Functional Assessment of Heart Failure Patients

Heart failure (HF) is the condition characterized by the inability of the heart to pump sufficient blood to meet the demands of the body. It has been well established that both the prevalence and incidence of HF is increasing.1 There are 2 primary types of HF, categorized by ejection fraction: Reduced ejection fraction and preserved ejection fraction.2 Additionally, HF is commonly classified into stages from mild to severe using a symptom-based scale related to functional limitations. One of the hallmark features of HF is exercise intolerance, which is accompanied by symptoms of fatigue and shortness of breath.3 As the disease progresses, patients experience a downward spiral as these symptoms typically result in reduced physical activity, which leads to progressively worsening exercise intolerance. Typically, patients with HF are faced with what can be termed a functional disability. Often, their reduced functional abilities restrict or may even prevent them from performing occupational tasks, which may result in loss of work. Additionally, it is well known that patients with HF experience impairment in the ability to carry out activities of daily living and suffer from reduced quality of life. The objective of this paper was to provide an overview of assessments of functional ability of patients with HF. Two categories of assessment are reviewed: Cardiovascular function and muscular function. The review includes procedural guidance on how to administer the assessments and information related to the advantages and disadvantages of each method. Because both HF types (reduced ejection fraction and preserved ejection fraction) are characterized by exercise intolerance, the procedures can be used effectively with either type of HF

Quantum adiabatic optimization and combinatorial landscapes

In this paper we analyze the performance of the Quantum Adiabatic Evolution algorithm on a variant of Satisfiability problem for an ensemble of random graphs parametrized by the ratio of clauses to variables, $\gamma=M/N$. We introduce a set of macroscopic parameters (landscapes) and put forward an ansatz of universality for random bit flips. We then formulate the problem of finding the smallest eigenvalue and the excitation gap as a statistical mechanics problem. We use the so-called annealing approximation with a refinement that a finite set of macroscopic variables (versus only energy) is used, and are able to show the existence of a dynamic threshold $\gamma=\gamma_d$ starting with some value of K -- the number of variables in each clause. Beyond dynamic threshold, the algorithm should take exponentially long time to find a solution. We compare the results for extended and simplified sets of landscapes and provide numerical evidence in support of our universality ansatz. We have been able to map the ensemble of random graphs onto another ensemble with fluctuations significantly reduced. This enabled us to obtain tight upper bounds on satisfiability transition and to recompute the dynamical transition using the extended set of landscapes.Comment: 41 pages, 10 figures; added a paragraph on paper's organization to the introduction, fixed reference

The Unholy Trinity of Financial Contagion

Over the last 20 years, some financial events, such as devaluations or defaults, have triggered an immediate adverse chain reaction in other countries -- which we call fast and furious contagion. Yet, on other occasions, similar events have failed to trigger any immediate international reaction. We argue that fast and furious contagion episodes are characterized by "the unholy trinity": (i) they follow a large surge in capital flows; (ii) they come as a surprise; and (iii) they involve a leveraged common creditor. In contrast, when similar events have elicited little international reaction, they were widely anticipated and took place at a time when capital flows had already subsided.

Peak Ventilation Reference Standards from Exercise Testing: From the FRIEND Registry

Peak Ventilation Reference Standards from Exercise Testing: From the FRIEND Registry. Med. Sci. Sports Exerc., Vol. 50, No. 12, pp. 2603–2608, 2018. Purpose: Cardiopulmonary exercise testing (CPX) provides valuable clinical information, including peak ventilation (V˙ Epeak), which has been shown to have diagnostic and prognostic value in the assessment of patients with underlying pulmonary disease. This report provides reference standards for V˙ Epeak derived from CPX on treadmills in apparently healthy individuals. Methods: Nine laboratories in the United States experienced in CPX administration with established quality control procedures contributed to the Fitness Registry and the Importance of Exercise National Database from 2014 to 2017. Data from 5232 maximal exercise tests from men and women without cardiovascular or pulmonary disease were used to create percentiles ofV˙ Epeak for both men and women by decade between 20 and 79 yr. Additionally, prediction equations were developed for V˙ Epeak using descriptive information. Results: V˙ Epeak was found to be significantly different between men and women and across age groups (P G 0.05). The rate of decline in V˙ Epeak was 8.0% per decade for both men and women. A stepwise regression model of 70% of the sample revealed that sex, age, and height were significant predictors ofV˙ Epeak. The equation was cross-validated with data from the remaining 30% of the sample with a final equation developed from the full sample (r = 0.73). Additionally, a linear regression model revealed forced expiratory volume in 1 s significantly predicted V˙ Epeak (r = 0.73). Conclusions: Reference standards were developed for V˙ Epeak for the United States population. Cardiopulmonary exercise testing laboratories will be able to provide interpretation of V˙ Epeak from these age and sex-specific percentile reference values or alternatively can use these nonexercise prediction equations incorporating sex, age, and height or with a single predictor of forced expiratory volume in 1 s

Variability of Objectively Measured Sedentary Behavior

The primary purpose of this study was to evaluate variability of sedentary behavior (SB) throughout a 7-d measurement period and to determine if G7 d of SB measurement would be comparable with the typical 7-d measurement period. Methods: Retrospective data from Ball State University_s Clinical Exercise Physiology Laboratory on 293 participants (99 men, 55 T 14 yr, body mass index = 29 T 5 kgImj2; 194 women, 51 T 12 yr, body mass index = 27 T 7 kgImj2) with seven consecutive days of data collected with ActiGraph accelerometers were analyzed (ActiGraph, Fort Walton Beach, FL). Time spent in SB (either G100 counts per minute or G150 counts per minute) and breaks in SB were compared between days and by sex using a two-way repeated-measures ANOVA. Stepwise regression was performed to determine if G7 d of SB measurement were comparable with the 7-d method, using an adjusted R2 of Q0.9 as a criterion for equivalence. Results: There were no differences in daily time spent in SB between the 7 d for all participants. However, there was a significant interaction between sex and days, with women spending less time in SB on both Saturdays and Sundays than men when using the 100 counts per minute cut-point. Stepwise regression showed using any 4 d would be comparable with a 7-d measurement (R2 9 0.90). Conclusions: When assessed over a 7-d measurement period, SB appears to be very stable from day to day, although there may be some small differences in time spent in SB and breaks in SB between men and women, particularly on weekend days. The stepwise regression analysis suggests that a measurement period as short as 4 d could provide comparable data (91% of variance) with a 1-wk assessment. Shorter assessment periods would reduce both researcher and subject burden in data collection