PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Optimal potassium removal in hemodialysis (HD) is an important but difficult to achieve goal, influenced by numerous factors. Two types of single-solute mathematical models have been previously proposed to assess potassium kinetics in HD: pseudo-one compartment ( p1) and two-compartment models (2c). We compared these two models in simulating potassium kinetics during HD sessions with different treatment settings. After estimation of unknown parameters via fitting to clinical data during 4 h sessions with a dialysate potassium of 2.6 ± 0.6 mmol/L, the models were used to simulate 4 HD sessions for each patient, resulting from the combination of session length (4 h vs. 8 h) and potassium dialysate concentration (2.6 vs. 0 mmol/L). The simulated potassium concentration profiles were similar under different treatment conditions, and predicted potassium removal during the treatments was 77 ± 24 mmol with the standard settings; both increases in session length and potassium dialysate to plasma concentration gradient resulted in a significant increase in potassium removed. Both models indicated similar minimum values of dialysate potassium concentration required to avoid post-HD hypokalemia: 1.18 ± 0.66 mmol/L for 4 h HD and 1.71 ± 0.52 mmol/L for 8 h HD. The models described similar kinetics for potassium during different combinations of treatment settings. Total removal of potassium and minimum dialysate concentration to avoid post-HD hypokalemia, were predicted without significant differences by both models. Although no model has a clear advantage in terms of describing clinical data, our analyses suggest that 2c might offer a better trade-off between physiological accuracy and over-parametrization.
Twórcy
  • Nalecz Institute of Biocybernetics and Biomedical Engineering PAS, Trojdena 4, 02-109 Warsaw, Poland
  • Nalecz Institute of Biocybernetics and Biomedical Engineering PAS, Warsaw, Poland
  • Department of Nephrology, Medical University of Lublin, Lublin, Poland
  • Department of Rehabilitation and Physiotherapy, Medical University of Lublin, Lublin, Poland
  • Nalecz Institute of Biocybernetics and Biomedical Engineering PAS, Warsaw, Poland
Bibliografia
  • [1] Iseki K, Uehara H, Nishime K, Tokuyama K, Yoshihara K, Kinjo K, et al. Impact of the initial levels of laboratory variables on survival in chronic dialysis patients. Am J Kidney Dis 1996;28(4):541–8.
  • [2] Kovesdy CP, Regidor DL, Mehrotra R, Jing J, McAllister CJ, Greenland S, et al. Serum and dialysate potassium concentrations and survival in hemodialysis patients. Clin J Am Soc Nephrol 2007;2(5):999–1007.
  • [3] Karnik JA, Young BS, Lew NL, Herget M, Dubinsky C, Lazarus JM, et al. Cardiac arrest and sudden death in dialysis units. Kidney Int 2001;60(1):350–7.
  • [4] Jadoul M, Thumma J, Fuller DS, Tentori F, Li Y, Morgenstern H, et al. Modifiable practices associated with sudden death among hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study. Clin J Am Soc Nephrol 2012;7 (5):765–74.
  • [5] Pun PH. Dialysate potassium concentration: should mass balance trump electrophysiology? Semin Dial 2018;31:567–75.
  • [6] Pun PH, Middleton JP. Dialysate potassium, dialysate magnesium, and hemodialysis risk. J Am Soc Nephrol 2017;28(12):3441–51.
  • [7] Genovesi S, Dossi C, Vigano MR, Galbiati E, Prolo F, Stella A, et al. Electrolyte concentration during haemodialysis and QT interval prolongation in uraemic patients. Europace 2008;10(6):771–7.
  • [8] Genovesi S, Valsecchi MG, Rossi E, Pogliani D, Acquistapace I, De Cristofaro V, et al. Sudden death and associated factors in a historical cohort of chronic haemodialysis patients. Nephrol Dial Transplant 2009;24(8):2529–36.
  • [9] Brunelli SM, Spiegel DM, Du Mond C, Oestreicher N, Winkelmayer WC, Kovesdy CP. Serum-to-dialysate potassium gradient and its association with short-term outcomes in hemodialysis patients. Nephrol Dial Transplant 2018;33(7):1207–14.
  • [10] Brunelli SM, Du Mond C, Oestreicher N, Rakov V, Spiegel DM. Serum potassium and short-term clinical outcomes among hemodialysis patients: impact of the long interdialytic interval. Am J Kidney Dis 2017;70(1):21–9.
  • [11] Lopes MB, Rocha PN, Pecoits-Filho R. Updates on medical management of hyperkalemia. Curr Opin Nephrol Hypertens 2019;28(5):417–23.
  • [12] Rocco MV, Lockridge Jr RS, Beck GJ, Eggers PW, Gassman JJ, Greene T, et al. The effects of frequent nocturnal home hemodialysis: the Frequent Hemodialysis Network Nocturnal Trial. Kidney Int 2011;80(10):1080–91.
  • [13] Basile C, Libutti P, Lisi P, Teutonico A, Vernaglione L, Casucci F, et al. Ranking of factors determining potassium mass balance in bicarbonate haemodialysis. Nephrol Dial Transplant 2015;30(3):505–13.
  • [14] Leypoldt JK, Agar BU, Bernardo AA, Culleton BF. Prescriptions of dialysate potassium concentration during short daily or long nocturnal (high dose) hemodialysis. Hemodial Int 2016;20(2):218–25.
  • [15] Leypoldt JK, Kraus MA, Jaber BL, Weinhandl ED, Collins AJ. Effect of dialysate potassium and lactate on serum potassium and bicarbonate concentrations during daily hemodialysis at low dialysate flow rates. BMC Nephrol 2019;20(1):252.
  • [16] Agar BU, Culleton BF, Fluck R, Leypoldt JK. Potassium kinetics during hemodialysis. Hemodial Int 2015;19(1):23–32.
  • [17] Ciandrini A, Severi S, Cavalcanti S, Fontanazzi F, Grandi F, Buemi M, et al. Model-based analysis of potassium removal during hemodialysis. Artif Organs 2009;33(10):835–43.
  • [18] Ursino M, Donati G. Mathematical model of potassium profiling in chronic dialysis. Contrib Nephrol 2017;190:134–45.
  • [19] Pietribiasi M, Waniewski J, Wójcik-Zaluska A, Zaluska W, Lindholm B. Model of fluid and solute shifts during hemodialysis with active transport of sodium and potassium. PLOS ONE 2018;13(12):e0209553.
  • [20] Akaike H. A new look at the statistical model identification. IEEE Trans Automatic Control 1974;19(6):716–23.
  • [21] Debowska M, Wojcik-Zaluska A, Ksiazek A, Zaluska W, Waniewski J. Phosphate, urea and creatinine clearances: haemodialysis adequacy assessed by weekly monitoring. Nephrol Dial Transplant 2015;30(1):129–36.
  • [22] Agar BU, Akonur A, Lo YC, Cheung AK, Leypoldt JK. Kinetic model of phosphorus mobilization during and after short and conventional hemodialysis. Clin J Am Soc Nephrol 2011;6(12):2854–60.
  • [23] Debowska M, Poleszczuk J, Wojcik-Zaluska A, Ksiazek A, Zaluska W. Phosphate kinetics during weekly cycle of hemodialysis sessions: application of mathematical modeling. Artif Organs 2015;39(12):1005–14.
  • [24] Lentner C, editor. Geigy scientific tables: physical chemistry, composition of blood, hematology, somatometric data. Geigy scientific tables. Vol. 3. 8th edition. Basle: Ciba-Geigy Limited; 1984.
  • [25] Burnham KP, Anderson DR. Model selection and multimodel inference. 2nd edition. New York: Springer- Verlag; 2002.
  • [26] Cavanaugh JE. Unifying the derivations for the Akaike and corrected Akaike information criteria. Stat Prob Lett 1997;33 (2):201–8.
  • [27] Leypoldt JK, Agar BU, Akonur A, Gellens ME, Culleton BF. Steady state phosphorus mass balance model during hemodialysis based on a pseudo one-compartment kinetic model. Int J Artif Organs 2012;35(11):969–80.
  • [28] Coli L, Ursino M, De Pascalis A, Brighenti C, Dalmastri V, La Manna G, et al. Evaluation of intradialytic solute and fluid kinetics. Setting up a predictive mathematical model. Blood Purif 2000;18(1):37–49.
  • [29] Scharfetter H, Wirnsberger G, Hutten H, Holzer H. Development and critical evaluation of an improved comprehensive multicompartment model for the exchange processes during hemodialysis. Biomed Tech (Berl) 1995;40 (3):54–63.
  • [30] Pun PH, Lehrich RW, Honeycutt EF, Herzog CA, Middleton JP. Modifiable risk factors associated with sudden cardiac arrest within hemodialysis clinics. Kidney Int 2011;79 (2):218–27.
  • [31] Ferrey A, You AS, Kovesdy CP, Nakata T, Veliz M, Nguyen DV, et al. Dialysate potassium and mortality in a prospective hemodialysis cohort. Am J Nephrol 2018;47(6):415–23.
  • [32] Al-Ghamdi G, Hemmelgarn B, Klarenbach S, Manns B, Wiebe N, Tonelli M. Dialysate potassium and risk of death in chronic hemodialysis patients. J Nephrol 2010;23 (1):33–40.
  • [33] Sargent GA, Gotch FA. Principles and biophysics of dialysis. In: Maher JF, editor. Replacement of renal function by dialysis. Dordrecht: Kluwer Academic Publishers; 1989. p. 53–96.
  • [34] Werynski A, Waniewski J. Theoretical description of mass transport in medical membrane devices. Artif Organs 1995;19(5):420–7.
  • [35] Jaffrin MY. Convective mass transfer in hemodialysis. Artif Organs 1995;19(11):1162–71.
  • [36] Guyton A, Hall J. The kidneys and body fluids. Textbook of medical physiology. Philadelphia: Elsevier Saunders; 2006. p. 291–306.
  • [37] Luo CH, Rudy Y. A model of the ventricular cardiac action potential, depolarization, repolarization, and their interaction. Circ Res 1991;68(6):1501–26.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dbeb2053-75e1-4e44-94ee-2c32853aa014
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.