Abstract 4370866: Evaluating the potential for SPAR analysis of ECGs with time matched disease progression to create a remote disease monitoring tool for patients with ATTR-Cardiac Myopathy aiming to reduce patient burden by avoiding frequent complex

Background: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a life-threatening condition, disease progression is currently measured using a combination of clinical, laboratory, MRI Imaging and ECG investigations multiple times a year, causing a significant disease burden to the patients. Simplifying investigations offers the potential to reducing disease burden, improve access and reduce health inequalities. Our novel mathematical method, Symmetric Projection Attractor Reconstruction (SPAR) analyses the complete morphology and variability of waveforms, This method has been shown to non-invasively assess vascular aging using PPG signals. SPAR amplifies small morphology changes on ECG which may be missed if focus resides on single points such as PQRST intervals or amplitudes, producing SPAR attractor images which can be readily interpreted by clinicians. Hypothesis: We hypothesised that SPAR analysis of ECG can sensitively detect aberrant changes on ECGs overtime to provide a new method to differentiate patients between stable and progression of their heart failure and to distinguish a threshold for significant progression. Methods: Longitudinal ECG and medical histories were collected and anonymised for ATTR-CM patients. ECG Waveform analysis was performed using a bespoke MATLAB software tool to transform ECG time-series into corresponding attractors. Results: Initial evaluation of a pilot analysis of a sub-set of the available data revealed attractors were able to see a stable attractor for patients who remained stable over 40 months. In contrast, patients who deteriorated, showed large attractor feature changes (fig1). Quantifying delta changes from the last ECG produces a cumulative graph indication a threshold for clinically concerning changes is possible(fig2). Conclusion: This pilot study illustrates that SPAR attractors highlight changes on the ECG that were consistent with deterioration in the patient’s clinical condition. Additional analysis for delta changes between attractor time points showed a disease trajectory. Further evaluation of the whole dataset to create a simplified diagnostic where patients could provide an ECG at home allowing more frequent clinical monitoring remotely negating the need for patients to undergo complex imagining and laboratory testing. Offering remote monitoring of patients to only bring deteriorating patients to clinic, reducing unecessary investigations and travel to health centres.

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Publication Details

Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4370866
Primary Topic
ECG Monitoring and Analysis
Type
article
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Abstract 4370866: Evaluating the potential for SPAR analysis of ECGs with time matched disease progression to create a remote disease monitoring tool for patients with ATTR-Cardiac Myopathy aiming to reduce patient burden by avoiding frequent complex

Manasi Nandi, James A. Rickard, Miquel Serna Pascual, Ulrike Lorch et al.
Circulation
ECG Monitoring and Analysis
article

Abstract 4370866: Evaluating the potential for SPAR analysis of ECGs with time matched disease progression to create a remote disease monitoring tool for patients with ATTR-Cardiac Myopathy aiming to reduce patient burden by avoiding frequent complex

Manasi Nandi, James A. Rickard, Miquel Serna Pascual, Ulrike Lorch, Jörg Täubel, Aga Krakowiak
article en

Abstract

Background: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a life-threatening condition, disease progression is currently measured using a combination of clinical, laboratory, MRI Imaging and ECG investigations multiple times a year, causing a significant disease burden to the patients. Simplifying investigations offers the potential to reducing disease burden, improve access and reduce health inequalities. Our novel mathematical method, Symmetric Projection Attractor Reconstruction (SPAR) analyses the complete morphology and variability of waveforms, This method has been shown to non-invasively assess vascular aging using PPG signals. SPAR amplifies small morphology changes on ECG which may be missed if focus resides on single points such as PQRST intervals or amplitudes, producing SPAR attractor images which can be readily interpreted by clinicians. Hypothesis: We hypothesised that SPAR analysis of ECG can sensitively detect aberrant changes on ECGs overtime to provide a new method to differentiate patients between stable and progression of their heart failure and to distinguish a threshold for significant progression. Methods: Longitudinal ECG and medical histories were collected and anonymised for ATTR-CM patients. ECG Waveform analysis was performed using a bespoke MATLAB software tool to transform ECG time-series into corresponding attractors. Results: Initial evaluation of a pilot analysis of a sub-set of the available data revealed attractors were able to see a stable attractor for patients who remained stable over 40 months. In contrast, patients who deteriorated, showed large attractor feature changes (fig1). Quantifying delta changes from the last ECG produces a cumulative graph indication a threshold for clinically concerning changes is possible(fig2). Conclusion: This pilot study illustrates that SPAR attractors highlight changes on the ECG that were consistent with deterioration in the patient’s clinical condition. Additional analysis for delta changes between attractor time points showed a disease trajectory. Further evaluation of the whole dataset to create a simplified diagnostic where patients could provide an ECG at home allowing more frequent clinical monitoring remotely negating the need for patients to undergo complex imagining and laboratory testing. Offering remote monitoring of patients to only bring deteriorating patients to clinic, reducing unecessary investigations and travel to health centres.

CirculationVol. 152(Suppl_3)
King's College London (GB)
Openalex Percentile: Top 51%
ECG Monitoring and Analysis
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