Real-time expert-system identification of blood pressure measurement accuracy during renal dialysis treatment

Stewart, Paul ORCID logo ORCID: , Stewart, Jill ORCID logo ORCID: , Noble, Rebecca, Viramontes-Horner, Daniela, Taal, Maarten and Selby, Nicholas (2023) Real-time expert-system identification of blood pressure measurement accuracy during renal dialysis treatment. engrXiv (Engineering Archive) . (Submitted to Publisher)

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Objective: Current practice relies on intermittent occluding arm cuff measurements to monitor blood pressure during hemodialysis and to detect hypotension. However, systematic reviews report measurement accuracy challenges associated with brachial cuff measurements observed in the general population, and the factors contributing to inaccuracy are likely to be accentuated during dialysis treatment. There is currently no formal process to identify unreliable cuff BP measurements, and staff generally rely on ad hoc extra measurements and averaging readings. The objective of the activity described in this paper was to design a computational method to identify unreliable cuff measurements as they are taken and thus provide decision support to practitioners on dialysis units. Reliable intermittent systolic measurements are fundamentally important to both the calibration of continuous blood pressure measurements, and methodologies to predict the onset of hypotension.

Methods: Patient studies with concurrent measurements of real-time continuous dialysis line pressure and intermittent systolic brachial cuff pressure during typically 4-hour, dialysis treatment sessions, revealed that some cuff measurements lay outside the prediction bounds associated with the expected quasi-linear (time-varying) relationship between arterial line and brachial pressure measurements. An AI expert system was designed, which embodies the mathematical relationships predicted by a system model, and a further complex rule-set which is able to discriminate between reliable and unreliable cuff measurements in real time based on sparse intermittent incoming data. The developed system was deployed on an observational patient study during hemodialysis treatments, outputting recommendations and justifications for accepting/rejecting cuff measurements. The accepted measurements were fed into a continuous, non-invasive systolic pressure estimator as calibration, enabling the reliability of the decisions made in the arterial line / systolic pressure domain to be verified in the systolic pressure / time domain.

Results: Data collected from a prospective, observational patient study exhibited robust identification of unreliable arm cuff measurements, with the system operating as decision support. Continuous, non invasive, SBP predictions exhibited enhanced accuracy, in a typical example case, reducing mean error from 16.7mmHg to 6.8mmHg

Conclusion: A hybrid hardware/software system has been designed which utilises non-invasive continuous measurement of arterial dialysis line pressure to improve intermittent arm cuff measurements in order by identifying unreliable arm cuff measurements. The expert system computational core showed robust operation in accepting or excluding incoming arm cuff measurements. The devised system can support two requirements in future applications. Firstly, offering a repeatable and robust methodology to identify unreliable arm cuff measurements. Secondly to support the development of reliable SBP prediction algorithms to enable early intervention to predict hypotensive episodes and enable early intervention to prevent intradialytic hypotension.

Abbreviations: cardiovascular disease (CVD); end-stage kidney disease (EKD); intradialytic hypotension (IDH); blood pressure (BP), systolic blood pressure (SBP), diastolic blood pressure (DBP), Hemodialysis (HD), expert system (ES)

Item Type: Article
Journal / Publication Title: engrXiv (Engineering Archive)
Publisher: Open Engineering Inc.
Departments: Institute of Engineering, Computing and Advanced Manufacture
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 International License.
Depositing User: Anna Lupton
Date Deposited: 25 May 2023 10:34
Last Modified: 13 Jan 2024 15:01


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