Simulating inadequate dialysis and its correction using an individualized patient-derived nomogram.

Area of Science:

• Nephrology
• Biomedical Engineering
• Clinical Informatics

Background:

• Automated peritoneal dialysis (APD) relies on computerized kinetic modeling for optimal dialysis adequacy.
• Patient non-compliance with APD prescriptions frequently leads to failure in achieving target dialysis adequacy.
• Existing methods lack effective strategies to compensate for APD treatment shortfalls due to non-compliance.

Purpose of the Study:

• To develop and validate a nomogram for estimating APD prescription adjustments.
• To determine if the nomogram can compensate for simulated non-compliance and achieve target weekly urea clearance (Kt/Vurea).
• To assess the nomogram's utility in real-world APD patient scenarios with varying compliance levels.

Main Methods:

• Individualized nomograms were created using PD Adequest (ver. 2.0) predicted Kt/Vurea data for various APD prescriptions.
• The nomogram estimated daily Kt/Vurea in 14 patients across three 1-month phases (compliant, non-compliant, adjusted).
• Comparisons were made between nomogram-computed, Adequest-predicted, and measured Kt/Vurea values.

Main Results:

• In the compliant phase, Adequest-predicted Kt/Vurea strongly agreed with measured and nomogram-computed values.
• During simulated non-compliance, nomogram-computed values were significantly lower than Adequest-predicted values.
• In the adjustment phase, the nomogram successfully estimated prescription changes, reducing the discrepancy between computed and predicted Kt/Vurea, achieving target adequacy.

Conclusions:

• A nomogram-based approach can effectively adjust APD prescriptions to compensate for non-compliance and meet Kt/Vurea targets.
• This method offers a potential strategy for patients to manage inadvertent dialysis shortfalls.
• The nomogram shows promise as a tool for maintaining dialysis adequacy in the face of patient non-compliance.