Development of an algorithm for predicting the risk of cough development during enalapril therapy in patients with arterial hypertension

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Abstract

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%.

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About the authors

I. V. Sychev

Russian Medical Academy of Continuous Professional Education

Author for correspondence.
Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-0227-2651
SPIN-code: 5162-3779

Junior Researcher, Research Institute of Molecular and Personalized Medicine

Russian Federation, Moscow

N. P. Denisenko

Russian Medical Academy of Continuous Professional Education

Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-3278-5941
SPIN-code: 5883-6249
Russian Federation, Moscow

A. V. Lapshtaeva

Ogarev Mordovia State University

Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-4828-2476
SPIN-code: 9138-6257
Russian Federation, Saransk

A. A. Kachanova

Russian Medical Academy of Continuous Professional Education

Email: sychev_iv@bk.ru
ORCID iD: 0000-0003-3194-4410
SPIN-code: 1214-8156
Russian Federation, Moscow

Sh. P. Abdullaev

Russian Medical Academy of Continuous Professional Education

Email: sychev_iv@bk.ru
ORCID iD: 0000-0001-9001-1499
SPIN-code: 1727-2158
Russian Federation, Moscow

Yu. Yu. Kupriyanov

Ogarev Mordovia State University

Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-4993-5515
SPIN-code: 7488-1830
Russian Federation, Saransk

L. N. Goncharova

Ogarev Mordovia State University

Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-4324-9071
SPIN-code: 5684-9502
Russian Federation, Saransk

K. B. Mirzaev

Russian Medical Academy of Continuous Professional Education

Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-9307-4994
SPIN-code: 8308-7599
Russian Federation, Moscow

D. A. Sychev

Russian Medical Academy of Continuous Professional Education

Email: sychev_iv@bk.ru
ORCID iD: 0000-0002-4496-3680
SPIN-code: 4525-7556
Russian Federation, Moscow

References

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  10. Sychev I.V., Denisenko N.P., Kachanova A.A., et al. Pharmacogenetic predictors of development of secondary to enalapril dry cough in hypertensive patients. Drug Metab Personal Ther. 2023;38(3):247–54. doi: 10.1515/dmpt-2023-0008.
  11. Сычев И.В., Денисенко Н.П., Качанова А.А. и др. Клинико-анамнестические предикторы развития сухого кашля у пациентов с кардиоваскулярной патологией на фоне приема эналаприла. Безопасность и риск фармакотерапии. 2023;11(2):231–40. [Sychev I.V., Denisenko N.P., Kachanova A.A., et al. Clinical Signs and Medical History as Predictors of Enalapril-Associated Dry Cough in Cardiovascular Patients. Safety Risk Pharmacother. 2023;11(2):231–40. (In Russ.)]. doi: 10.30895/2312-7821-2023-11-2-231-240.

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2. Fig. ROC curve of the logistic regression model

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