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

Mechanical Application in Demining: Modernising Clearance Methods

Even as mechanical mine clearance systems are increasingly employed throughout the world, the full potential of these machines remains to be seen. Further study of the issue has prompted the Geneva International Center for Humanitarian Demining (GICHD) to release the “Study of Mechanical Application in Mine Action,” due in December 2003

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

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

Cardiorespiratory Fitness Is Inversely Associated With Clustering of Metabolic Syndrome Risk Factors: The Ball State Adult Fitness Program Longitudinal Lifestyle Study

Objective: The focus of this study was the association between the metabolic syndrome (MetSyn) and cardiorespiratory fitness (CRF) defined as maximal oxygen uptake (VO2max). Although previous research has shown a relationship between MetSyn and CRF, most studies are based on less objective measures of CRF and different cardiometabolic risk factor thresholds from earlier guidelines

The Association Between the Long-Term Change in Directly Measured Cardiorespiratory Fitness and Mortality Risk

Introduction: There is a strong inverse association between cardiorespiratory fitness (CRF) and mortality outcomes. This relationship has predominantly been assessed cross-sectionally, however low CRF is a modifiable risk factor, thus assessing this association using a single baseline measure may be sub-optimal. Purpose: To examine the association of the long-term change in CRF, measured using cardiopulmonary exercise testing (CPX) with all-cause and disease-specific mortality. Methods: Participants included 833 apparently healthy men and women (42.9±10.8 years) who underwent two maximal CPXs, the second CPX being ≥ 1 year following the baseline assessment. Participants were followed for 17.7 ± 11.8 years for allcause, cardiovascular disease (CVD), and cancer mortality. Cox-proportional hazard models were performed to determine the association between the change in CRF, computed as visit 1 (V1) peak oxygen consumption (VO2peak (ml·kg-1·min-1)) – visit 2 (V2) VO2peak, and mortality outcomes. Results: During follow-up, 172 participants died. Overall, the change in CPX-derived CRF was inversely related to all-cause, CVD, and cancer mortality (p\u3c0.05). Each 1 ml·kg-1·min-1 increase was associated with a 10.8, 14.7, and 15.9% reductions in allcause, CVD, and cancer mortality, respectively. The inverse relationship between CRF and all-cause mortality remained significant (p\u3c0.05) when men and women were examined independently, after adjusting for years since first CPX, baseline VO2peak, and age. Conclusion: Long-term changes in CRF were inversely related to mortality outcomes, and mortality was better predicted by CRF measured at subsequent examination than baseline CRF. These findings support the recent American Heart Association scientific statement advocating CRF as a clinical vital sign that should be assessed routinely in clinical practice, as well as support regular participation in physical activity to maintain adequate CRF levels across the lifespan

Clinical Perspectives on Incorporating Cardiorespiratory Fitness in Clinical Practice

Cardiorespiratory fitness (CRF) has been documented as a strong, independent predictor of non-communicable disease and mortality in both clinical and apparently healthy populations. This well-established relationship has impelled organizations, including the American Heart Association, to release scientific statements highlighting the importance of accurate quantification of CRF. Current knowledge of the relationship between CRF and mortality is predominantly based on estimated CRF obtained from varying indirect methods. Cardiopulmonary exercise testing (CPX), the gold standard method of CRF measurement, provides a more accurate and reliable quantification of CRF compared to estimated methods. This review provides support for the diagnostic and prognostic use of CRF based on the current literature and makes a case for the use of CPX when available, as well as the need for standardization of normative values defining CRF levels to increase the efficacy of the risk assessment. Further, clinical applications of CPX-derived CRF are discussed, providing clinicians with recommendations on how to use and interpret this measure in practice to guide clinical decisions and improve patient outcomes

Reference Standards for Body Fat Measure Using GE Dual Energy X-Ray Absorptiometry in Caucasian Adults

Background Dual energy x-ray absorptiometry (DXA) is an established technique for the measurement of body composition. Reference values for these variables, particularly those related to fat mass, are necessary for interpretation and accurate classification of those at risk for obesityrelated health complications and in need of lifestyle modifications (diet, physical activity, etc.). Currently, there are no reference values available for GE-Healthcare DXA systems and it is known that whole-body and regional fat mass measures differ by DXA manufacturer. Objective To develop reference values by age and sex for DXA-derived fat mass measurements with GE-Healthcare systems. Methods A de-identified sample of 3,327 participants (2,076 women, 1,251 men) was obtained from Ball State University\u27s Clinical Exercise Physiology Laboratory and University of Wisconsin- Milwaukee\u27s Physical Activity & Health Research Laboratory. All scans were completed using a GE Lunar Prodigy or iDXA and data reported included percent body fat (%BF), fat mass index (FMI), and ratios of android-to-gynoid (A/G), trunk/limb, and trunk/leg fat measurements. Percentiles were calculated and a factorial ANOVA was used to determine differences in the mean values for each variable between age and sex. Results Normative reference values for fat mass variables from DXA measurements obtained from GE-Healthcare DXA systems are presented as percentiles for both women and men in 10- year age groups. Women had higher (p\u3c0.01) mean %BF and FMI than men, whereas men had higher (p\u3c0.01) mean ratios of A/G, trunk/limb, and trunk/leg fat measurements than women

Comparison of Four Fitbit and Jawbone Activity Monitors with a Research-Grade ActiGraph Accelerometer for Estimating Physical Activity and Energy Expenditure

Background/aim Consumer-based physical activity (PA) monitors have become popular tools to track PA behaviours. Currently, little is known about the validity of the measurements provided by consumer monitors. We aimed to compare measures of steps, energy expenditure (EE) and active minutes of four consumer monitors with one research-grade accelerometer within a semistructured protocol. Methods Thirty men and women (18–80 years old) wore Fitbit One (worn at the waist), Fitbit Zip (waist), Fitbit Flex (wrist), Jawbone UP24 (wrist) and one waist-worn research-grade accelerometer (ActiGraph) while participating in an 80 min protocol. A validated EE prediction equation and active minute cut-points were applied to ActiGraph data. Criterion measures were assessed using direct observation (step count) and portable metabolic analyser (EE, active minutes). A repeated measures analysis of variance (ANOVA) was used to compare differences between consumer monitors, ActiGraph, and criterion measures. Similarly, a repeated measures ANOVA was applied to a subgroup of subjects who didn’t cycle. Results Participants took 3321±571 steps, had 28±6 active min and expended 294±56 kcal based on criterion measures. Comparatively, all monitors underestimated steps and EE by 13%–32% (p\u3c0.01); additionally the Fitbit Flex, UP24, and ActiGraph underestimated active minutes by 35%–65% (p\u3c0.05). Underestimations of PA and EE variables were found to be similar in the subgroup analysis. Conclusion Consumer monitors had similar accuracy for PA assessment as the ActiGraph, which suggests that consumer monitors may serve to track personal PA behaviours and EE. However, due to discrepancies among monitors, individuals should be cautious when comparing relative and absolute differences in PA values obtained using different monitors

Raw and Count Data Comparability of Hip-Worn ActiGraph GT3X+ and Link Accelerometers

To enable inter- and intrastudy comparisons it is important to ascertain comparability among accelerometer models. Purpose: The purpose of this study was to compare raw and count data between hip-worn ActiGraph GT3X+ and GT9X Link accelerometers. Methods: Adults (n = 26 (n = 15 women); age, 49.1 T 20.0 yr) wore GT3X+ and Link accelerometers over the right hip for an 80-min protocol involving 12–21 sedentary, household, and ambulatory/exercise activities lasting 2–15 min each. For each accelerometer, mean and variance of the raw (60 Hz) data for each axis and vector magnitude (VM) were extracted in 30-s epochs. A machine learning model (Montoye 2015) was used to predict energy expenditure in METs from the raw data. Raw data were also processed into activity counts in 30-s epochs for each axis and VM, with Freedson 1998 and 2011 count-based regression models used to predictMETs. Time spent in sedentary, light, moderate, and vigorous intensities was derived from predicted METs from each model. Correlations were calculated to compare raw and count data between accelerometers, and percent agreement was used to compare epoch-by-epoch activity intensity. Results: For raw data, correlations for mean acceleration were 0.96 T 0.05, 0.89 T 0.16, 0.71 T 0.33, and 0.80 T 0.28, and those for variance were 0.98 T 0.02, 0.98 T 0.03, 0.91 T 0.06, and 1.00 T 0.00 in the X, Y, and Z axes and VM, respectively. For count data, corresponding correlations were 1.00 T 0.01, 0.98 T 0.02, 0.96 T 0.04, and 1.00 T 0.00, respectively. Freedson 1998 and 2011 count-based models had significantly higher percent agreement for activity intensity (95.1% T 5.6% and 95.5% T 4.0%) compared with theMontoye 2015 raw data model (61.5% T 27.6%; P G 0.001). Conclusions: Count data were more highly comparable than raw data between accelerometers. Data filtering and/or more robust raw data models are needed to improve raw data comparability between ActiGraph GT3X+ and Link accelerometers