Advancements in Biomarkers for Assessing Dialysis Efficiency: A Comprehensive Review
DOI:
https://doi.org/10.58222/juvokes.v3i2.1182Kata Kunci:
Biomarkers, Dialysis efficiency, Chronic kidney disease, Personalized nephrology, Point-of-care diagnosticsAbstrak
This review discusses the recent development in biomarkers of dialysis efficiency in patients suffering from CKD and ESRD. The systematic review covered literature in the years 2019 to 2024 with emerging biomarkers and their clinical application along with innovative ways to detect the biomarkers. Traditional biomarkers are the urea reduction ratio (URR) and Kt/V, while newer biomarkers like β2-microglobulin, cystatin C, and fibroblast growth factor 23 (FGF23) receive increased recognition regarding their ability to better present patient health. These biomarkers could dramatically enhance personalization of treatment through precise adjustments in dialysis regimens that may promote better patient outcomes. All of these developments are further driven by technological advancements, for instance, optical sensors and point-of-care devices, for real-time and more sensitive detection of biomarkers. Indeed, the integration of these new biomarkers and technologies may revolutionize dialysis patient monitoring, enabling more tailored and effective strategies.
Referensi
Hill, N. R., Fatoba, S. T., Oke, J. L., Hirst, J. A., O'Callaghan, C. A., Lasserson, D. S., & Hobbs, F. D. R. (2016). Global prevalence of chronic kidney disease–a systematic review and meta-analysis. PloS one, 11(7), e0158765.
Daugirdas, J. T. (2015). Measuring intradialytic hypotension to improve quality of care. Journal of the American Society of Nephrology, 26(3), 512-514.
Chávez-Íñiguez, J. S., Maggiani-Aguilera, P., González-Barajas, D., Rizo-Topete, L., Galindo, P., Rifkin, B., Chávez-Alonso, G., Martínez-Aguilar, A. I., Pérez-Hernández, C., Hernández-Morales, K., Camacho-Guerrero, J. R., Pérez-Venegas, M. A., Oseguera-González, A. N., Murguia-Soto, C., Navarro-Blackaller, G., Medina-González, R., Alcantar-Vallin, L., Renoirte-López, K., & García-García, G. (2023). Urea Reduction in Acute Kidney Injury and Mortality Risk. Kidney & blood pressure research, 48(1), 357–366. https://doi.org/10.1159/000530237
Khan, S. R., Hossain, M. B., Miah, M. O. F., Nira, N. H., Islam, M. S., & Ara, J. (2024). Evaluation of Determinants to Achieve Target Urea Reduction Ratio on Maintenance Hemodialysis Patients in Bangladesh. Mymensingh medical journal : MMJ, 33(3), 724–730.
Fotiadou, E., Georgianos, P. I., Vaios, V., Sgouropoulou, V., Divanis, D., Karligkiotis, A., Leivaditis, K., Chourdakis, M., Zebekakis, P. E., & Liakopoulos, V. (2022). Feeding during Dialysis Increases Intradialytic Blood Pressure Variability and Reduces Dialysis Adequacy. Nutrients, 14(7), 1357. https://doi.org/10.3390/nu14071357
Chidiac, C., Chelala, D., Nassar, D., Beaini, C., Azar, H., Finianos, S., Boueri, C., Hawi, J., Abdo, I., & Aoun, M. (2022). Routine laboratory testing in hemodialysis: how frequently is it needed?. BMC nephrology, 23(1), 344. https://doi.org/10.1186/s12882-022-02971-9
Ekart, R., Varda, L., Vodošek Hojs, N., Dvoršak, B., Piko, N., Bevc, S., & Hojs, R. (2022). Early Detection of Arteriovenous Fistula Stenosis in Hemodialysis Patients through Routine Measurements of Dialysis Dose (Kt/V). Blood purification, 51(1), 15–22. https://doi.org/10.1159/000514939
Béguin, L., Krummel, T., Longlune, N., Galland, R., Couchoud, C., & Hannedouche, T. (2021). Dialysis dose and mortality in haemodialysis: is higher better?. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 36(12), 2300–2307. https://doi.org/10.1093/ndt/gfab202
Gautier, N., Sampol, J., Zagdoun, E., Duquennoy, S., Dione, D. J. P., Edet, S., Lobbedez, T., & Ficheux, M. (2022). What Total Body Water Measurement Should Be Used for Prescribing the Dialysis Dose in Low-Flow Home Daily Dialysis?. Blood purification, 51(6), 540–547. https://doi.org/10.1159/000517815
Kashani, K., Rosner, M. H., & Ostermann, M. (2020). Creatinine: From physiology to clinical application. European journal of internal medicine, 72, 9–14. https://doi.org/10.1016/j.ejim.2019.10.025
Vega, J., & Huidobro E, J. P. (2019). Efectos en la función renal de la suplementación de creatina con fines deportivos [Effects of creatine supplementation on renal function]. Revista medica de Chile, 147(5), 628–633. https://doi.org/10.4067/S0034-98872019000500628
Song, D. K., Hong, Y. S., Sung, Y. A., & Lee, H. (2022). Association of serum creatinine levels and risk of type 2 diabetes mellitus in Korea: a case control study. BMC endocrine disorders, 22(1), 4. https://doi.org/10.1186/s12902-021-00915-2
Chen, D. C., Potok, O. A., Rifkin, D., & Estrella, M. M. (2022). Advantages, Limitations, and Clinical Considerations in Using Cystatin C to Estimate GFR. Kidney360, 3(10), 1807–1814. https://doi.org/10.34067/KID.0003202022
Lees, J. S., Fabian, J., & Shlipak, M. G. (2024). Cystatin C should be routinely available for estimating kidney function. Current opinion in nephrology and hypertension, 33(3), 337–343. https://doi.org/10.1097/MNH.0000000000000980
Spencer, S., Desborough, R., & Bhandari, S. (2023). Should Cystatin C eGFR Become Routine Clinical Practice?. Biomolecules, 13(7), 1075. https://doi.org/10.3390/biom13071075
Paats, J., Adoberg, A., Arund, J., Fridolin, I., Lauri, K., Leis, L., Luman, M., & Tanner, R. (2021). Optical Method and Biochemical Source for the Assessment of the Middle-Molecule Uremic Toxin β2-Microglobulin in Spent Dialysate. Toxins, 13(4), 255. https://doi.org/10.3390/toxins13040255
Brunati, C. C. M., Gervasi, F., Cabibbe, M., Ravera, F., Menegotto, A., Querques, M., & Colussi, G. (2019). Single Session and Weekly Beta 2-Microglobulin Removal with Different Dialytic Procedures: Comparison between High-Flux Standard Bicarbonate Hemodialysis, Post-Dilution Hemodiafiltration, Short Frequent Hemodialysis with NxStage Technology and Automated Peritoneal Dialysis. Blood purification, 48(1), 86–96. https://doi.org/10.1159/000499830
Yu, S., Yang, H., Chen, W., Yuan, H., Xiong, X., Fu, P., & Zeng, X. (2023). Middle-size molecule clearance as measured by β2-microglobulin in high-flux versus low-flux dialysis and hemodiafiltration: A prospective randomized controlled trial. Artificial organs, 47(1), 38–46. https://doi.org/10.1111/aor.14423
Yamamoto S. (2019). Molecular mechanisms underlying uremic toxin-related systemic disorders in chronic kidney disease: focused on β2-microglobulin-related amyloidosis and indoxyl sulfate-induced atherosclerosis-Oshima Award Address 2016. Clinical and experimental nephrology, 23(2), 151–157. https://doi.org/10.1007/s10157-018-1588-9
Quarles L. D. (2019). Fibroblast growth factor 23 and α-Klotho co-dependent and independent functions. Current opinion in nephrology and hypertension, 28(1), 16–25. https://doi.org/10.1097/MNH.0000000000000467
Tresguerres, F. G. F., Torres, J., López-Quiles, J., Hernández, G., Vega, J. A., & Tresguerres, I. F. (2020). The osteocyte: A multifunctional cell within the bone. Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft, 227, 151422. https://doi.org/10.1016/j.aanat.2019.151422
Ridker, P. M., & Rane, M. (2021). Interleukin-6 Signaling and Anti-Interleukin-6 Therapeutics in Cardiovascular Disease. Circulation research, 128(11), 1728–1746. https://doi.org/10.1161/CIRCRESAHA.121.319077
Wei, W., Huang, X., Yang, L., Li, J., Liu, C., Pu, Y., Yu, W., Wang, B., Ma, L., Zhang, L., Fu, P., & Zhao, Y. (2023). Neutrophil-to-Lymphocyte ratio as a prognostic marker of mortality and disease severity in septic Acute kidney injury Patients: A retrospective study. International immunopharmacology, 116, 109778. https://doi.org/10.1016/j.intimp.2023.109778
El Karoui, K., Fervenza, F. C., & De Vriese, A. S. (2024). Treatment of IgA Nephropathy: A Rapidly Evolving Field. Journal of the American Society of Nephrology : JASN, 35(1), 103–116. https://doi.org/10.1681/ASN.0000000000000242
Batchelor, E. K., Kapitsinou, P., Pergola, P. E., Kovesdy, C. P., & Jalal, D. I. (2020). Iron Deficiency in Chronic Kidney Disease: Updates on Pathophysiology, Diagnosis, and Treatment. Journal of the American Society of Nephrology : JASN, 31(3), 456–468. https://doi.org/10.1681/ASN.2019020213
Vasquez-Rios, G., Katz, R., Levitan, E. B., Cushman, M., Parikh, C. R., Kimmel, P. L., Bonventre, J. V., Waikar, S. S., Schrauben, S. J., Greenberg, J. H., Sarnak, M. J., Ix, J. H., Shlipak, M. G., & Gutierrez, O. M. (2023). Urinary Biomarkers of Kidney Tubule Health and Mortality in Persons with CKD and Diabetes Mellitus. Kidney360, 4(9), e1257–e1264. https://doi.org/10.34067/KID.0000000000000226
Hu, L., Napoletano, A., Provenzano, M., Garofalo, C., Bini, C., Comai, G., & La Manna, G. (2022). Mineral Bone Disorders in Kidney Disease Patients: The Ever-Current Topic. International journal of molecular sciences, 23(20), 12223. https://doi.org/10.3390/ijms232012223
Romejko, K., Markowska, M., & Niemczyk, S. (2023). The Review of Current Knowledge on Neutrophil Gelatinase-Associated Lipocalin (NGAL). International journal of molecular sciences, 24(13), 10470. https://doi.org/10.3390/ijms241310470
Zheng, Q., Yang, H., Sun, L., Wei, R., Fu, X., Wang, Y., Huang, Y., Liu, Y. N., & Liu, W. J. (2020). Efficacy and safety of HIF prolyl-hydroxylase inhibitor vs epoetin and darbepoetin for anemia in chronic kidney disease patients not undergoing dialysis: A network meta-analysis. Pharmacological research, 159, 105020. https://doi.org/10.1016/j.phrs.2020.105020
Januzzi, J. L., Mohebi, R., Liu, Y., Sattar, N., Heerspink, H. J. L., Tefera, E., Vaduganathan, M., Butler, J., Yavin, Y., Li, J., Pollock, C. A., Perkovic, V., Neal, B., & Hansen, M. K. (2023). Cardiorenal Biomarkers, Canagliflozin, and Outcomes in Diabetic Kidney Disease: The CREDENCE Trial. Circulation, 148(8), 651–660. https://doi.org/10.1161/CIRCULATIONAHA.123.065251
Ennes Dourado Ferro, F., de Sousa Lima, V. B., Mello Soares, N. R., Franciscato Cozzolino, S. M., & do Nascimento Marreiro, D. (2011). Biomarkers of metabolic syndrome and its relationship with the zinc nutritional status in obese women. Nutricion hospitalaria, 26(3), 650–654. https://doi.org/10.1590/S0212-16112011000300032
Ojo O. (2019). Dietary Intake and Type 2 Diabetes. Nutrients, 11(9), 2177. https://doi.org/10.3390/nu11092177
Aune D. (2019). Plant Foods, Antioxidant Biomarkers, and the Risk of Cardiovascular Disease, Cancer, and Mortality: A Review of the Evidence. Advances in nutrition (Bethesda, Md.), 10(Suppl_4), S404–S421. https://doi.org/10.1093/advances/nmz042
Vesnina, A., Prosekov, A., Atuchin, V., Minina, V., & Ponasenko, A. (2022). Tackling Atherosclerosis via Selected Nutrition. International journal of molecular sciences, 23(15), 8233. https://doi.org/10.3390/ijms23158233
Htay, H., Choo, J. C. J., Huang, D. H., Jayaballa, M., Johnson, D. W., Koniman, R., Oei, E. L., Suai, T. C., Wu, S. Y., & Foo, M. W. Y. (2024). Rapid point-of-care test for diagnosis of peritonitis in peritoneal dialysis patients. Peritoneal dialysis international : journal of the International Society for Peritoneal Dialysis, 8968608241234728. Advance online publication. https://doi.org/10.1177/08968608241234728
Goodlad, C., George, S., Sandoval, S., Mepham, S., Parekh, G., Eberl, M., Topley, N., & Davenport, A. (2020). Measurement of innate immune response biomarkers in peritoneal dialysis effluent using a rapid diagnostic point-of-care device as a diagnostic indicator of peritonitis. Kidney international, 97(6), 1253–1259. https://doi.org/10.1016/j.kint.2020.01.044
Lee, H., Liu, K. H., Yang, Y. H., Liao, J. D., Lin, B. S., Wu, Z. Z., Chang, A. C., Tseng, C. C., Wang, M. C., & Tsai, Y. S. (2024). Advances in uremic toxin detection and monitoring in the management of chronic kidney disease progression to end-stage renal disease. The Analyst, 149(10), 2784–2795. https://doi.org/10.1039/d4an00057a
Sun, T., Qu, S., Huang, T., Ping, Y., Lin, Q., Cao, Y., Liu, W., Wang, D., Kong, P., & Tao, Z. (2021). Rapid and sensitive detection of L-FABP for prediction and diagnosis of acute kidney injury in critically ill patients by chemiluminescent immunoassay. Journal of clinical laboratory analysis, 35(11), e24051. https://doi.org/10.1002/jcla.24051
Oyaert, M., & Delanghe, J. (2019). Progress in Automated Urinalysis. Annals of laboratory medicine, 39(1), 15–22. https://doi.org/10.3343/alm.2019.39.1.15
Postek, W., & Garstecki, P. (2022). Droplet Microfluidics for High-Throughput Analysis of Antibiotic Susceptibility in Bacterial Cells and Populations. Accounts of chemical research, 55(5), 605–615. https://doi.org/10.1021/acs.accounts.1c00729
Kolluri, S., Lin, J., Liu, R., Zhang, Y., & Zhang, W. (2022). Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review. The AAPS journal, 24(1), 19. https://doi.org/10.1208/s12248-021-00644-3
Boehm, K. M., Aherne, E. A., Ellenson, L., Nikolovski, I., Alghamdi, M., Vázquez-García, I., Zamarin, D., Long Roche, K., Liu, Y., Patel, D., Aukerman, A., Pasha, A., Rose, D., Selenica, P., Causa Andrieu, P. I., Fong, C., Capanu, M., Reis-Filho, J. S., Vanguri, R., Veeraraghavan, H., … Shah, S. P. (2022). Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer. Nature cancer, 3(6), 723–733. https://doi.org/10.1038/s43018-022-00388-9
Poweleit, E. A., Vinks, A. A., & Mizuno, T. (2023). Artificial Intelligence and Machine Learning Approaches to Facilitate Therapeutic Drug Management and Model-Informed Precision Dosing. Therapeutic drug monitoring, 45(2), 143–150. https://doi.org/10.1097/FTD.0000000000001078
Thagaard, J., Broeckx, G., Page, D. B., Jahangir, C. A., Verbandt, S., Kos, Z., Gupta, R., Khiroya, R., Abduljabbar, K., Acosta Haab, G., Acs, B., Akturk, G., Almeida, J. S., Alvarado-Cabrero, I., Amgad, M., Azmoudeh-Ardalan, F., Badve, S., Baharun, N. B., Balslev, E., Bellolio, E. R., … Specht Stovgaard, E. (2023). Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer. The Journal of pathology, 260(5), 498–513. https://doi.org/10.1002/path.6155












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