Adaptive Peritoneal Dialysis Fluid Removal Control
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Solution Overview
Problem
Current peritoneal dialysis systems lack the ability to adjust dialysis parameters between sessions based on changing patient needs, relying on pre-set settings and failing to optimize treatment effectiveness and patient comfort.
Innovation Solution
A computer-implemented method and system that receive patient parameters from previous sessions to determine and adjust a new peritoneal dialysis prescription, including osmotic agent concentration, dwell time, and number of cycles, using sensors and a processor to generate and deliver optimized dialysate for subsequent sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-set dialysis parameters are used, then device operation is simple, but treatment effectiveness cannot be optimized for changing patient needs
Solution Approach 1:
The system receives patient parameters from previous dialysis sessions and uses this feedback to automatically adjust dialysis parameters for subsequent sessions. The processor analyzes intersession data and modifies the dialysis prescription to optimize treatment effectiveness based on actual patient response.
Solution Approach 2:
The dialysis system automatically adjusts its own operating parameters based on received patient data without requiring manual reprogramming by the user. The system self-optimizes by generating adjusted dialysis parameters internally and using them for subsequent treatment sessions.
2Adaptability or versatility
If dialysis parameters are adjusted between sessions, then treatment effectiveness is improved, but device complexity increases
Solution Approach 1:
The dialysis system transitions from static pre-set parameters to dynamic adaptive parameters that change based on patient response. The system continuously adapts dialysis parameters between sessions by receiving new patient data and generating updated prescriptions tailored to individual patient needs.
Solution Approach 2:
The system modifies dialysis parameters such as osmotic agent concentration, dwell time, and number of cycles based on analyzed patient parameters from previous sessions. These parameter changes enable customization of treatment to optimize effectiveness for each patient's specific condition.
3Productivity
If manual parameter entry is required, then system operation is simple, but time consumption increases and optimization is limited
Solution Approach 1:
The system performs preliminary analysis of patient parameters from previous sessions before the current treatment begins. By pre-processing intersession data and generating adjusted parameters in advance, the system eliminates time-consuming manual setup during treatment sessions.
Solution Approach 2:
The system replaces manual parameter entry and adjustment with automated electronic processing. The processor automatically receives, analyzes, and generates optimized dialysis parameters based on patient data, substituting manual mechanical operations with automated computational processes.
4Reliability
If fixed dialysis prescriptions are used, then treatment consistency is maintained, but patient comfort and effectiveness vary
Solution Approach 1:
The system applies customized dialysis parameters tailored to individual patient needs while maintaining overall treatment consistency. By adjusting parameters such as osmotic agent concentration and dwell time based on specific patient parameters, the system optimizes treatment for each patient's condition.
Solution Approach 2:
The dialysis prescription transitions from a fixed static plan to a dynamic adaptive plan that evolves based on patient response. The system maintains treatment consistency through structured sessions while adapting parameters between sessions to improve patient comfort and effectiveness.
Data Source
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AI summary
The invention relates to systems and methods for optimizing a peritoneal dialysate therapy session based on one or more patient or system parameters obtained from a previous peritoneal dialysis therapy session. The systems and methods include various sensors, flow paths, and processors to adjust a peritoneal dialysis prescription for a subsequent therapy session based on data received during or after one or more previous therapy session. For example, a first peritoneal dialysis therapy session can provide data on patient or system parameters that can adjust the dialysis parameters used to deliver a subsequent peritoneal dialysis therapy session. The method can be computer implemented. The system can also include a peritoneal dialysate generation flow path.