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Zaccaria Ricci - One of the best experts on this subject based on the ideXlab platform.

  • CA.R.PE.DI.E.M. (Cardio–Renal Pediatric Dialysis Emergency Machine): evolution of continuous renal replacement therapies in infants. A personal journey
    Pediatric Nephrology, 2012
    Co-Authors: Claudio Ronco, Francesco Garzotto, Zaccaria Ricci
    Abstract:

    Pedriatric acute kidney injury (AKI) is a well-described clinical syndrome that is characterized by a reduction of both the urine output and glomerular filtration rate. AKI in critically ill children is typically associated with multiple organ dysfunction. A dramatic increase in the incidence of AKI in pediatric intensive care units has been observed in the last 10 years. Unfortunately, the absence of sufficiently effective preventive and therapeutic measures at the present time has limited significant improvements in AKI care. Morality in patients with severe AKI remains unacceptably high (>50 %), with renal replacement therapy (RRT) remaining the most effective form of support for these patients. Despite technological advances during the last 10 years which have resulted in the development of the so-called “third-generation Dialysis Machines” that are characterized by the highest level of safety and accuracy, a truly pedriatric RRT system has never been developed. Consequently, Dialysis/hemofiltration in critically ill children is currently performed by adapting adult systems to the much smaller pediatric patients. In particular, research in this field should focus on children weighing less than 10 kg for whom the delivery of RRT is a clinical and technological challenge. We describe here the evolution of pediatric RRT during the last 30 years and report in detail on the CARPEDIEM project, which has recently been established to finally provide neonates and infants with a reliable Dialysis Machine that is specifically designed for this age group.

  • ca r pe di e m cardio renal pediatric Dialysis emergency Machine evolution of continuous renal replacement therapies in infants a personal journey
    Pediatric Nephrology, 2012
    Co-Authors: Claudio Ronco, Francesco Garzotto, Zaccaria Ricci
    Abstract:

    Pedriatric acute kidney injury (AKI) is a well-described clinical syndrome that is characterized by a reduction of both the urine output and glomerular filtration rate. AKI in critically ill children is typically associated with multiple organ dysfunction. A dramatic increase in the incidence of AKI in pediatric intensive care units has been observed in the last 10 years. Unfortunately, the absence of sufficiently effective preventive and therapeutic measures at the present time has limited significant improvements in AKI care. Morality in patients with severe AKI remains unacceptably high (>50 %), with renal replacement therapy (RRT) remaining the most effective form of support for these patients. Despite technological advances during the last 10 years which have resulted in the development of the so-called “third-generation Dialysis Machines” that are characterized by the highest level of safety and accuracy, a truly pedriatric RRT system has never been developed. Consequently, Dialysis/hemofiltration in critically ill children is currently performed by adapting adult systems to the much smaller pediatric patients. In particular, research in this field should focus on children weighing less than 10 kg for whom the delivery of RRT is a clinical and technological challenge. We describe here the evolution of pediatric RRT during the last 30 years and report in detail on the CARPEDIEM project, which has recently been established to finally provide neonates and infants with a reliable Dialysis Machine that is specifically designed for this age group.

Claudio Ronco - One of the best experts on this subject based on the ideXlab platform.

  • CA.R.PE.DI.E.M. (Cardio–Renal Pediatric Dialysis Emergency Machine): evolution of continuous renal replacement therapies in infants. A personal journey
    Pediatric Nephrology, 2012
    Co-Authors: Claudio Ronco, Francesco Garzotto, Zaccaria Ricci
    Abstract:

    Pedriatric acute kidney injury (AKI) is a well-described clinical syndrome that is characterized by a reduction of both the urine output and glomerular filtration rate. AKI in critically ill children is typically associated with multiple organ dysfunction. A dramatic increase in the incidence of AKI in pediatric intensive care units has been observed in the last 10 years. Unfortunately, the absence of sufficiently effective preventive and therapeutic measures at the present time has limited significant improvements in AKI care. Morality in patients with severe AKI remains unacceptably high (>50 %), with renal replacement therapy (RRT) remaining the most effective form of support for these patients. Despite technological advances during the last 10 years which have resulted in the development of the so-called “third-generation Dialysis Machines” that are characterized by the highest level of safety and accuracy, a truly pedriatric RRT system has never been developed. Consequently, Dialysis/hemofiltration in critically ill children is currently performed by adapting adult systems to the much smaller pediatric patients. In particular, research in this field should focus on children weighing less than 10 kg for whom the delivery of RRT is a clinical and technological challenge. We describe here the evolution of pediatric RRT during the last 30 years and report in detail on the CARPEDIEM project, which has recently been established to finally provide neonates and infants with a reliable Dialysis Machine that is specifically designed for this age group.

  • ca r pe di e m cardio renal pediatric Dialysis emergency Machine evolution of continuous renal replacement therapies in infants a personal journey
    Pediatric Nephrology, 2012
    Co-Authors: Claudio Ronco, Francesco Garzotto, Zaccaria Ricci
    Abstract:

    Pedriatric acute kidney injury (AKI) is a well-described clinical syndrome that is characterized by a reduction of both the urine output and glomerular filtration rate. AKI in critically ill children is typically associated with multiple organ dysfunction. A dramatic increase in the incidence of AKI in pediatric intensive care units has been observed in the last 10 years. Unfortunately, the absence of sufficiently effective preventive and therapeutic measures at the present time has limited significant improvements in AKI care. Morality in patients with severe AKI remains unacceptably high (>50 %), with renal replacement therapy (RRT) remaining the most effective form of support for these patients. Despite technological advances during the last 10 years which have resulted in the development of the so-called “third-generation Dialysis Machines” that are characterized by the highest level of safety and accuracy, a truly pedriatric RRT system has never been developed. Consequently, Dialysis/hemofiltration in critically ill children is currently performed by adapting adult systems to the much smaller pediatric patients. In particular, research in this field should focus on children weighing less than 10 kg for whom the delivery of RRT is a clinical and technological challenge. We describe here the evolution of pediatric RRT during the last 30 years and report in detail on the CARPEDIEM project, which has recently been established to finally provide neonates and infants with a reliable Dialysis Machine that is specifically designed for this age group.

Francesco Garzotto - One of the best experts on this subject based on the ideXlab platform.

  • CA.R.PE.DI.E.M. (Cardio–Renal Pediatric Dialysis Emergency Machine): evolution of continuous renal replacement therapies in infants. A personal journey
    Pediatric Nephrology, 2012
    Co-Authors: Claudio Ronco, Francesco Garzotto, Zaccaria Ricci
    Abstract:

    Pedriatric acute kidney injury (AKI) is a well-described clinical syndrome that is characterized by a reduction of both the urine output and glomerular filtration rate. AKI in critically ill children is typically associated with multiple organ dysfunction. A dramatic increase in the incidence of AKI in pediatric intensive care units has been observed in the last 10 years. Unfortunately, the absence of sufficiently effective preventive and therapeutic measures at the present time has limited significant improvements in AKI care. Morality in patients with severe AKI remains unacceptably high (>50 %), with renal replacement therapy (RRT) remaining the most effective form of support for these patients. Despite technological advances during the last 10 years which have resulted in the development of the so-called “third-generation Dialysis Machines” that are characterized by the highest level of safety and accuracy, a truly pedriatric RRT system has never been developed. Consequently, Dialysis/hemofiltration in critically ill children is currently performed by adapting adult systems to the much smaller pediatric patients. In particular, research in this field should focus on children weighing less than 10 kg for whom the delivery of RRT is a clinical and technological challenge. We describe here the evolution of pediatric RRT during the last 30 years and report in detail on the CARPEDIEM project, which has recently been established to finally provide neonates and infants with a reliable Dialysis Machine that is specifically designed for this age group.

  • ca r pe di e m cardio renal pediatric Dialysis emergency Machine evolution of continuous renal replacement therapies in infants a personal journey
    Pediatric Nephrology, 2012
    Co-Authors: Claudio Ronco, Francesco Garzotto, Zaccaria Ricci
    Abstract:

    Pedriatric acute kidney injury (AKI) is a well-described clinical syndrome that is characterized by a reduction of both the urine output and glomerular filtration rate. AKI in critically ill children is typically associated with multiple organ dysfunction. A dramatic increase in the incidence of AKI in pediatric intensive care units has been observed in the last 10 years. Unfortunately, the absence of sufficiently effective preventive and therapeutic measures at the present time has limited significant improvements in AKI care. Morality in patients with severe AKI remains unacceptably high (>50 %), with renal replacement therapy (RRT) remaining the most effective form of support for these patients. Despite technological advances during the last 10 years which have resulted in the development of the so-called “third-generation Dialysis Machines” that are characterized by the highest level of safety and accuracy, a truly pedriatric RRT system has never been developed. Consequently, Dialysis/hemofiltration in critically ill children is currently performed by adapting adult systems to the much smaller pediatric patients. In particular, research in this field should focus on children weighing less than 10 kg for whom the delivery of RRT is a clinical and technological challenge. We describe here the evolution of pediatric RRT during the last 30 years and report in detail on the CARPEDIEM project, which has recently been established to finally provide neonates and infants with a reliable Dialysis Machine that is specifically designed for this age group.

Bo Olde - One of the best experts on this subject based on the ideXlab platform.

  • Detection of Needle Dislodgement Using Extracorporeal Pressure Signals : A Feasibility Study
    'Ovid Technologies (Wolters Kluwer Health)', 2020
    Co-Authors: Holmer Mattias, Bo Olde, Sandberg Frida, Sörnmo Leif
    Abstract:

    Venous needle dislodgement (VND) during Dialysis is a rarely occurring adverse event, which becomes life-threatening if not handled promptly. Because the standard venous pressure alarm, implemented in most Dialysis Machines, has low sensitivity, a novel approach using extracted cardiac information to detect needle dislodgement is proposed. Four features are extracted from the arterial and venous pressure signals of the Dialysis Machine, characterizing the mean venous pressure, the venous cardiac pulse pressure, the time delay, and the correlation between the two pressure signals. The features serve as input to a support vector Machine (SVM), which determines whether dislodgement has occurred. The SVM is first trained on a set of laboratory data, and then tested on another set of laboratory data as well as on a small data set from clinical hemoDialysis sessions. The results show that dislodgement can be detected after 12-17 s, corresponding to 24-143 ml blood loss. The standard venous pressure alarm used in clinical routine only detects 50% of the VNDs, whereas the novel method detects all VNDs and has a false alarm rate of 0.12 per hour, provided that the amplitude of the extracted cardiac pressure signal exceeds 1 mmHg. The results are promising; however, the method needs to be tested on a larger set of clinical data to better establish its performance

  • Monitoring respiration using the pressure sensors in a Dialysis Machine
    Physiological Measurement, 2019
    Co-Authors: Frida Sandberg, Mattias Holmer, Bo Olde
    Abstract:

    OBJECTIVE: Although respiratory problems are common among patients with end-stage renal disease, respiration is not continuously monitored during Dialysis. The purpose of the present study is to investigate the feasibility of monitoring respiration using the pressure sensors of the Dialysis Machine. APPROACH: Respiration induces variations in the blood pressure that propagates to the extracorporeal circuit of the Dialysis Machine. However, the magnitude of these variations are very small compared to pressure variations induced by the Dialysis Machine. We propose a new method, which involves adaptive template subtraction and peak conditioned spectral averaging, to estimate respiration rate from the pressure sensor signals. Using this method, an estimate of the respiration rate is obtained every 5th second provided that the signal quality is sufficient. The method is evaluated for continuous monitoring of respiration rate in nine Dialysis treatment sessions. MAIN RESULTS: The median absolute deviation between the estimated respiration rate from the pressure sensor signals and a reference capnography recording was 0.02 Hz (1.3 breaths per min). SIGNIFICANCE: Our results suggest that continuous monitoring of respiration using the pressure sensors of the Dialysis Machine is feasible. The main advantage with such monitoring is that no additional sensors are required which may cause patient discomfort. (Less)

  • Monitoring respiration using the pressure sensors in a Dialysis Machine
    'IOP Publishing', 2019
    Co-Authors: Sandberg Frida, Holmer Mattias, Bo Olde
    Abstract:

    OBJECTIVE: Although respiratory problems are common among patients with end-stage renal disease, respiration is not continuously monitored during Dialysis. The purpose of the present study is to investigate the feasibility of monitoring respiration using the pressure sensors of the Dialysis Machine. APPROACH: Respiration induces variations in the blood pressure that propagates to the extracorporeal circuit of the Dialysis Machine. However, the magnitude of these variations are very small compared to pressure variations induced by the Dialysis Machine. We propose a new method, which involves adaptive template subtraction and peak conditioned spectral averaging, to estimate respiration rate from the pressure sensor signals. Using this method, an estimate of the respiration rate is obtained every 5th second provided that the signal quality is sufficient. The method is evaluated for continuous monitoring of respiration rate in nine Dialysis treatment sessions. MAIN RESULTS: The median absolute deviation between the estimated respiration rate from the pressure sensor signals and a reference capnography recording was 0.02 Hz (1.3 breaths per min). SIGNIFICANCE: Our results suggest that continuous monitoring of respiration using the pressure sensors of the Dialysis Machine is feasible. The main advantage with such monitoring is that no additional sensors are required which may cause patient discomfort

  • heart rate estimation from dual pressure sensors of a Dialysis Machine
    Computing in Cardiology Conference, 2015
    Co-Authors: Mattias Holmer, Frida Sandberg, Bo Olde, Kristian Solem, Leif Sornmo
    Abstract:

    Dialysis patients often suffer from cardiovascular diseases, motivating the use of continuous monitoring of cardiac activity in clinical routine. Cardiac pressure pulses propagate through the vascular system and enter the extracorporeal blood circuit of a Dialysis Machine, where the pulses are captured by pressure sensors. The cardiac pulses are obscured by the much stronger pressure pulses originating from the peristaltic blood pump. We have previously shown that a cardiac signal can be extracted from the venous pressure signal. However, that method has been found to perform less well at very low cardiac pressure pulse amplitudes. In the present study, we propose a novel method which addresses this issue by using the signals from both the arterial and the venous pressure sensors. The method is compared to the previous method on clinical data using a photoplethysmogram as reference. The results suggests that heart rate can be estimated more accurately from pressure signals with lower cardiac signal amplitude when both arterial and venous pressure are used, compared to when only the venous signal is used.

  • CinC - Heart rate estimation from dual pressure sensors of a Dialysis Machine
    2015 Computing in Cardiology Conference (CinC), 2015
    Co-Authors: Mattias Holmer, Frida Sandberg, Bo Olde, Kristian Solem, Leif Sornmo
    Abstract:

    Dialysis patients often suffer from cardiovascular diseases, motivating the use of continuous monitoring of cardiac activity in clinical routine. Cardiac pressure pulses propagate through the vascular system and enter the extracorporeal blood circuit of a Dialysis Machine, where the pulses are captured by pressure sensors. The cardiac pulses are obscured by the much stronger pressure pulses originating from the peristaltic blood pump. We have previously shown that a cardiac signal can be extracted from the venous pressure signal. However, that method has been found to perform less well at very low cardiac pressure pulse amplitudes. In the present study, we propose a novel method which addresses this issue by using the signals from both the arterial and the venous pressure sensors. The method is compared to the previous method on clinical data using a photoplethysmogram as reference. The results suggests that heart rate can be estimated more accurately from pressure signals with lower cardiac signal amplitude when both arterial and venous pressure are used, compared to when only the venous signal is used.

Kristian Solem - One of the best experts on this subject based on the ideXlab platform.

  • heart rate estimation from dual pressure sensors of a Dialysis Machine
    Computing in Cardiology Conference, 2015
    Co-Authors: Mattias Holmer, Frida Sandberg, Bo Olde, Kristian Solem, Leif Sornmo
    Abstract:

    Dialysis patients often suffer from cardiovascular diseases, motivating the use of continuous monitoring of cardiac activity in clinical routine. Cardiac pressure pulses propagate through the vascular system and enter the extracorporeal blood circuit of a Dialysis Machine, where the pulses are captured by pressure sensors. The cardiac pulses are obscured by the much stronger pressure pulses originating from the peristaltic blood pump. We have previously shown that a cardiac signal can be extracted from the venous pressure signal. However, that method has been found to perform less well at very low cardiac pressure pulse amplitudes. In the present study, we propose a novel method which addresses this issue by using the signals from both the arterial and the venous pressure sensors. The method is compared to the previous method on clinical data using a photoplethysmogram as reference. The results suggests that heart rate can be estimated more accurately from pressure signals with lower cardiac signal amplitude when both arterial and venous pressure are used, compared to when only the venous signal is used.

  • CinC - Heart rate estimation from dual pressure sensors of a Dialysis Machine
    2015 Computing in Cardiology Conference (CinC), 2015
    Co-Authors: Mattias Holmer, Frida Sandberg, Bo Olde, Kristian Solem, Leif Sornmo
    Abstract:

    Dialysis patients often suffer from cardiovascular diseases, motivating the use of continuous monitoring of cardiac activity in clinical routine. Cardiac pressure pulses propagate through the vascular system and enter the extracorporeal blood circuit of a Dialysis Machine, where the pulses are captured by pressure sensors. The cardiac pulses are obscured by the much stronger pressure pulses originating from the peristaltic blood pump. We have previously shown that a cardiac signal can be extracted from the venous pressure signal. However, that method has been found to perform less well at very low cardiac pressure pulse amplitudes. In the present study, we propose a novel method which addresses this issue by using the signals from both the arterial and the venous pressure sensors. The method is compared to the previous method on clinical data using a photoplethysmogram as reference. The results suggests that heart rate can be estimated more accurately from pressure signals with lower cardiac signal amplitude when both arterial and venous pressure are used, compared to when only the venous signal is used.

  • estimation of respiratory information from the built in pressure sensors of a Dialysis Machine
    Computing in Cardiology Conference, 2014
    Co-Authors: Frida Sandberg, Mattias Holmer, Bo Olde, Kristian Solem
    Abstract:

    The purpose of the present study is to determine the feasibility of estimating respiratory information from the built-in pressure sensors of a Dialysis Machine. The study database consists of simultaneous recordings of pressure signals and capnographic signals from 6 patients during 7 hemoDialysis treatment sessions. Respiration rates were estimated using respiratory induced variations in the beat-to-beat interval series of the cardiac component of the pressure signal and respiratory induced baseline variations in the pressure signal, respectively. The estimated respiration rates were compared to a reference respiration rate determined from the capnograhpic signal. The root-mean-square error of the estimated respiration rate from the baseline variations of the pressure signal was 2.10 breaths/min; the corresponding error of the estimated respiration rate from the beat-to-beat interval series of the cardiac component was 4.95 breaths/min. The results suggest that it is possible to estimate respiratory information from the pressure sensors.

  • CinC - Estimation of respiratory information from the built-in pressure sensors of a Dialysis Machine
    2014
    Co-Authors: Frida Sandberg, Mattias Holmer, Bo Olde, Kristian Solem
    Abstract:

    The purpose of the present study is to determine the feasibility of estimating respiratory information from the built-in pressure sensors of a Dialysis Machine. The study database consists of simultaneous recordings of pressure signals and capnographic signals from 6 patients during 7 hemoDialysis treatment sessions. Respiration rates were estimated using respiratory induced variations in the beat-to-beat interval series of the cardiac component of the pressure signal and respiratory induced baseline variations in the pressure signal, respectively. The estimated respiration rates were compared to a reference respiration rate determined from the capnograhpic signal. The root-mean-square error of the estimated respiration rate from the baseline variations of the pressure signal was 2.10 breaths/min; the corresponding error of the estimated respiration rate from the beat-to-beat interval series of the cardiac component was 4.95 breaths/min. The results suggest that it is possible to estimate respiratory information from the pressure sensors.

  • Estimation of Respiratory Information from the Built-In Pressure Sensors of a Dialysis Machine
    2014
    Co-Authors: Frida Sandberg, Mattias Holmer, Bo Olde, Kristian Solem
    Abstract:

    The purpose of the present study is to determine the feasibility of estimating respiratory information from the built-in pressure sensors of a Dialysis Machine. The study database consists of simultaneous recordings of pressure signals and capnographic signals from 6 patients during 7 hemoDialysis treatment sessions. Respiration rates were estimated using respiratory induced variations in the beat- to-beat interval series of the cardiac component of the pressure signal and respiratory induced baseline varia- tions in the pressure signal, respectively. The estimated respiration rates were compared to a reference respira- tion rate determined from the capnograhpic signal. The root-mean-square error of the estimated respiration rate from the baseline variations of the pressure signal was 2.10 breaths/min; the corresponding error of the estimated res- piration rate from the beat-to-beat interval series of the cardiac component was 4.95 breaths/min. The results sug- gest that it is possible to estimate respiratory information from the pressure sensors. (Less)