American Journal of Clinical and Experimental Medicine

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Statistical Analysis of Brain Natriuretic Peptide in the Treatment of Heart Failure

Received: 10 June 2015    Accepted: 15 June 2015    Published: 18 September 2015
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Abstract

In the clinical researches, large number of clinical verifications has demonstrated that the Brain Natriuretic Peptide can be used in heart failure detection. Some relevant studies illustrate Plasma Brain Natriuretic Peptide can be affected by many factors, such as gender, age, environment of therapy, and so forth. This paper analyzes valid data of a clinical experiment, and finds out the influence of concomitant variables in diagnose of heart failure, then analyzes the outcome of rhNRG-1 on each individual. The phrase ‘Brain Natriuretic Peptide’ in the article specified N-terminal Prohormone of Brain Natriuretic Peptide (Nt-Pro BNP) in this dissertation. In this paper, the main analyzing method is Logistic Regression. It is used for estimating the Parameters of a qualitative model. The outcome, in other words, the probabilities is to describe the possible results of a single trial. By using this method, we could discuss the triggers of diseases and popularize it to other problems that concentrate on the cause. Moreover, the binary logistic model is for predicting a binary response based on one or more predictor variables. The main steps of this dissertation is data screening, missing values handling, descriptive statistics analyzing, then the Logistic Regression, and finally draw a conclusion.

DOI 10.11648/j.ajcem.20150305.14
Published in American Journal of Clinical and Experimental Medicine (Volume 3, Issue 5, September 2015)
Page(s) 222-227
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

N-terminal Prohormone, Brain Natriuretic Peptide, Heart Failure, Biostatistics, Logistic Regression

References
[1] Safety and feasibility of using serial infusions of nesiritide for heart failure in an out patient setting (from the FUSION I trial). Yancy CW et al. American Journal of Cardiology. 2004 1; 94(5):595-601.
[2] Liu Xin, Tong Wang. Clinical significance and research progress of brain natriuretic peptide in plasma. International Journal of medical testing medicine 2009.3. 30 No. 3.
[3] Shi Chenghu, Hu Fengtao. Clinical application of BNP brain natriuretic peptide [R]. Hubei County, Huanggang City, Huangmei Province, the people's Hospital, laboratory. 1671-8194 (2013) 12-0470-02.
[4] Chen Xiaofei. BNP value analysis of cardiac function classification and prognosis in patients with chronic heart failure [J]. Modern diagnosis and treatment, 2012.Dec23 (12): 2122-2123.
[5] Liang Xiaoying. The influence factors of BNP and NT-proBNP detection threshold concentration [J]. Chinese Practical Medicine, December 2007 second volume thirty-sixth: 161-163.
[6] Zheng Siju. B type natriuretic peptide as indicators of the significance of determination of heart dysfunction [J]. Shenyang army medicine, May 2005 eighteenth volume third: 209-211.
[7] Han Jing. History, status quo and future of heart failure drug therapy [C]. 2012.4.12.
[8] Yang Yurong. Clinical significance of B natriuretic peptide in heart failure [J]. Chinese modern drug application, August 2010 fourth volume fifteenth: 39-40.
[9] Zhang Xiaojun. The effect of BNP on the cardiac function classification in patients with heart failure J Lab Diagn March, Vol16, 2012, No.3:472-474. Chin.
[10] Xiao Yipin. To investigate the clinical analysis of surgical treatment for colon cancer [J], Chinese health nutrition clinical medicine, 2013.12 (on):6961-6962.
[11] Zhang Xiaohui, Essien, Huo Xinghui, Li Lu. Discussion on the standardization of clinical trial management for drugs [J], Changchun Institute of traditional Chinese Medicine 2003 3.
Author Information
  • Mathematics and Applied Mathematics, Hangzhou Dianzi University, Zhejiang, China

  • School of Information, Beijing Wuzi University, Beijing, China

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    Yizeng Li, Hong Zhang. (2015). Statistical Analysis of Brain Natriuretic Peptide in the Treatment of Heart Failure. American Journal of Clinical and Experimental Medicine, 3(5), 222-227. https://doi.org/10.11648/j.ajcem.20150305.14

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    ACS Style

    Yizeng Li; Hong Zhang. Statistical Analysis of Brain Natriuretic Peptide in the Treatment of Heart Failure. Am. J. Clin. Exp. Med. 2015, 3(5), 222-227. doi: 10.11648/j.ajcem.20150305.14

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    AMA Style

    Yizeng Li, Hong Zhang. Statistical Analysis of Brain Natriuretic Peptide in the Treatment of Heart Failure. Am J Clin Exp Med. 2015;3(5):222-227. doi: 10.11648/j.ajcem.20150305.14

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  • @article{10.11648/j.ajcem.20150305.14,
      author = {Yizeng Li and Hong Zhang},
      title = {Statistical Analysis of Brain Natriuretic Peptide in the Treatment of Heart Failure},
      journal = {American Journal of Clinical and Experimental Medicine},
      volume = {3},
      number = {5},
      pages = {222-227},
      doi = {10.11648/j.ajcem.20150305.14},
      url = {https://doi.org/10.11648/j.ajcem.20150305.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajcem.20150305.14},
      abstract = {In the clinical researches, large number of clinical verifications has demonstrated that the Brain Natriuretic Peptide can be used in heart failure detection. Some relevant studies illustrate Plasma Brain Natriuretic Peptide can be affected by many factors, such as gender, age, environment of therapy, and so forth. This paper analyzes valid data of a clinical experiment, and finds out the influence of concomitant variables in diagnose of heart failure, then analyzes the outcome of rhNRG-1 on each individual. The phrase ‘Brain Natriuretic Peptide’ in the article specified N-terminal Prohormone of Brain Natriuretic Peptide (Nt-Pro BNP) in this dissertation. In this paper, the main analyzing method is Logistic Regression. It is used for estimating the Parameters of a qualitative model. The outcome, in other words, the probabilities is to describe the possible results of a single trial. By using this method, we could discuss the triggers of diseases and popularize it to other problems that concentrate on the cause. Moreover, the binary logistic model is for predicting a binary response based on one or more predictor variables. The main steps of this dissertation is data screening, missing values handling, descriptive statistics analyzing, then the Logistic Regression, and finally draw a conclusion.},
     year = {2015}
    }
    

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    AU  - Yizeng Li
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    JO  - American Journal of Clinical and Experimental Medicine
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    AB  - In the clinical researches, large number of clinical verifications has demonstrated that the Brain Natriuretic Peptide can be used in heart failure detection. Some relevant studies illustrate Plasma Brain Natriuretic Peptide can be affected by many factors, such as gender, age, environment of therapy, and so forth. This paper analyzes valid data of a clinical experiment, and finds out the influence of concomitant variables in diagnose of heart failure, then analyzes the outcome of rhNRG-1 on each individual. The phrase ‘Brain Natriuretic Peptide’ in the article specified N-terminal Prohormone of Brain Natriuretic Peptide (Nt-Pro BNP) in this dissertation. In this paper, the main analyzing method is Logistic Regression. It is used for estimating the Parameters of a qualitative model. The outcome, in other words, the probabilities is to describe the possible results of a single trial. By using this method, we could discuss the triggers of diseases and popularize it to other problems that concentrate on the cause. Moreover, the binary logistic model is for predicting a binary response based on one or more predictor variables. The main steps of this dissertation is data screening, missing values handling, descriptive statistics analyzing, then the Logistic Regression, and finally draw a conclusion.
    VL  - 3
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    ER  - 

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