Improving Heart Failure Readmission Costs and Outcomes With a Hospital-to-Home Readmission Intervention Program.

A retrospective cohort study was performed of the Hospital-to-Home (H2H) program, a rapid clinic follow-up program for patients with recent heart failure (HF) admissions at the University of Virginia Health System. There were 6761 hospitalizations among 4685 patients (age 67.5 ± 14.

Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study.

Background: Charted vital signs and laboratory results represent intermittent samples of a patient's dynamic physiologic state and have been used to calculate early warning scores to identify patients at risk of clinical deterioration. We hypothesized that the addition of cardiorespiratory dynamics measured from continuous electrocardiography (ECG) monitoring to intermittently sampled data improves the predictive validity of models trained to detect clinical deterioration prior to intensive care unit (ICU) transfer or unanticipated death.

Methods And Findings: We analyzed 63 patient-years of ECG data from 8,105 acute care patient admissions at a tertiary care academic medical center.

Acute Noncardiovascular Illness in the Cardiac Intensive Care Unit.

Background: Fifty years after the inception of the cardiac intensive care unit (CICU), noncardiovascular illnesses have become more prevalent and may contribute to morbidity and mortality.

Objectives: The authors performed multivariate statistical analyses to determine the association of acute noncardiovascular illnesses with outcomes, including length of stay (LOS), mortality, and hospital readmission.

Methods: We studied 1,042 admissions between October 12, 2013 and November 28, 2014 to the CICU at the University of Virginia Health System, a tertiary-care academic medical center.

Hemorrhage Prediction Models in Surgical Intensive Care: Bedside Monitoring Data Adds Information to Lab Values.

Hemorrhage is a frequent complication in surgery patients; its identification and management have received increasing attention as a target for quality improvement in patient care in the Intensive Care Unit (ICU). The purposes of this work were 1) to find an early detection model for hemorrhage by exploring the range of data mining methods that are currently available, and 2) to compare prediction models utilizing continuously measured physiological data from bedside monitors to those using commonly obtained laboratory tests. We studied 3766 patients admitted to the University of Virginia Health System Surgical Trauma Burn ICU.

New-Onset Atrial Fibrillation in the Critically Ill.

Objective: To determine the association of new-onset atrial fibrillation with outcomes, including ICU length of stay and survival.

Design: Retrospective cohort of ICU admissions. We found atrial fibrillation using automated detection (≥ 90 s in 30 min) and classed as new-onset if there was no prior diagnosis of atrial fibrillation.

External validation in an intermediate unit of a respiratory decompensation model trained in an intensive care unit.

Background: Preventing urgent intubation and upgrade in level of care in patients with subclinical deterioration could be of great utility in hospitalized patients. Early detection should result in decreased mortality, duration of stay, and/or resource use. The goal of this study was to externally validate a previously developed, vital sign-based, intensive care unit, respiratory instability model on a separate population, intermediate care patients.

Signatures of Subacute Potentially Catastrophic Illness in the ICU: Model Development and Validation.

Objectives: Patients in ICUs are susceptible to subacute potentially catastrophic illnesses such as respiratory failure, sepsis, and hemorrhage that present as severe derangements of vital signs. More subtle physiologic signatures may be present before clinical deterioration, when treatment might be more effective. We performed multivariate statistical analyses of bedside physiologic monitoring data to identify such early subclinical signatures of incipient life-threatening illness.

Incidence of Atrial Fibrillation following Alcohol Septal Ablation for Hypertrophic Cardiomyopathy.

Background: Patients with hypertrophic cardiomyopathy (HCM) are at a fourfold to sixfold higher risk of developing atrial fibrillation (AF) compared to the general population, though incidence rates among patients undergoing alcohol septal ablation (ASA) are not well characterized. The purpose of this study was to evaluate atrial fibrillation incidence following ASA.

Methods: We studied 132 consecutive HCM patients without comorbid AF that underwent 154 ASA procedures.

Heart rate dynamics preceding hemorrhage in the intensive care unit.

Occult hemorrhage in surgical/trauma intensive care unit (STICU) patients is common and may lead to circulatory collapse. Continuous electrocardiography (ECG) monitoring may allow for early identification and treatment, and could improve outcomes. We studied 4,259 consecutive admissions to the STICU at the University of Virginia Health System.

Classification of cardiac rhythm using heart rate dynamical measures: validation in MIT-BIH databases.

Background: Identification of atrial fibrillation (AF) is a clinical imperative. Heartbeat interval time series are increasingly available from personal monitors, allowing new opportunity for AF diagnosis.

Goal: Previously, we devised numerical algorithms for identification of normal sinus rhythm (NSR), AF, and SR with frequent ectopy using dynamical measures of heart rate.

Heart rate dynamics distinguish among atrial fibrillation, normal sinus rhythm and sinus rhythm with frequent ectopy.

Atrial fibrillation (AF) is usually detected by inspection of the electrocardiogram waveform, a task made difficult when the signal is distorted by noise. The RR interval time series is more frequently available and accurate, yet linear and nonlinear time series analyses that detect highly varying and irregular AF are vulnerable to the common finding of frequent ectopy. We hypothesized that different nonlinear measures might capture characteristic features of AF, normal sinus rhythm (NSR), and sinus rhythm (SR) with frequent ectopy in ways that linear measures might not.

Local dynamics of heart rate: detection and prognostic implications.

The original observation that reduced heart rate variability (HRV) confers poor prognosis after myocardial infarction has been followed by many studies of heart rate dynamics. We tested the hypothesis that an entropy-based local dynamics measure gave prognostic information in ambulatory patients undergoing 24-h electrocardiography. In this context, entropy is the probability that short templates will find matches in the time series.

Left ventricular systolic function following alcohol septal ablation for symptomatic hypertrophic cardiomyopathy.

Because alcohol septal ablation (ASA) for the treatment of symptomatic hypertrophic cardiomyopathy (HC) with left ventricular (LV) outflow tract (LVOT) obstruction results in a myocardial infarct of up to 10% of ventricular mass, LV systolic function could decline over time. We evaluated LV function during longitudinal follow-up in a cohort of patients who underwent ASA. We studied 145 consecutive patients with HC that underwent 167 ASA procedures from 2002 to 2011.

Dynamic analysis of cardiac rhythms for discriminating atrial fibrillation from lethal ventricular arrhythmias.

Background: Implantable cardioverter-defibrillators (ICDs), the first line of therapy for preventing sudden cardiac death in high-risk patients, deliver appropriate shocks for termination of ventricular tachycardia (VT)/ventricular fibrillation. A common shortcoming of ICDs is imperfect rhythm discrimination, resulting in the delivery of inappropriate shocks for atrial fibrillation (AF). An underexplored area for rhythm discrimination is the difference in dynamic properties between AF and VT/ventricular fibrillation.

Estimating divergence dates and evaluating dating methods using phylogenomic and mitochondrial data in squamate reptiles.

Recently, phylogenetics has expanded to routinely include estimation of clade ages in addition to their relationships. Various dating methods have been used, but their relative performance remains understudied. Here, we generate and assemble an extensive phylogenomic data set for squamate reptiles (lizards and snakes) and evaluate two widely used dating methods, penalized likelihood in r8s (r8s-PL) and Bayesian estimation with uncorrelated relaxed rates among lineages (BEAST).