Cemal Ozemek

Cardiopulmonary Exercise Testing: What Is its Value?

Compared with traditional exercise tests, cardiopulmonary exercise testing (CPET) provides a thorough assessment of exercise integrative physiology involving the pulmonary, cardiovascular, muscular, and cellular oxidative systems. Due to the prognostic ability of key variables, CPET applications in cardiology have grown impressively to include all forms of exercise intolerance, with a predominant focus on heart failure with reduced or with preserved ejection fraction. As impaired cardiac output and peripheral oxygen diffusion are the main determinants of the abnormal functional response in cardiac patients, invasive CPET has gained new popularity, especially for diagnosing early heart failure with preserved ejection fraction and exercise-induced pulmonary hypertension. The most impactful advance has recently come from the introduction of CPET combined with echocardiography or CPET imaging, which provides basic information regarding cardiac and valve morphology and function. This review highlights modern CPET use as a single or combined test that allows the pathophysiological bases of exercise limitation to be translated, quite easily, into clinical practice.

Assessing the Value of Moving More-The Integral Role of Qualified Health Professionals

Being physically active or, in a broader sense, simply moving more throughout each day is one of the most important components of an individuals health plan. In conjunction with regular exercise training, taking more steps in a day and sitting less are also important components of ones movement portfolio. Given this priority, health care professionals must develop enhanced skills for prescribing and guiding individualized movement programs for all their patients. An important component of a health care professionals ability to prescribe movement as medicine is competency in assessing an individuals risk for untoward events if physical exertion was increased. The ability to appropriately assess ones risk before advising an individual to move more is integral to clinical decision-making related to subsequent testing if needed, exercise prescription, and level of supervision with exercise training. At present, there is a lack of clarity pertaining to how a health care professional should go about assessing an individuals readiness to move more on a daily basis in a safe manner. Therefore, this perspectives article clarifies key issues related to prescribing movement as medicine and presents a new process for clinical assessment before prescribing an individualized movement program.

Nonpharmacologic management of hypertension: a multidisciplinary approach

Purpose of review Nonpharmacologic lifestyle modification interventions (LMIs), such as increasing physical activity, dietary modification, weight-loss, reducing alcohol consumption and smoking cessation, are effective strategies to lower resting blood pressures (BPs) in prehypertensive or hypertensive patients. However, the limited time shared between a physician and a patient is not adequate to instill an adoption of LMI. The purpose of this review is to therefore highlight evidence-based BP lowering, LMI strategies that can feasibly be implemented in clinical practices. Recent findings Interventions focusing on modifying physical activity, diet, weight-loss, drinking and smoking habits have established greater efficacy in reducing elevated BP compared with providing guideline recommendations based on national guidelines. Alone greater reductions in BP can be achieved through programmes that provide frequent contact time with exercise, nutrition and/or wellness professionals. Programmes that educate individuals to lead peer support groups can be an efficient method of ensuring compliance to LMI. Summary Evidence of a multidisciplinary approach to LMI is an effective and attractive model in managing elevated BP. This strategy is an attractive model that provides the necessary patient attention to confer lifestyle maintenance.

Refining the Risk Prediction of Cardiorespiratory Fitness With Network Analysis: A Welcome and Needed Line of Inquiry

The value of ascertaining an individual’s cardiorespiratory fitness (CRF) is clear; a convincing body of evidence spanning several decades supports the importance of determining CRF in apparently healthy individuals, as well as those at risk for or diagnosed with ≥1 chronic diseases. In fact, CRF is now viewed as a vital sign, recognized as one of the most powerful prognostic markers for mortality and providing a window into one’s future health trajectory.1 CRF has traditionally been considered to be synonymous with peak aerobic capacity or oxygen consumption (Vo2), either estimated from treadmill speed/grade or ergometer Watts (ie, metabolic equivalents) or directly measured through ventilatory expired gas analysis. We have now come to appreciate the fact that CRF, from the perspective of an aerobic exercise stimulus, is ideally represented by a collection of measures that synergistically provide a multidimensional view of CRF. These exercise measures may be grouped into the following categories: (1) aerobic capacity or peak Vo2; (2) ventilatory efficiency, commonly assessed as the minute ventilation/carbon dioxide production (VE/Vco2) slope; (3) hemodynamics (ie, blood pressure); (4) electrocardiography, capturing both heart rate and rhythm; (5) pulmonary function and inspiratory muscle strength and endurance; and (6) symptomatology, including exertional dyspnea, leg fatigue, and angina. Traditional exercise testing on a treadmill or cycle ergometer, which entails hemodynamics, electrocardiography, and symptomatology monitoring, combined with ventilatory expired gas analysis, defines cardiopulmonary exercise testing (CPET) and provides an optimal multidimensional assessment of CRF. CPET consistently demonstrates diagnostic and prognostic utility, as well as the ability to gauge therapeutic efficacy. Scientific statements from the United States and Europe support the use of CPET in apparently healthy …

Factors Associated With Cardiorespiratory Fitness at Completion of Cardiac Rehabilitation: Identification of Specific Patient Features Requiring Attention

BACKGROUND We aimed to determine and compare predictors of postcardiac rehabilitation (CR) cardiorespiratory fitness (CRF), improvements in a large cohort of subjects with varying baseline CRF levels completing CR for ischemic heart disease and to refine prediction models further by baseline CRF. METHODS The Alberta Provincial Project for Outcomes Assessment in Coronary Heart disease (APPROACH) and TotalCardiology (TotalCardiology, Inc, Calgary, Alberta, Canada) databases were used retrospectively to obtain information on 10,732 (1955 [18.2%] female; mean age 60.4, standard deviation [SD] 10.5 years) subjects who completed the 12-week comprehensive CR program between 1996 and 2016. Peak metabolic equivalents (METs) were determined at program start and completion and identified patients at baseline with low fitness (L-Fit) (< 5 METs), moderate fitness (M-Fit, 5-8 METs), or high fitness (H-Fit, > 8 METs). Multivariable linear regression models were developed to predict METs at completion of the program. RESULTS Across all fitness groups, mean baseline METs was the strongest predictor of CRF at completion of CR. Other factors-including sex, age, current smoking status, obesity, and diabetes-were highly predictive of post-CR CRF (all P < 0.05). Compared with H-fit patients, coronary artery bypass graft and chronic obstructive pulmonary disease in L-Fit patients, and cerebrovascular disease in M-Fit patients had an additional negative effect on the overall model variance in post-CR CRF. CONCLUSION Expected CRF at the end of CR is highly predictable, with several key patient factors being clear determinants of CRF. Although most identified patient factors are not modifiable, our analysis highlights populations that may require extra attention over the course of CR to attain maximal benefit.

Enhancing Participation in Cardiac Rehabilitation: A Question of Proximity and Integration of Outpatient Services

Numerous investigations have established the strong clinical utility of cardiac rehabilitation, while clinical guidelines continually call for a high level of referral and participation. Historically, medical facilities have faced challenges referring eligible patients to cardiac rehabilitation, enrolling only a small portion of those receiving referral. Consequently, less than ~10% of qualifying patients receive any amount of cardiac rehabilitation. This sobering figure has prompted many efforts to identify barriers to referral as well as enrollment and accordingly propose strategies to bolster participation rates. Although reports have highlighted improvements through focused approaches, enrollment rates still lag behind the goal of reaching 70% by 2022, proposed by the Million Hearts Cardiac Rehabilitation Collaborative. An area of inquiry that has received little to no attention in this effort has been the influence of proximity between physician-driven outpatient clinics and cardiac rehabilitation facilities. In this report we outline the development and design of a clinical faculty practice aimed to maintainclose geographical proximity between our physicianclinic and the cardiac rehabilitation area. We also propose that our impressive enrollment rates of 57% within our facility and 73% when including patients that started alternative exercise programs were likely due to establishing a close proximity between the respective practices.

Cardiopulmonary Exercise Testing in Patients With Heart Failure and a Preserved Ejection Fraction: Filling the Prognostic Knowledge Gap

Given the sobering rise of heart failure (HF) with a preserved ejection fraction (HFpEF) and the increasing financial burden of HF-related hospital readmissions, it is imperative to identify patients at increased risk of rehospitalization in order to initiate aggressive medical and healthy living interventions. Cardiopulmonary exercise testing (CPX) has gained much scientific traction, showcasing its usefulness for predicting rehospitalizations, adverse events, and mortality. Although the evidence demonstrating the prognostic strength of CPX in HFpEF patients lags behind the mounting evidence collected in HF patients with a reduced ejection fraction (HFrEF), the few studies that exist reveal similar observations between the 2 phenotypes. The study by Palau et al., published in Revista Española de Cardiologı́a, demonstrates for the first time the power of percent-predicted peak oxygen consumption (VO2) in identifying HFpEF patients that were at an increased risk of recurrent hospital admissions over a 3-month period. Their findings contribute valuable data that extend the evidence supporting the application of CPX in clinical settings and encourage the use of percent-predicted peak VO2 in patients with HFpEF, which has been established as a powerful prognosticator in HFrEF. Of note, Palau et al. identified an independent, linear association with recurrent all-cause and cardiovascular mortality as well as acute HF admissions in an elderly, highly symptomatic HFpEF cohort. A 10% reduction in percent-predicted peak VO2 was associated with a 32% increased risk of recurrent hospitalization, which remained significant when the minute ventilation/carbon dioxide production (VE/VCO2) slope was added to the multivariate model. However, the VE/VCO2 slope on its own was not predictive of recurrent hospitalizations. Globally, these findings are a valuable contribution to the limited HFpEF literature showcasing the value of CPX in predicting recurrent hospital readmissions. Many of the initial investigations related to the exploration of CPX markers have been conducted in patients with HFrEF. Since the initial landmark studies highlighting the strength of mortality prediction using peak VO2, 8–10 many efforts have been made to identify stronger predictive measures. Assessment of ventilatory efficiency (ie, the VE/VCO2 slope) has emerged as a more telling predictor of events, hospitalizations, morbidity, and mortality in patients with HFrEF, compared with peak VO2. 11,12 Similarly, identification of a cyclic or oscillatory breathing pattern in roughly 30% of HFrEF patients in response to increasing exercise intensity (ie, exercise oscillatory ventilation [EOV]) has also emerged as an equally–if not more–predictive marker of cardiac events compared with VE/VCO2 slope in HFrEF. 11,12 In contrast, a clear ranking of the most powerful event predictors has not emerged in the HFpEF population. Guazzi et al. reported the superior prognostic power of EOV compared with VE/VCO2 and peak VO2, while VE/VCO2 outperformed peak VO2 in predicting cardiac events in patients with HFpEF. Yan et al. confirmed the stronger predictive power of VE/VCO2 compared with peak VO2, but did not assess EOV. It is worth mentioning that neither of these studies calculated percent-predicted peak VO2, a robust predictor–more so than peak VO2 alone–in a cohort with a wide age range. Indeed, the severity of a person’s disease state greatly impairs oxidative capacity; however, the inevitable decline in peak VO2 with age confounds comparisons of peak VO2 across various ages (ie, 50-year-old and 70-year-old HF patients). It may therefore be more accurate to calculate a patient’s percentage of predicted peak VO2 to establish prognostic significance in a cohort of varying ages. Furthermore, percent-predicted peak VO2 has been shown to be equally–if not more–predictive of adverse events than VE/VCO2 when the Wasserman/Hansen prediction equation is used in patients with HFrEF. Shafiq et al. were the first to evaluate the predictive power of percent-predicted peak VO2 in patients with HFpEF. Their comprehensive, retrospective analysis tested the strength to predict mortality and cardiac transplants in 173 HFpEF patients and the findings partly contradicted previous findings in patients with HFrEF or HFpEF. Percent-predicted peak VO2 (chisquare = 15.0, hazard ratio per 10%, P < .001) was found to be the strongest predictor of events, followed by peak VO2 (chi-square = 11.8, P = .001). However, the VE/VCO2 slope (chi-square = 0.4, P = .54) and EOV (chi-square = 0.15, P = .70) were not significant predictors. Although the current study by Palau et al. did not evaluate EOV, their observation of percent-predicted peak VO2 outperforming the VE/VCO2 slope (which was not a significant predictor on its own) in predicting recurrent hospitalizations was Rev Esp Cardiol. 2018;71(4):237–239