Snyder, Eric M.

INTRODUCTION Treatment with β‐antagonists in heart failure (HF) elicits known cardioprotective benefits. Recent work has suggested that administration of a β‐agonist can induce lung fluid clearance in healthy subjects and HF patients. However, the impact of β‐antagonists on the diffusing capacity of the lungs for carbon monoxide (DLCO, to assess lung fluid changes) remains unclear. PURPOSE To examine the relationship between β‐antagonist use and lung diffusion in HF patients. METHODS A retrospective analysis was performed on 102 HF patients seen at Mayo Clinic between 1995–2010. Patients were divided into two groups: BB=patients prescribed β‐antagonists (n=70) and NB=patients not prescribed β‐antagonists (n=32). Medical records were examined ±1 year from the time of the most recent exercise stress test for age (yrs), sex, height (cm), weight (kg), body mass index (BMI) and β‐antagonist status. Outcome variables included DLCO, left ventricular ejection fraction (LVEF), cardiac output (Q), and cardiac output corrected for body surface area (CI). Independent‐samples t‐test compared age, height, weight, and BMI between BB and NB. A Chi‐Squared test compared New York Heart Association (NYHA) classification and sex between NB and BB. Comparison of DLCO, LVEF, Q, CI, DLCO corrected for CI (DLCO/CI), and DLCO corrected for Q (DLCO/Q) between NB and BB was performed with an independent‐samples t‐test. Data are reported as mean ± standard deviation (SD) or frequency (percentage) where applicable. RESULTS There were no differences in age (75±12 vs. 76±13yrs), height (172±10 vs. 173±9cm), weight (84±20 vs. 86±18kg), or BMI (28±6 vs. 29±5kg/m 2 ) between NB vs. BB, respectively. Neither NYHA classification (χ 2 =0.159; p =0.98) or sex (χ 2 =0.066; p =0.80) were different between NB and BB groups. No differences were found for LVEF (36.8±17.3 vs. 31.6±15.6%) or DLCO (20.32±7.6 vs. 19.35±5.7ml/min/mmHg) for NB vs. BB, respectively. Compared to NB, the BB group demonstrated lower CI (0.72±0.3 vs. 0.56±0.3, p =0.006) and Q (1.47±0.6 vs. 1.15±0.6, p =0.01), while both DLCO/CI and DLCO/Q were higher in BB (31.32±14.1 vs. 43.84±29.5, p =0.005 and 15.84±7.5 vs. 21.93±16.2, p =0.01, respectively). CONCLUSIONS These data suggest that HF patients prescribed β‐antagonist therapy demonstrate better lung diffusion for a given cardiac output compared to HF patients not prescribed β‐antagonist therapy.

INTRODUCTION Bronchodilator therapy via β‐agonists has been considered a controversial treatment option for patients with cardiovascular disease, including heart failure (HF), due to previous studies suggesting increased rates of mortality. A major limitation to several previous studies is the lack of similar baseline characteristics between groups; therefore, a matched control comparison is yet to be explored. PURPOSE To evaluate the relationship between bronchodilator therapy and survival in HF patients. METHODS A retrospective analysis was performed on 96 HF patients who underwent a cardiopulmonary exercise test between the years 1994–2010. Patients were divided into two groups: 48 patients on bronchodilator therapy (BDT) and 48 matched controls (CTL). Patients were matched based on age (yrs), height (cm), weight (kg), body mass index (BMI), New York Heart Association (NYHA) classification, and cardioselective β‐blocker medication during the time of their cardiopulmonary exercise test. Patients were followed for an average of ten years for an endpoint of cardiovascular mortality. An independent samples t‐test was performed comparing BDT and CTL for age (yrs), height (cm), weight (kg), and BMI, to determine comparable baseline characteristics. A Chi‐Squared test compared NYHA classification, cardioselective β‐blocker status, and sex between BDT and CTL. A log rank test was performed to determine differences in survival distributions between BDT and CTL. RESULTS There were no significant demographic differences between groups (age: 59.8 vs. 60.3yrs; height: 172.1 vs. 171.9cm; weight: 86.9 vs. 86.2kg; and BMI: 28.9 vs. 28.6kg/m 2 for BDT vs. CTL, respectively). NYHA classification (χ 2 =0.00; p =1.0), cardioselective β‐blocker status (χ 2 =0.14; p =0.71) and sex (χ 2 =0.202; p =0.65) were not different between groups. BDT patients demonstrated an event rate of 51.1% compared to 42.6% for CTL patients over the same time period. The survival distribution for BDT compared to CTL was not statistically different, χ 2 (1) = 1.49, p =0.22. CONCLUSION These data suggest that HF patients on bronchodilator therapy demonstrate no significant difference in survival compared to matched HF controls. In contrast to previous work, our data suggests bronchodilator therapy does not elicit increased mortality in these HF patients.

Introduction A disproportionate increase in ventilation relative to carbon dioxide output (V E /VCO 2 ) slope is a strong prognostic indicator in heart failure with reduced (HFrEF) or preserved ejection fraction (HFpEF) patients. Similarly, secondary pulmonary hypertension also poses a profound mortality risk in these patients. Exaggerated ventilation and pulmonary pressures appear to parallel one another during exercise in HF. However, an underlying pathophysiologic mechanism relating these two outcomes remains incompletely understood. Thus, the aim of this study was to determine associations between anatomical and physiologic metrics of ventilatory control and pulmonary pressures during exercise in HFrEF and HFpEF. Methods 32 HFpEF and 33 HFrEF (EF: 62±2 vs 22±1%; male: 17 and 31; age: 70±2 and 55±2 yrs; BMI: 34±1 and 28±1 kg/m 2 ; weight: 98±4 and 86±3 (all P <0.05), respectively, participated in cardiopulmonary exercise testing during right heart catheterization. Measures of pulmonary pressures included: systolic (PASP); diastolic (PADP); mean (mPAP); wedge (PCWP); pulse (PP); transpulmonary gradient (TPG). Partial pressure of arterial oxygen (PaO 2 ) and carbon dioxide (PaCO 2 ) were measured via radial arterial catheterization. Ventilation was measured continuously using a breath by breath metabolic measurement system. We calculated dead space to tidal volume [Vd/Vt=(V E ×PaCO 2 )‐(863×VCO 2 )/(V E ×PaCO 2 )] and Alveolar‐arterial oxygen gradient (A‐a)=PAO 2 ‐PaO 2 ; V E /VCO 2 slope=rest to peak exercise. Results At rest, pulmonary pressures did not differ between groups ( P >0.05); whereas Vd/Vt was lower in HFpEF vs HFrEF (0.42±0.02 vs 0.48±0.01, respectively, P =0.03). At peak exercise, HFpEF had higher PCWP (34.8±1.2 vs 30.2±1.5 mm Hg, P =0.02) and PADP (35.4±1.3 vs 29.8±1.6 mm Hg, P =0.02), but lower Vd/Vt (0.32±0.02 vs 0.38±0.01, P =0.03) and V E /VCO 2 slope (35.3±1.6 vs 43.5±2.0, P <0.01) vs HFrEF. At peak in HFpEF, Vd/Vt was related to PASP (r=0.40, P =0.03), PP (r=0.44, P =0.01), and TPG (r=0.53, P <0.01), and A‐a was related to PASP (r=0.43, P =0.01), PP (r=0.44, P =0.01), and TPG (r=0.46, P <0.01). At peak in HFrEF, Vd/Vt was related to PADP (r=0.41, P =0.02), and A‐a was related to PASP (r=0.43, P <0.01), PADP (r=0.42, P =0.01), and mPAP (r=0.44, P <0.01). There were no significant relationships between measures of pulmonary pressures and PaCO 2 . Remaining correlations between pulmonary pressures and anatomical or physiologic metrics of ventilatory control were negligible in both groups ( P >0.05). Conclusion These data suggest pulmonary pressures play a role in dead space ventilation during exercise in HF. Moreover, as suggested by the A‐a gradient, augmented pulmonary pressures may contribute to an exacerbation of ventilation/perfusion mismatch during exercise in both HFrEF and HFpEF patients. Support or Funding Information None

Introduction Several common and functional genes are known to contribute to renal, blood vessel, and cardiac functional characteristics associated with sodium (Na + ) handling, vascular reactivity, and cardiac output, respectively. Many of these same genes are suggested to contribute to differential responsiveness to blood pressure (BP) therapy. Few studies have explored the simultaneous phenotypic consequence of multiple genes critical for BP control. Despite a significant impulse of the medical community towards personalized medicine, BP therapy is typically guided by algorithms that do not include a patient's genetic information. Purpose The purpose of this study was to determine the impact of 14 genes on time to BP control in response to common BP therapy, with a specific focus on genes associated with drug metabolism and protein function in the kidney, the blood vessels, and the heart. Methods Eighty‐six patients completed one study visit consisting of a buccal swab for DNA extraction and genotyping, measurement of ambulatory BP, and a medical chart review for objective BP history. Genes in the analysis included those that encode for one drug metabolizing enzyme (CYP2D6), renal Na + handling (SCNN1A, WNK1, SLC12A3, and Alpha Adducin), vascular function (angiotensin, ACE, angiotensin‐II receptor type‐I, and renin), and cardiac function (the β 1 and β 2 adrenergic receptors ADRB1 and ADRB2, respectively). Results Genetic variation of WNK1 (rs1159744) demonstrated differential responses to diuretic therapy (determined as those with blood pressure under 140/90 vs. those above 140/90 according to genotype)(WNK1=GG>CG/CC, P<0.05). Genes that encode ADRB1 (rs1801252), ADRB2 (rs1042713), and CYP2D6 (rs3892097) demonstrated differential response to β‐blocker therapy (ADRB1=Ser/Ser>SerThr/ThrThr, ADRB2=GG>AG/AA, CYP2D6=CC>CT/TT, P<0.05). Genes that encode angiotensin (rs699), ACE (rs1799752), and renin (rs12750834) demonstrated differential response to ACE‐inhibition and angiotensin receptor blockade (angiotensin=CT/TT>CC, ACE=Ins/Ins>InsDel/DelDel, renin=AG/AA>GG, p<0.05). Conclusion These results demonstrate that genetic variants encoding proteins involved in renal Na + handling, vascular function, and cardiac output influence response to BP therapy for their respective drug classes. Support or Funding Information Funded by Geneticure

Introduction Hypertension is one of the most important preventable contributors to disease and death worldwide and represents the most common condition seen in the primary care setting. Approximately one in three adults living in the US has hypertension. Despite the prevalence and impact of hypertension, little data exists on the average time to blood pressure (BP) control in US patients and time to control according to common BP medication classes. Purpose Therefore, the purpose of this study was to assess the average time to BP control in adults with controlled hypertension, according to drug class. Methods For this study we assessed how long (in months) and how many clinic visits were needed in order to control BP according to common medication classes in patients with existing hypertension. The study was performed at two clinical sites where patients came in for one visit for an in‐clinic assessment of BP and for completion of a patient survey regarding their history of BP. The primary care physician performed a chart review for a detailed objective BP history. Results Ninety‐nine patients completed all aspects of the study (age=58±0.8yrs., %female=46, height=169±1.0cm, weight=86±1.4kg, BMI=29.9±0.4m/kg 2 ). The average initial BP was 151±2mmHg systolic (SBP), 91±1mmHg diastolic, and 111±1mmHg mean arterial (MAP). Patients demonstrated a significant drop in BP with therapy (SBP=16mmHg, DBP=10mmHg, MAP=12mmHg). Patients were prescribed an average of 1.8 BP medications (62% on ACE‐inhibitor, 42% on diuretic, 33% on β‐blocker, 27% on angiotensin receptor blocker, and 16% on Ca + channel blocker). The average time to BP control was 14.9 months or 3.6 clinic visits. Patients on a diuretic had the longest time to BP control, while patients on a Ca + channel blocker had the shortest time to control (diuretic=19.5±10.4, angiotensin receptor blocker=22.8±13.1, ACE‐inhibitor=22.2±11.4, β‐blocker=24.5±16.9, Ca + channel blocker=9.9±4.5 months, pANOVA<0.05). In contrast, patients on a Ca + channel blocker had significantly more clinic visits to attain BP control (diuretic=4.5±0.6, ACE‐inhibitor=3.1±0.4, angiotensin receptor blocker=3.9±0.6, β‐blocker=4.9±0.7, Ca + channel blocker=5.1±0.7 visits). Conclusion These results suggest important differences in the time to BP control, and the number of office visits necessary for BP control according to common classes of hypertension therapies. Funding was provided by Geneticure, LLC Support or Funding Information Funded by Geneticure

Introduction: Assessment of cardiac function during exercise is critical in the clinical evaluation of patients with heart failure with preserved (HFpEF) or reduced (HFrEF) ejection fraction. Direct invasive measurement of cardiac power (CP) and stroke work (SW) are robust measures of cardiac function. Non-invasive gas exchange based surrogates may provide practical means of assessing cardiac function in clinical and research settings; however, the relationship between invasive and non-invasive measurement of CP or SW during exercise is unclear in HFpEF and HFrEF. We aimed to assess relationships between invasive and non-invasive measures of CP and SW during exercise in HFpEF and HFrEF. Methods: HFpEF (n=47) and HFrEF (n=29) (age 71±10 vs 55±10 yrs; EF% 62±8 vs 21±6%; BSA 2.1±0.3 vs 2.1±0.2 m 2 ; weight 99±22 vs 87±15 kg; peak work 36±14 vs 37±13 watts (W), respectively; all p<0.05, except peak work) underwent peak exercise testing during right heart catheterization. Invasive measurement of cardiac pressures, hemodynamics, and arterial pressures were recorded at rest, 20 W, and peak work. Continuous measurement of HR and VO 2 occurred from rest to peak work via 12-lead ECG and metabolic measurement system, respectively. Invasive measurements were calculated as, CP=(MAP–RAP) x Q x 2.22х10 -3 ; SW=(MAP–PCWP) x SV I x 0.133; and non-invasive as, CP=VO 2 x MAP; SW=VO 2 /HR x MAP. All indices adjusted for body surface area. Results: At rest, there were moderate relationships between invasive and non-invasive measures of CP and SW in HFpEF (r=0.56 and 0.48) and HFrEF (0.57 and 0.73), respectively (all p<0.05). At 20 W, relationships between invasive and non-invasive measures of CP and SW strengthened in HFpEF (r=0.74 and 0.69) and HFrEF (0.74 and 0.72), respectively (all p<0.05). The relationships noted between invasive and non-invasive measures of CP and SW at 20 W persisted at peak work in HFpEF (r=0.74 and 0.67) and HFrEF (0.78 and 0.69), respectively (all p<0.05). Conclusion: These data suggest that non-invasive estimates of CP and SW correlate closely with invasive measures and may be reasonable surrogates for these indices during peak exercise testing in both HFpEF and HFrEF patients.

Introduction: Invasive measurement of cardiac power (CP) and stroke work (SW) during exercise are robust indices of cardiac function and relate to syndrome severity and prognosis in heart failure patients with preserved (HFpEF) or reduced (HFrEF) ejection fraction. Because invasive measurement via catheterization laboratories are not always readily available, non-invasive cardiopulmonary exercise testing to estimate cardiac function is routinely performed in the clinical evaluation of HFpEF and HFrEF. However, it is unknown how VO 2 relates with CP and SW in HFpEF vs HFrEF. We compared relationships between CP and SW with VO 2 at rest and peak exercise in HFpEF vs HFrEF. Methods: 30 HFpEF and 32 HFrEF (EF: 62±2 vs 22±1%; males: 17 vs 30; age: 70±2 vs 55±2 yrs; BMI: 34±1 vs 28±1 kg/m 2 ; wt: 98±4 vs 86±3 kg (all p<0.05)) participated in exercise testing during right heart catheterization. Oxygen consumption (VO 2 ) was measured continuously from rest to peak work. Invasive measures at rest and peak work included mean radial arterial pressure (MAP), right atrial pressure (RAP), and pulmonary capillary wedge pressure (PCWP). We calculated CP=(MAP–RAP) x Q I x 2.22х10 -3 and SW=(MAP–PCWP) x SV I x 0.133. Results: At rest, R 2 between VO 2 and CP or SW were not different between HFpEF (CP=0.41, SW=0.30) and HFrEF (CP=0.39, SW=0.15). Slopes did not differ significantly between HFpEF (CP=0.13, SW=0.01) and HFrEF (CP=0.16, SW=0.01) for regressions between VO 2 and CP or SW; but, fitted intercepts of the regression showed significantly higher intercepts in HFrEF (CP=0.89, SW=1.16) vs HFpEF (CP=0.05, SW=0.27) for VO 2 vs CP and SW, respectively. At peak exercise, R 2 between VO 2 and CP or SW were not different between HFpEF (CP=0.48, SW=0.64) and HFrEF (CP=0.70, SW=0.67). Slopes did not differ between HFpEF (CP=0.18, SW=0.02) and HFrEF (CP=0.15, SW=0.02) for regressions between VO 2 and CP or SW, whereas the fitted intercepts the slope of the regression were significantly higher in HFrEF (CP=5.1, SW=4.4) vs HFpEF (CP=3.2, SW=2.0) for VO 2 vs CP and SW, respectively. Conclusion: Our data suggest that despite lower VO 2 relative to CP and SW in HFpEF, both the strength of relationship and rate of increase in VO 2 relative to CP and SW are similar between HFpEF and HFrEF at rest and peak exercise.

Introduction: Neural feedback from skeletal muscle during exercise contributes to changes in pulmonary pressures in healthy individuals. Heart failure patients (HF) often develop pulmonary hypertension; however, the relationship between muscle afferent feedback and the pulmonary vasculature in HF remains unclear. Hypothesis: We examined the influence of metaboreceptor stimulation on pulmonary vascular capacitance using a validated non-invasive gas exchange equivalent (GX CAP ) in HF. Methods: Eleven HF patients (age 51±5 yrs; EF, 32±3%; NYHA class, 1.6±0.2) and 11 controls (CTL; age 43±3 yrs) completed 3 cycling session (4-min at 60% of peak oxygen consumption, VO 2 ). Session one: baseline control trial. Sessions 2 and 3: bilateral upper-thigh tourniquets inflated suprasystolic for 2 min at end-exercise (regional circulatory occlusion, RCO) with or without addition of inspired CO 2 to maintain end-exercise end-tidal CO 2 (P ET CO 2 ) (RCO+CO 2 ) (randomized). Rest, exercise, and recovery heart rate (HR), P ET CO 2 , and VO 2 were measured. O 2 pulse (VO 2 /HR) and GX CAP (O 2 pulseхP ET CO 2 ) were calculated. Results: During all conditions at end-exercise, HF demonstrated significantly lower GX CAP compared to CTL (p<0.01). Percent change in GX CAP from end-exercise to 2 min post-exercise was attenuated in HF compared to CTL (41±5% vs 64±1%, respectively, p<0.01) during the baseline trial. During RCO, HF had a 55±6% reduction in GX CAP from end-exercise compared to 77±2% in CTL (p<0.01). During RCO+CO 2 , HF had a 49±4% reduction in GX CAP from end-exercise compared to 69±2% in CTL (p<0.01). GX CAP was similar between sessions within HF. The CTL group demonstrated an attenuated return of GX CAP during RCO compared to both baseline and RCO+CO 2 (p<0.01) with no difference between baseline and RCO+CO 2 . Conclusion: These data suggest the exercise mediated rise and post-exercise recovery of pulmonary vascular capacitance are attenuated in HF during constant-load submaximal exercise compared to CTL. Additionally, our data confirm previous reports that locomotor muscle afferent feedback influences pulmonary vascular capacitance in CTL; however, this model of locomotor muscle metaboreflex stimulation appears to a differential response in HF compared to CTL.

Introduction: Physical activity (PA) is known to be effective in treating and preventing many lifestyle diseases including CVD, stroke, depression, type II diabetes, Alzheimer’s disease, as well as breast and colon cancer. To date the direct medical cost-savings of PA as a medical intervention are poorly understood. Hypothesis: We hypothesized that a 10% increase in the proportion of US citizens who meet the minimum weekly exercise requirements of 150 minutes per week would lead to savings in direct medical costs (DMC) and cases prevented, as related to the above diseases. Methods: Population Attributable Risk (PAR) was calculated as PAR= (1+Prf x (RR-1))/(Prf x(RR-1)), where Prf is the percentage of the U.S. population not meeting minimum exercise requirements and RR is the relative risk of disease for sedentary versus physically active individuals. Prf and RR data were retrieved from the most recent and comprehensive meta-analyses and systematic reviews. PAR was calculated for each disease under two conditions; first, Prf was equal to the current percent (9.6%) of the population estimated to achieve the minimum weekly PA requirements. Second, Prf was equal to the initial Prf plus 10 percent (19.6%). For each condition the following were calculated: Attributable DMC=(PAR x DMC), preventable cases=(PAR x Prevalence) and Savings=(Condition 2- Condition 1). Results: The Prevalence, RR, PAR and DMC are provided in Table 1. This table also describes the potential savings in DMC and new cases by improving the Prf by 10%. A 10% increase in US citizens who meet the minimum weekly exercise requirements could lead to a total savings of 10.78 billion USD in DMC and 2.1 million cases prevented related to the studied diseases. Conclusion: A healthcare system directed PA intervention that effectively leads to a 10% increase in US citizens that meet minimum weekly exercise requirements and costs less than 10.78 billion dollars has the potential to be cost-effective, and prevent and treat, millions of cases in the United States.