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Title: Continuous monitoring during haemodialysis
Author: Meredith, David James
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
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Intradialytic Hypotension (IDH) is the commonest complication of maintenance haemodialysis and is associated with increased morbidity and mortality. However, there is no standardised definition of IDH, making comparisons between studies difficult. This observational study with a total of 80 patients and over 600 dialysis sessions showed a poor correlation between symptoms and hypotension. Importantly, patients experienced low blood pressure without symptoms, so continuous intradialytic blood pressure monitoring is required to identify this asymptomatic group. In light of these findings, a revised definition of IDH is suggested. This study also aimed to identify predictors of IDH that could be detected in sufficient time to allow a mitigating intervention. A novel non-invasive alternative for continuous blood pressure monitoring is introduced which uses intra-fistula pressure data from the sensors sited in the extracorporeal circuit of the dialysis machine. Results show that in the majority of patients, changes in intra-fistula pressure correlate with blood pressure measurements obtained by a standard oscillometric device. To investigate whether IDH can be predicted, a photoplethysmogram (PPG) waveform was obtained from a pulse oximeter attached to the finger or ear. Continuous PPG monitoring of patients with IDH during dialysis demonstrated that some IDH episodes were predictable using the variation in the PPG baseline with respiration as a surrogate for low blood volume. Additionally, the area under the curve of the PPG waveform can be used as a surrogate for cardiac output and peripheral vascular tone, resulting in a reasonable predictor for potentially critical changes in blood pressure during dialysis. Individually, the novel metrics described here are limited in their identification of IDH in all patients affected, but in combination they may be used to develop a multi-parameter predictive model. The relative merits of personalised versus population-based models are explored and a conclusion is drawn that personalised multi-parameter data fusion modelling for haemodialysis patients would be an important area for future work.
Supervisor: Pugh, Christopher W.; Tarassenko, Lionel Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Physiology ; Nephrology ; Cardiovascular disease ; Medical sciences ; Biomedical engineering ; haemodialysis ; intradialytic hypotension ; blood pressure