Publications by authors named "David J Cornforth"

Purpose: Cardiac autonomic dysfunction in idiopathic Parkinson's disease (PD) manifests as reduced heart rate variability (HRV). In the present study, we explored the deceleration capacity of heart rate (DC) in patients with idiopathic PD, an advanced HRV marker that has proven clinical utility.

Methods: Standard and advanced HRV measures derived from 7-min electrocardiograms in 20 idiopathic PD patients and 27 healthy controls were analyzed.

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Purpose: Cardiac autonomic dysfunction manifests as reduced heart rate variability (HRV) in idiopathic Parkinson's disease (PD), but no significant reduction has been found in PD patients who carry the LRRK2 mutation. Novel HRV features have not been investigated in these individuals. We aimed to assess cardiac autonomic modulation through standard and novel approaches to HRV analysis in individuals who carry the LRRK2 G2019S mutation.

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The time series of interbeat intervals of the heart reveals much information about disease and disease progression. An area of intense research has been associated with cardiac autonomic neuropathy (CAN). In this work we have investigated the value of additional information derived from the magnitude, sign and acceleration of the intervals.

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Aims: Cardiac autonomic reflex tests (CARTs) are time consuming and require patient cooperation for detecting cardiac autonomic neuropathy (CAN). Heart rate variability (HRV) analysis requires less patient cooperation and is quicker to complete. However the reliability of HRV results as a clinical tool, with respect to length of recording and accuracy of diagnosis is inconclusive.

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Purpose: Individuals with eating disorder (ED) are at an increased risk of cardiac arrhythmias due to cardiac dysautonomia, which may be exacerbated if depression is also present. The aim of the study was to use heart rate analysis as a marker for cardiac dysautonomia in patients with eating disorders and depression as a comorbidity.

Methods: Clinical data, including presence of depression, was obtained from all participants.

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Socioeconomic status (SES) is a risk factor for cardiovascular disease (CVD) and either low or high heart rate variability (HRV) at rest has been shown to predict cardiovascular morbidity and mortality. The study investigated the extent HRV features can predict SES. Four hundred and twenty eight people were randomly selected from the commercial districts (high SES) and slum areas (low SES) within Dhaka city.

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Background: Physiological interactions are abundant within, and between, body systems. These interactions may evolve into discrete states during pathophysiological processes resulting from common mechanisms. An association between arterial stenosis, identified by low ankle-brachial pressure index (ABPI) and cardiovascular disease (CVD) as been reported.

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Visualization models can assist in understanding the complex pattern of disease, where the signs may be buried in complex data. In this work we propose a new method for visualization of data derived from Heart Rate Variability (HRV) analysis, to indicate whether a person has developed, or is developing, signs of definite Cardiac Autonomic Neuropathy (CAN). Here, the visualizations are compared with actual data recorded from people attending a diabetes clinic with and without definite CAN.

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Heart rate variability (HRV) is recognized to carry early diagnostic value regarding cardiac autonomic neuropathy (CAN). A number of different HRV analysis algorithms have been proposed for the assessment of CAN, each of them providing partly differing information about HRV time series. Instead of confining to a limited set of HRV features, a multi-dimensional approach incorporating a multitude of HRV parameters could be an optimal way of assessing the changes in HRV related to CAN.

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Cardiac autonomic neuropathy (CAN) is a disease that involves nerve damage leading to an abnormal control of heart rate. An open question is to what extent this condition is detectable from heart rate variability (HRV), which provides information only on successive intervals between heart beats, yet is non-invasive and easy to obtain from a three-lead ECG recording. A variety of measures may be extracted from HRV, including time domain, frequency domain, and more complex non-linear measures.

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Heart rate variability (HRV) is reduced in diabetes mellitus (DM) patients, suggesting dysfunction of cardiac autonomic regulation and an increased risk for cardiac events. The aim of this paper was to examine the associations of blood glucose level (BGL), glycated hemoglobin (HbA1c), and duration of diabetes with cardiac autonomic regulation assessed by HRV analysis. Resting electrocardiogram (ECG), recorded over 20 min in supine position, and clinical measurements of 189 healthy controls and 93 type 2 DM (T2DM) patients were analyzed.

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Cardiac Autonomic Neuropathy (CAN) is a disease that involves nerve damage leading to abnormal control of heart rate. CAN affects the correct operation of the heart and in turn leads to associated arrhythmias and heart attack. An open question is to what extent this condition is detectable by the measurement of Heart Rate Variability (HRV).

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Heart rate variability (HRV) is reduced in diabetes mellitus (DM) patients, suggesting dysfunction of cardiac autonomic regulation which has been associated with increased risk for pathological cardiac events. In this paper, we examined changes in HRV complexity in association to blood glucose level (BGL) and duration of diabetes. Resting HRV and BGL measurements of 32 healthy controls and 54 type 2 DM (T2DM) patients were analyzed.

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