A system for determining the magnitude of the ultrafiltration volume expected in a peritoneal dialysis treatment
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Solution Overview
Problem
Current methods for predicting ultrafiltration volume in peritoneal dialysis are cumbersome, costly, time-consuming, and prone to error, failing to accurately account for individual patient membrane changes due to anatomical and hydration status variations, leading to suboptimal fluid balance and potential membrane damage.
Innovation Solution
A system using a peritoneal treatment machine with sensors and a controller to measure intraperitoneal pressure, fitting a simplified ultrafiltration model with a patient-specific aggregated reflection coefficient to predict ultrafiltration volume, allowing continuous adaptation to individual membrane characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the peritoneal equilibration test (PET) is used to obtain membrane parameters, then membrane transport characteristics can be measured, but the process is cumbersome, costly, time-consuming and highly prone to error
Solution Approach 1:
The patent extracts the essential information needed for membrane parameter determination from routine peritoneal dialysis treatment data, specifically using intraperitoneal pressure measurements during the fill phase. This eliminates the need for separate, complex PET testing while maintaining measurement accuracy for membrane transport characteristics.
Solution Approach 2:
The patent creates a simplified mathematical model that copies the functional output of the complex PET test by using pressure-volume relationships during routine PD treatment. This model provides equivalent membrane parameter information without requiring the complex testing procedure, thereby reducing device complexity while maintaining measurement precision.
2Reliability
If membrane parameters are tested frequently to track changes, then timely treatment intervention is enabled, but valuable clinician time is consumed and patient burden increases
Solution Approach 1:
The system enables self-service by automatically determining membrane parameters from routine treatment data without requiring manual intervention. The controller processes intraperitoneal pressure measurements and calculates membrane characteristics automatically, eliminating the need for clinician involvement in parameter determination and reducing both time loss and patient burden while maintaining reliable tracking of membrane changes.
Solution Approach 2:
The patent implements continuous monitoring of membrane parameters by incorporating them into routine peritoneal dialysis treatment cycles. The system continuously measures intraperitoneal pressure and updates membrane parameter estimates without requiring separate testing sessions, thereby enabling timely treatment intervention while eliminating interruptions to patient care and reducing overall time consumption.
3Reliability
If the glucose content of PD fluid is increased to compensate for ultrafiltration failure, then fluid balance is improved, but glucose exposure and membrane damage increase
Solution Approach 1:
The system performs preliminary determination of membrane parameters and prediction of ultrafiltration volume before initiating treatment. By calculating the expected ultrafiltration based on measured intraperitoneal pressure and patient-specific membrane characteristics, the system enables proactive adjustment of PD fluid composition and treatment parameters to achieve target fluid balance without requiring excessive glucose exposure, thereby preventing membrane damage while maintaining fluid control.
Solution Approach 2:
The patent dynamically adjusts treatment parameters including PD fluid composition and treatment duration based on real-time membrane parameter measurements and ultrafiltration predictions. By continuously monitoring intraperitoneal pressure and updating membrane characteristics, the system optimizes glucose content and other parameters to achieve fluid balance with minimal glucose exposure, thereby reducing harmful effects on the membrane while maintaining reliable fluid control.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate and timely prediction of ultrafiltration volume, enabling optimized peritoneal dialysis prescriptions and reducing glucose exposure, thus mitigating membrane damage and improving patient care.
Implementation Method 1
The peritoneal membrane is semipermeable and allows the passage of water and small solutes from the peritoneal cavity to the bloodstream
Implementation Method 2
Solute transport across the peritoneal membrane occurs through diffusion processes
Implementation Method 3
a sensor for repeatedly measuring a sensed value during the treatment performed on the patient
Implementation Method 4
a controller programmed to predict the magnitude of the ultrafiltration volume expected during a treatment performed according to a prescription based on a model of ultrafiltration
Data Source
AI summary
The present disclosure relates to a system for predicting the magnitude of ultrafiltration volume expected in a peritoneal dialysis treatment for an individual patient, the system comprising:—a peritoneal treatment machine configured to perform cycles of a peritoneal treatment performed on the patient according to a prescription by controlling at least one actuator and/or valve of the peritoneal treatment machine, the cycles comprising a fill phase, a dwell phase and a drain phase,—a sensor for repeatedly measuring a sensed value during the treatment performed on the patient,—a controller programmed to predict the magnitude of ultrafiltration volume expected during a treatment performed according to a prescription based on a model of ultrafiltration, and to fit parameter values of the model to the individual patient based on the values measured by the sensor, wherein the model of ultrafiltration uses a patient-specific aggregated reflection coefficient as a parameter representing the overall average effect of different pores of the peritoneum and of different solutes present in the peritoneal cavity and the blood plasma on the differential crystalloid osmotic pressure between the peritoneal cavity and blood plasma.