Integration of Biomarkers in III and IV CKD Patients for Evaluation of Their Predictive Value for CVD in CKD Patients

Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 15 | Issue : 03 | Page : 1 12
    By

    Vijaya Kumar Malladi,

  • Bhamidipaty Kanaka Durgaprasad,

  • Rama Rao Malla,

  1. PG Student, Department of Microbiology, Central Institute of Fisheries Technology (ICAR-CIFT), Visakhapatnam, Andhra Pradesh, India
  2. Professor, Department of Radiodiagnosis, NRIIMS, Visakhapatnam, Andhra Pradesh, India
  3. Professor, Department of Biochemistry and Bioinformatics, GIS, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India

Abstract

Background: Chronic kidney disease (CKD) is presently characterized by the presence of proteinuria and/or a diagnosis of renal impairment. The worldwide significance of CKD is underscored by the fact that its prevalence and incidence have doubled over the past three decades. This paper provides an overview of the existing evidence regarding biomarkers in individuals with CVD or CKD, with a particular focus on the emerging biomarkers (i.e., eGFR, sALB, UACR, hs-CRP, p-FGN, h-FABP, serum lipids and CIMT). Additionally, it explores the potential contributions of these markers to understanding the interactions between the heart and kidney and their application in diagnostic and therapeutic approaches for cardiorenal syndrome. Methods: Receiver operating characteristic (ROC) curve analyses were performed to identify the optimal cut-off values and evaluate the predictive performance for cardiovascular disease (CVD) in patients with stage III and IV chronic kidney disease (CKD). The Youden Index, a statistical approach that maximizes the combined sensitivity and specificity, was used to determine the cut-off points. Results: In integration of eGFR, sALB, UACR, hs-CRP, p-FGN, h-FABP, serum lipids and CIMT reveals that the Sn and Sn of all biomarkers of stage III was 100 and 62 and stage IV was 97.8 and 98.2, respectively, while PPV of stage III was 48.70 and stage IV was 95.70, respectively. Further, the NPV of stage III was 100.00 and stage IV was 99.10, respectively, however, AUC in stage III was 0.81 and stage IV was 0.98 and DA of stage III was 74.35 and stage IV was 97.4 in CKD patients. Conclusion: Combination of eGFR, sALB and UACR – best for stage III CKD Combination of all the biomarkers used in this study – best for stage IV CKD.

Keywords: Biomarkers, cardiovascular disease, chronic kidney disease, C-reactive protein, eGFR, UACR, hs-CRP, p-FGN, h-FABP, serum lipids, CIMT and serum creatinine

[This article belongs to Research and Reviews: A Journal of Medicine ]

How to cite this article:
Vijaya Kumar Malladi, Bhamidipaty Kanaka Durgaprasad, Rama Rao Malla. Integration of Biomarkers in III and IV CKD Patients for Evaluation of Their Predictive Value for CVD in CKD Patients. Research and Reviews: A Journal of Medicine. 2025; 15(03):1-12.
How to cite this URL:
Vijaya Kumar Malladi, Bhamidipaty Kanaka Durgaprasad, Rama Rao Malla. Integration of Biomarkers in III and IV CKD Patients for Evaluation of Their Predictive Value for CVD in CKD Patients. Research and Reviews: A Journal of Medicine. 2025; 15(03):1-12. Available from: https://journals.stmjournals.com/rrjom/article=2025/view=228978


References

  1. Utsumi K, Katsura K, Iino Y, Katayama Y. Blood pressure control in patients with chronic kidney disease. J Nippon Med Sch. 2012;79(2):111–4. doi:10.1272/jnms.79.111.
  2. Zhu Y, Tao S, Zhang D, Xiao J, Wang X, Yuan L, et al. Association between fibrinogen/albumin ratio and severity of coronary artery calcification in patients with chronic kidney disease: A retrospective study. PeerJ. 2022;10:e13550. doi:10.7717/peerj.13550.
  3. Banait T, Wanjari A, Danade V, Banait S, Jain J. Role of High-Sensitivity C-reactive Protein (Hs-CRP) in Non-communicable Diseases: A Review. Cureus. 2022;14(10):e30225. doi:10.7759/cureus.30225.
  4. Scarpioni R, Ricardi M, Melfa L, Cristinelli L. Dyslipidemia in chronic kidney disease: Are statins still indicated in reduction cardiovascular risk in patients on dialysis treatment? Cardiovasc Ther. 2010;28(6):361–8. doi:10.1111/j.1755-5922.2010.00182.x.
  5. Ye XD, He Y, Wang S, Wong GT, Irwin MG, Xia Z. Heart-type fatty acid binding protein (H-FABP) as a biomarker for acute myocardial injury and long-term post-ischemic prognosis. Acta Pharmacol Sin. 2018;39(7):1155–63. doi:10.1038/aps.2018.37.
  6. Sathi S, Mahapatra H, Sunder S, Jayaraman R, Sharma N, Verma H, et al. Nontraditional cardiovascular biomarkers and estimation of cardiovascular risk in predialysis chronic kidney disease patients and their correlations with carotid intima media thickness. Nephrourol Mon. 2014;6(6):e22112. doi:10.5812/numonthly.22112.
  7. Khanna NN, Jamthikar AD, Gupta D, Nicolaides A, Araki T, Saba L, et al. Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study. Comput Biol Med. 2019;105:125–43.
  8. Sun J, Axelsson J, Machowska A, Heimbürger O, Bárány P, Lindholm B, et al. Biomarkers of Cardiovascular Disease and Mortality Risk in Patients with Advanced CKD. Clin J Am Soc Nephrol. 2016;11(7):1163–72. doi:10.2215/cjn.10441015.
  9. Adejumo OA, Okaka EI, Okwuonu CG, Iyawe IO, Odujoko OO. Serum C-reactive protein levels in pre-dialysis chronic kidney disease patients in southern Nigeria. Ghana Med J. 2016;50(1):31–8. doi:10.4314/gmj.v50i1.5.
  10. Akpinar G, Duman A, Gulen B, Kapci M, Altinbilek E, Ikizceli I. Role of H-FABP values in determining the etiologic factors of the cardiac injuries. Pan Afr Med J. 2017;26:36. doi:10.11604/pamj.2017.26.36.8746.
  11. Al-Hadi HA, William B, Fox KA. Serum level of heart-type Fatty Acid-binding protein in patients with chronic renal failure. Sultan Qaboos Univ Med J. 2009;9(3):311–4.
  12. Allain CC, Poon LS, Chan CS, Richmond W, Fu PC. Enzymatic determination of total serum cholesterol. Clin Chem. 1974;20(4):470–5.
  13. Amano H, Yoshimura K, Iijima R, Waki K, Matsumoto K, Ueda H, et al. A slight decrease in the serum albumin level is associated with the rapid progression of kidney dysfunction, even within the normal range. Intern Med. 2020;59(21):2679–85. doi:10.2169/internalmedicine.4466-20.
  14. Ammirati AL. Chronic Kidney Disease. Rev Assoc Med Bras (1992). 2020;66 Suppl 1:S03–9. doi:10.1590/1806-9282.66.S1.3
  15. Arzpeyma SF, Saheli YH, Sattarzadeh AB, Kazemnezhad Leyli E. Studying the relationship between the risk factors of cardiovascular diseases and carotid intima‐media thickness (CIMT) in renal patients undergoing hemodialysis admitted to Razi Hospital and Caspian Dialysis Center in Rasht, 2017. Rev Latinoam Hipertens. 2018;13(3):251–8.
  16. Azzazy HM, Pelsers MM, Christenson RH. Unbound free fatty acids and heart-type fatty acid-binding protein: diagnostic assays and clinical applications. Clin Chem. 2006;52(1):19–29. doi:10.1373/clinchem.2005.056143.
  17. Lawal OM, Balogun MO, Akintomide AO, Ayoola OO, Mene-Afejuku TO, Ogunlade O, et al. Carotid Intima-Media Thickness: A Surrogate Marker for Cardiovascular Disease in Chronic Kidney Disease Patients. Clin Med Insights Cardiol. 2019;13:1179546819852941. doi:10.1177/1179546819852941.
  18. Lee C, Park KH, Joo YS, Nam KH, Chang TI, Kang EW, et al. Low High-Sensitivity C-Reactive Protein Level in Korean Patients With Chronic Kidney Disease and Its Predictive Significance for Cardiovascular Events, Mortality, and Adverse Kidney Outcomes: Results From KNOW-CKD. J Am Heart Assoc. 2020;9(21):e017980. doi:10.1161/jaha.120.017980.
  19. Lee Y, Park S, Lee S, Kim Y, Kang MW, Cho S, et al. Lipid profiles and risk of major adverse cardiovascular events in CKD and diabetes: A nationwide population-based study. PLoS One. 2020;15(4):e0231328. doi:10.1371/journal.pone.0231328.
  20. Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. Definition and classification of chronic kidney disease: A position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2005;67(6):2089–100. doi:10.1111/j.1523-1755.2005.00365.x.
  21. Lopez-Giacoman S, Madero M. Biomarkers in chronic kidney disease, from kidney function to kidney damage. World J Nephrol. 2015;4(1):57–73. doi:10.5527/wjn.v4.i1.57.
  22. Makita S, Nakamura M, Satoh K, Tanaka F, Onoda T, Kawamura K, et al. Serum C-reactive protein levels can be used to predict future ischemic stroke and mortality in Japanese men from the general population. Atherosclerosis. 2009;204(1):234–8. doi:10.1016/j.atherosclerosis.2008.07.040.
  23. Malhotra R, Katz R, Jotwani V, Agarwal A, Cohen DL, Cushman WC, et al. Estimated GFR Variability and Risk of Cardiovascular Events and Mortality in SPRINT (Systolic Blood Pressure Intervention Trial). Am J Kidney Dis. 2021;78(1):48–56. doi:10.1053/j.ajkd.2020.10.016.
  24. Mandal C, Dutta PK. Study of Prevalence of Cardiovascular Abnormalities Using ECG & 2D- Echo in Chronic Kidney Disease Patients in Kolkata. J Assoc Physicians India. 2020;68(1):74.
  25. Manolis AA, Manolis TA, Melita H, Mikhailidis DP, Manolis AS. Low serum albumin: A neglected predictor in patients with cardiovascular disease. Eur J Intern Med. 2022;102:24–39. doi:10.1016/j.ejim.2022.05.004.
  26. Manolis AA, Manolis TA, Melita H, Mikhailidis DP, Manolis AS. Low serum albumin: A neglected predictor in patients with cardiovascular disease. Eur J Intern Med. 2022;102:24–39. doi:10.1016/j.ejim.2022.05.004.
  27. Marcos AG, Watanabe R, Lemos MM, Canziani ME. Evaluation of intima-media thickness in patients with chronic kidney disease not on dialysis: A prospective study of 24 months. J Bras Nefrol. 2014;36(1):35–41. doi:10.5935/0101-2800.20140007.
  28. Massy ZA, Taupin P, Jungers P, Landais P. Prediction model of coronary heart disease in patients with chronic kidney disease: Role of plasma fibrinogen as a new prognostic variable. Prilozi. 2005;26(2):63–77.
  29. Matsushita K, Ballew SH, Coresh J. Cardiovascular risk prediction in people with chronic kidney disease. Curr Opin Nephrol Hypertens. 2016;25(6):518–23. doi:10.1097/mnh.0000000000000265.
  30. McCann CJ, Glover BM, Menown IB, Moore MJ, McEneny J, Owens CG, et al. Prognostic value of a multimarker approach for patients presenting to hospital with acute chest pain. Am J Cardiol. 2009;103(1):22–8. doi:10.1016/j.amjcard.2008.08.026.
  31. Meng Z, Zhao Y, He Y. Fibrinogen Level Predicts Outcomes in Critically Ill Patients with Acute Exacerbation of Chronic Heart Failure. Dis Markers. 2021;2021:6639393. doi:10.1155/2021/6639393.
Regular Issue Subscription Original Research
Volume 15
Issue 03
Received 17/05/2025
Accepted 22/06/2025
Published 09/10/2025
Publication Time 145 Days
35

Login


My IP

PlumX Metrics