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NDT Advance Access published online on February 13, 2007
Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfl799
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Prevention of dialysis hypotension episodes using fuzzy logic control system

Elena Mancini1, Emanuele Mambelli1, Mina Irpinia1, Danila Gabrielli2, Carmelo Cascone3, Ferruccio Conte4, Gina Meneghel5, Fosco Cavatorta6, Alessandro Antonelli7, Giuseppe Villa8, Antonio Dal Canton9, Leonardo Cagnoli10, Filippo Aucella11, Fulvio Fiorini12, Enzo Gaggiotti13, Giorgio Triolo14, Vitale Nuzzo15 and Antonio Santoro1

Nephrology and Dialysis Departments of 1Nephrology, Dialysis and Hypertension Division, Policlinico S.Orsola-Malpighi, Bologna, Italy, 2Ospedale Regionale, Aosta, 3Ospedale S. Giacomo Apostolo, Castelfranco Veneto (TV), 4Ospedale Uboldo, Cernusco sul Naviglio (MI), 5Ospedale Civile Dolo, 6Ospedale Civile, Imperia,7Ospedale Campo di Marte, Lucca, 8Fondazione S. Maugeri, Pavia, 9IRCCS Policlinico S. Matteo, Università di Pavia, 10Ospedale degli Infermi, Rimini, 11IRCCS ‘Casa Sollievo della Sofferenza’, S.Giovanni Rotondo (FG), 12Ospedale dei Fiori, Sanremo, 13Policlinico Le Scotte, Siena, 14Azienda Ospedaliera C.T.O., Maria Adelaide Civile Torino and 15Ospedale Pia Fondazione ‘Cardinal Panico’, Tricase (LE), Italy

Correspondence and offprint requests to: Dr Antonio Santoro, Malpighi Nephrology, Dialysis & Hypertension Division, Policlinico S. Orsola-Malpighi, Via P. Palagi 9, 40138 Bologna, Italy. Email: santoro{at}aosp.bo.it



  Abstract

Background. Automatic systems for stabilizing blood pressure (BP) during dialysis are few and only control those variables indirectly related to BP. Due to complex BP regulation under dynamic dialysis conditions, BP itself appears to be the most consistent input parameter for a device addressed to preventing dialysis hypotension (DH).

Methods. An automatic system (ABPS, automatic blood pressure stabilization) for BP control by fluid removal feedback regulation is implemented on a dialysis machine (Dialog Advanced, Braun). A fuzzy logic (FL) control runs in the system, using instantaneous BP as the input variable governing the ultrafiltration rate (UFR) according to the BP trend. The system is user-friendly and just requires the input of two data: critical BP (individually defined as the possible level of DH risk) and the highest UFR applicable (percentage of the mean UFR). We evaluated this system's capacity to prevent DH in 55 RDT hypotension-prone patients. Sessions with (treatment A) and without (treatment B) ABPS were alternated one-by-one for 30 dialysis sessions per patient (674 with ABPS vs 698 without).

Results. Despite comparable treatment times and UF volumes, severe DH appeared in 8.3% of sessions in treatment A vs 13.8% in treatment B (–39%, P = 0.01). Mild DH fell non-significantly (–12.3%). There was a similar percentage of sessions in which the planned body weight loss was not achieved and dialysis time was prolonged.

Conclusions. In conclusion, FL may be suited to interpreting and controlling the trend of a determined multi-variable parameter like BP. The medical knowledge of the patient and the consequent updating of input parameters depending on the patient's clinical conditions seem to be the main factors for obtaining optimal results.

Keywords: biofeedback control; blood pressure; dialysis hypotension; fuzzy control; haemodynamics

Received for publication: 25. 5.06
Accepted in revised form: 7.12.06


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