewski, Jacek
    Debiec, Aleksander
    Pogoda-Wesolowska, Aleksandra
    Zebrowski, Jan
    LIFE-BASEL, 2023, 13 (04):
  • [22] Stroke Severity and Comorbidity Index for Prediction of Mortality after Ischemic Stroke from the Virtual International Stroke Trials Archive-Acute Collaboration
    Phan, Thanh G.
    Clissold, Benjamin
    Ly, John
    Ma, Henry
    Moran, Chris
    Srikanth, Velandai
    JOURNAL OF STROKE & CEREBROVASCULAR DISEASES, 2016, 25 (04) : 835 - 842
  • [23] Low Pulse Pressure After Acute Ischemic Stroke is Associated With Unfavorable Outcomes: The Taiwan Stroke Registry
    Tang, Sung-Chun
    Yin, Jiu-Haw
    Liu, Chung-Hsiang
    Sun, Ming-Hui
    Lee, Jiunn-Tay
    Sun, Yu
    Hsu, Chih-Shan
    Sun, Mu-Chien
    Lin, Ching-Huang
    Chen, Chih-Hung
    Lien, Li-Ming
    Muo, Chih-Hsin
    Jeng, Jiann-Shing
    Hsu, Chung Y.
    JOURNAL OF THE AMERICAN HEART ASSOCIATION, 2017, 6 (06):
  • [24] Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction
    Jabal, Mohamed Sobhi
    Joly, Olivier
    Kallmes, David
    Harston, George
    Rabinstein, Alejandro
    Huynh, Thien
    Brinjikji, Waleed
    FRONTIERS IN NEUROLOGY, 2022, 13
  • [25] The Association of Glaucoma with Ischemic Stroke and Functional Outcome after Ischemic Stroke from the Perspective of Causality
    He, Qiang
    Wang, Wenjing
    Xu, Dingkang
    Xiong, Yang
    Tao, Chuanyuan
    Ma, Lu
    You, Chao
    CEREBROVASCULAR DISEASES, 2025, 53 (06) : 674 - 682
  • [26] Prediction of functional outcome of ischemic stroke patients in northwest China
    Liu, Xuedong
    Lv, Yali
    Wang, Bo
    Zhao, Gang
    Yan, Yongping
    Xu, Dezhong
    CLINICAL NEUROLOGY AND NEUROSURGERY, 2007, 109 (07) : 571 - 577
  • [27] An Association Study on Renalase Polymorphisms and Ischemic Stroke in a Chinese Population
    Zhang, Ruyou
    Li, Xiaoying
    Liu, Nana
    Guo, Xijuan
    Liu, Wei
    Ning, Chunping
    Wang, Zhenzhen
    Sun, Litao
    Fu, Songbin
    NEUROMOLECULAR MEDICINE, 2013, 15 (02) : 396 - 404
  • [28] Adiponectin Gene Polymorphism and Ischemic Stroke Subtypes in a Chinese Population
    Li, Shanshan
    Lu, Ning
    Li, Zhongnan
    Jiao, Bin
    Wang, Hanping
    Yang, Jia
    Yu, Tao
    JOURNAL OF STROKE & CEREBROVASCULAR DISEASES, 2017, 26 (05) : 944 - 951
  • [29] Outcome Prediction Models for Endovascular Treatment of Ischemic Stroke: Systematic Review and External Validation
    Kremers, Femke
    Venema, Esmee
    Duvekot, Martijne
    Yo, Lonneke
    Bokkers, Reinoud
    Nijeholt, Geert Lycklama A.
    van Es, Adriaan
    van der Lugt, Aad
    Majoie, Charles
    Burke, James
    Roozenbeek, Bob
    Lingsma, Hester
    Dippel, Diederik
    STROKE, 2022, 53 (03) : 825 - 836
  • [30] Clinical and biochemical predictors of late-outcome in patients after ischemic stroke
    Bielewicz, Joanna Ewa
    Kurzepa, Jacek
    Kamieniak, Piotr
    Daniluk, Beata
    Szczepanska-Szerej, Anna
    Rejdak, Konrad
    ANNALS OF AGRICULTURAL AND ENVIRONMENTAL MEDICINE, 2020, 27 (02) : 290 - 294