Vol 6, No 4 (2021)
Original article
Published online: 2021-11-16

open access

Page views 5823
Article views/downloads 419
Get Citation

Connect on Social Media

Connect on Social Media

Glomerular filtration formulas to assess clinical and neuropsychological status in geriatric patients with chronic heart failure: a comparison of three formulas

Agnieszka Stachowicz-Karpińska1, Alicja Popiołek12, Aleksandra Chyrek-Tomaszewska12, Grzegorz Pulkowski2, Andrzej Brymora3, Anna Lewandowska4, Robert Szafkowski5, Alina Borkowska1, Maciej Kazimierz Bieliński1
Medical Research Journal 2021;6(4):305-311.

Abstract

Introduction: Impaired renal function is a common problem among elderly patients with chronic heart failure. It is related to prognosis and treatment. The most proper assessment of glomerular filtration in this population seems to be crucial, but despite technological advances, it is still relatively difficult. This study aimed to find the best glomerular filtration formula in the group of geriatric patients with chronic heart failure, which would correlate with their clinical and psychological status.

Material and methods: The study was conducted in a group of 101 hospitalized patients aged over 60 with stable chronic heart failure. All patients were subjected to clinical and psychological evaluation. Obtained data were compared with the estimated glomerular filtration rate calculated by three equations (Cockcroft-Gault with adjustment for body surface area, Modification of Diet in Renal Disease, and Chronic Kidney Disease Epidemiology).

Results:
For all 3 formulas, statistically significant correlations were found between renal function and age, the New York Heart Association functional class, a period of hospitalization, N-terminal-pro-B-type natriuretic peptide, and a 6-minute walk test score. The widest range of values was found for the Cockcroft-Gault formula with adjustment for body surface area. The Cockcroft-Gault formula with adjustment for body surface area showed also strong associations with cognitive functioning.

Conclusions: Renal function calculated by the Cockcroft-Gault formula with adjustment for body surface area highly correlates with psychological parameters among geriatric patients with congestive heart failure (CHF).

Article available in PDF format

View PDF Download PDF file

References

  1. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure. Rev Esp Cardiol (Engl Ed). 2016; 69(12): 1167.
  2. Dardiotis E, Giamouzis G, Mastrogiannis D, et al. Cognitive impairment in heart failure. Cardiol Res Pract. 2012; 2012: 595821.
  3. Hill E, Taylor J. Chronic heart failure care planning: considerations in older patients. Card Fail Rev. 2017; 3(1): 46–51.
  4. Scherbakov N, Haeusler KG, Doehner W. Ischemic stroke and heart failure: facts and numbers. ESC Heart Fail. 2015; 2(1): 1–4.
  5. Qiu C, Winblad B, Marengoni A, et al. Heart failure and risk of dementia and Alzheimer disease: a population-based cohort study. Arch Intern Med. 2006; 166(9): 1003–1008.
  6. Eisele M, Blozik E, Störk S, et al. Recognition of depression and anxiety and their association with quality of life, hospitalization and mortality in primary care patients with heart failure - study protocol of a longitudinal observation study. BMC Fam Pract. 2013; 14: 180.
  7. Garcia S, Spitznagel MB, Cohen R, et al. Depression is associated with cognitive dysfunction in older adults with heart failure. Cardiovasc Psychiatry Neurol. 2011; 2011: 368324.
  8. Cannon JA, McMurray JJv, Quinn TJ. 'Hearts and minds': association, causation and implication of cognitive impairment in heart failure. Alzheimers Res Ther. 2015; 7(1): 22.
  9. Zamora E, Lupón J, Vila J, et al. Estimated glomerular filtration rate and prognosis in heart failure. J Am Coll Cardiol. 2012; 59(19): 1709–1715.
  10. Löfman I, Szummer K, Hagerman I, et al. Prevalence and prognostic impact of kidney disease on heart failure patients. Open Heart. 2016; 3(1): e000324.
  11. Szummer K, Evans M, Carrero JJ, et al. Comparison of the chronic kidney disease epidemiology collaboration, the modification of diet in renal disease study and the Cockcroft-Gault equation in patients with heart failure. Open Heart. 2017; 4(2): e000568.
  12. KDIGO CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013; 3(1).
  13. Sasaki Y, Marioni R, Kasai M, et al. Chronic kidney disease: a risk factor for dementia onset: a population-based study. The Osaki-Tajiri Project. J Am Geriatr Soc. 2011; 59(7): 1175–1181.
  14. Franke K, Ristow M, Gaser C, et al. Alzheimer's Disease Neuroimaging Initiative. Gender-specific impact of personal health parameters on individual brain aging in cognitively unimpaired elderly subjects. Front Aging Neurosci. 2014; 6: 94.
  15. Raman M, Middleton RJ, Kalra PA, et al. Estimating renal function in old people: an in-depth review. Int Urol Nephrol. 2017; 49(11): 1979–1988.
  16. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976; 16(1): 31–41.
  17. Levey AS, Coresh J, Greene T, et al. Chronic Kidney Disease Epidemiology Collaboration. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006; 145(4): 247–254.
  18. Levey AS, Stevens LA, Schmid CH, et al. CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009; 150(9): 604–612.
  19. Szummer K, Lundman P, Jacobson SH, et al. SWEDEHEART. Cockcroft-Gault is better than the modification of diet in renal disease study formula at predicting outcome after a myocardial infarction: data from the Swedish web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART). Am Heart J. 2010; 159(6): 979–986.
  20. Zdrojewski Ł, Rutkowski B. MDRD or CKD-EPI equation — revolution or evolution? Forum Nefrologiczne. 2014; 7(1): 38–44.
  21. ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002; 166(1): 111–117.
  22. Jarzemski P, Brzoszczyk B, Popiołek A, et al. Cognitive function, depression, and anxiety in patients undergoing radical prostatectomy with and without adjuvant treatment. Neuropsychiatr Dis Treat. 2019; 15: 819–829.
  23. Kitamura M, Izawa KP, Taniue H, et al. Activities of daily living at different levels of renal function in elderly hospitalized heart failure patients. Aging Clin Exp Res. 2018; 30(1): 45–51.
  24. Elias MF, Davey A, Dore GA, et al. Kidney disease and cognitive function. Contrib Nephrol. 2013; 179(2): 42–57.
  25. Burns CM, Knopman DS, Tupper DE, et al. Prevalence and risk of severe cognitive impairment in advanced chronic kidney disease. J Gerontol A Biol Sci Med Sci. 2018; 73(3): 393–399.
  26. Silverwood RJ, Richards M, Pierce M, et al. NSHD scientific and data collection teams. Cognitive and kidney function: results from a British birth cohort reaching retirement age. PLoS One. 2014; 9(1): e86743.
  27. Palmer N, Sink K, Smith S, et al. Kidney disease and cognitive function: African American-Diabetes Heart Study MIND. American Journal of Nephrology. 2014; 40(3): 200–207.
  28. Ferreira JP, Girerd N, Pellicori P, et al. Heart ‘OMics’ in AGEing (HOMAGE) initiative and the High-Risk Myocardial Infarction database initiative. Renal function estimation and Cockroft-Gault formulas for predicting cardiovascular mortality in population-based, cardiovascular risk, heart failure and post-myocardial infarction cohorts: The Heart 'OMics' in AGEing (HOMAGE) and the high-risk myocardial infarction database initiatives. BMC Med. 2016; 14(1): 181.
  29. Parsh J, Seth M, Aronow H, et al. Choice of estimated glomerular filtration rate equation impacts drug-dosing recommendations and risk stratification in patients with chronic kidney disease undergoing percutaneous coronary interventions. J Am Coll Cardiol. 2015; 65(25): 2714–2723.
  30. Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med. 2004; 351(13): 1296–1305.
  31. Weidmann ZM, Breidthardt T, Twerenbold R, et al. Prediction of mortality using quantification of renal function in acute heart failure. Int J Cardiol. 2015; 201: 650–657.
  32. Oreopoulos A, Padwal R, Kalantar-Zadeh K, et al. Body mass index and mortality in heart failure: a meta-analysis. Am Heart J. 2008; 156(1): 13–22.
  33. Bieliński M, Lesiewska N, Jaracz M, et al. Brain-derived neurotrophic factor val66met polymorphism in contex of executive functions and working memory in obese patients. Neuropsychiatry. 2018; 8(1): 111–118.