CARDIOMETABOLIC RISK PREDICTION IN PATIENTS WITH NON-ALCOHOLIC FATTY LIVER DISEASE COMBINED WITH SUBCLINICAL HYPOTHYROIDISM

Olena Kolesnikova

kolesnikova1973@gmail.com
Government Institution "L. T. Malaya Therapy Institute of the National Academy of Medical Science of Ukraine", Kharkiv, Ukraine (Ukraine)
http://orcid.org/0000-0001-5606-6621

Olena Vysotska


National Aerospace University "Kharkiv Aviation Institute", Kharkiv, Ukraine (Ukraine)
http://orcid.org/0000-0003-3723-9771

Anna Potapenko


Government Institution "L. T. Malaya Therapy Institute of the National Academy of Medical Science of Ukraine", Kharkiv, Ukraine (Ukraine)
http://orcid.org/0000-0002-1658-0156

Anastasia Radchenko


Government Institution "L. T. Malaya Therapy Institute of the National Academy of Medical Science of Ukraine", Kharkiv, Ukraine (Ukraine)
http://orcid.org/0000-0002-9687-8218

Anna Trunova


National Aerospace University "Kharkiv Aviation Institute", Kharkiv, Ukraine (Ukraine)
http://orcid.org/0000-0001-7069-0674

Natalia Virstyuk


Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine (Ukraine)
http://orcid.org/0000-0002-5794-8754

Liudmyla Vasylevska-Skupa


Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine (Ukraine)
http://orcid.org/0000-0002-1989-7175

Aliya Kalizhanova


Institute of Information and Computational Technologies, Almaty, Kazakhstan (Kazakhstan)
http://orcid.org/0000-0002-5979-9756

Nazerka Mukanova


Gymnasium No. 159 named after Y. Altynsarin, Almaty, Kazakhstan (Kazakhstan)
http://orcid.org/0009-0002-7945-7187

Abstract

One of the most common diseases of our time is non-alcoholic fatty liver disease (NAFLD). Recently published research results indicate that patients with NAFLD along with traditional risk factors for cardiovascular diseases (CVD) have "new" risk factors such as endothelial dysfunction (ED), carotid intima-media thickness (CIMT), an increase in the CRP level, as well as risk factors combined into the Framingham scale. It is also known that combination of NAFLD with subclinical hypothyroidism (SH) forms an abnormal metabolic phenotype, which is associated with cardiometabolic risk factors. The study of cardiometabolic predictors and vascular markers in patients with NAFLD in combination with SH will provide an opportunity to improve the strategy of cardiovascular events prevention in such comorbid patients.


Keywords:

cardiometabolic risk, non-alcoholic fatty liver disease, subclinical hypothyroidism, prediction, binary regression logistic analysis, validation of prognostic models

Bano A., Chaker L., Plompen E. P. C., et al.: Thyroid Function and the Risk of Nonalcoholic Fatty Liver Disease: The Rotterdam Study. J Clin Endocrinol Metab. 101(8), 2016, 3204–3211.
DOI: https://doi.org/10.1210/jc.2016-1300   Google Scholar

Belyalov F. I.: Prognozirovaniye i shkaly v kardiologii 2ye-izd. MEDPRESS-inform, Moscow 2018.
  Google Scholar

Belialov F. I.: Risk prediction scores of diseases. Complex Issues of Cardiovascular Diseases 7(1), 2018, 84–93 [http://doi.org/10.17802/2306-1278-2018-7-1-84-93].
DOI: https://doi.org/10.17802/2306-1278-2018-7-1-84-93   Google Scholar

Georgiyants M., Khvysyuk O., Boguslavskaуa N. et al.: Development of a mathematical model for predicting postoperative pain among patients with limb injuries. Eastern-European Journal of Enterprise Technologies 2, N4(86), 2017, 4–9 [http://doi.org/10.15587/1729-4061.2017.95157].
DOI: https://doi.org/10.15587/1729-4061.2017.95157   Google Scholar

Graham I., Atar D., Borch-Johnsen K. et al.: European guidelines on cardiovascular disease prevention in clinical practice: full text. Eur. J. Cardiovasc. Prev. Rehabil. 14, 2007, S1–S113.
  Google Scholar

Kojuri J., Boostani R., Dehghani P., Nowroozipour F., Saki N.: Prediction of acute myocardial infarction with artificial neural networks in patients with nondiagnostic electrocardiogram. Journal of Cardiovascular Disease Research. 6(2), 2015, 51–60.
DOI: https://doi.org/10.5530/jcdr.2015.2.2   Google Scholar

Kolesnikova E. V.: Sovremennyy patsiyent s zabolevaniyem pechenii patologiyey serdechno-sosudistoy sistemy: kakoy vybor sdelat? Contemporary gastroenterology 2(76), 2014, 85–94.
  Google Scholar

Kolesnikova O. V., Nemtsova V. D.: Effect of preventive measures for major metabolic parameters in patients with non-alcoholic fatty liver disease and cardiovascular risk. The ESC Textbook of Preventive Cardiology. Comprehensive, practical, and the official textbook of the European Association for Cardiovascular Prevention and Rehabilitation. Oxford University press, 2015.
  Google Scholar

Koval S. M., Snihurska I. O., Vysotska O. et al.: Prognosis of essential hypertension progression in patients with abdominal obesity. Wójcik W., Pavlov S., Kalimoldayev, M. (Eds.): Information Technology in Medical Diagnostics II. Taylor & Francis Group, CRC Press, Balkema book, London 2019.
DOI: https://doi.org/10.1201/9780429057618-32   Google Scholar

Krak I. V., Kryvonos I. G., Kulias A. I.: Applied aspects of the synthesis and analysis of voice information. Cybernetics and Systems Analysis 49(4), 2013, 589–596.
DOI: https://doi.org/10.1007/s10559-013-9545-9   Google Scholar

Krak I., Kondratiuk S.: Cross-platform software for the development of sign communication system: Dactyl language modelling. 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies – CSIT, 2017, 1,8098760, 167–170
DOI: https://doi.org/10.1109/STC-CSIT.2017.8098760   Google Scholar

Ludwig U., Holzner D., Denzer C. et al.: Subclinical and clinical hypothyroidism and non-alcoholic fatty liver disease: a cross-sectional study of a random population sample aged 18 to 65 years. BMC Endocr Disord. 15. 2015, 41.
DOI: https://doi.org/10.1186/s12902-015-0030-5   Google Scholar

Ross D. S., Burch G. B, Cooper D. S. et al.: American Thyroid Association Guidelines for Diagnosis and Management of Hyperthyroidism and other causes of Thyrotoxicosis. Thyroid 26(10), 2016, 1343–1421.
DOI: https://doi.org/10.1089/thy.2016.0229   Google Scholar

Sinn D. H., Cho S. J., Gu S. et al.: Persistent Nonalcoholic Fatty Liver Disease Increases Risk for Carotid Atherosclerosis. Gastroenterology 151(3), 2016, 481–488.
DOI: https://doi.org/10.1053/j.gastro.2016.06.001   Google Scholar

Strashnenko A. N., Vysotskaya E. V., Demin Y. A. et al.: A method for prognosis of primary open-angle glaucoma. International Review on Computers and Software 8, 2013, 1943–1949.
  Google Scholar

Weiwei He, Xiaofei An, Ling Li et al.: Relationship between Hypothyroidism and Non-Alcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis. Front Endocrinol (Lausanne) 8, 2017, 335.
DOI: https://doi.org/10.3389/fendo.2017.00335   Google Scholar

Weng S. F., Reps J., Kai J., Garibaldi J. M., Qureshi N.: Can machinelearning improve cardiovascular risk prediction using routine clinical data? PLOS ONE 12(4), 2017, e0174944 [http://doi.org/10.1371/journal.pone.0174944].
DOI: https://doi.org/10.1371/journal.pone.0174944   Google Scholar

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Published
2023-06-30

Cited by

Kolesnikova, O., Vysotska, O., Potapenko, A., Radchenko, A., Trunova, A., Virstyuk, N., … Mukanova, N. (2023). CARDIOMETABOLIC RISK PREDICTION IN PATIENTS WITH NON-ALCOHOLIC FATTY LIVER DISEASE COMBINED WITH SUBCLINICAL HYPOTHYROIDISM. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 13(2), 64–68. https://doi.org/10.35784/iapgos.3654

Authors

Olena Kolesnikova 
kolesnikova1973@gmail.com
Government Institution "L. T. Malaya Therapy Institute of the National Academy of Medical Science of Ukraine", Kharkiv, Ukraine Ukraine
http://orcid.org/0000-0001-5606-6621

Authors

Olena Vysotska 

National Aerospace University "Kharkiv Aviation Institute", Kharkiv, Ukraine Ukraine
http://orcid.org/0000-0003-3723-9771

Authors

Anna Potapenko 

Government Institution "L. T. Malaya Therapy Institute of the National Academy of Medical Science of Ukraine", Kharkiv, Ukraine Ukraine
http://orcid.org/0000-0002-1658-0156

Authors

Anastasia Radchenko 

Government Institution "L. T. Malaya Therapy Institute of the National Academy of Medical Science of Ukraine", Kharkiv, Ukraine Ukraine
http://orcid.org/0000-0002-9687-8218

Authors

Anna Trunova 

National Aerospace University "Kharkiv Aviation Institute", Kharkiv, Ukraine Ukraine
http://orcid.org/0000-0001-7069-0674

Authors

Natalia Virstyuk 

Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine Ukraine
http://orcid.org/0000-0002-5794-8754

Authors

Liudmyla Vasylevska-Skupa 

Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine Ukraine
http://orcid.org/0000-0002-1989-7175

Authors

Aliya Kalizhanova 

Institute of Information and Computational Technologies, Almaty, Kazakhstan Kazakhstan
http://orcid.org/0000-0002-5979-9756

Authors

Nazerka Mukanova 

Gymnasium No. 159 named after Y. Altynsarin, Almaty, Kazakhstan Kazakhstan
http://orcid.org/0009-0002-7945-7187

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