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Возможности совместного использования шкалы GRACE и различных индексов коморбидности для повышения эффективности оценки риска госпитальной летальности у больных с острым коронарным синдромом
Возможности совместного использования шкалы GRACE и различных индексов коморбидности для повышения эффективности оценки риска госпитальной летальности у больных с острым коронарным синдромом
Зыков М.В., Дьяченко Н.В., Велиева Р.М., Кашталап В.В., Барбараш О.Л. Возможности совместного использования шкалы GRACE и различных индексов коморбидности для повышения эффективности оценки риска госпитальной летальности у больных с острым коронарным синдромом. Терапевтический архив. 2022;94(7):816–821. DOI: 10.26442/00403660.2022.07.201742
DOI: 10.26442/00403660.2022.07.201742
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DOI: 10.26442/00403660.2022.07.201742
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Аннотация
Цель. Оценить возможности совместного со шкалой GRACE (Global Registry of Acute Coronary Events) использования индексов коморбидности для оценки риска госпитальной летальности при остром коронарном синдроме (ОКС).
Материалы и методы. В регистровое исследование включены 2305 пациентов с ОКС. Частота выполнения коронарной ангиографии составила 54,0%, чрескожного коронарного вмешательства (ЧКВ) – 26,9%. Госпитальная летальность при ОКС составила 4,8%, при инфаркте миокарда – 9,4%. Всем пациентам проведен анализ выраженности коморбидности по системе CIRS (Cumulative Illness Rating Scale), индексу коморбидности Charlson (Charlson Comorbidity Index – CCI) и шкале хронических заболеваний (Chronic Disease Score – CDS), рассчитан балл по GRACE ACS Risk Score, проведена оценка коморбидности по собственной шкале, основанной на суммировании 9 заболеваний (сахарного диабета, фибрилляции предсердий, перенесенного инсульта, артериальной гипертензии, ожирения, периферического атеросклероза, тромбоцитопении, анемии, хронической болезни почек).
Результаты. Установлено, что индексы CDS и CIRS не связаны с риском госпитальной летальности. При ССI≥3 частота летальных исходов возрастала с 4,1 до 6,1% (χ2=4,12, р=0,042). С нарастанием тяжести коморбидности от минимальной (не более 1 заболевания) до выраженной (4 и более заболевания) по собственной шкале госпитальная летальность возрастала с 1,2 до 7,4% (χ2=23,8, р<0,0001). В отличие от других шкал коморбидности собственная модель эффективнее оценивает госпитальный прогноз как в группе консервативного лечения (χ2=8,0, р=0,018), так и в группе ЧКВ (χ2=28,5, р=0,00001). Именно в подгруппе ЧКВ факторы коморбидности, вошедшие в собственную модель, позволили повысить значение площади под ROC-кривой шкалы GRACE с 0,80 (0,74–0,87) до 0,90 (0,85–0,95).
Заключение. CCI и собственная модель коморбидности (но не СDS и CIRS) связаны с риском госпитальной летальности. Модель оценки коморбидности по 9-балльной системе (но не CCI, CDS и CIRS) позволяет существенно улучшить прогностическую значимость шкалы GRACE.
Ключевые слова: острый коронарный синдром, коморбидность, шкала GRACE, госпитальный прогноз
Materials and methods. The registry study included 2,305 patients with ACS. The frequency of coronary angiography was 54.0%, percutaneous coronary intervention (PCI) – 26.9%. Hospital mortality with ACS was 4.8%, with myocardial infarction – 9.4%. All patients underwent a comorbidity assessment according to the CIRS system (Cumulative Illness Rating Scale), according to the CCI (Charlson Comorbidity Index) and the CDS (Chronic Disease Score) scale, according to their own scale, which is based on the summation of 9 diseases (diabetes mellitus, atrial fibrillation, stroke, arterial hypertension, obesity, peripheral atherosclerosis, thrombocytopenia, anemia, chronic kidney disease). All patients underwent a mortality risk assessment using the GRACE ACS Risk scale.
Results. It was found that the CDS and CIRS indices are not associated with the risk of hospital mortality. With CCI≥3, the frequency of death outcomes increased from 4.1 to 6.1% (χ2=4.12, p=0.042). With an increase in the severity of comorbidity from minimal (no more than 1 disease) to severe (4 or more diseases) according to its own scale, hospital mortality increased from 1.2 to 7.4% (χ2=23.8, p<0.0001). In contrast to other scales of comorbidity, our own model more efficiently estimates the hospital prognosis both in the conservative treatment group (χ2=8.0, p=0.018) and in the PCI group (χ2=28.5, p=0.00001). It was in the PCI subgroup that the comorbidity factors included in their own model made it possible to increase the area under the ROC curve of the GRACE scale from 0.80 (0.74–0.87) to 0.90 (0.85–0.95).
Conclusion. CCI and its own comorbidity model, but not CDS and CIRS, are associated with the risk of hospital mortality. The model for assessing comorbidity on a 9-point scale, but not CCI, CDS and CIRS, can significantly improve the predictive value of the GRACE scale.
Keywords: acute coronary syndrome, comorbidity, GRACE ACS risk score, hospital prognosis
Материалы и методы. В регистровое исследование включены 2305 пациентов с ОКС. Частота выполнения коронарной ангиографии составила 54,0%, чрескожного коронарного вмешательства (ЧКВ) – 26,9%. Госпитальная летальность при ОКС составила 4,8%, при инфаркте миокарда – 9,4%. Всем пациентам проведен анализ выраженности коморбидности по системе CIRS (Cumulative Illness Rating Scale), индексу коморбидности Charlson (Charlson Comorbidity Index – CCI) и шкале хронических заболеваний (Chronic Disease Score – CDS), рассчитан балл по GRACE ACS Risk Score, проведена оценка коморбидности по собственной шкале, основанной на суммировании 9 заболеваний (сахарного диабета, фибрилляции предсердий, перенесенного инсульта, артериальной гипертензии, ожирения, периферического атеросклероза, тромбоцитопении, анемии, хронической болезни почек).
Результаты. Установлено, что индексы CDS и CIRS не связаны с риском госпитальной летальности. При ССI≥3 частота летальных исходов возрастала с 4,1 до 6,1% (χ2=4,12, р=0,042). С нарастанием тяжести коморбидности от минимальной (не более 1 заболевания) до выраженной (4 и более заболевания) по собственной шкале госпитальная летальность возрастала с 1,2 до 7,4% (χ2=23,8, р<0,0001). В отличие от других шкал коморбидности собственная модель эффективнее оценивает госпитальный прогноз как в группе консервативного лечения (χ2=8,0, р=0,018), так и в группе ЧКВ (χ2=28,5, р=0,00001). Именно в подгруппе ЧКВ факторы коморбидности, вошедшие в собственную модель, позволили повысить значение площади под ROC-кривой шкалы GRACE с 0,80 (0,74–0,87) до 0,90 (0,85–0,95).
Заключение. CCI и собственная модель коморбидности (но не СDS и CIRS) связаны с риском госпитальной летальности. Модель оценки коморбидности по 9-балльной системе (но не CCI, CDS и CIRS) позволяет существенно улучшить прогностическую значимость шкалы GRACE.
Ключевые слова: острый коронарный синдром, коморбидность, шкала GRACE, госпитальный прогноз
________________________________________________
Materials and methods. The registry study included 2,305 patients with ACS. The frequency of coronary angiography was 54.0%, percutaneous coronary intervention (PCI) – 26.9%. Hospital mortality with ACS was 4.8%, with myocardial infarction – 9.4%. All patients underwent a comorbidity assessment according to the CIRS system (Cumulative Illness Rating Scale), according to the CCI (Charlson Comorbidity Index) and the CDS (Chronic Disease Score) scale, according to their own scale, which is based on the summation of 9 diseases (diabetes mellitus, atrial fibrillation, stroke, arterial hypertension, obesity, peripheral atherosclerosis, thrombocytopenia, anemia, chronic kidney disease). All patients underwent a mortality risk assessment using the GRACE ACS Risk scale.
Results. It was found that the CDS and CIRS indices are not associated with the risk of hospital mortality. With CCI≥3, the frequency of death outcomes increased from 4.1 to 6.1% (χ2=4.12, p=0.042). With an increase in the severity of comorbidity from minimal (no more than 1 disease) to severe (4 or more diseases) according to its own scale, hospital mortality increased from 1.2 to 7.4% (χ2=23.8, p<0.0001). In contrast to other scales of comorbidity, our own model more efficiently estimates the hospital prognosis both in the conservative treatment group (χ2=8.0, p=0.018) and in the PCI group (χ2=28.5, p=0.00001). It was in the PCI subgroup that the comorbidity factors included in their own model made it possible to increase the area under the ROC curve of the GRACE scale from 0.80 (0.74–0.87) to 0.90 (0.85–0.95).
Conclusion. CCI and its own comorbidity model, but not CDS and CIRS, are associated with the risk of hospital mortality. The model for assessing comorbidity on a 9-point scale, but not CCI, CDS and CIRS, can significantly improve the predictive value of the GRACE scale.
Keywords: acute coronary syndrome, comorbidity, GRACE ACS risk score, hospital prognosis
Полный текст
Список литературы
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14. Tisminetzky M, Gurwitz JH, Miozzo R, et al. Impact of cardiac- and noncardiac-related conditions on adverse outcomes in patients hospitalized with acute myocardial infarction. J Comorb. 2019;9:2235042X19852499. DOI:10.1177/2235042X19852499
15. Canivell S, Muller O, Gencer B, et al. Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome. PLoS One. 2018;13(4):e0195174. DOI:10.1371/journal.pone.0195174
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21. Hudzik B, Korzonek-Szlacheta I, Szkodziński J, et al. Association between multimorbidity and mean platelet volume in diabetic patients with acute myocardial infarction. Acta Diabetol. 2018;55(2):175-83. DOI:10.1007/s00592-017-1079-6
22. Choi DH, Kang SH, Song H. Mean platelet volume: a potential biomarker of the risk and prognosis of heart disease. Korean J Intern Med. 2016;31(6):1009-17. DOI:10.3904/kjim.2016.078
23. Fabbri E, An Y, Zoli M, et al. Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers. J Gerontol A Biol Sci Med Sci. 2015;70(1):63-70. DOI:10.1093/gerona/glu127
24. Ferreira GD, Simões JA, Senaratna C, et al. Physiological markers and multimorbidity: A systematic review. J Comorb. 2018;8(1):2235042X18806986. DOI:10.1177/2235042X18806986
25. Castellon X, Bogdanova V. Chronic Inflammatory Diseases and Endothelial Dysfunction. Aging Dis. 2016;7(1):81-9. DOI:10.14336/AD.2015.0803
26. Paulus WJ, Tschöpe C. A novel paradigm for heart failure with preserved ejection fraction comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol. 2013;62(4):263-71. DOI:10.1016/j.jacc.2013.02.092
2. Alieva MG. Risk stratification, registers and prognostic scales in acute coronary syndrome. South of Russia: Ecology, Development. 2017;12(3):159-65 (in Russian). DOI:10.18470/1992-1098-2017-3-159-165
3. Barbarash OL, Duplyakov DV, Zateischikov DA, et al. 2020 Clinical practice guidelines for Acute coronary syndrome without ST segment elevation. Russian Journal of Cardiology. 2021;26(4):4449 (in Russian). DOI:10.15829/1560-4071-2021-4449
4. Collet JP, Thiele H, Barbato E, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289‑367. DOI:10.1093/eurheartj/ehaa575. Erratum in: Eur Heart J. 2021;42(19):1908. Erratum in: Eur Heart J. 2021;42(19):1925
5. Gerber Y, Weston SA, Enriquez-Sarano M, et al. Contemporary Risk Stratification After Myocardial Infarction in the Community: Performance of Scores and Incremental Value of Soluble Suppression of Tumorigenicity-2. J Am Heart Assoc. 2017;6(10):e005958. DOI:10.1161/JAHA.117.005958
6. Liu XJ, Wan ZF, Zhao N, et al. Adjustment of the GRACE score by HemoglobinA1c enables a more accurate prediction of long-term major adverse cardiac events in acute coronary syndrome without diabetes undergoing percutaneous coronary intervention. Cardiovasc Diabetol. 2015;14:110. DOI:10.1186/s12933-015-0274-4
7. Bai XF, Zhang YP, Zhou J, et al. Combination of the CYP2C19 metabolizer and the GRACE risk score better predicts the long-term major adverse cardiac events in acute coronary syndrome undergoing percutaneous coronary intervention. Thromb Res. 2018;170:142-7. DOI:10.1016/j.thromres.2018.08.016
8. Widera C, Pencina MJ, Meisner A, et al. Adjustment of the GRACE score by growth differentiation factor 15 enables a more accurate appreciation of risk in non-ST-elevation acute coronary syndrome. Eur Heart J. 2012;33(9):1095-104. DOI:10.1093/eurheartj/ehr444
9. Zykov MV, Kashtalap VV, Bykova IS, et al. The relationship between multimorbidity and cardiovascular risk in patients with acute coronary syndrome. Kardiologicheskii vestnik. 2018;2:59-65 (in Russian). DOI:10.17116/cardiobulletin201813259
10. Oganov RG, Denisov IN, Simanenkov VI, et al. Comorbidities in practice. Clinical guidelines. Cardiovascular Therapy and Prevention. 2017;16(6):5-56 (in Russian).
DOI:10.15829/1728-8800-2017-6-5-56
11. Erickson SR, Cole E, Kline-Rogers E, Eagle KA. The Addition of the Charlson Comorbidity Index to the GRACE Risk Prediction Index Improves Prediction of Outcomes in Acute Coronary Syndrome. Popul Health Manag. 2014;17(1):54-9. DOI:10.1089/pop.2012.0117
12. Radovanovic D, Seifert B, Urban P, et al. Validity of Charlson Comorbidity Index in patients hospitalised with acute coronary syndrome. Insights fr om the nationwide AMIS Plus registry 2002–2012. Heart. 2014;100(4):288-94. DOI:10.1136/heartjnl-2013-304588
13. Erne P, Gutzwiller F, Urban P, et al. Characteristics and Outcome in Acute Coronary Syndrome Patients with and without Established Modifiable Cardiovascular Risk Factors: Insights from the Nationwide AMIS Plus Registry 1997–2010. Cardiology. 2012;121(4):228-36. DOI:10.1159/000337324
14. Tisminetzky M, Gurwitz JH, Miozzo R, et al. Impact of cardiac- and noncardiac-related conditions on adverse outcomes in patients hospitalized with acute myocardial infarction. J Comorb. 2019;9:2235042X19852499. DOI:10.1177/2235042X19852499
15. Canivell S, Muller O, Gencer B, et al. Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome. PLoS One. 2018;13(4):e0195174. DOI:10.1371/journal.pone.0195174
16. Granger CB, Goldberg RJ, Dabbous O, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med. 2003;163(19):2345-53. DOI:10.1001/archinte.163.19.2345
17. Chen YH, Huang SS, Lin SJ. TIMI and GRACE Risk Scores Predict Both Short-Term and Long-Term Outcomes in Chinese Patients with Acute Myocardial Infarction. Acta Cardiol Sin. 2018;34(1):4-12. DOI:10.6515/ACS.201801_34(1).20170730B
18. D'Ascenzo F, Biondi-Zoccai G, Moretti C, et al. TIMI, GRACE and alternative risk scores in Acute Coronary Syndromes: Ameta-analysis of 40 derivation studies on 216,552 patients and of 42 validation studies on 31,625 patients. Contemp Clin Trials. 2012;33(3):507-14. DOI:10.1016/j.cct.2012.01.001
19. Erlikh AD, Barbarash OL, Kashtalap VV, Gratsiansky NA. Compliance with clinical practice guidelines for non ST-segment elevation acute coronary syndrome: association between outcomes and predictors of poor management (RECoRd-3 registry data). Complex Issues of Cardiovascular Diseases. 2016;(2):75-82 (in Russian).
DOI:10.17802/2306-1278-2016-2-75-82
20. Byrne RA, Joner M, Kastrati A. Stent thrombosis and restenosis: what have we learned and wh ere are we going? The Andreas Grüntzig Lecture ESC 2014. Eur Heart J. 2015;36(47):3320-31. DOI:10.1093/eurheartj/ehv511
21. Hudzik B, Korzonek-Szlacheta I, Szkodziński J, et al. Association between multimorbidity and mean platelet volume in diabetic patients with acute myocardial infarction. Acta Diabetol. 2018;55(2):175-83. DOI:10.1007/s00592-017-1079-6
22. Choi DH, Kang SH, Song H. Mean platelet volume: a potential biomarker of the risk and prognosis of heart disease. Korean J Intern Med. 2016;31(6):1009-17. DOI:10.3904/kjim.2016.078
23. Fabbri E, An Y, Zoli M, et al. Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers. J Gerontol A Biol Sci Med Sci. 2015;70(1):63-70. DOI:10.1093/gerona/glu127
24. Ferreira GD, Simões JA, Senaratna C, et al. Physiological markers and multimorbidity: A systematic review. J Comorb. 2018;8(1):2235042X18806986. DOI:10.1177/2235042X18806986
25. Castellon X, Bogdanova V. Chronic Inflammatory Diseases and Endothelial Dysfunction. Aging Dis. 2016;7(1):81-9. DOI:10.14336/AD.2015.0803
26. Paulus WJ, Tschöpe C. A novel paradigm for heart failure with preserved ejection fraction comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol. 2013;62(4):263-71. DOI:10.1016/j.jacc.2013.02.092
2. Алиева М.Г. Стратификация риска, регистры и прогностические шкалы при остром коронарном синдроме. Юг России: экология, развитие. 2017;12(3):159-65 [Alieva MG. Risk stratification, registers and prognostic scales in acute coronary syndrome. South of Russia: Ecology, Development. 2017;12(3):159-65 (in Russian)].
DOI:10.18470/1992-1098-2017-3-159-165
3. Барбараш О.Л., Дупляков Д.В., Затейщиков Д.А., и др. Острый коронарный синдром без подъема сегмента ST электрокардиограммы. Клинические рекомендации 2020. Российский кардиологический журнал. 2021;26(4):4449 [Barbarash OL, Duplyakov DV, Zateischikov DA, et al. 2020 Clinical practice guidelines for Acute coronary syndrome without ST segment elevation. Russian Journal of Cardiology. 2021;26(4):4449 (in Russian)]. DOI:10.15829/1560-4071-2021-4449
4. Collet JP, Thiele H, Barbato E, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289‑367. DOI:10.1093/eurheartj/ehaa575. Erratum in: Eur Heart J. 2021;42(19):1908. Erratum in: Eur Heart J. 2021;42(19):1925
5. Gerber Y, Weston SA, Enriquez-Sarano M, et al. Contemporary Risk Stratification After Myocardial Infarction in the Community: Performance of Scores and Incremental Value of Soluble Suppression of Tumorigenicity-2. J Am Heart Assoc. 2017;6(10):e005958. DOI:10.1161/JAHA.117.005958
6. Liu XJ, Wan ZF, Zhao N, et al. Adjustment of the GRACE score by HemoglobinA1c enables a more accurate prediction of long-term major adverse cardiac events in acute coronary syndrome without diabetes undergoing percutaneous coronary intervention. Cardiovasc Diabetol. 2015;14:110. DOI:10.1186/s12933-015-0274-4
7. Bai XF, Zhang YP, Zhou J, et al. Combination of the CYP2C19 metabolizer and the GRACE risk score better predicts the long-term major adverse cardiac events in acute coronary syndrome undergoing percutaneous coronary intervention. Thromb Res. 2018;170:142-7. DOI:10.1016/j.thromres.2018.08.016
8. Widera C, Pencina MJ, Meisner A, et al. Adjustment of the GRACE score by growth differentiation factor 15 enables a more accurate appreciation of risk in non-ST-elevation acute coronary syndrome. Eur Heart J. 2012;33(9):1095-104. DOI:10.1093/eurheartj/ehr444
9. Зыков М.В., Кашталап В.В., Быкова И.С., и др. Связь мультиморбидности с риском развития сердечно-сосудистых осложнений у пациентов с острым коронарным синдромом. Кардиологический вестник. 2018;2:59-65 [Zykov MV, Kashtalap VV, Bykova IS, et al. The relationship between multimorbidity and cardiovascular risk in patients with acute coronary syndrome. Kardiologicheskii vestnik. 2018;2:59-65 (in Russian)]. DOI:10.17116/cardiobulletin201813259
10. Оганов Р.Г., Денисов И.Н., Симаненков В.И., и др. Коморбидная патология в клинической практике. Клинические рекомендации. Кардиоваскулярная терапия и профилактика. 2017;16(6):5‑56 [Oganov RG, Denisov IN, Simanenkov VI, et al. Comorbidities in practice. Clinical guidelines. Cardiovascular Therapy and Prevention. 2017;16(6):5-56 (in Russian)]. DOI:10.15829/1728-8800-2017-6-5-56
11. Erickson SR, Cole E, Kline-Rogers E, Eagle KA. The Addition of the Charlson Comorbidity Index to the GRACE Risk Prediction Index Improves Prediction of Outcomes in Acute Coronary Syndrome. Popul Health Manag. 2014;17(1):54-9. DOI:10.1089/pop.2012.0117
12. Radovanovic D, Seifert B, Urban P, et al. Validity of Charlson Comorbidity Index in patients hospitalised with acute coronary syndrome. Insights fr om the nationwide AMIS Plus registry 2002–2012. Heart. 2014;100(4):288-94. DOI:10.1136/heartjnl-2013-304588
13. Erne P, Gutzwiller F, Urban P, et al. Characteristics and Outcome in Acute Coronary Syndrome Patients with and without Established Modifiable Cardiovascular Risk Factors: Insights from the Nationwide AMIS Plus Registry 1997–2010. Cardiology. 2012;121(4):228-36. DOI:10.1159/000337324
14. Tisminetzky M, Gurwitz JH, Miozzo R, et al. Impact of cardiac- and noncardiac-related conditions on adverse outcomes in patients hospitalized with acute myocardial infarction. J Comorb. 2019;9:2235042X19852499. DOI:10.1177/2235042X19852499
15. Canivell S, Muller O, Gencer B, et al. Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome. PLoS One. 2018;13(4):e0195174. DOI:10.1371/journal.pone.0195174
16. Granger CB, Goldberg RJ, Dabbous O, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med. 2003;163(19):2345-53. DOI:10.1001/archinte.163.19.2345
17. Chen YH, Huang SS, Lin SJ. TIMI and GRACE Risk Scores Predict Both Short-Term and Long-Term Outcomes in Chinese Patients with Acute Myocardial Infarction. Acta Cardiol Sin. 2018;34(1):4-12. DOI:10.6515/ACS.201801_34(1).20170730B
18. D'Ascenzo F, Biondi-Zoccai G, Moretti C, et al. TIMI, GRACE and alternative risk scores in Acute Coronary Syndromes: Ameta-analysis of 40 derivation studies on 216,552 patients and of 42 validation studies on 31,625 patients. Contemp Clin Trials. 2012;33(3):507-14. DOI:10.1016/j.cct.2012.01.001
19. Эрлих А.Д., Барбараш О.Л., Кашталап В.В., Грацианский Н.А. Степень следования клиническим руководствам при остром коронарном синдроме без подъема ST: связь с исходами, предикторы «плохого» лечения (результаты регистра «РЕКОРД-3»). Комплексные проблемы сердечно-сосудистых заболеваний. 2016;(2):75-82 [Erlikh AD, Barbarash OL, Kashtalap VV, Gratsiansky NA. Compliance with clinical practice guidelines for non ST-segment elevation acute coronary syndrome: association between outcomes and predictors of poor management (RECoRd-3 registry data). Complex Issues of Cardiovascular Diseases. 2016;(2):75-82 (in Russian)]. DOI:10.17802/2306-1278-2016-2-75-82
20. Byrne RA, Joner M, Kastrati A. Stent thrombosis and restenosis: what have we learned and wh ere are we going? The Andreas Grüntzig Lecture ESC 2014. Eur Heart J. 2015;36(47):3320-31. DOI:10.1093/eurheartj/ehv511
21. Hudzik B, Korzonek-Szlacheta I, Szkodziński J, et al. Association between multimorbidity and mean platelet volume in diabetic patients with acute myocardial infarction. Acta Diabetol. 2018;55(2):175-83. DOI:10.1007/s00592-017-1079-6
22. Choi DH, Kang SH, Song H. Mean platelet volume: a potential biomarker of the risk and prognosis of heart disease. Korean J Intern Med. 2016;31(6):1009-17. DOI:10.3904/kjim.2016.078
23. Fabbri E, An Y, Zoli M, et al. Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers. J Gerontol A Biol Sci Med Sci. 2015;70(1):63-70. DOI:10.1093/gerona/glu127
24. Ferreira GD, Simões JA, Senaratna C, et al. Physiological markers and multimorbidity: A systematic review. J Comorb. 2018;8(1):2235042X18806986. DOI:10.1177/2235042X18806986
25. Castellon X, Bogdanova V. Chronic Inflammatory Diseases and Endothelial Dysfunction. Aging Dis. 2016;7(1):81-9. DOI:10.14336/AD.2015.0803
26. Paulus WJ, Tschöpe C. A novel paradigm for heart failure with preserved ejection fraction comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol. 2013;62(4):263-71. DOI:10.1016/j.jacc.2013.02.092
________________________________________________
2. Alieva MG. Risk stratification, registers and prognostic scales in acute coronary syndrome. South of Russia: Ecology, Development. 2017;12(3):159-65 (in Russian). DOI:10.18470/1992-1098-2017-3-159-165
3. Barbarash OL, Duplyakov DV, Zateischikov DA, et al. 2020 Clinical practice guidelines for Acute coronary syndrome without ST segment elevation. Russian Journal of Cardiology. 2021;26(4):4449 (in Russian). DOI:10.15829/1560-4071-2021-4449
4. Collet JP, Thiele H, Barbato E, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289‑367. DOI:10.1093/eurheartj/ehaa575. Erratum in: Eur Heart J. 2021;42(19):1908. Erratum in: Eur Heart J. 2021;42(19):1925
5. Gerber Y, Weston SA, Enriquez-Sarano M, et al. Contemporary Risk Stratification After Myocardial Infarction in the Community: Performance of Scores and Incremental Value of Soluble Suppression of Tumorigenicity-2. J Am Heart Assoc. 2017;6(10):e005958. DOI:10.1161/JAHA.117.005958
6. Liu XJ, Wan ZF, Zhao N, et al. Adjustment of the GRACE score by HemoglobinA1c enables a more accurate prediction of long-term major adverse cardiac events in acute coronary syndrome without diabetes undergoing percutaneous coronary intervention. Cardiovasc Diabetol. 2015;14:110. DOI:10.1186/s12933-015-0274-4
7. Bai XF, Zhang YP, Zhou J, et al. Combination of the CYP2C19 metabolizer and the GRACE risk score better predicts the long-term major adverse cardiac events in acute coronary syndrome undergoing percutaneous coronary intervention. Thromb Res. 2018;170:142-7. DOI:10.1016/j.thromres.2018.08.016
8. Widera C, Pencina MJ, Meisner A, et al. Adjustment of the GRACE score by growth differentiation factor 15 enables a more accurate appreciation of risk in non-ST-elevation acute coronary syndrome. Eur Heart J. 2012;33(9):1095-104. DOI:10.1093/eurheartj/ehr444
9. Zykov MV, Kashtalap VV, Bykova IS, et al. The relationship between multimorbidity and cardiovascular risk in patients with acute coronary syndrome. Kardiologicheskii vestnik. 2018;2:59-65 (in Russian). DOI:10.17116/cardiobulletin201813259
10. Oganov RG, Denisov IN, Simanenkov VI, et al. Comorbidities in practice. Clinical guidelines. Cardiovascular Therapy and Prevention. 2017;16(6):5-56 (in Russian).
DOI:10.15829/1728-8800-2017-6-5-56
11. Erickson SR, Cole E, Kline-Rogers E, Eagle KA. The Addition of the Charlson Comorbidity Index to the GRACE Risk Prediction Index Improves Prediction of Outcomes in Acute Coronary Syndrome. Popul Health Manag. 2014;17(1):54-9. DOI:10.1089/pop.2012.0117
12. Radovanovic D, Seifert B, Urban P, et al. Validity of Charlson Comorbidity Index in patients hospitalised with acute coronary syndrome. Insights fr om the nationwide AMIS Plus registry 2002–2012. Heart. 2014;100(4):288-94. DOI:10.1136/heartjnl-2013-304588
13. Erne P, Gutzwiller F, Urban P, et al. Characteristics and Outcome in Acute Coronary Syndrome Patients with and without Established Modifiable Cardiovascular Risk Factors: Insights from the Nationwide AMIS Plus Registry 1997–2010. Cardiology. 2012;121(4):228-36. DOI:10.1159/000337324
14. Tisminetzky M, Gurwitz JH, Miozzo R, et al. Impact of cardiac- and noncardiac-related conditions on adverse outcomes in patients hospitalized with acute myocardial infarction. J Comorb. 2019;9:2235042X19852499. DOI:10.1177/2235042X19852499
15. Canivell S, Muller O, Gencer B, et al. Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome. PLoS One. 2018;13(4):e0195174. DOI:10.1371/journal.pone.0195174
16. Granger CB, Goldberg RJ, Dabbous O, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med. 2003;163(19):2345-53. DOI:10.1001/archinte.163.19.2345
17. Chen YH, Huang SS, Lin SJ. TIMI and GRACE Risk Scores Predict Both Short-Term and Long-Term Outcomes in Chinese Patients with Acute Myocardial Infarction. Acta Cardiol Sin. 2018;34(1):4-12. DOI:10.6515/ACS.201801_34(1).20170730B
18. D'Ascenzo F, Biondi-Zoccai G, Moretti C, et al. TIMI, GRACE and alternative risk scores in Acute Coronary Syndromes: Ameta-analysis of 40 derivation studies on 216,552 patients and of 42 validation studies on 31,625 patients. Contemp Clin Trials. 2012;33(3):507-14. DOI:10.1016/j.cct.2012.01.001
19. Erlikh AD, Barbarash OL, Kashtalap VV, Gratsiansky NA. Compliance with clinical practice guidelines for non ST-segment elevation acute coronary syndrome: association between outcomes and predictors of poor management (RECoRd-3 registry data). Complex Issues of Cardiovascular Diseases. 2016;(2):75-82 (in Russian).
DOI:10.17802/2306-1278-2016-2-75-82
20. Byrne RA, Joner M, Kastrati A. Stent thrombosis and restenosis: what have we learned and wh ere are we going? The Andreas Grüntzig Lecture ESC 2014. Eur Heart J. 2015;36(47):3320-31. DOI:10.1093/eurheartj/ehv511
21. Hudzik B, Korzonek-Szlacheta I, Szkodziński J, et al. Association between multimorbidity and mean platelet volume in diabetic patients with acute myocardial infarction. Acta Diabetol. 2018;55(2):175-83. DOI:10.1007/s00592-017-1079-6
22. Choi DH, Kang SH, Song H. Mean platelet volume: a potential biomarker of the risk and prognosis of heart disease. Korean J Intern Med. 2016;31(6):1009-17. DOI:10.3904/kjim.2016.078
23. Fabbri E, An Y, Zoli M, et al. Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers. J Gerontol A Biol Sci Med Sci. 2015;70(1):63-70. DOI:10.1093/gerona/glu127
24. Ferreira GD, Simões JA, Senaratna C, et al. Physiological markers and multimorbidity: A systematic review. J Comorb. 2018;8(1):2235042X18806986. DOI:10.1177/2235042X18806986
25. Castellon X, Bogdanova V. Chronic Inflammatory Diseases and Endothelial Dysfunction. Aging Dis. 2016;7(1):81-9. DOI:10.14336/AD.2015.0803
26. Paulus WJ, Tschöpe C. A novel paradigm for heart failure with preserved ejection fraction comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol. 2013;62(4):263-71. DOI:10.1016/j.jacc.2013.02.092
Авторы
М.В. Зыков*1–3, Н.В. Дьяченко1,3, Р.М. Велиева1, В.В. Кашталап1,4, О.Л. Барбараш1,4
1 ФГБНУ «Научно-исследовательский институт комплексных проблем сердечно-сосудистых заболеваний», Кемерово, Россия;
2 ФГБОУ ВО «Кубанский государственный медицинский университет» Минздрава России, Краснодар, Россия;
3 ГБУЗ «Городская больница №4 г. Сочи» Минздрава Краснодарского края, Сочи, Россия;
4 ФГБОУ ВО «Кемеровский государственный медицинский университет» Минздрава России, Кемерово, Россия
*mvz83@mail.ru
1 Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia;
2 Kuban State Medical University, Krasnodar, Russia;
3 City Hospital No. 4 Sochi, Sochi, Russia;
4 Kemerovo State Medical University, Kemerovo, Russia
*mvz83@mail.ru
1 ФГБНУ «Научно-исследовательский институт комплексных проблем сердечно-сосудистых заболеваний», Кемерово, Россия;
2 ФГБОУ ВО «Кубанский государственный медицинский университет» Минздрава России, Краснодар, Россия;
3 ГБУЗ «Городская больница №4 г. Сочи» Минздрава Краснодарского края, Сочи, Россия;
4 ФГБОУ ВО «Кемеровский государственный медицинский университет» Минздрава России, Кемерово, Россия
*mvz83@mail.ru
________________________________________________
1 Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia;
2 Kuban State Medical University, Krasnodar, Russia;
3 City Hospital No. 4 Sochi, Sochi, Russia;
4 Kemerovo State Medical University, Kemerovo, Russia
*mvz83@mail.ru
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