Development of an algorithm for predicting the risk of cough development during enalapril therapy in patients with arterial hypertension
- 作者: Sychev I.V.1, Denisenko N.P.1, Lapshtaeva A.V.2, Kachanova A.A.1, Abdullaev S.P.1, Kupriyanov Y.Y.2, Goncharova L.N.2, Mirzaev K.B.1, Sychev D.A.1
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隶属关系:
- Russian Medical Academy of Continuous Professional Education
- Ogarev Mordovia State University
- 期: 卷 31, 编号 9 (2024)
- 页面: 150-154
- 栏目: Коморбидность
- URL: https://journals.eco-vector.com/2073-4034/article/view/680155
- DOI: https://doi.org/10.18565/pharmateca.2024.9.150-154
- ID: 680155
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详细
Background. Angiotensin-converting enzyme inhibitors (ACE inhibitors), in particular enalapril, have retained a leading role in the treatment of arterial hypertension (AH) over the past decades, but at the same time have a side effect in the form of cough, which is one of the main reasons for a significant decrease in the quality of life of patients and subsequent drug withdrawal. An important clinical task is to create an algorithm for predicting the risk of cough development for personalizing enalapril therapy.
Objective. Creation of an algorithm for predicting the risk of cough development while taking enalapril for personalizing ACE inhibitor therapy in hypertensive patients.
Methods. To create an algorithm for predicting the risk of cough development while taking enalapril, multivariate modeling was performed using the logistic regression method.
Results. During the multivariate logistic regression analysis, genetic factors were selected in the form of rs2306283 SLCO1B1, rs495828 ABO, rs8176746 ABO gene polymorphisms, as well as data on the presence of allergic diseases and manifestations in close relatives, which together formed a model for predicting the risk of cough development while taking enalapril in hypertensive patients.
Conclusion. The presented model demonstrates high prognostic significance, has sufficient information content (R2=0.31) and allows to predict the development of cough while taking enalapril with an accuracy of 76.5%.
全文:
作者简介
I. Sychev
Russian Medical Academy of Continuous Professional Education
编辑信件的主要联系方式.
Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-0227-2651
SPIN 代码: 5162-3779
Junior Researcher, Research Institute of Molecular and Personalized Medicine
俄罗斯联邦, MoscowN. Denisenko
Russian Medical Academy of Continuous Professional Education
Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-3278-5941
SPIN 代码: 5883-6249
俄罗斯联邦, Moscow
A. Lapshtaeva
Ogarev Mordovia State University
Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-4828-2476
SPIN 代码: 9138-6257
俄罗斯联邦, Saransk
A. Kachanova
Russian Medical Academy of Continuous Professional Education
Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-3194-4410
SPIN 代码: 1214-8156
俄罗斯联邦, Moscow
Sh. Abdullaev
Russian Medical Academy of Continuous Professional Education
Email: sychev_iv@bk.ru
ORCID iD: 0000-0001-9001-1499
SPIN 代码: 1727-2158
俄罗斯联邦, Moscow
Yu. Kupriyanov
Ogarev Mordovia State University
Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-4993-5515
SPIN 代码: 7488-1830
俄罗斯联邦, Saransk
L. Goncharova
Ogarev Mordovia State University
Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-4324-9071
SPIN 代码: 5684-9502
俄罗斯联邦, Saransk
K. Mirzaev
Russian Medical Academy of Continuous Professional Education
Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-9307-4994
SPIN 代码: 8308-7599
俄罗斯联邦, Moscow
D. Sychev
Russian Medical Academy of Continuous Professional Education
Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-4496-3680
SPIN 代码: 4525-7556
俄罗斯联邦, Moscow
参考
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