Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG

Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, ∼15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment

A case-series study to explore the efficacy of foot orthoses in treating first metatarsophalangeal joint pain

Background: First metatarsophalangeal (MTP) joint pain is a common foot complaint which is often considered to be a consequence of altered mechanics. Foot orthoses are often prescribed to reduce 1 stMTP joint pain with the aim of altering dorsiflexion at propulsion. This study explores changes in 1 stMTP joint pain and kinematics following the use of foot orthoses.Methods: The effect of modified, pre-fabricated foot orthoses (X-line ®) were evaluated in thirty-two patients with 1 stMTP joint pain of mechanical origin. The primary outcome was pain measured at baseline and 24 weeks using the pain subscale of the foot function index (FFI). In a small sub-group of patients (n = 9), the relationship between pain and kinematic variables was explored with and without their orthoses, using an electromagnetic motion tracking (EMT) system.Results: A significant reduction in pain was observed between baseline (median = 48 mm) and the 24 week endpoint (median = 14.50 mm, z = -4.88, p < 0.001). In the sub-group analysis, we found no relationship between pain reduction and 1 stMTP joint motion, and no significant differences were found between the 1 stMTP joint maximum dorsiflexion or ankle/subtalar complex maximum eversion, with and without the orthoses.Conclusions: This observational study demonstrated a significant decrease in 1 stMTP joint pain associated with the use of foot orthoses. Change in pain was not shown to be associated with 1 stMTP joint dorsiflexion nor with altered ankle/subtalar complex eversion. Further research into the effect of foot orthoses on foot function is indicated. © 2010 Welsh et al; licensee BioMed Central Ltd

Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death

James E Skinner1, Michael Meyer2, Brian A Nester3, Una Geary4, Pamela Taggart4, Antoinette Mangione4, George Ramalanjaona5, Carol Terregino6, William C Dalsey41Vicor Technologies, Inc., Boca Raton, FL, USA; 2Max Planck Institute for Experimental Physiology, Goettingen, Germany; 3Lehigh Valley Hospital, Allentown, PA, USA; 4Albert Einstein Medical Center, Philadelphia, PA, USA; 5North Shore University Hospital, Plainview, NY, USA; 6Cooper Medical Center, Camden, NJ, USAObjective: Comparative algorithmic evaluation of heartbeat series in low-to-high risk cardiac patients for the prospective prediction of risk of arrhythmic death (AD).Background: Heartbeat variation reflects cardiac autonomic function and risk of AD. Indices based on linear stochastic models are independent risk factors for AD in post-myocardial infarction (post-MI) cohorts. Indices based on nonlinear deterministic models have superior predictability in retrospective data.Methods: Patients were enrolled (N = 397) in three emergency departments upon presenting with chest pain and were determined to be at low-to-high risk of acute MI (>7%). Brief ECGs were recorded (15 min) and R-R intervals assessed by three nonlinear algorithms (PD2i, DFA, and ApEn) and four conventional linear-stochastic measures (SDNN, MNN, 1/f-Slope, LF/HF). Out-of-hospital AD was determined by modified Hinkle–Thaler criteria.Results: All-cause mortality at one-year follow-up was 10.3%, with 7.7% adjudicated to be AD. The sensitivity and relative risk for predicting AD was highest at all time-points for the nonlinear PD2i algorithm (p ≤ 0.001). The sensitivity at 30 days was 100%, specificity 58%, and relative risk >100 (p ≤ 0.001); sensitivity at 360 days was 95%, specificity 58%, and relative risk >11.4 (p ≤ 0.001).Conclusions: Heartbeat analysis by the time-dependent nonlinear PD2i algorithm is comparatively the superior test.Keywords: autonomic nervous system, regulatory systems, electrophysiology, heart rate variability, sudden cardiac death, ventricular arrhythmias, ECG, HRV, PD2i, nonlinear, nonlinear, chao

Nonlinear dynamics of heart rate variability during experimental hemorrhage in ketamine-anesthetized rats.

Indexes of heart rate variability (HRV) based on linear stochastic models are independent risk factors for arrhythmic death (AD). An index based on a nonlinear deterministic model, a reduction in the point correlation dimension (PD2i), has been shown in both animal and human studies to have a higher sensitivity and specificity for predicting AD. Dimensional reduction subsequent to transient ischemia was examined previously in a simple model system, the intrinsic nervous system of the isolated rabbit heart. The present study presents a new model system in which the higher cerebral centers are blocked chemically (ketamine inhibition of N-methyl-D-aspartate receptors) and the system is perturbed over a longer 15-min interval by continuous hemorrhage. The hypothesis tested was that dimensional reduction would again be evoked, but in association with a more complex relationship between the system variables. The hypothesis was supported, and we interpret the greater response complexity to result from the larger autonomic superstructure attached to the heart. The complexities observed in the nonlinear heartbeat dynamics constitute a new genre of autonomic response, one clearly distinct from a hardwired reflex or a cerebrally determined defensive reaction

Comparison of linear-stochastic and nonlinear-deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death.

OBJECTIVE: Comparative algorithmic evaluation of heartbeat series in low-to-high risk cardiac patients for the prospective prediction of risk of arrhythmic death (AD). BACKGROUND: Heartbeat variation reflects cardiac autonomic function and risk of AD. Indices based on linear stochastic models are independent risk factors for AD in post-myocardial infarction (post-MI) cohorts. Indices based on nonlinear deterministic models have superior predictability in retrospective data. METHODS: Patients were enrolled (N = 397) in three emergency departments upon presenting with chest pain and were determined to be at low-to-high risk of acute MI (\u3e7%). Brief ECGs were recorded (15 min) and R-R intervals assessed by three nonlinear algorithms (PD2i, DFA, and ApEn) and four conventional linear-stochastic measures (SDNN, MNN, 1/f-Slope, LF/HF). Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. RESULTS: All-cause mortality at one-year follow-up was 10.3%, with 7.7% adjudicated to be AD. The sensitivity and relative risk for predicting AD was highest at all time-points for the nonlinear PD2i algorithm (p 100 (p 11.4 (p CONCLUSIONS: Heartbeat analysis by the time-dependent nonlinear PD2i algorithm is comparatively the superior test

Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG.

Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) \u3e7%. Brief digital ECGs (\u3e1000 heartbeats, approximately 15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk \u3e24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment