Determination of the probable time of myocardial infarction development in patients with type 2 diabetes mellitus
https://doi.org/10.52727/2078-256X-2021-17-2-12-21
Abstract
Aim of the study was to create a method for assessing the probabilistic time of development of acute myocardial infarction (AMI) in patients with a confirmed diagnosis of type 2 diabetes mellitus (DM).
Material and methods. The work was carried out on the basis of the Regional Vascular Center No. 1 (Novosibirsk). A retrospective analysis of the data of 115 patients diagnosed with AMI in combination with verified type 2 DM who were hospitalized in the period from 2018 to 2019 was performed. In all patients included in the study, clinical and demographic, anamnestic, physical, functional, and laboratory data were assessed in accordance with the federal standard for the diagnosis and treatment of this pathology. The nature and duration of the course, drug therapy for diabetes mellitus were assessed according to medical documents and databases. Further, a regression model was built for assessing the probabilistic time of development of AMI in patients with type 2 DM.
Results. The author’s model for assessing the probabilistic time of development of acute myocardial infarction in patients with type 2 DM included eight indicators that significantly correlated with the dependent variable and weakly correlated with each other: patient gender, chronic kidney disease with a decrease in glomerular filtration rate to 60 ml/min/1.73 m2, diabetic retinopathy, verified peripheral polyneuropathy, cigarette smoking 1 pack or more, the number of hemodynamically significant coronary artery stenoses according to the results of selective coronary angiography, the use of short-acting insulin as part of hypoglycemic therapy, the use of long-acting insulin as part of hypoglycemic therapy.
Conclusion. The study demonstrates the high predictive ability of the author’s approach for determining the individual predicted time for the development of AMI in a patient with type 2 DM. The introduction of the developed method into real clinical practice will make it possible to personally manage type 2 DM patients and to reduce the individual risk of such a formidable cardiovascular complication as myocardial infarction.
About the Authors
N. G. LozhkinaRussian Federation
630091, Novosibirsk, Krasny av., 52
630008, Novosibirsk, Leningradskaya str., 113
A. A. Tolmacheva
Russian Federation
630091, Novosibirsk, Krasny av., 52
Yu. E. Voskoboinikov
Russian Federation
630089, Novosibirsk, Boris Bogatkov str., 175/1
V. N. Maksimov
Russian Federation
630047, Novosibirsk, Zalesskogo str., 6
Yu. I. Ragino
Russian Federation
630047, Novosibirsk, Zalesskogo str., 6
Yu. I. Bravve
Russian Federation
630091, Novosibirsk, Krasny av., 52
630008, Novosibirsk, Leningradskaya str., 113
References
1. Rawshani A., Rawshani A., Franzén S., Sattar N., Eliasson B., Svensson A.M., Zethelius B., Miftaraj M., McGuire D.K., Rosengren A., Gudbjörnsdottir S. Risk factors, mortality, and cardiovascular outcomes in patients with type 2 diabetes. N. Engl. J. Med., 2018; 379 (7): 633–644. doi: 10.1056/NEJMoa1800256
2. Lejay A., Fang F., John R., Van J.A., Barr M., Thaveau F., Chakfe N., Geny B., Scholey J.W. Ischemia reperfusion injury, ischemic conditioning and diabetes mellitus. J. Mol. Cell. Cardiol., 2016 Feb; 91: 11–22. doi: 10.1016/j.yjmcc.2015.12.020
3. Sathyapalan T. Pre-diabetes mellitus newly diagnosed after myocardial infarction adversely affects prognosis in patients without known diabetes. Diab. Vasc. Dis. Res., 2019 Nov; 16 (6): 489–497. doi: 10.1177/1479164119845561
4. Cosentino F., Grant P.J., Aboyans V., Bailey C.J., Ceriello A., Delgado V., Federici M., Filippatos G., Grobbee D.E., Hansen T.B., Huikuri H.V., Johansson I., Juni P., Lettino M., Marx N., Mellbin L.G., Ostgren C.J., Rocca B., Roffi M., Sattar N., Seferovic P.M., Sousa-Uva M., Valensi P., Wheeler D.C., Group E.S.C.S.D. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur. Heart J., 2020; 41 (2): 255–323. doi: 10.1093/eurheartj/ehz486
5. Garganeeva A.A., Kuzheleva E.A., Borel K.N., Kondratyeva D.S., Afanasiev S.A. Diabetes mellitus type 2 and acute myocardial infarction: prognostic options for interaction in patients of different age groups. Diabetes Mellitus., 2018; 21 (2): 105–112. (In Russ.) doi: 10.14341/DM8828
6. Mardanov B.U., Pyak V.Е., Korneeva M.N., Akhmedova E.B. The influence of diabetes mellitus on the course and outcomes of myocardial infarction in patients undergoing percutaneous coronary interventions. Cardiovascular Therapy and Prevention, 2016; 15 (6): 13–18. (In Russ.) doi: 10.15829/1728-8800-2016-6-13-18
7. Ibanez B., James S., Agewall S., Antunes M.J., Bucciarelli-Ducci C., Bueno H., Caforio A.L.P., Crea F., Goudevenos J.A., Halvorsen S., Hindricks G., Kastrati A., Lenzen M.J., Prescott E., Roffi M., Valgimigli M., Varenhorst C., Vranckx P., Widimsky P., Group E.S.C.S.D. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur. Heart. J., 2018; 39 (2): 119–177. doi: 10.1093/eurheartj/ehx393
8. Yunkerov V.I., Grigorev S.G. Mathematical and statistical processing of medical research data. S.-Petersburg: VMedA, 2002. P. 266. (In Russ.)
9. Voskoboinikov Yu.E. Econometrics in Excel: Paired and Multiple Regression Models. S.-Petersburg: Lan’, 2016. P. 260. (In Russ.)
10. Edqvist J., Rawshani A., Adiels M., Björck L., Lind M., Svensson A.M., Gudbjörnsdottir S., Sattar N., Rosengren A. Contrasting associations of body mass index and hemoglobin A1c on the excess risk of acute myocardial infarction and heart failure in type 2 diabetes mellitus. J. Am. Heart Assoc., 2019; 8 (24): e013871. doi: 10.1161/JAHA.119.013871
11. Action to Control Cardiovascular Risk in Diabetes Follow-On (ACCORDION) eye study group and the Action to Control Cardiovascular Risk in Diabetes Follow-On (ACCORDION) study group. Persistent effects of intensive glycemic control on retinopathy in type 2 diabetes in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) follow-on study. Diabetes Care, 2016; 39 (7): 1089–1100. doi: 10.2337/dc16-0024
12. Agashe S., Petak S. Cardiac autonomic neuropathy in diabetes mellitus. Methodist Debakey. Cardiovasc. J., 2018; 14 (4): 251–256. doi: 10.14797/mdcj-14-4-251
13. Ruospo M., Saglimbene V.M., Palmer S.C., de Cosmo S., Pacilli A., Lamacchia O., Cignarelli M., Fioretto P., Vecchio M., Craig J.C., Strippoli G.F. Glucose targets for preventing diabetic kidney disease and its progression. Cochrane Database Syst. Rev., 2017; 6 (6): CD010137. doi: 10.1002/14651858.CD010137.pub2
14. Lo C., Toyama T., Wang Y., Lin J., Hirakawa Y., Jun M., Cass A., Hawley C.M., Pilmore H., Badve S.V., Perkovic V., Zoungas S. Insulin and glucose-lowering agents for treating people with diabetes and chronic kidney disease. Cochrane Database Syst. Rev., 2018; 9 (9): CD011798. doi: 10.1002/14651858.CD011798.pub2
15. Dasgupta I., Singh A.K. Review: In diabetes, intensive and standard glycemic control do not differ for endstage kidney disease or death. Ann. Intern. Med., 2017; 167 (8): JC47. doi: 10.7326/ACPJC-2017-167-8-047
16. Cushman W.C., Whelton P.K., Fine L.J., Wright J.T.Jr, Reboussin D.M., Johnson K.C., Oparil S.; SPRINT Study Research Group. SPRINT trial results: Latest news in hypertension management. Hypertension, 2016; 67 (2): 263–265. doi: 10.1161/hypertensionaha.115.06722
Review
For citations:
Lozhkina N.G., Tolmacheva A.A., Voskoboinikov Yu.E., Maksimov V.N., Ragino Yu.I., Bravve Yu.I. Determination of the probable time of myocardial infarction development in patients with type 2 diabetes mellitus. Ateroscleroz. 2021;17(2):12-21. (In Russ.) https://doi.org/10.52727/2078-256X-2021-17-2-12-21