Renal Autoregulation Monitoring via Flow-Pressure Correlation
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Solution Overview
Problem
Existing methods fail to accurately monitor autoregulation in patients, particularly in organs like the kidney, which is crucial for preventing organ damage due to varying autoregulatory behaviors and patient-specific factors affecting blood flow variability.
Innovation Solution
A system and method using a blood flow monitor with an ultrasound transducer probe and a hemodynamic pressure sensor to continuously measure renal blood flow and arterial pressure, evaluating their mathematical relationship to determine an autoregulation profile and risk of acute kidney injury.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing monitoring methods are used, then the monitoring process is simple, but the measurement precision of autoregulation is insufficient
Solution Approach 1:
The monitoring system is divided into separate functional modules: a blood flow monitor for measuring renal blood flow, a blood pressure monitor for measuring arterial pressure, and an autoregulation analysis module that processes data from both sources. This segmentation allows each component to be optimized independently while working together to provide comprehensive autoregulation monitoring.
Solution Approach 2:
The patent combines blood flow monitoring and blood pressure monitoring into an integrated system that simultaneously measures both parameters and analyzes their relationship to determine autoregulation status. This merging of functions enables comprehensive monitoring that cannot be achieved with separate standalone devices.
2Reliability
If continuous monitoring of renal blood flow and arterial pressure is implemented, then the reliability of autoregulation detection is improved, but the loss of time for data processing increases
Solution Approach 1:
The system continuously monitors blood flow and blood pressure parameters in real-time, maintaining constant data collection without interruption. This continuous monitoring ensures that autoregulation changes are detected immediately as they occur, eliminating the delays associated with periodic or intermittent measurements.
Solution Approach 2:
The system processes the relationship between blood flow and blood pressure data to provide real-time feedback on autoregulation status. This feedback mechanism allows the system to continuously adjust and refine its monitoring based on the dynamic relationship between the measured parameters, improving both reliability and responsiveness.
3Adaptability or versatility
If patient-specific factors such as age and vascular hardening are considered, then the adaptability of autoregulation monitoring is improved, but the device complexity increases
Solution Approach 1:
The system dynamically adjusts its monitoring and analysis parameters based on patient-specific characteristics such as age, vascular health status, and baseline blood pressure. This dynamic adaptation allows the system to optimize its measurements and interpretations for each individual patient without requiring manual reconfiguration or complex custom programming.
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
Enables real-time monitoring of renal autoregulation, allowing for immediate intervention to maintain optimal blood flow and prevent acute kidney injury, bypassing the need for biomarker delays.
Implementation Method 1
a first sensor configured to continuously measure a signal of a renal blood flow
Implementation Method 2
a second sensor configured to continuously measure an arterial pressure signal
Data Source
AI summary
A system includes a first sensor to continuously measure a signal of a renal blood flow of a patient. A second sensor continuously measures an arterial pressure signal of the patient. A blood flow monitor is in communication with the first and second sensors. The blood flow monitor includes system memory that stores monitoring software code and a processor. The processor is configured to execute the monitoring software code to estimate a flow rate of the renal blood flow of the patient from the signal of the renal blood flow and monitor changes in the flow rate of the renal blood flow over time. The processor is also configured to execute the monitoring software code to monitor changes in the arterial pressure signal over time and evaluate a mathematical relationship between the changes in the arterial pressure signal and the changes in the flow rate of the renal blood flow.