РИСКИ СЕРДЕЧНО-СОСУДИСТЫХ ОСЛОЖНЕНИЙ У БОЛЬНЫХ САХАРНЫМ ДИАБЕТОМ 2-ГО ТИПА (НА ПРИМЕРЕ ПОЛИКЛИНИК ГОРОДА АЛМАТЫ)

Молдобаева М.С.; Барменбаева М.О,; Красницкая М.В.

DOI: 10.32415/jscientia_2022_8_4_23�36

��

EDN: ASJXIN

�� -�� 2-�� (�� )

1

�. �. �� 1, �. �. �� 2, �. �. ��

1 �� . �.�. ��, ��, �� 2 �� . �.�. ��, ��, ��

. �� m_moldobaeva@mail.ru

��. �� (��) �� (��) ��-�� (��) �� -�� . ��, �� , �� , �� . �� . �� 398 �� 2-�� (�� 2) � �� . ��, � �� , �� , �� (��) � ��. � �� 4 ��. �� SC/EASD (2019) � ESC/EACPR (2016) �� . ��. �� (�� 8,18�8,7%, �� 3,24�3,79 ��/�, �� 1,94�2,24 ��/�, �� 138,7�150,6/84,4� 91,9 �� . ��.) �� (�� <7�7,5%), �� (�� < 1,4 ��/�, �� < 1,7 ��/�), �� (�� 120�130/70�80 �� . ��.) � �� (�� 208�1080 ��/��, �� (CKD-EPI) 50,6�80,6 ��/��), �� . ��. �� 2 � �� . �� : �� (100%), �� (�� 18,1% �� 31,8% � �� ), �� (100%), � �� (�� 13,8% �� 52,1% � �� ). �� 2, �� .

�� : �� , �� , �� , ��.

�� : �� .�., �� .�., �� .�. �� -�� 2-�� (�� ) // Juvenis scientia. 2022. �� 8. � 4. �. 23�36. DOI: 10.32415/jscientia_2022_8_4_23�36. EDN: ASJXIN.

�� Creative Commons �Attribution� (��) 4.0 ��.

DOI: 10.32415/jscientia_2022_8_4_23�36

Original article

EDN: ASJXIN

RISKS OF CARDIOVASCULAR COMPLICATIONS IN PATIENTS WITH TYPE 2 DIABETES MELLITUS (BY THE EXAMPLE OF POLYCLINICS IN ALMATY)

1

M. S. Moldobaeva 1, M. O. Barmenbaeva 2, M. V. Krasnitskaya

1 Kyrgyz State Medical Academy named after I.K. Akhunbaev, Bishkek, Kyrgyz Republic 2 Kazakh National Medical University named after S.D. Asfendiyarov, Almaty, Republic of Kazakhstan

. Moldobaeva Marina � m_moldobaeva@mail.ru

INTRODUCTION. In diabetes mellitus, uncontrolled hyperglycemia and a combination of risk factors (RF) of cardiovascular complications (CVC) are the causes of fatal cardiovascular events. Achieving tar�get levels of glycemia, blood pressure, lipid profile, and weight loss has been shown to slow or stabilize CVC. PATIENTS AND METHODS. We examined 398 patients with type 2 diabetes in outpatient clinics of Almaty city according to conventional criteria of carbohydrate and fat metabolism disorders, arterial hypertension (AH) and detection of nephropathy. Depending on the duration of diabetes mellitus, pa�tients were divided into 4 groups. Risk groups of CVC were identified according to ESC/EASD (2019) and ESC/EACPR (2016) categories. RESULTS. All examined patients did not reach (glycated hemoglobin 8.18�8.7%, LDL cholesterol 3.24�

3.79 mmol/l, triglycerides 1.94�2.24 mmol/l, blood pressure 138.7�150.6/84.4�91.9 mm Hg) target levels of carbohydrate (glycated hemoglobin <7�7.5%), fat metabolism (LDL cholesterol < 1.4 mmol/l, triglycerides < 1.7 mmol/l), blood pressure (BP 120�130/70�80 mm Hg). They also had signs of ne�phropathy (daily albuminuria 208�1080 mg/d, GFR (CKD-EPI) 50.6�80.6 ml/min), which were more pro�nounced with increasing duration of DM. CONCLUSION. The patients with type 2 diabetes in polyclinics of Almaty city have very high category of cardiovascular risk in all groups due to the following RF: dyslipidemia (100%), AH (from 18.1% to 31.8% depending on the duration of diabetes), excessive body weight (100%), as well as target organ damage such as diabetic nephropathy (from 13.8% to 52.1% depending on the duration of diabetes). Primary care physicians inevitably meet with patients with type 2 diabetes mellitus, so it is important to start combating the individual risks of CVC already in this area of health care.

KEYWORDS: diabetes mellitus, risk factors, categories of cardiovascular risk, polyclinic.

FOR CITATION: Moldobaeva MS, Barmenbaeva MO, Krasnitskaya MV. Risks of cardiovascular complica�tions in patients with type 2 diabetes mellitus (by the example of polyclinics in Almaty). Juvenis scientia. 2022;8(4):23�36. DOI: 10.32415/jscientia_2022_8_4_23-36.

This article is licensed under a Creative Commons Attribution 4.0 International License.

��

�� (��) � �� , �� -�� (��).

�� (HbA1c) [1].

�� (��) �� , �� , �� . � �� 4045 �� 60 �� 79 �� -�� (��) � �� 2-�� (�� 2) .8 �� 2 �� 2 ��; �� 2 � �� .60 �� (��) �� [2]. ��, �� HbA1c �� 1% �� 2 �� 30-�� -�� (��) � �� [3]. �� , �� [4].

�� 2 �� 15 % �� . �� 2 �� 32%, �� 21%, �� 10%, �� 7,6 % [5]. �� 2 �� 127�160 %, �� 56%, �� 132% � �� 5,8 �� 6,4 �� 50 �� [6, 7], � �� , �� 49,6% �� 2 �� [5]. �� (IDF) � 2021 �� 6,7 �� 20�79 �� , �� 12,2% �� [8]; � 2019 �� [9].

�� , �� b�1� >8 % �� 36,0 % �� 2, �� (��) � 69,1 %, �� 44,2 %, �� 27,3 %, �� 10,2 %, �� (��) � 16,3 %, �� 7,0 %. �� , �� , �� , �� HbA1c, �� (��) �� (��) � �� (��) [10]. � �� LIPIDOGRAM (2015) �� , �� -�� , �� HbA1c <7 % �� 55 % �� 2, �� 48 % �� 43 % �� (p<0,01), �� (<1,4 ��/�, � �� ESC/EAS, 2019) � ��, �� 5 % ��, �� , �� , �� , �� . �� (<1,8 ��/�, ESC/EAS, 2011) �� , �� -�� 10 % �� [11]. �� DA VINCI �� -�� (ESC/EAS, 2019) � 54 % �� [12].

�� , ��, �� , �� . �� , �� [9]. �� 2 ��, �� , �� , �� (��), �� HbA1c � ��-�� [13].

�� (��), �� (��-��) � �� , �� [14]. �� The UK Prospective Diabetes Study (UKPDS) ��, �� 2 �� 16 % �� , �.�. ��-�� (��) �� 2 [15]. �� [16, 17].

�� , �� (��) � �� -�� (��) �� [18].

�� ESC/EASD (2019) �� ESC/ EACPR (2016) �� : �� , �� (��, �� , �� <60 ��/��/1,73 �2 , �� (��) �� ), �� .3 �� (��, ��, ��, ��, ��), �� 1-�� (�� 1) � �� >20 ��; �� .10 �� ; �� <10 �� [19, 20].

�� (ADA, 2022) �� / �� (Risk Estimator Plus) (�� tools.acc.org/ASCVD-Risk-Estimator-Plus) [21].

�� , �� , �� , �� HbA1C, ��-�� [19, 22�25].

�� , �� , �� [9]. ��, �� , �� [26, 27]. �� 271174 �� 2 � �� (1355870 ��): �� HbA1c �� , �� , �� HbA1c, �� -�� -�� [13].

� �� (��) �� 2 � �� [28], � �� (��). �� , � �� , �� . �� . �� 1 �. �� (��). �� , �� 2 �� , �� -��, � 27% �� 58%; �� 17% �� 34%, �� 49% �� 90% [29]. �� . �� : �b�1� 7�9% �� 25,4% � �� 1 � 28,5% � �� 2, �b�1� >9% �� 60,6% � �� 1 � 63 % � �� 2 [30], �� -�� 50% �� , �� [31].

�� , �� .

�� , ��-�� , ��, ��, � �� 2 �� .

��

�� -�� 2-�� .

��

�� .� �� 2016�2019 �� [32], � �� (2000).

� �� . ��, �� 3� � �� 5�. �� (1964�2000) [33].

�� . �. �. �� (31.05.2016 �.). �� , �� 2,5 ��. �� . �� -�� 398 �� 2, � �� 144 �� 254 ��. �� 4 �� 2-�� : 1-� �� 3 �� (188 � 47,2%), 2-� �� 3 �� 5 �� (88 � 22,1 %), 3-� �� 5 �� 10 �� (78 � 19,6%), 4-� �� 10 � �� (44 � 11,1 %).

�� : �� 45�59 �� (�� , ��, 1962) [34], �� 2, �� HbA1c .6,5 % [35�37]. �� (�� I-II) �� . �� , �� 30 �� 2015 �� (�� 18) [38].

�� : ��, �� ; �� 2 �� , �� , �� , �� 3-� �� (�� 180/110 �� .��.), �� , �� (��) III-IV �� NYHA, �� III-IV ��, �� , �� 4�5, �� , �� , ��-��, ��, ��, �� , �� , �� .

�� (��) (�� ) [39] � �� (��, 1997) [40].

�� , �� 3 �� 2019 �� (�� 74) [41]. �� ESC/ESH (2018), ESC/EASD (2019) � ADA (2021) [19, 21, 23].

�� bA1� �� , �� [22, 42�44].

�� , ��-��, ��-�� COBAS INTEGRA 800 (�� , ��).

�� /�� URISTIK H8, H10, �11 � �11-��. �� , �� <30 ��/�� [45]. �� KDIGO (2012) [46].

�� COBAS INTEGRA 800 (�� , ��) �� . �� CREJ2 � �� 44�80 ��/� (0,50�0,90 ��/��), � �� 62�106 ��/� (0,70�1,20 ��/��) [47].

�� CKD-EPI (2009), �� [46, 48]. �� MDRD (2006) [49].

�� 2 � �� , �� ESC/EASD (2019) � ESC/ EACPR (2016) [19, 20].

�� (�), �� (.), �� R � 95-�� (��) � �� -�� [50, 51]. �� U �� (�� , ��, �� CKD-EPI � MDRD, �� , ��-��, ��-��, �� (��), ��) � �� (HbA1c, �� , ��). �� IBM SPSS Statistics ��

22.0 (SPSS Inc., Chicago, IL, USA).

��

�� 10 �� (88,9 %). �� 2 �� : � �� 55,2�4,7 ��, � �� 55,5�4,3 ��.

�� 1-� �� .

�� HbA1c �� . �� . �� , �� , �� , � �� , �� (��. ��. 1).

�� 1

��

�� (��/�) HbA1c (%)

1-� �� 10,05�2,77 8,70�1,81

2-� �� 9,86�3,78 8,58�1,86

3-� �� 9,08�2,28 8,18�1,57

4-� �� 10,20�2,24 8,58�1,90

�� : � �� 2 �� 10 �� , �� (p2�4<0,001; p3�4=0,002); �� -�� 2, �� (p>0,05). �� (p>0,05).

�� HbA1c � ��-�� (R=+0,375).

�� 398 �� : �� (20,1 %), �� (4,5 %), �� (6,3 %). �� 5,3% �� 3 �� 18,1 % �� 10 ��, �. �. �� (R= +0,83) (��. ��. 1).

�� , �� 150,6�1,9 �� . ��. � �� 91,9�1,3 �� . ��. �� 10 ��. �� . �� (�� p <0,01, p <0,001;

1�4 3�4

��ėp <0,001, p <0,001) (��. ��.2).

1�4 3�4

�� (p1�2<0,001, p <0,001, p <0,001), �� , � ��

2�3 3�4

��, �� (��. ��. 2).

�� 1-� �� 4-� �� (� 82,0�0,1 ��/� �� 130,5�0,7 ��/� (p<0,001), �� (p <0,001, p <0,001,

1�2 2�3

p3�4<0,001). �� CKD-EPI �� (p <0,001, p <0,001,

1�2 2�3

p3�4<0,001). ��, �� MDRD � �� 1-� �� (� �� 3 ��), �� 4-� ��.

�� 1. ��

�� 2. ��

�� . 2. �� , � �� 2 �� , �� , �� 3 ��, � �� , �� CKD-EPI �� 60 ��/��. �� , �� 30�300 ��/�� [52�55].

�� MDRD �� , �� . �� MDRD �� CKD-EPI, �� , � �� , �� , �� . �� , �� 3 ��, �� .

�� , �� , �� .

�� , �� 3 �� 7,9% �� , 13,8 % � ��, 18,1 % � ��; � ��

�� 2

��

�� (��/��) �� (CKD-EPI) (��/��)

�� 3 �� 208,0�1,4 (95% �� 207,8�208,2) 80,6�1,5 (95% �� 80,4�80,8)

3�5 �� 240,0�1,2 (95% �� 239,8�240,3) 68,2�1,7 (95% �� 67,8�68,6)

5�10 �� 434,0�0,5 (95% �� 433,9�434,1) 62,6�1,4 (95% �� 62,3�62,9)

�� 10 �� 1080,0�1,1 (95% �� 1079,6�1080,4) 50,6�1,9 (95% �� 49,9�51,3)

�� , �� . � �� 3 �� 5 �� 9,0 % �� , 29,4% ��, 20,5% � ��, � �� , �� . � �� 5 �� 10 �� 15,3 % �� , 37,1 % � ��, 19,3 % � ��, � �� , �� . � �� 10 �� 27,3 % �� , 52,1% ��, 31,8% ��, �� , �� .

�� , � �� : �� (100 %), �� (�� 18,1 % �� 31,8 %), �� (100 %), � �� (�� 13,8% �� 52,1%).

�� : ��, ��, �� , �� 2, � �� , � �� .

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

��

�� , �� 2-�� -�� . �� -�� , �� .

�� -�� 2-�� 3 � � 5 �. �� , �� . �� , �� 3 ��. �� , �� -�� .

�� -�� . �� , �� . �� 1-� ��. �� . �� 10 �� (�� CKD-EPI), � �� MDRD � �� 1-� ��. �� , � �� , �� 3 �� . �� -�� , �� , �� MDRD. �� , �� 3 �� .

�� , �� -�� , �� .

�� -�� : �� , ��, ��

�� [REFERENCES]

�� , ��, ��.

�� (��, ��, �� , ��) �� 2-�� , �� -�� .

��: �� .

�� : �� .

�� : �� , �� , �� .

1. Roussel R, Steg PG, Mohammedi K, et al. Prevention of cardiovascular disease through reduction of glycae�mic exposure in type 2 diabetes: A perspective on glucose-lowering interventions. Diabetes Obes Metab. 2018;20(2):238-244. DOI: 10.1111/dom.13033

2.

Wannamethee SG, Shaper AG, Whincup PH, et al. Impact of diabetes on cardiovascular disease risk and all-cause mortality in older men: influence of age at onset, diabetes duration, and established and novel risk factors. Arch Intern Med. 2011;171(5):404-410. DOI: 10.1001/archinternmed.2011.2

3.

Shah AS, Dolan LM, Kimball TR, et al. Influence of duration of diabetes, glycemic control, and traditional cardiovascular risk factors on early atherosclerotic vascular changes in adolescents and young adults with type 2 diabetes mellitus. J Clin Endocrinol Metab. 2009;94(10):3740-3745. DOI: 10.1210/jc.2008-2039

4.

Meyer MF, Lieps D, Schatz H, et al. Influence of the duration of type 2 diabetes on early functional and morphological markers of atherosclerosis compared to the impact of coexisting classic cardiovascular risk

factors. Exp Clin Endocrinol Diabetes. 2008;116(5):298-304. DOI: 10.1055/s-2008-1042404

5.

Einarson TR, Acs A, Ludwig C, Panton UH. Prevalence of cardiovascular disease in type 2 diabetes: a sys�tematic literature review of scientific evidence from across the world in 2007-2017. Cardiovasc Diabetol. 2018;17(1):83. DOI: 10.1186/s12933-018-0728-6

6.

Emerging Risk Factors Collaboration, Sarwar N, Gao P, et al. Diabetes mellitus, fasting blood glucose con�centration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215-2222. DOI: 10.1016/S0140-6736(10)60484-9

7.

Rao Kondapally Seshasai S, Kaptoge S, Thompson A, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829-841. DOI: 10.1056/NEJMoa1008862

8.

IDF Diabetes Atlas. 2021; 10th edition. 135 p.

9.

IDF Diabetes Atlas. 2019; 9th edition. 168 �.

10.

�� .�., �� .�., �� .�., � ��. �� 2 ��: �� -�� 2 // ��

��. 2016. �. 19, � 6. �. 443-456. [Dedov II, Kalashnikova MF, Belousov DYu, et al. Assessing rou�

tine healthcare pattern for type 2 diabetes mellitus in Russia: the results of �harmacoepidemiological

study (FORSIGHT-DM2). Diabetes Mellitus. 2016;19(6):443-456. (In Russ)]. DOI: 10.14341/DM8146, EDN:

ZXMDVZ

11.

Studzinski K, Tomasik T, Windak A, et al. The Differences in the Prevalence of Cardiovascular Disease, Its Risk Factors, and Achievement of Therapeutic Goals among Urban and Rural Primary Care Patients in Poland: Results from the LIPIDOGRAM 2015 Study. J Clin Med. 2021;10(23):5656. DOI: 10.3390/jcm10235656

12.

Ray KK, Molemans B, Schoonen WM, et al. EU-Wide Cross-Sectional Observational Study of Lipid-Modifying Therapy Use in Secondary and Primary Care: the DA VINCI study. Eur J Prev Cardiol. 2021;28(11):1279�1289. DOI: 10.1093/eurjpc/zwaa047

13.

Rawshani A, Rawshani A, Franzen S, et al. 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

14.

Sugden M. Holness M. Pathophysiology of diabetic dyslipidemia: implications for atherogenesis and treat�ment. Clin. Lipidol. 2011;6(4):401-411. DOI: 10.2217/clp.11.32

15.

Davis TM, Coleman RL, Holman RR; UKPDS Group. Prognostic significance of silent myocardial infarction in newly diagnosed type 2 diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS) 79. Circulation. 2013;127(9):980-987. DOI: 10.1161/CIRCULATIONAHA.112.000908

16.

Goldberg IJ. Clinical review 124: Diabetic dyslipidemia: causes and consequences. J Clin Endocrinol Metab. 2001;86(3):965-971. DOI: 10.1210/jcem.86.3.7304

17.

Shen X. Lipid disorders in diabetes mellitus and current management. Curr. Pharmaceut. Anal. 2007;3(1):17�24. DOI: 10.2174/157341207779802386

18.

Chronic Kidney Disease Prognosis Consortium, Matsushita K, van der Velde M, et al. Association of es�timated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in gen�eral population cohorts: a collaborative meta-analysis. Lancet. 2010;375(9731):2073-2081. DOI: 10.1016/ S0140-6736(10)60674-5

19.

Cosentino F, Grant PJ, Aboyans V, et al. 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/eur�heartj/ehz486

20.

Piepoli MF, Hoes AW, Agewall S, et al. 2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts)Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Eur Heart J. 2016;37(29):2315-2381. DOI: 10.1093/eurheartj/ ehw106

21.

American Diabetes Association Professional Practice Committee. 10. Cardiovascular Disease and Risk Management: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S144-S174. DOI: 10.2337/dc22-S010

22.

�� .�., �� .�., �� .�. �� . �.: �� , 2019. [Dedov II, Shestakova MV, Majorov AY. Algoritmy specializirovannoj medicinskoj pomoshhi bol'nym saharnym diabetom (Algorithms of specialized medical care for patients with diabetes mellitus). Moscow: UP PRINT, 2019. (in Russ)].

23.

Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hyperten�sion. Eur Heart J. 2018;39(33):3021-3104. DOI: 10.1093/eurheartj/ehy339

24.

American Diabetes Association. Standards of Medical Care in Diabetes-2022 Abridged for Primary Care Providers. Clin Diabetes. 2022;40(1):10-38. DOI: 10.2337/cd22-as01

25.

Grossman A, Grossman E. Blood pressure control in type 2 diabetic patients. Cardiovasc Diabetol.

2017;16(1):3. DOI: 10.1186/s12933-016-0485-3

26.

Napoli R, Formoso G, Piro S, et al. Management of type 2 diabetes for prevention of cardiovascular disease. An expert opinion of the Italian Diabetes Society. Nutr Metab Cardiovasc Dis. 2020;30(11):1926-1936. DOI: 10.1016/j.numecd.2020.07.012

27.

Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e563-e595. DOI: 10.1161/CIR.0000000000000677

28.

�� .�., �� .�., �� .�., � ��. �� 2020 ��. ��-��, 2021. [Zhangarasheva GK, Zhaksalykova GB, Kenesova AA, et al. Statisticheskij sbornik �Zdorov'e naselenija Respubliki Kazahstan i dejatel'nost' organizacij zdravoohranenija v 2020 godu� (Statistical collection "Health of the population of the Republic of Kazakhstan and the activities of health care organizations in 2020). Nur-Sultan, 2021. (in Russ)].

29.

�� .�., �� .�., �� .�., � ��. �� 1 �. �� (�� ) // �� . 2020. � 3. �. 488-494. [Zhakieva GR, Ibragimova NZ, Nurbaulina EB, et al. Evaluation of preliminary results of the implementation of the disease management program in the city polyclinic no. 1 in Aktobe (retro�spective study). Vestnik Kazahskogo Nacional'nogo medicinskogo universiteta. 2020;3:488-494. (in Russ)]. EDN: OFSKQW

30.

�� . �., �� . �., �� . �., � ��. �� 1 � 2 �� // �� . 2017. � 1. �. 308-312. [Nurbekova �A, Alipova AT, Konyrbaeva AB, et al. Comparative analysis the level of compensation between patients with type 1 and type 2 diabetes in Almaty. Vestnik Kazahskogo Nacional'nogo medicinskogo universiteta. 2017;1:308-312. (in Russ)]. EDN: XPAHCX

31. �� .�. �� -�� 2 �� . ��. ��. ... �� PhD. 2018. [Tazhieva AE. Sostojanie i sovershenstvovanie organizacii ambulatorno-poliklinicheskoj pomoshhi bol'nym saharnym diabetom 2 tipa v g. Almaty (State and improvement of the organization of outpatient care for patients with diabetes mellitus type 2 in Almaty): diss�2018. (in Russ)]

32.

�� . URL: https://bmcudp.kz/ ru/patients/prevention/puz/programmy-upravleniya-khronicheskimi-neinfektsionnymi-zabolevaniyami [Chronic Non-Communicable Disease Management Program. (in Russ). URL: https://bmcudp.kz/ru/pa�tients/prevention/puz/programmy-upravleniya-khronicheskimi-neinfektsionnymi-zabolevaniyami]

33.

�� . URL: http://rostgmu.ru/wp-content/ uploads/2014/12/WMA_Helsinki.pdf [The Declaration of Helsinki of the World Medical Association. (in Russ). URL: http://rostgmu.ru/wp-content/uploads/2014/12/WMA_Helsinki.pdf]

34.

�� . �� . �.: �� , 1985. [Demograficheskij jenciklope�dicheskij slovar'. Rabochaja klassifikacii vozrastnyh rubezhej vtoroj poloviny zhizni cheloveka (Demographic encyclopedic dictionary. Working Classification of the Second Half of Human Life). Moscow: Sovetskaja jenciklopedija, 1985. (in Russ)].

35.

MedElement: �� 2 �� (2017). URL: https://diseases.me�delement.com. [MedElement: Clinical Protocol for Type 2 Diabetes Mellitus (2017). (in Russ). URL: https://

diseases.medelement.com]

36.

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33 Suppl 1(Suppl 1):S62-S69. DOI: 10.2337/dc10-S062

37.

International Expert Committee. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care. 2009;32(7):1327-1334. DOI: 10.2337/dc09-9033

38.

MedElement: �� . �� (2015). URL: https://diseases.medelement.com. [MedElement: Ischemic heart disease. Stable exertional angina (2015). (in Russ). URL: https://diseases.medelement.com]

39.

Quetelet A. Sur l�homme et le developpement de ses facultes: ou, Essai de physique sociale. Paris, 1835.

40.

WHO. Obesity : preventing and managing the global epidemic : report of a WHO Consultation on Obesity, Geneva, 3-5 June 1997. URL: https://apps.who.int/iris/handle/10665/63854

41.

MedElement: �� (2019). URL: https://diseases. medelement.com. [MedElement: Arterial Hypertension Clinical Protocol (2019). (in Russ). URL: https:// diseases.medelement.com]

42.

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

American Diabetes Association. Standards of medical care in diabetes � 2019. Diabetes Care. 2019;42(1):1�193. DOI: 10.2337/cd18-0105

43.

Garber AJ, Abrahamson MJ, Barzilay JI, et al. Consensus Statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the Comprehensive Type 2 Diabetes Management Algorithm -2018 executive summary. Endocr Pract. 2018;24(1):91-120. DOI: 10.4158/CS�2017-0153

44.

Davies MJ, D'Alessio DA, Fradkin J, et al. Management of Hyperglycemia in Type 2 Diabetes, 2018. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2018;41(12):2669-2701. DOI: 10.2337/dci18-0033

45.

�� .�., �� .�., �� .�., � ��. �� . �� : �� , ��, �� // ��. 2012. �. 16, � 1. �. 89-115. [Smirnov AV, Shilov EM, Dobronravov VA, et al. Nacional'nye rekomendacii. Hronicheskaja bolezn' pochek: osnovnye principy skrininga, diagnostiki, profilaktiki i pod�hody k lecheniju (National guidelines. Chronic Kidney Disease: Basic Principles of Screening, Diagnosis, Prevention, and Treatment Approaches). Nefrologija. 2012;1(16):89-115 (in Russ)]. EDN: NJWAGE

46.

Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3:1-150. DOI: 10.1038/kisup.2012.73

47.

Myers GL, Miller WG, Coresh J, et al. Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program. Clin Chem. 2006;52(1):5-18. DOI: 10.1373/clinchem.2005.0525144

48.

Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-612. DOI: 10.7326/0003-4819-150-9-200905050-00006

49.

Shahbaz H, Gupta M. Creatinine Clearance. In: StatPearls. Treasure Island (FL): StatPearls Publishing; July 26, 2021.

50.

��-��. �� R. URL: https://www.easycalculation. com/ru/statistics/correlation.php. [Online calculator. Calculation of the correlation coefficient R (in Russ). URL: https://www.easycalculation.com/ru/statistics/correlation.php]

51.

��-��. �� . URL: https://math.semestr.ru/group/interval.php [Online calculator. �onfidence interval (in Russ). URL: https://math.semestr.ru/group/interval.php]

52.

Iseki K, Ikemiya Y, Iseki C, Takishita S. Proteinuria and the risk of developing end-stage renal disease. Kidney Int. 2003;63(4):1468-1474. DOI: 10.1046/j.1523-1755.2003.00868.x

53.

Mogensen CE. Microalbuminuria predicts clinical proteinuria and early mortality in maturity-onset diabe�tes. N Engl J Med. 1984;310(6):356-360. DOI: 10.1056/NEJM198402093100605

54.

Mogensen CE. Microalbuminuria as a predictor of clinical diabetic nephropathy. Kidney Int. 1987;31(2):673�689. DOI: 10.1038/ki.1987.50

55.

Verhave JC, Gansevoort RT, Hillege HL, et al. An elevated urinary albumin excretion predicts de novo de�velopment of renal function impairment in the general population. Kidney Int Suppl. 2004;(92):S18-S21.

DOI: 10.1111/j.1523-1755.2004.09205.x

�� [AUTHORS]

. �� , �� , ��, �� . �.�. ��; ORCID 0000-0001-5869-885X; email: m_moldobaeva@mail. ru.

�� , �� 1 �� . �.�. ��; ORCID 0000-0002-2952-1569.

�� , �� . �.�.��; ORCID 0000-0001-9500-6322.

. Moldobaeva Marina Satarovna, Doctor of Medical Sciences, Professor, Head of Department of Propaedeutics of Internal Medicine with Endocrinology Course, Kyrgyz State Medical Academy named after I.K. Akhunbaev; ORCID 0000�0001-5869-885X; email: m_moldobaeva@mail.ru.

Barmenbaeva Maira Olzhabaevna, Assistant, Department of General Medicine No. 1, Kazakh National Medical University named after

S.D. Asfendiyarov; ORCID 0000-0002-2952-1569.

Krasnitskaya Milena Vladimirovna, Assistant, Department of Propaedeutics of Internal Medicine with Endocrinology Course, Kyrgyz State Medical Academy named after I.K. Akhunbaev; ORCID 0000�0001-9500-6322.

�� : 14.07.2022 �� : 23.08.2022 ��: 30.08.2022

Аннотация научной статьи по клинической медицине, автор научной работы — Молдобаева М. С., Барменбаева М. О,, Красницкая М. В.

Похожие темы научных работ по клинической медицине , автор научной работы — Молдобаева М. С., Барменбаева М. О,, Красницкая М. В.

RISKS OF CARDIOVASCULAR COMPLICATIONS IN PATIENTS WITH TYPE 2 DIABETES MELLITUS (BY THE EXAMPLE OF POLYCLINICS IN ALMATY)

Текст научной работы на тему «РИСКИ СЕРДЕЧНО-СОСУДИСТЫХ ОСЛОЖНЕНИЙ У БОЛЬНЫХ САХАРНЫМ ДИАБЕТОМ 2-ГО ТИПА (НА ПРИМЕРЕ ПОЛИКЛИНИК ГОРОДА АЛМАТЫ)»