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Прогностическое значение параметра аутофлюоресценции кожи у пациентов, получающих программный гемодиализ - Научно-практический журнал Cardioсоматика Том 16, №1 (2025)
Прогностическое значение параметра аутофлюоресценции кожи у пациентов, получающих программный гемодиализ
Коновалова Д.Ю., Лебедев П.А., Логинов А.А., Поваляева Р.А., Корнилин Д.В., Гришанов В.Н., Комарова М.В. Прогностическое значение параметра аутофлюоресценции кожи у пациентов, получающих программный гемодиализ // CardioСоматика. 2025. Т. 16, № 1. С. 84–93. DOI: 10.17816/CS636905 EDN: AMXZKA
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Аннотация
Обоснование. Программный гемодиализ (ПГД) до сих пор остаётся наиболее распространённой формой заместительной почечной терапии, потребность в которой значительна. Эта высокозатратная технология усовершенствована в последние десятилетия, однако уровень смертности всё ещё высок. В настоящее время выявлен целый ряд параметров, ассоциированных с негативным прогнозом, среди которых аутофлюоресценция кожи (АФК) — доступный способ определения в тканях конечных продуктов гликирования (гликотоксинов).
Цель. Установить прогностическую роль АФК, а также её взаимосвязи с клиническими показателями и метаболическими сдвигами у пациентов, получающих ПГД.
Материалы и методы. В проспективное наблюдение (средний срок 49 мес.) включены 88 пациентов (47 из них — мужчины), получающих ПГД, средний возраст — 58,01±13,79 года. Оригинальный ридер использован для неинвазивного определения АФК. Первичной конечной точкой выбрана общая летальность.
Результаты. Подтверждено значительное увеличение АФК у пациентов, получающих ПГД. Параметр АФК детерминирован (R2=46%) индексом коморбидности Чарльсона, табакокурением (годы) и калием крови. Также установлены высокозначимые прямые коррелятивные связи с параметрами гипертрофии левого желудочка и отрицательные — с его фракцией выброса. Смертельный исход зарегистрирован у 38 пациентов, наиболее часто ассоциирован с острой сердечно-сосудистой недостаточностью у 23 (61%). Уровень АФК, измеренный исходно в сочетании с альбумином, щелочной фосфатазой, С-реактивным белком крови, в модели прогноза общей смертности обеспечили чувствительность 72%, специфичность 84%. Модель с включением параметра динамики АФК обеспечивает чувствительность 89%, специфичность — 91%, точность прогноза — 89,9%.
Заключение. Полученные результаты позволяют рассматривать АФК как интегральный независимый параметр прогноза общей летальности, отражающего воспалительный, метаболический, электролитный профиль и ремоделирование сердечно-сосудистой системы у пациентов ПГД.
Ключевые слова: параметр аутофлюоресценции кожи, программный гемодиализ, прогноз, общая летальность, сердечно-сосудистая смертность
AIM: To determine the prognostic value of skin autofluorescence and its associations with clinical parameters and metabolic disturbances in patients undergoing maintenance hemodialysis.
MATERIALS AND METHODS: A total of 88 patients (47 men) undergoing maintenance hemodialysis were prospectively observed over a mean period of 49 months. The mean age was 58.01±13.79 years. Skin autofluorescence was noninvasively assessed using a specialized reader. All-cause mortality was selected as the primary endpoint.
RESULTS: A significant increase in skin autofluorescence was confirmed in patients receiving maintenance hemodialysis. Skin autofluorescence was found to be determined (R2=46%) by the Charlson comorbidity index, duration of tobacco use (in years), and serum potassium levels. Skin autofluorescence demonstrated statistically significant correlations with parameters of left ventricular hypertrophy and negative correlations with left ventricular ejection fraction. Death occurred in 38 patients, most commonly due to acute cardiovascular failure (23 patients, 61%). Baseline skin autofluorescence level, combined with serum albumin, alkaline phosphatase, and C-reactive protein levels, yielded a prognostic model for all-cause mortality with 72% sensitivity and 84% specificity. A model incorporating skin autofluorescence changes achieved 89% sensitivity, 91% specificity, and 89.9% predictive accuracy.
CONCLUSION: The findings support the use of skin autofluorescence as an integral, independent predictor of all-cause mortality in patients undergoing maintenance hemodialysis. Skin autofluorescence reflects inflammatory and metabolic status, electrolyte imbalances, and cardiovascular remodeling.
Keywords: skin autofluorescence, maintenance hemodialysis, prognosis, all-cause mortality, cardiovascular mortality
Цель. Установить прогностическую роль АФК, а также её взаимосвязи с клиническими показателями и метаболическими сдвигами у пациентов, получающих ПГД.
Материалы и методы. В проспективное наблюдение (средний срок 49 мес.) включены 88 пациентов (47 из них — мужчины), получающих ПГД, средний возраст — 58,01±13,79 года. Оригинальный ридер использован для неинвазивного определения АФК. Первичной конечной точкой выбрана общая летальность.
Результаты. Подтверждено значительное увеличение АФК у пациентов, получающих ПГД. Параметр АФК детерминирован (R2=46%) индексом коморбидности Чарльсона, табакокурением (годы) и калием крови. Также установлены высокозначимые прямые коррелятивные связи с параметрами гипертрофии левого желудочка и отрицательные — с его фракцией выброса. Смертельный исход зарегистрирован у 38 пациентов, наиболее часто ассоциирован с острой сердечно-сосудистой недостаточностью у 23 (61%). Уровень АФК, измеренный исходно в сочетании с альбумином, щелочной фосфатазой, С-реактивным белком крови, в модели прогноза общей смертности обеспечили чувствительность 72%, специфичность 84%. Модель с включением параметра динамики АФК обеспечивает чувствительность 89%, специфичность — 91%, точность прогноза — 89,9%.
Заключение. Полученные результаты позволяют рассматривать АФК как интегральный независимый параметр прогноза общей летальности, отражающего воспалительный, метаболический, электролитный профиль и ремоделирование сердечно-сосудистой системы у пациентов ПГД.
Ключевые слова: параметр аутофлюоресценции кожи, программный гемодиализ, прогноз, общая летальность, сердечно-сосудистая смертность
________________________________________________
AIM: To determine the prognostic value of skin autofluorescence and its associations with clinical parameters and metabolic disturbances in patients undergoing maintenance hemodialysis.
MATERIALS AND METHODS: A total of 88 patients (47 men) undergoing maintenance hemodialysis were prospectively observed over a mean period of 49 months. The mean age was 58.01±13.79 years. Skin autofluorescence was noninvasively assessed using a specialized reader. All-cause mortality was selected as the primary endpoint.
RESULTS: A significant increase in skin autofluorescence was confirmed in patients receiving maintenance hemodialysis. Skin autofluorescence was found to be determined (R2=46%) by the Charlson comorbidity index, duration of tobacco use (in years), and serum potassium levels. Skin autofluorescence demonstrated statistically significant correlations with parameters of left ventricular hypertrophy and negative correlations with left ventricular ejection fraction. Death occurred in 38 patients, most commonly due to acute cardiovascular failure (23 patients, 61%). Baseline skin autofluorescence level, combined with serum albumin, alkaline phosphatase, and C-reactive protein levels, yielded a prognostic model for all-cause mortality with 72% sensitivity and 84% specificity. A model incorporating skin autofluorescence changes achieved 89% sensitivity, 91% specificity, and 89.9% predictive accuracy.
CONCLUSION: The findings support the use of skin autofluorescence as an integral, independent predictor of all-cause mortality in patients undergoing maintenance hemodialysis. Skin autofluorescence reflects inflammatory and metabolic status, electrolyte imbalances, and cardiovascular remodeling.
Keywords: skin autofluorescence, maintenance hemodialysis, prognosis, all-cause mortality, cardiovascular mortality
Полный текст
Список литературы
1. Echefu G, Stowe I, Burka S, et al. Pathophysiological concepts and screening of cardiovascular disease in dialysis patients. Front Nephrol. 2023;3:1198560. doi: 10.3389/fneph.2023.1198560 EDN: JESPBM
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3. Bello AK, Okpechi IG, Osman MA, et al. Epidemiology of haemodialysisoutcomes. Nat Rev Nephrol. 2022;18(6):378–395. doi: 10.1038/s41581-022-00542-7
4. Wojtaszek E, Oldakowska-Jedynak U, Kwiatkowska M, et al. Uremic Toxins, Oxidative Stress, Atherosclerosis in Chronic Kidney Disease, and Kidney Transplantation. Oxid Med Cell Longev. 2021;2021:6651367. doi: 10.1155/2021/6651367 EDN: KXCZKP
5. Liakopoulos V, Roumeliotis S, Gorny X, et al. Oxidative Stress in Hemodialysis Patients: A Review of the Literature. Oxid Med Cell Longev. 2017;2017:3081856. doi: 10.1155/2017/3081856
6. Meerwaldt R, Graaff R, Oomen PH, et al. Simple non-invasive assessment of advanced glycation endproduct accumulation. Diabetologia. 2004;47:1324–1330. doi: 10.1007/s00125-004-1451-2 EDN: FTKNVQ
7. Davydova NA, Lebedev PA, Ayupov AM, et al. Skin autofluorescence parameter as an adverse prognosis factor in patients with peripheral forms of atherosclerosis. Saratov Journal of Medical Scientific Research. 2022;18(4):568–575. EDN: JLCCQS
8. Golubev RV, Papayan GV, Glazunova AA, et al. Examination of skin autofluorescence for the determination of glycation end-products in patients on chronic hemodialysis. Terapevticheskii arkhiv. 2016;88(6):65–72. doi: 10.17116/terarkh201688665-72 EDN: WAIPAJ
9. Kornilin DV, Grishanov VN, Cherepanov KV. Pulse excitation fluorescence meter for diagnostic purposes. Proc. SPIE, Biophotonics: Photonic Solutions for Better Health Care VI. 2018;10685:1068515. doi: 10.1117/12.2306588 EDN: YBTJXV
10. Rattanasompattikul M, Feroze U, Molnar MZ, et al. Charlson comorbidity scoreisa strong predictor of mortality inhemodialysis patients. Int Urol Nephrol. 2012;44(6):1813–1823. doi: 10.1007/s11255-011-0085-9
11. Barge-Caballero E, García-López F, Marzoa-Rivas R, et al. Prognostic Value of the Nutritional Risk Index in Heart Transplant Recipients. Rev Esp Cardiol (Engl Ed.). 2017;70:639–645. doi: 10.1016/j.recesp.2016.11.015
12. Lebedev PA, Davydova NA, Paranina EV, Skuratova MA. Skin autofluorescence as an indicator of advanced glycation end‑product accumulation in the prognosis of age-related cardiovascular disease: literature review. CardioSomatics. 2023;14(1):37–48. doi: 10.17816/CS225838 EDN: OVLYWI
13. CalviñoJ, CigarranS, Gonzalez-TabaresL, et al. Advanced glycation end products (AGEs) estimated by skin autofluorescence are related with cardiovascular risk in renal transplant. PLoS One. 2018;13(8):e0201118. doi: 10.1371/journal.pone.0201118
14. Gopal P, Reynaert NL, Scheijen JL, et al. Plasma advanced glycation end-products and skin autofluorescence are increased in COPD. Eur Respir J. 2014;43:430–438. doi: 10.1183/09031936.00135312
15. Viramontes HD, Selby NM, Taal MW. Factors Associated With Change in Skin Autofluorescence, a Measure of Advanced Glycation End Products, in Persons Receiving Dialysis. Kidney Int Rep. 2020;5(5):654–662. doi: 10.1016/j.ekir.2020.02.003 EDN: EQOFPO
16. Vareesangthip K, Fan S, Davenport A. Is the measurement of tissue advanced glycosylation products by skin autofluorescence associated with mortality in patients treated by peritoneal dialysis? J Nephrol. 2023;36(1):217–224. doi: 10.1007/s40620-022-01415-9 EDN: YFDZZK
17. Epifânio APS, Balbino KP, Ribeiro SMR, et al. Clinical-nutritional, inflammatory and oxidative stress predictors in hemodialysis mortality: a review. Nutr Hosp. 2018;35(2):461–468. doi: 10.20960/nh.1266
18. de Roij van Zuijdewijn CL, ter Wee PM, Chapdelaine I, et al. A Comparison of 8 Nutrition-Related Tests to Predict Mortality in Hemodialysis Patients. J Ren Nutr. 2015;25(5):412–419. doi: 10.1053/j.jrn.2015.02.005
19. Hörner DV, Selby NM, Taal MW. Skin autofluorescence and malnutrition as predictors of mortality in persons receiving dialysis: a prospective cohort study. J Hum Nutr Diet. 2020;33(6):852–861. doi: 10.1111/jhn.12764 EDN: LTLQAN
20. Kitamura H, Yotsueda R, Hiyamuta H, et al. Serum alkaline phosphatase and infection-related mortality in hemodialysis patients: ten-year outcomes of the Q-cohort study. Clin Exp Nephrol. 2022;26(11):1119–1129. doi: 10.1007/s10157-022-02255-4 EDN: VZIOJZ
21. Kitamura H, Yamada S, Hiyamuta H, et al. Serum Alkaline Phosphatase Levels and Increased Risk of Brain Hemorrhage in Hemodialysis Patients: The Q-Cohort Study. J Atheroscler Thromb. 2022;29(6):923–936. doi: 10.5551/jat.62885
22. Alves FC, Sun J, Qureshi AR, et al. The higher mortality associated with low serum albumin is dependent on systemic inflammation in end-stage kidney disease. PLoS One. 2018;13(1):e0190410. doi: 10.1371/journal.pone.0190410
2. Tonelli M, Karumanchi SA, Thadhani R. Epidemiology and mechanisms of uremia-related cardiovasculardisease. Circulation. 2016;133(5):518–536. doi: 10.1161/CIRCULATIONAHA.115.018713
3. Bello AK, Okpechi IG, Osman MA, et al. Epidemiology of haemodialysisoutcomes. Nat Rev Nephrol. 2022;18(6):378–395. doi: 10.1038/s41581-022-00542-7
4. Wojtaszek E, Oldakowska-Jedynak U, Kwiatkowska M, et al. Uremic Toxins, Oxidative Stress, Atherosclerosis in Chronic Kidney Disease, and Kidney Transplantation. Oxid Med Cell Longev. 2021;2021:6651367. doi: 10.1155/2021/6651367 EDN: KXCZKP
5. Liakopoulos V, Roumeliotis S, Gorny X, et al. Oxidative Stress in Hemodialysis Patients: A Review of the Literature. Oxid Med Cell Longev. 2017;2017:3081856. doi: 10.1155/2017/3081856
6. Meerwaldt R, Graaff R, Oomen PH, et al. Simple non-invasive assessment of advanced glycation endproduct accumulation. Diabetologia. 2004;47:1324–1330. doi: 10.1007/s00125-004-1451-2 EDN: FTKNVQ
7. Davydova NA, Lebedev PA, Ayupov AM, et al. Skin autofluorescence parameter as an adverse prognosis factor in patients with peripheral forms of atherosclerosis. Saratov Journal of Medical Scientific Research. 2022;18(4):568–575. EDN: JLCCQS
8. Golubev RV, Papayan GV, Glazunova AA, et al. Examination of skin autofluorescence for the determination of glycation end-products in patients on chronic hemodialysis. Terapevticheskii arkhiv. 2016;88(6):65–72. doi: 10.17116/terarkh201688665-72 EDN: WAIPAJ
9. Kornilin DV, Grishanov VN, Cherepanov KV. Pulse excitation fluorescence meter for diagnostic purposes. Proc. SPIE, Biophotonics: Photonic Solutions for Better Health Care VI. 2018;10685:1068515. doi: 10.1117/12.2306588 EDN: YBTJXV
10. Rattanasompattikul M, Feroze U, Molnar MZ, et al. Charlson comorbidity scoreisa strong predictor of mortality inhemodialysis patients. Int Urol Nephrol. 2012;44(6):1813–1823. doi: 10.1007/s11255-011-0085-9
11. Barge-Caballero E, García-López F, Marzoa-Rivas R, et al. Prognostic Value of the Nutritional Risk Index in Heart Transplant Recipients. Rev Esp Cardiol (Engl Ed.). 2017;70:639–645. doi: 10.1016/j.recesp.2016.11.015
12. Lebedev PA, Davydova NA, Paranina EV, Skuratova MA. Skin autofluorescence as an indicator of advanced glycation end‑product accumulation in the prognosis of age-related cardiovascular disease: literature review. CardioSomatics. 2023;14(1):37–48. doi: 10.17816/CS225838 EDN: OVLYWI
13. CalviñoJ, CigarranS, Gonzalez-TabaresL, et al. Advanced glycation end products (AGEs) estimated by skin autofluorescence are related with cardiovascular risk in renal transplant. PLoS One. 2018;13(8):e0201118. doi: 10.1371/journal.pone.0201118
14. Gopal P, Reynaert NL, Scheijen JL, et al. Plasma advanced glycation end-products and skin autofluorescence are increased in COPD. Eur Respir J. 2014;43:430–438. doi: 10.1183/09031936.00135312
15. Viramontes HD, Selby NM, Taal MW. Factors Associated With Change in Skin Autofluorescence, a Measure of Advanced Glycation End Products, in Persons Receiving Dialysis. Kidney Int Rep. 2020;5(5):654–662. doi: 10.1016/j.ekir.2020.02.003 EDN: EQOFPO
16. Vareesangthip K, Fan S, Davenport A. Is the measurement of tissue advanced glycosylation products by skin autofluorescence associated with mortality in patients treated by peritoneal dialysis? J Nephrol. 2023;36(1):217–224. doi: 10.1007/s40620-022-01415-9 EDN: YFDZZK
17. Epifânio APS, Balbino KP, Ribeiro SMR, et al. Clinical-nutritional, inflammatory and oxidative stress predictors in hemodialysis mortality: a review. Nutr Hosp. 2018;35(2):461–468. doi: 10.20960/nh.1266
18. de Roij van Zuijdewijn CL, ter Wee PM, Chapdelaine I, et al. A Comparison of 8 Nutrition-Related Tests to Predict Mortality in Hemodialysis Patients. J Ren Nutr. 2015;25(5):412–419. doi: 10.1053/j.jrn.2015.02.005
19. Hörner DV, Selby NM, Taal MW. Skin autofluorescence and malnutrition as predictors of mortality in persons receiving dialysis: a prospective cohort study. J Hum Nutr Diet. 2020;33(6):852–861. doi: 10.1111/jhn.12764 EDN: LTLQAN
20. Kitamura H, Yotsueda R, Hiyamuta H, et al. Serum alkaline phosphatase and infection-related mortality in hemodialysis patients: ten-year outcomes of the Q-cohort study. Clin Exp Nephrol. 2022;26(11):1119–1129. doi: 10.1007/s10157-022-02255-4 EDN: VZIOJZ
21. Kitamura H, Yamada S, Hiyamuta H, et al. Serum Alkaline Phosphatase Levels and Increased Risk of Brain Hemorrhage in Hemodialysis Patients: The Q-Cohort Study. J Atheroscler Thromb. 2022;29(6):923–936. doi: 10.5551/jat.62885
22. Alves FC, Sun J, Qureshi AR, et al. The higher mortality associated with low serum albumin is dependent on systemic inflammation in end-stage kidney disease. PLoS One. 2018;13(1):e0190410. doi: 10.1371/journal.pone.0190410
2. Tonelli M, Karumanchi SA, Thadhani R. Epidemiology and mechanisms of uremia-related cardiovasculardisease. Circulation. 2016;133(5):518–536. doi: 10.1161/CIRCULATIONAHA.115.018713
3. Bello AK, Okpechi IG, Osman MA, et al. Epidemiology of haemodialysisoutcomes. Nat Rev Nephrol. 2022;18(6):378–395. doi: 10.1038/s41581-022-00542-7
4. Wojtaszek E, Oldakowska-Jedynak U, Kwiatkowska M, et al. Uremic Toxins, Oxidative Stress, Atherosclerosis in Chronic Kidney Disease, and Kidney Transplantation. Oxid Med Cell Longev. 2021;2021:6651367. doi: 10.1155/2021/6651367 EDN: KXCZKP
5. Liakopoulos V, Roumeliotis S, Gorny X, et al. Oxidative Stress in Hemodialysis Patients: A Review of the Literature. Oxid Med Cell Longev. 2017;2017:3081856. doi: 10.1155/2017/3081856
6. Meerwaldt R, Graaff R, Oomen PH, et al. Simple non-invasive assessment of advanced glycation endproduct accumulation. Diabetologia. 2004;47:1324–1330. doi: 10.1007/s00125-004-1451-2 EDN: FTKNVQ
7. Davydova NA, Lebedev PA, Ayupov AM, et al. Skin autofluorescence parameter as an adverse prognosis factor in patients with peripheral forms of atherosclerosis. Saratov Journal of Medical Scientific Research. 2022;18(4):568–575. EDN: JLCCQS
8. Golubev RV, Papayan GV, Glazunova AA, et al. Examination of skin autofluorescence for the determination of glycation end-products in patients on chronic hemodialysis. Terapevticheskii arkhiv. 2016;88(6):65–72. doi: 10.17116/terarkh201688665-72 EDN: WAIPAJ
9. Kornilin DV, Grishanov VN, Cherepanov KV. Pulse excitation fluorescence meter for diagnostic purposes. Proc. SPIE, Biophotonics: Photonic Solutions for Better Health Care VI. 2018;10685:1068515. doi: 10.1117/12.2306588 EDN: YBTJXV
10. Rattanasompattikul M, Feroze U, Molnar MZ, et al. Charlson comorbidity scoreisa strong predictor of mortality inhemodialysis patients. Int Urol Nephrol. 2012;44(6):1813–1823. doi: 10.1007/s11255-011-0085-9
11. Barge-Caballero E, García-López F, Marzoa-Rivas R, et al. Prognostic Value of the Nutritional Risk Index in Heart Transplant Recipients. Rev Esp Cardiol (Engl Ed.). 2017;70:639–645. doi: 10.1016/j.recesp.2016.11.015
12. Lebedev PA, Davydova NA, Paranina EV, Skuratova MA. Skin autofluorescence as an indicator of advanced glycation end‑product accumulation in the prognosis of age-related cardiovascular disease: literature review. CardioSomatics. 2023;14(1):37–48. doi: 10.17816/CS225838 EDN: OVLYWI
13. CalviñoJ, CigarranS, Gonzalez-TabaresL, et al. Advanced glycation end products (AGEs) estimated by skin autofluorescence are related with cardiovascular risk in renal transplant. PLoS One. 2018;13(8):e0201118. doi: 10.1371/journal.pone.0201118
14. Gopal P, Reynaert NL, Scheijen JL, et al. Plasma advanced glycation end-products and skin autofluorescence are increased in COPD. Eur Respir J. 2014;43:430–438. doi: 10.1183/09031936.00135312
15. Viramontes HD, Selby NM, Taal MW. Factors Associated With Change in Skin Autofluorescence, a Measure of Advanced Glycation End Products, in Persons Receiving Dialysis. Kidney Int Rep. 2020;5(5):654–662. doi: 10.1016/j.ekir.2020.02.003 EDN: EQOFPO
16. Vareesangthip K, Fan S, Davenport A. Is the measurement of tissue advanced glycosylation products by skin autofluorescence associated with mortality in patients treated by peritoneal dialysis? J Nephrol. 2023;36(1):217–224. doi: 10.1007/s40620-022-01415-9 EDN: YFDZZK
17. Epifânio APS, Balbino KP, Ribeiro SMR, et al. Clinical-nutritional, inflammatory and oxidative stress predictors in hemodialysis mortality: a review. Nutr Hosp. 2018;35(2):461–468. doi: 10.20960/nh.1266
18. de Roij van Zuijdewijn CL, ter Wee PM, Chapdelaine I, et al. A Comparison of 8 Nutrition-Related Tests to Predict Mortality in Hemodialysis Patients. J Ren Nutr. 2015;25(5):412–419. doi: 10.1053/j.jrn.2015.02.005
19. Hörner DV, Selby NM, Taal MW. Skin autofluorescence and malnutrition as predictors of mortality in persons receiving dialysis: a prospective cohort study. J Hum Nutr Diet. 2020;33(6):852–861. doi: 10.1111/jhn.12764 EDN: LTLQAN
20. Kitamura H, Yotsueda R, Hiyamuta H, et al. Serum alkaline phosphatase and infection-related mortality in hemodialysis patients: ten-year outcomes of the Q-cohort study. Clin Exp Nephrol. 2022;26(11):1119–1129. doi: 10.1007/s10157-022-02255-4 EDN: VZIOJZ
21. Kitamura H, Yamada S, Hiyamuta H, et al. Serum Alkaline Phosphatase Levels and Increased Risk of Brain Hemorrhage in Hemodialysis Patients: The Q-Cohort Study. J Atheroscler Thromb. 2022;29(6):923–936. doi: 10.5551/jat.62885
22. Alves FC, Sun J, Qureshi AR, et al. The higher mortality associated with low serum albumin is dependent on systemic inflammation in end-stage kidney disease. PLoS One. 2018;13(1):e0190410. doi: 10.1371/journal.pone.0190410
________________________________________________
2. Tonelli M, Karumanchi SA, Thadhani R. Epidemiology and mechanisms of uremia-related cardiovasculardisease. Circulation. 2016;133(5):518–536. doi: 10.1161/CIRCULATIONAHA.115.018713
3. Bello AK, Okpechi IG, Osman MA, et al. Epidemiology of haemodialysisoutcomes. Nat Rev Nephrol. 2022;18(6):378–395. doi: 10.1038/s41581-022-00542-7
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Авторы
Д.Ю. Коновалова*1, П.А. Лебедев1, А.А. Логинов2, Р.А. Поваляева2, Д.В. Корнилин3, В.Н. Гришанов3, М.В. Комарова3
1Самарский государственный медицинский университет, Самара, Россия;
2Самарская областная клиническая больница им В.Д. Середавина, Самара, Россия;
3Самарский национальный исследовательский университет им. акад. С.П. Королева, Самара, Россия
*snowflake0605@mail.ru
1Samara State Medical University, Samara, Russia;
2Seredavin Samara Regional Clinical Hospital, Samara, Russia;
3Korolev Samara National Research University, Samara, Russia
*snowflake0605@mail.ru
1Самарский государственный медицинский университет, Самара, Россия;
2Самарская областная клиническая больница им В.Д. Середавина, Самара, Россия;
3Самарский национальный исследовательский университет им. акад. С.П. Королева, Самара, Россия
*snowflake0605@mail.ru
________________________________________________
1Samara State Medical University, Samara, Russia;
2Seredavin Samara Regional Clinical Hospital, Samara, Russia;
3Korolev Samara National Research University, Samara, Russia
*snowflake0605@mail.ru
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