Automatic Control of Blood Volume Trends during Hemodialysis

Santoro, Antonio; Mancini, Elena; Paolini, Francesco; Spongano, M.; Zucchelli, P

doi:10.1097/00002480-199407000-00033

Cited by 47 publications

(42 citation statements)

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“…IDH are caused by an imbalance between the prescribed weight loss, the plasma refilling capacity, and the cardiovascular system compensatory mechanism. To prevent IDH, an innovative, multi-input multi-output controller named Hemocontrol TM has been developed [36]. Hemocontrol TM assesses 3 variables (blood volume, total weight loss, and average dialysate sodium level) and controls 2 dialysis parameters (UF and dialysate sodium level).…”

Section: Hemocontrol Tm and ML Systemsmentioning

confidence: 99%

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy

et al. 2018

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Background: Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient’s quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of “big data” and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L’Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Summary and Key Messages: Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising approaches for the prescription and monitoring of hemodialysis therapy. Current dialysis machines are continuously improving due to innovative technological developments, but patient safety is still a key challenge. Real-time monitoring systems, coupled with automatic instantaneous biofeedback, will allow changing dialysis prescriptions continuously. The integration of vital sign monitoring with dialysis parameters will produce large data sets that will require the use of data analysis techniques, possibly from the area of machine learning, in order to make better decisions and increase the safety of patients.

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Section: Hemocontrol Tm and ML Systemsmentioning

confidence: 99%

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy

et al. 2018

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“…The Hemocontrol® blood volume management system was first designed by Santoro and colleagues (Santoro et al, 1994) and afterwards modified in collaboration with the HospalGambro research group. It is available on the Integra® and Artis® machines (with a few updates on the latter).…”

Section: Hemocontrol® Systemmentioning

confidence: 99%

“…Of note, most studies that reported beneficial effects of biofeedback systems found similar results with regard to RBV changes during HD suggesting that reduction of IDH might not be exclusively explained by RBV preservation. As postulated by several authors, it is possible that treatment with BV automatic feedback exerts its favourable hemodynamic effect by preventing rapid RBV fluctuations (Santoro et al, 1994). To evaluate whether BP stabilisation obtained per-dialysis with Hemocontrol® in IDHprone patients was also sustained in the post-HD period, Franssen et al (2005) used 24h BP monitoring in a small prospective study.…”

Section: Reduction Of Intradialytic Hypotension and Nursing Interventmentioning

confidence: 99%

Automated Blood Volume Regulation During Hemodialysis

Chapdelaine¹,

Déziel²,

Madore³

2011

Progress in Hemodialysis - From Emergent Biotechnology to Clinical Practice

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“…Over the last 3 years we have studied more than 80 regular HD patients for more than 300 HD sessions with a noninvasive contin uous computerized recording system of all the above-cited control hemodynamic parame ters, as previously published [12][13][14][15][16], Sys tolic, diastolic, and MBP were automatically measured every 10 min with a monitor equipped with a cuff and oscillometric sensor (Critikon, Dinamap 845. Tampa.…”

Section: Personal M Ethods Of Studymentioning

confidence: 99%