Effect of 8-week exercise-based cardiac rehabilitation on cardiac autonomic function: A randomized controlled trial in myocardial infarction patients Nórton Luís Oliveira, PhD, a Fernando Ribeiro, PhD, a,b Madalena Teixeira, MD, c Lilibeth Campos, MD, d Alberto Jorge Alves, PhD, a Gustavo Silva, PhD, a and José Oliveira, PhD a Porto, Aveiro, and Vila Nova de Gaia, Portugal

Purpose The purpose of this study is to evaluate the effects of an 8-week exercise-based cardiac rehabilitation program on traditional and nonlinear heart rate variability (HRV) indexes, assessing the potential confounding influences of habitual physical activity (PA) and dietary intake. Methods In this parallel-group trial, 96 patients (56 ± 10 years old) were randomized to the exercise group (EG) or to the control group (CG) 4 weeks after an acute myocardial infarction. Exercise-based cardiac rehabilitation program consisted of aerobic exercise at 70% to 85% of maximal heart rate for 3 sessions per week plus usual care. The CG received only usual care. The baseline and final assessments comprised resting short-term HRV (primary outcome) by a Polar R-R recorder under controlled breathing (12 breaths per minute), habitual PA by accelerometers, and dietary intake by a 4-day food diary. Results

Two patients in each group dropped out and were not included in the intention-to-treat analysis. In the remaining 92 patients (EG = 47 and CG = 45), at baseline, only a difference in the proportion of nitrate medication use was significant between groups. After 8 weeks, no significant changes were found between groups on traditional and nonlinear HRV indexes (eg, ln HF, EG from 5.7 ± 1.5 to 5.9 ± 1.3 and CG from 5.5 ± 1.6 to 5.5 ± 1.5), habitual PA, and dietary intake.

Conclusion Eight weeks of exercise-based cardiac rehabilitation program is an insufficient stimulus to improve cardiac autonomic function in post–myocardial infarction patients under optimal medication and with high levels of traditional and nonlinear HRV indexes at baseline. (Am Heart J 2014;0:1-9.e3.)

An unbalanced cardiac autonomic modulation (ie, increased sympathetic outflow and reduced parasympathetic activity) is a detrimental condition in post– myocardial infarction (MI) patients. 1 A widely used method to estimate the cardiac autonomic modulation is the assessment of heart rate variability (HRV). 2 Depressed HRV suggests the deregulation of cardiac autonomic control, 3 which has been independently associated with all-cause mortality, sudden cardiac death, and the recurrence of cardiac events in MI

From the aResearch Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto, Porto, Portugal, bSchool of Health Sciences, University of Aveiro, Aveiro, Portugal, cCardiology Department, Centro Hospitalar de Gaia/Espinho, Vila Nova de Gaia, Portugal, and dPhysical Medicine and Rehabilitation Department, Centro Hospitalar de Gaia/Espinho, Vila Nova de Gaia, Portugal. ClinicalTrials.gov Identifier: NCT01432639. Submitted August 7, 2013; accepted February 11, 2014. Reprint requests: Norton Luis Oliveira, PhD, Rua Dr Plácido Costa, 91-Research Centre in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto CEP-4200.450, Porto, Portugal. E-mail: [email protected] 0002-8703/$ - see front matter © 2014, Mosby, Inc. All rights reserved. http://dx.doi.org/10.1016/j.ahj.2014.02.001

patients. 4,5 Furthermore, studies have shown that some nonlinear HRV indexes can be even more powerful predictors of mortality than the traditional HRV indexes (ie, indexes of time and frequency domains) and are able to preserve their prognostic power in post-MI patients under optimized β-blocker medication. 6 Therefore, interventions to improve HRV could be beneficial. Indeed, in a study with post-MI patients treated with propanolol, the improvement in HRV was accompanied by a better prognosis. 7 Another type of intervention is exercise training, although its effects on the impaired autonomic function of MI patients are controversial even when similar exercise programs are used. 8,9 The discrepancy between the results of previous studies might be related to methodological issues such as the lack of control of breathing frequency during the HRV assessment 10 and/or the lack of assessment of potential confounders like the chronic effects of habitual physical activity (PA) and dietary intake. 11,12 Therefore, because reduced vagal activity, as represented by a decreased HRV, has been related to increased susceptibility of malignant ventricular arrhythmia, especially in episodes of myocardial ischemia, 13 the main

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Figure 1

Study design.

purpose of this study was to assess, in post-MI patients, the effects of an exercise-based cardiac rehabilitation program on traditional and nonlinear HRV indexes, controlling the breathing frequency and assessing the potential confounding influences of habitual PA and dietary intake.

Methods Study design, randomization, and implementation This study was a parallel-group, randomized controlled trial (RCT) that was performed from May 2011 to November 2012 at the Centro Hospitalar de Vila Nova de Gaia/Espinho, Portugal. Every patient who agreed to participate in the study provided a written informed consent. In brief, 4 weeks after the acute MI, consenting patients were randomly assigned to an exercisebased cardiac rehabilitation program (EG) or to a control group (CG) receiving usual medical care (ie, regular appointments with a cardiologist and optimized medication) (Figure 1). A randomization by blocks was used, and an allocation sequence based on a fixed block size of 8 was generated with a computer

random number generator by an investigator not involved in the trial. A cardiologist aware of the study design conducted the enrolment and assignment. Because exercise training composed the intervention, it was not possible for those implementing it to be blind to the assignment. However, the outcome evaluators were blind to the group assignment. At baseline and after 8 weeks, each participant underwent several evaluations in the same sequence and at the same period of the day (ie, morning), the latter to avoid bias due to circadian rhythms. The Hospital Ethics Committee granted ethical approval (reference 627/2010), all procedures were conducted according to the Declaration of Helsinki, and the trial has been registered at ClinicalTrials.gov (NCT01432639).

Participants Eligible patients were those aged ≥18 years, men and women, referred to the Hospital Cardiology Department after an acute MI. Exclusion criteria included the presence of uncontrolled cardiac arrhythmias, unstable angina pectoris, uncontrolled hypertension, significant valvular disease, diagnosis of heart failure, uncontrolled metabolic disease (eg, uncontrolled

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diabetes and thyroid disease), presence of pulmonary and renal comorbidities, conditions limiting participation in exercise training (eg, peripheral artery disease, orthopedic limitations, and musculoskeletal disorder), abnormal hemodynamic responses, myocardial ischemia, and/or severe ventricular arrhythmias during baseline exercise testing.

Measurements Anthropometrics. Height was assessed by a standard wallmounted stadiometer. Body mass and percentage of fat mass were measured using a Tanita Inner Scan BC-522 (Tanita, Tokyo, Japan) with the patients wearing light clothing without shoes. Body mass index (BMI) (kilograms per square meter) was calculated. Waist circumference was measured at the midpoint between the lowest rib and the iliac crest.

Cardiorespiratory fitness. Peak oxygen uptake (VO2peak) was assessed by ergospirometry (Cardiovit CS-200 Ergo Spiro; Schiller, Baar, Switzerland) during a maximal or symptomlimited treadmill exercise test (modified Bruce protocol).

Resting hemodynamic and autonomic function. Patients were asked to avoid strenuous exercise and caffeinecontaining products or alcohol consumption for at least 24 hours before evaluation. The evaluation room was kept quiet, semidark, and with an average temperature of 22°C. Recording of R-R interval data was performed using the Polar RS800CX (Polar Electro OY, Kempele, Finland) with a temporal resolution of 1 ms. The Polar system is a valid and reliable instrument for the short-term HRV assessment. 14 The assessments were performed in supine position, controlling the breathing rate by matching it to a metronome-paced frequency of 12 breaths per minute. Following 20 minutes of recording, R-R interval data were downloaded into Polar Precision Performance Software SW (Polar Electro OY). Through the Kubios HRV Software 2.0 for Windows (The Biomedical Signal Analysis Group, University of Kuopio, Finland), ectopic beats or arrhythmias were excluded, and R-R data were detrended 15 and resampled at 4 Hz. Finally, the last 5 minutes of recording was selected and used for calculating HRV indexes. Time domain indexes included the mean R-R interval, SD of the R-R interval (SDNN), and square root of the mean of the squares of successive R-R interval differences (RMSSD). Frequency domain indexes were the low frequency power (LF; 0.004-0.15 Hz), high frequency power (HF; 0.15-0.4 Hz), and LF/HF ratio, which were determined using the nonparametric method (Fast Fourier transform). In addition, the nonlinear HRV indexes sample entropy and shortterm fractal scaling exponent (DFA1), which are complexity measures of biological signals (eg, heart rate), were calculated. When performed under controlled laboratory conditions and by short-term recordings, most HRV indexes in the time and frequency domains reflect predominantly the cardiac vagal modulation. 16 This is also true for the LF power and the LF/HF ratio, although these indexes were initially believed to reflect sympathetic activity and sympathovagal balance, respectively. 17 A lower value of sample entropy reflects less complexity and can be related with increased sympathetic and decreased vagal modulation. 18 Regarding DFA1, a value near 1 is associated with healthy heart dynamic, and values near 0.5 and 1.5 are suggestive of less favorable cardiac health. 19 The mean resting heart rate was also calculated in this evaluation. At least 3 blood pressure measurements were made in right arm using Colin

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model BP 8800 monitor (Critikron, Inc, Tampa, FL) after the 20 minutes of HRV assessment with the arm well supported and relaxed at the level of the heart. Intervals of 1 minute were complied between the measures. The average of these multiple measurements was used.

Daily PA. To obtain a picture of the habitual daily PA, accelerometers (Actigraph GT1M; ActiGraph, LLC, Pensacola, FL) were used for seven consecutive days. Patients wore the accelerometer positioned on the right hip during the day, except while sleeping, bathing, and during aquatic activities. The software PROPERO (developed by the University of Southern Denmark, 2011) was used to reduce the raw activity data from the accelerometers into daily PA. The average minutes per day spent at different PA intensities was determined according to cut points relating counts per minute to PA intensity. 20

Dietary intake. Patients were instructed to record food and beverage intakes for 4 days (Sunday and 3 weekdays). Skilled nutritionists performed a comprehensive nutrient analysis (ie, total energy intake, consumption of protein, carbohydrates, total fiber, sodium, total fat, saturated fat, monounsaturated fat, cholesterol, and n-3 and n-6 fatty acids) with the Food Processor Plus (version 7.02; ESHA Research, Salem, OR). Exercise training program. Exercise training encompassed 3 supervised exercise sessions per week for 8 weeks (10 minutes of warm-up, 30 minutes of aerobic exercise on a cycloergometer or treadmill at 70%-85% of maximal heart rate achieved in the exercise test and 10 minutes of cool-down). During the exercise sessions, the participants' heart rate was continuously monitored by electrocardiogram, and levels of exertion were assessed with the Borg scale. In addition, these patients were also under the usual medical care and follow-up (ie, regular appointments with a cardiologist and optimized medication). Sample size calculation and statistical analysis. The power calculation was computed a priori based on a published meta-analysis 21 that reported a training effect on HRV of 0.3. Assuming a power of 99% and using a repeated measures analysis of variance (ANOVA) within-between interaction at the 5% significance level revealed a need for 84 patients. A target of 93 patients was identified to accommodate an expected maximal dropout rate of 10%. Normal data distribution was verified by Shapiro-Wilk test. Continuous variables not normally distributed were transformed to their natural logarithm or square root for subsequent analysis (ie, days hospitalized, body mass, BMI, systolic blood pressure, SDNN, RMSSD, LF, HF, LF/HF, carbohydrates, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, n-3 fatty acid, n-6 fatty acid and sodium, and total, sedentary, light and moderate to vigorous PA). Nevertheless, the values are presented in the original scale for clarity reasons. At baseline, the Student independent t test and χ 2 test were used to perform betweentreatments comparisons as appropriate. A repeated-measures ANOVA or analysis of covariance, both with Bonferroni adjustment, was used to compare the changes in the primary and secondary outcomes between treatments over time (treatment × time) as appropriate. When a significant treatment × time interaction was observed, a univariate general linear model (treatment as fixed factor with or without a

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Figure 2

Flow diagram patients.

covariate) was performed to ascertain the differences at the final assessment between treatments. First, the intention-to-treat principle was applied to the analysis of the outcomes for all participants based on their assigned treatments. In addition, a per-protocol analysis was conducted without participants that did not attend at least 80% of the exercise sessions and changed the medication to examine the biological effects of the treatment. Effect size was reported using partial η 2 (η 2p). Statistical significance was set at P b .05 for all tests. SPSS 18.0 (SPSS, Inc, Chicago, IL) was used for all analysis. This trial is funded by European Regional Development Fund through the Operational Competitiveness Programme and by Foundation for Science and Technology (FCT) of Portugal— within the projects FCOMP-01-0124-FEDER-014706 (reference FCT: PTDC/DES/113753/2009) and PEst-OE/SAU/UI0617/2011. The authors received no compensation related to the develop-

ment of the manuscript. The FCT supported the authors Oliveira, N.L. (grant no. SFRH/BD/48875/2008) and Ribeiro, F. (grant no. SFRH/BPD/69965/2010). The authors are solely responsible for study design, conduct and analyses, and drafting and editing the final manuscript.

Results Intention-to-treat analysis From 256 patients assessed for eligibility, 96 were recruited and agreed to participate in the study being randomized to the EG or CG (Figure 2). After the baseline assessments, 2 patients dropped out of each group; therefore, they were not included in the data analysis. However, comparisons between patients who dropped out and those who completed the study revealed no

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significant differences in their baseline values (P N .05 for all). In the remaining patients (n = 92), the only difference in baseline values between EG (n = 47) and CG (n = 45) was the proportion of patients using nitrate medication (χ 2 = 4.35, P = .037), in favor of EG (Table I). Therefore, between-groups comparisons were adjusted using nitrates as a covariate for those variables where biological plausibility existed, as indicated in Tables II and III. The mean attendance of the EG at exercise sessions was 18.9 ± 7.3 sessions. Table II shows the changes in anthropometrics, resting hemodynamic, cardiorespiratory fitness, and autonomic function for both groups. No significant treatment × time interaction was found in the traditional (time and frequency domain) and nonlinear HRV indexes (primary outcome) or in the diastolic blood pressure, resting heart rate, and waist circumference (P N .05). The VO2peak increased in the EG (2.11 ± 3.92 mL/kg per minute) and remained unchanged in the CG (−0.07 ± 2.65 mL/kg per minute) (treatment × time interaction: η 2p = 0.11). This improvement in VO2peak was confirmed by the significant mean difference between groups at the final assessment. A significant treatment × time interaction was observed on body mass (η 2p = 0.04), BMI (η 2p = 0.04), fat percentage (η 2p = 0.04), and systolic blood pressure (η 2p = 0.06). However, there were no significant mean differences between groups (P N 0.05) in these variables at final assessment. Table III shows the data for daily PA, which were available for 32 patients on the EG and 39 patients on the CG. Missing data stemmed from nonuse of accelerometers. A significant treatment × time interaction was observed in sedentary activity (η 2p = 0.06), but no difference was found between groups in the final assessment (P N .05). There were no significant changes in the time spent at light and moderate to vigorous intensities. Regarding dietary intake, 39 patients in the EG and 45 patients in the CG provided complete data (Table IV). No significant changes in nutrient intakes were observed between groups.

Per-protocol analysis Because the benefits of exercise training on several outcomes appear to be dose dependent, 22 we performed a per-protocol analysis excluding those patients who did not perform the exercise training (n = 5), did not attend at least to 80% of the exercise sessions (n = 3), and changed the medication (n = 1) during the study period (Figure 2). The results were similar to those observed in the intention-to-treat analysis for most variables (Supplementary Tables I-IV), but with an additional significant treatment × time interaction for waist circumference (change [centimeters]: EG [−1.38 ± 3.48] vs CG [0.17 ± 3.28], P = .040, η 2p = 0.05). However, for that variable, the between-groups comparisons of the final assessment did not show any significant difference (P N .05) (Supplementary Table II). No adverse events were

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Table I. Baseline demographic and clinical characteristics Exercise group (n = 47) Age (y) Sex (male) Family history Diabetes mellitus Hypertension Currently smoking Hyperlipidemia Overweight/obesity LVEF (%) Site of infarction (anterior) No. of coronary vessels involved 1 vessel 2 vessels No. of infarctions First Second PTCA Days hospitalized Antiplatelets ACE inhibitors β-Blockers Lipid-lowering drugs Nitrates ARBs Diuretics Calcium-channel blockers Fasting glucose (mg/dL) Total cholesterol (mg/dL) HDL cholesterol (mg/dL) LDL cholesterol (mg/dL) Triglycerides (mg/dL)

54.8 40 10 8 43 22 47 33 52.8 22

Control group (n = 45)

(10.6) (85.1%) (21.3%) (17.0%) (91.5%) (46.8%) (100%) (70.2%) (9.5) (46.8%)

58.6 (10.7) 37 (82.2%) 6 (13.3%) 14 (31.1%) 44 (97.8%) 22 (48.9%) 45 (100%) 36 (80.0%) 54.5 (7.4) 15 (33.3%)

37 (78.7%) 10 (21.3%)

37 (82.2%) 8 (17.8%)

43 4 44 5.2 47 43 43 42 10 2 3 1 91.2 132.3 38.2 71.8 112.9

(91.5%) (8.5%) (93.6%) (3.5) (100%) (91.5%) (91.5%) (89.4%) (21.3%)⁎ (4.3%) (6.4%) (2.1%) (13.8) (26.9) (7.4) (20.7) (48.7)

37 (82.2%) 8 (17.8%) 39 (86.7%) 4.1 (1.6) 45 (100%) 42 (93.3%) 45 (100%) 41 (91.1%) 2 (4.4%) 4 (8.9%) 4 (8.9%) 98.6 (23.0) 138.1 (31.4) 38.9 (6.4) 75.0 (26.5) 121.0 (45.4)

Data are expressed as mean (SD) or n (%). Criteria for diabetes are based on fasting blood glucose level N125 mg/dL or current treatment with insulin or oral antidiabetic agents; hypertension, based on seated blood pressure N140/90 mm Hg or antihypertensive treatment; overweight, based on BMI ≥25 b30 kg/m2; obesity, based on BMI ≥30 kg/m2; and hyperlipidemia, based on fasting total cholesterol N175 mg/dL or use of antilipidemic medication. Abbreviations ACE, angiotensinconverting enzyme; ARB, angiotensin II receptor blocker; HDL, high-density lipoprotein; LDL, low-density lipoprotein; LVEF, left ventricular ejection fraction; PTCA, percutaneous transluminal coronary angioplasty. ⁎ Significantly different from control group, P b .05.

registered during the exercise-based cardiac rehabilitation program.

Discussion The main finding of this RCT was that there were no changes in HRV indexes in response to exercise training, despite significant changes in VO2peak in the EG. This RCT is the first one where important methodological issues were taken into account. A previous study showed that respiratory rate influences the R-R intervals or heart rate fluctuations. 10 Therefore, breathing frequency control is essential to guarantee equal evaluation conditions across the study measurements. In addition, previous studies showed that lifestyle factors such as habitual PA 11 and dietary intake 12 are associated with changes in HRV

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Table II. Changes in anthropometrics, resting hemodynamic, cardiorespiratory fitness, and autonomic function Exercise group (n = 47) Baseline mean (SD) Anthropometrics Height (cm) Body mass (kg) BMI (kg/m2) Fat percentage (%) Waist circumference (cm) Resting hemodynamic⁎

VO2peak (ml.kg -1.min -1) Autonomic function—HRV⁎ Mean RR (ms) SDNN (ms) RMSSD (ms) ln LF ln HF LF/HF Short-term fractal scaling exponent (DFA1) Sample entropy

Baseline mean (SD)

Difference (95% CI) at final assessment

Final mean (SD)

Pa

(7.2) (10.7) (3.3) (6.6) (8.5)

– 75.2 (11.1) 27.6 (3.5) 28.7 (7.0) 96.9 (8.7)

– .046 .046 .042 .086

– 0.001 (−0.06 −0.03 (−0.09 −2.61 (−5.46 −2.17 (−5.94

to 0.06) to 0.02) to 0.24) to 1.60)

– .979 .228 .072 .256

Pb

(8.8) (10.2) (3.6) (6.4) (8.7)

– 75.2 (10.3) 26.7 (3.7) 26.1 (6.8) 94.7 (9.4)

126.5 (19.8) 72.1 (9.1) 56.9 (8.4)

125.7 (17.2) 71.0 (7.5) 55.8 (7.6)

132.7 (16.8) 74.1 (8.7) 58.0 (8.1)

129.2 (14.5) 72.8 (7.4) 58.8 (8.8)

.016 .346 .171

−0.03 (−0.08 to 0.02) −1.88 (−5.09 to 1.32) −2.72 (−6.23 to 0.79)

.242 .247 .127

27.6 (7.3)

29.7 (8.8)

26.9 (5.6)

26.8 (6.1)

.001

3.70 (0.50 to 6.91)

.024

168.0 76.0 27.0 26.5 95.8

Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Resting heart rate (beats/min) Cardiorespiratory fitness⁎

Final mean (SD)

Control group (n = 45)

1038.1 32.6 36.5 5.4 5.7 1.0 0.9

(150.6) (24.9) (29.2) (1.3) (1.5) (0.9) (0.3)

1052.9 37.0 40.6 5.7 5.9 1.0 0.9

1.5 (0.4)

(145.7) (23.4) (27.0) (1.4) (1.3) (0.7) (0.3)

1.4 (0.4)

165.1 75.0 27.5 28.2 96.7

1001.6 35.0 37.8 5.3 5.5 1.1 0.9

(135.2) (33.1) (33.6) (1.6) (1.6) (0.9) (0.3)

1.4 (0.5)

1008.2 32.8 34.9 5.2 5.5 1.2 1.0

(145.3) (26.0) (29.6) (1.6) (1.5) (1.2) (0.3)

1.3 (0.4)

.711 .369 .321 .462 .532 .992 .440

36.23 0.23 0.24 0.55 0.47 −0.01 −0.01

.710

(−25.99 to 98.44) (−0.05 to 0.52) (−0.06 to 0.55) (−0.08 to 1.19) (−0.13 to 1.08) (−0.18 to 0.17) (−0.13 to 0.11)

0.07 (−0.11 to 0.25)

.250 .106 .109 .087 .124 .929 .900 .440

Abbreviations: Mean RR, Mean RR intervals; MET, metabolic equivalent; ln, natural logarithm. Positive and negative differences are in favor of the exercise group. Pa for treatment × time interaction with repeated-measures ANOVA. Pb for univariate general linear model. ⁎ Analysis of these variables was adjusted for nitrate medication.

Table III. Changes in daily PA Exercise group (n = 32)

Control group (n = 39)

Baseline mean (SD) Final mean (SD) Baseline mean (SD) Final mean (SD) Daily PA⁎ Total PA (counts/min) Sedentary (min/d) Light (min/d) MVPA (min/d)

426.6 398.7 295.7 38.2

(221.2) (82.1) (77.5) (32.3)

479.3 372.0 278.2 43.0

(262.9) (66.2) (93.2) (32.3)

407.4 379.5 286.9 38.0

(155.1) (68.5) (81.1) (26.1)

402.9 382.5 297.2 35.7

(162.8) (85.6) (104.9) (24.7)

Pa

Difference (95% CI) at final assessment

.056 1.74 (−0.65 to .040 −0.34 (−1.33 to .106 −0.48 (−1.88 to .301 0.46 (−0.72 to

4.14) 0.65) 0.93) 1.64)

Pb

.151 .499 .501 .442

Abbreviation: MVPA, moderate to vigorous PA. Positive and negative differences are in favor of the exercise group. Pa for treatment × time interaction with repeated-measures ANOVA. Pb for univariate general linear model. ⁎ Analysis of these variables was adjusted for nitrate medication.

indexes. In this study, at baseline, the levels of moderate to vigorous PA and several components of dietary intake were already in the current recommendations 23,24 and did not change after 8 weeks for either group. Collectively, these data ensure that none of these methodological issues biased the results of HRV. The results of this study indicate that a short-term, exercise-based cardiac rehabilitation program is not effective for improving cardiac autonomic modulation. In fact, other RCTs reported such negative findings 8,25-29 despite the differences in the sample size (12-26

participants), the length of the intervention (2-24 weeks), and the amount of exercise performed, which was higher than our in at least 1 study. 25 There are also RCTs reporting improvements on the traditional HRV indexes. 9,30-32 However, these studies used a higher total amount of exercise and/or training load than this study, as for example, a longer program duration, 32 a higher intensity, 32 an additional home-based program, 30 and higher training frequency 31 in addition to including coronary artery disease patients with different clinical presentations (ie, angina pectoris, coronary artery bypass

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Table IV. Changes in dietary intake Exercise group (n = 39) Baseline mean (SD) Dietary intake Energy (kcal) Carbohydrates (g) Protein (g) Total fat (g) Saturated fat (g) Monounsaturated fat (g) Polyunsaturated fat (g) Cholesterol (mg) n-3 fatty acid (g) n-6 fatty acid (g) Total fiber (g) Calcium (mg) Sodium (g)

1626.3 187.6 83.1 50.3 12.4 19.1 8.9 208.9 0.6 7.4 14.9 717.7 1.4

(357.8) (46.2) (19.7) (19.4) (5.3) (6.9) (6.7) (69.1) (0.5) (6.6) (5.3) (287.4) (0.5)

Final mean (SD)

1572.2 (363.4) 172.1 (36.6) 80.5 (20.6) 49.1 (18.0) 13.0 (7.1) 18.3 (5.6) 8.5 (5.8) 209.0 (64.0) 0.6 (0.5) 6.9 (5.5) 13.5 (4.8) 661.4 (258.3) 1.6 (1.0)

Control group (n = 45) Baseline mean (SD)

1670.1 192.6 84.4 50.3 12.9 20.4 7.4 212.7 0.6 5.9 14.9 782.5 1.4

(484.6) (58.3) (26.6) (22.7) (9.0) (9.4) (2.8) (87.6) (0.5) (2.6) (5.6) (476.5) (0.6)

Final mean (SD)

1551.3 174.7 78.5 46.7 11.8 18.0 7.1 209.1 0.5 5.6 13.8 681.5 1.4

(389.4) (43.6) (18.8) (16.4) (6.4) (6.5) (2.8) (65.3) (0.3) (2.8) (5.2) (282.3) (0.5)

Pa

.409 .790 .481 .746 .548 .337 .995 .828 .791 .898 .734 .514 .586

Difference (95% CI) at final assessment

20.93 −0.01 1.99 0.05 0.16 0.04 0.09 −0.11 0.01 0.18 −0.31 −20.04 0.03

(−143.39 to 185.24) (−0.11 to 0.09) (−6.58 to 10.56) (−0.10 to 0.21) (−0.23 to 0.54) (−0.12 to 0.19) (−0.12 to 0.29) (−28.25 to 28.03) (−0.09 to 0.12) (−0.12 to 0.48) (−2.50 to 1.89) (−138.18 to 98.10) (−0.16 to 0.22)

Pb

.801 .875 .646 .501 .421 .614 .394 .994 .811 .242 .782 .737 .791

Positive and negative differences are in favor of the exercise group. Pa for treatment × time interaction with repeated-measures ANOVA. Pb for univariate general linear model.

graft, percutaneous transluminal coronary angioplasty). 26,31,32 Given the differences between studies on the interventions and population characteristics, it is difficult to justify similarities or dissimilarities in the sense of results. Possible explanations for the lack of changes in HRV could be related to the baseline values, which were higher than those reported in other studies. 30-32 It is conceivable that the high values of HRV at baseline in our sample might have limited the magnitude of change in the cardiac autonomic modulation in the EG. Furthermore, β-blockers and angiotensin-converting enzyme inhibitors have a positive influence on HRV. 7,33 Because most patients in this study were pharmacologically treated with these drugs before the beginning of the study, it may be possible that the HRV had improved in response to medication, and consequently, the exercise training program did not have any additional effect. This assumption agrees with the conclusion of a systematic review. 21 Another possible explanation for the higher mean values at baseline is the fact of a considerable amount of patients in our sample underwent coronary angioplasty before the exercise intervention, and this procedure was previously showed to improve cardiac autonomic function. 21,34 To best of our knowledge, there is only 1 study with coronary artery disease patients investigating the effects of exercise training on the nonlinear HRV indexes. 35 The authors compared two exercise training programs with different intensities (moderate vs high intensity) and reported no changes in HRV, despite significant improvements on VO2peak, which is in line with our findings. Although these indexes present a highest predictive value and the better representation of a higher number of

factors involved in the regulation of heart rate, 6 our explanation for the lack of changes in response to exercise is the same as that for traditional indexes. Cardiorespiratory fitness (VO2peak) improved with exercise training. The mean change in the EG (2.1 mL/ kg per minute in the intention-to-treat analysis and 2.8 mL/kg per minute in the per-protocol analysis) is consistent with that reported (2.6 ± 1.6 mL/kg per minute) by a recent systematic review and meta-analysis. 36 This is an important finding because higher cardiorespiratory fitness levels are related to a decreased risk of all-cause mortality and improvements in survival. 37 Although the final mean values of systolic blood pressure are not significantly different between the groups, the reduction observed in the CG and not in the EG deserves a comment. Indeed, both groups were under pharmacological treatment with antihypertensive drugs. In addition, the mean value at baseline of systolic blood pressure in the CG was within the high normal category of blood pressure (130-139 mm Hg), whereas the mean value of the EG was within the normal category (120-129 mm Hg). 38 Therefore, it is plausible that medication had an effect in the more elevated systolic blood pressure of the CG, with more “room” for improvement than the EG. In addition, at baseline, the EG was in the normal category, and therefore, it is conceivable that the exercise program length or intensity—or both—is insufficient to induce further improvements. The limitations of this study should be discussed. On average, our sample consisted of patients that presented at baseline good levels of HRV, cardiorespiratory fitness, blood pressure, habitual PA, and dietary intake. Therefore, the results of this study should not be generalized to

8 Oliveira et al

patients with a more debilitated clinical condition. Another limitation was the number of participants randomized to the exercise-based cardiac rehabilitation program that did not perform it or attended b80% of the exercise sessions (8/47 participants). The reason most often given by patients for not accomplishing the exercise sessions was the economic costs of transportation to the hospital and/or difficulties coping with professional duties. An additional limitation is the missing data on habitual PA and dietary intake. Nevertheless, a representative number of patients (EG = 68% and CG = 86%) provided data on PA and a substantial amount of patients (EG = 83% and CG = 100%) on dietary intake. In conclusion, our results reveal that, in post-MI patients under optimal medication and with high levels of HRV at baseline, a short-term exercise-based cardiac rehabilitation program is not effective in adding benefits in cardiac autonomic function. In contrast, even with high baseline VO2peak levels, this program was effective for increasing cardiorespiratory fitness, which is beneficial because it is associated with a lower risk of all-cause mortality in this population.

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12. Mozaffarian D, Stein PK, Prineas RJ, et al. Dietary fish and omega-3 fatty acid consumption and heart rate variability in US adults. Circulation 2008;117(9):1130-7. 13. Rubart M, Zipes DP. Mechanisms of sudden cardiac death. J Clin Invest 2005;115(9):2305-15. 14. Nunan D, Donovan G, Jakovljevic DG, et al. Validity and reliability of short-term heart-rate variability from the Polar S810. Med Sci Sports Exerc 2009;41(1):243-50. 15. Tarvainen MP, Ranta-Aho PO, Karjalainen PA. An advanced detrending method with application to HRV analysis. IEEE Trans Biomed Eng 2002;49(2):172-5. 16. Martinmaki K, Rusko H, Kooistra L, et al. Intraindividual validation of heart rate variability indexes to measure vagal effects on hearts. Am J Physiol Heart Circ Physiol 2006;290(2):H640-7. 17. Malik M, Bigger JT, Camm AJ, et al. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Eur Heart J 1996;17(3):354-81. 18. Porta A, Tobaldini E, Guzzetti S, et al. Assessment of cardiac autonomic modulation during graded head-up tilt by symbolic analysis of heart rate variability. Am J Physiol Heart Circ Physiol 2007;293(1):H702-8. 19. Goldberger AL, Amaral LA, Hausdorff JM, et al. Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci U S A 2002;99(Suppl 1):2466-72. 20. Troiano RP, Berrigan D, Dodd KW, et al. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008;40(1):181-8. 21. Nolan RP, Jong P, Barry-Bianchi SM, et al. Effects of drug, biobehavioral and exercise therapies on heart rate variability in coronary artery disease: a systematic review. Eur J Cardiovasc Prev Rehabil 2008;15(4):386-96. 22. Hammill BG, Curtis LH, Schulman KA, et al. Relationship between cardiac rehabilitation and long-term risks of death and myocardial infarction among elderly Medicare beneficiaries. Circulation 2010; 121(1):63-70. 23. Smith Jr SC, Benjamin EJ, Bonow RO, et al. AHA/ACCF Secondary Prevention and Risk Reduction Therapy for Patients with Coronary and other Atherosclerotic Vascular Disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation. Circulation 2011;124(22): 2458-73. 24. Lichtenstein AH, Appel LJ, Brands M, et al. Diet and lifestyle recommendations revision 2006: a scientific statement from the American Heart Association Nutrition Committee. Circulation 2006; 114(1):82-96. 25. Duru F, Candinas R, Dziekan G, et al. Effect of exercise training on heart rate variability in patients with new-onset left ventricular dysfunction after myocardial infarction. Am Heart J 2000;140(1): 157-61. 26. Takeyama J, Itoh H, Kato M, et al. Effects of physical training on the recovery of the autonomic nervous activity during exercise after coronary artery bypass grafting: effects of physical training after CABG. Jpn Circ J 2000;64(11):809-13. 27. Oya M, Itoh H, Kato K, et al. Effects of exercise training on the recovery of the autonomic nervous system and exercise capacity after acute myocardial infarction. Jpn Circ J 1999;63(11): 843-8. 28. Leitch JW, Newling RP, Basta M, et al. Randomized trial of a hospital-based exercise training program after acute myocardial infarction: cardiac autonomic effects. J Am Coll Cardiol 1997; 29(6):1263-8.

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29. Mazzuero G, Lanfranchi P, Colombo R, et al. Long-term adaptation of 24-h heart rate variability after myocardial infarction. Chest 1992; 101(5_Supplement):304S-8S. 30. Tsai M-W, Chie W-C, Kuo TB, et al. Effects of exercise training on heart rate variability after coronary angioplasty. Phys Ther 2006; 86(5):626-35. 31. Iellamo F, Legramante JM, Massaro M, et al. Effects of a residential exercise training on baroreflex sensitivity and heart rate variability in patients with coronary artery disease: a randomized, controlled study. Circulation 2000;102(21):2588-92. 32. Stahle A, Nordlander R, Bergfeldt L. Aerobic group training improves exercise capacity and heart rate variability in elderly patients with a recent coronary event. A randomized controlled study. Eur Heart J 1999;20(22):1638-46. 33. Binkley PF, Haas GJ, Starling RC, et al. Sustained augmentation of parasympathetic tone with angiotensin-converting enzyme inhibition in patients with congestive heart failure. J Am Coll Cardiol 1993; 21(3):655-61. 34. Malfatto G, Blengino S, Annoni L, et al. Original articles primary coronary angioplasty and subsequent cardiovascular rehabilitation

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are linked to a favorable sympathovagal balance after a first anterior myocardial infarction. Ital Heart J 2005;6(1):21-7. Currie KD, Rosen LM, Millar PJ, et al. Heart rate recovery and heart rate variability are unchanged in patients with coronary artery disease following 12 weeks of high-intensity interval and moderateintensity endurance exercise training. Appl Physiol Nutr Metab 2013; 38(6):644-50. Valkeinen H, Aaltonen S, Kujala UM. Effects of exercise training on oxygen uptake in coronary heart disease: a systematic review and meta-analysis. Scand J Med Sci Sports 2010;20(4): 545-55. Myers J, Prakash M, Froelicher V, et al. Exercise capacity and mortality among men referred for exercise testing. N Engl J Med 2002;346(11):793-801. Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Bohm M, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J 2013;34(28): 2159-219.

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Appendix. Supplementary data Supplementary Table I. Baseline demographic and clinical characteristics (per-protocol analysis) Exercise group (n = 39) Age (ye) Sex (male) Family history Diabetes mellitus Hypertension Currently smoking Hyperlipidemia Overweight/obesity LVEF (%) Site of infarction (anterior) No. of coronary vessels involved 1 vessel 2 vessels No. of infarctions First Second PTCA Days hospitalized Antiplatelets ACE inhibitors β-Blockers Lipid-lowering drugs Nitrates ARBs Diuretics Calcium-channel blockers Fasting glucose (mg/dL) Total cholesterol (mg/dL) HDL cholesterol (mg/dL) LDL cholesterol (mg/dL) Triglycerides (mg/dL)

54.6 33 10 6 36 19 39 28 52.9 16

(11.2) (84.6%) (25.6%) (15.4%) (92.3%) (48.7%) (100%) (71.8%) (8.9) (41.0%)

31 (79.5%) 8 (20.5%) 37 (94.9%) 2 (5.1%) 36 (92.3%) 5.3 (3.8) 39 (100%) 36 (92.3%) 36 (92.3%) 36 (92.3%) 9 (23.1%)⁎ 2 (5.1%) 1 (2.6%) – 91.1 (13.8) 131.9 (28.2) 38.4 (7.7) 71.9 (21.4) 109.4 (51.7)

Control group (n = 44) 59.0 36 6 14 43 22 44 35 54.5 15

(10.6) (81.8%) (13.6%) (31.8%) (97.7%) (50.0%) (100%) (79.5%) (7.4) (34.1%)

36 (81.8%) 8 (18.2%) 36 (81.8%) 8 (18.2%) 38 (86.4%) 4.1 (1.6) 44 (100%) 41 (93.2%) 44 (100%) 40 (90.9%) 2 (4.5%) – 4 (9.1%) 3 (6.8%) 98.8 (23.2) 138.6 (31.6) 39.0 (6.4) 75.4 (26.7) 120.8 (45.9)

Data are expressed as mean (SD) or n (%). Criteria for diabetes are based on fasting blood glucose level N125 mg/dL or current treatment with insulin or oral antidiabetic agents; hypertension, based on seated blood pressure N140/90 mm Hg or antihypertensive treatment; overweight, based on BMI ≥25 b30 kg/m2; obesity, based on BMI ≥30 kg/m2; hyperlipidemia, based on fasting total cholesterol N175 mg/dL or use of antilipidemic medication. Abbreviations: ACE, Angiotensin-converting enzyme; ARB, angiotensin II receptor blocker; HDL, high-density lipoprotein; LDL, low-density lipoprotein; LVEF, left ventricular ejection fraction; PTCA, percutaneous transluminal coronary angioplasty. ⁎ Significantly different from control group, P b .05.

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Oliveira et al 9.e2

Supplementary Table II. Changes in anthropometrics, resting hemodynamic, cardiorespiratory fitness, and autonomic function (per-protocol analysis) Exercise group (n = 39) Baseline mean (SD) Anthropometrics Height (cm) Body mass (kg) BMI (kg/m2) Fat percentage (%) Waist circumference (cm) Resting hemodynamic⁎

167.2 75.4 27.0 26.3 95.3

Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Resting heart rate (beats/min) Cardiorespiratory fitness⁎ VO2peak (mL/kg/min) Autonomic function—HRV⁎ Mean RR (ms) SDNN (ms) RMSSD (ms) ln LF ln HF LF/HF Short-term fractal scaling exponent (DFA1) Sample entropy

Final mean (SD)

– 74.3 (9.8) 26.6 (3.6) 25.9 (6.8) 93.9 (9.0)

(8.7) (10.1) (3.5) (6.4) (8.6)

Control group (n = 44) Baseline mean (SD)

165.3 75.0 27.4 28.2 96.7

Difference (95% CI) at final assessment

Final mean (SD)

Pa

(7.3) (10.8) (3.4) (6.7) (8.6)

– 75.3 (11.2) 27.5 (3.5) 28.8 (7.0) 96.9 (8.8)

– .019 .019 .037 .040

– −0.01 (−0.07 −0.03 (−0.09 −2.92 (−5.96 −2.99 (−6.88

to 0.05) to 0.02) to 0.11) to 0.90)

– .703 .223 .058 .130

Pb

126.3 (20.8) 72.0 (9.3) 56.3 (7.8)

125.0 (18.1) 70.7 (8.1) 54.9 (6.6)

132.5 (16.9) 73.9 (8.6) 58.2 (8.1)

129.2 (14.7) 72.7 (7.4) 59.2 (8.5)

.044 .494 .739

−0.04 (−0.10 to 0.02) −2.02 (−5.56 to 1.52) −3.65 (−7.13 to 0.16)

.172 .260 .051

28.0 (7.4)

30.8 (8.7)

26.7 (5.6)

26.5 (5.8)

b.001

5.11 (1.84 to 8.38)

.003

999.8 (135.7) 32.5 (26.2) 34.3 (29.6) 5.2 (1.6) 5.5 (1.5) 1.2 (1.2) 1.0 (0.3)

.328 .382 .316 .345 .587 .502 .441

1.3 (0.4)

.854

1041.9 33.1 36.8 5.4 5.8 0.9 0.9

(144.9) (26.3) (30.3) (1.3) (1.5) (0.7) (0.3)

1067.9 37.6 42.1 5.8 6.0 1.0 0.9

1.5 (0.4)

(136.6) (23.6) (28.4) (1.4) (1.3) (0.8) (0.2)

1.4 (0.4)

998.8 35.0 37.7 5.3 5.5 1.1 0.9

(135.4) (33.5) (34.0) (1.6) (1.6) (0.9) (0.3)

1.4 (0.5)

54.15 0.26 0.28 0.68 0.55 0.02 −0.02

(−7.12 to 115.42) (−0.05 to 0.57) (−0.05 to 0.61) (0.00 to 1.36) (−0.10 to 1.20) (−0.17 to 0.21) (−0.14 to 0.11)

0.09 (−0.10 to 0.28)

.082 .103 .091 .052 .094 .841 .780 .327

Abbreviations: Mean RR, Mean RR intervals; MET, metabolic equivalent; ln, natural logarithm. Positive and negative differences are in favor of the exercise group. Pa for treatment × time interaction with repeated-measures ANOVA. Pb for univariate general linear model. ⁎ Analysis of these variables was adjusted for nitrate medication.

Supplementary Table III. Changes in daily PA (per-protocol analysis) Exercise group (n = 27)

Control group (n = 38)

Baseline mean (SD) Final mean (SD) Baseline mean (SD) Final mean (SD) Daily PA⁎ Total PA (counts/min) Sedentary (min/d) Light (min/d) MVPA (min/d)

427.5 402.5 290.3 39.6

(233.1) (87.4) (60.5) (33.3)

478.1 371.3 273.0 43.1

(256.2) (66.5) (75.3) (29.7)

Abbreviation: MVPA, Moderate to vigorous PA. Positive and negative differences are in favor of the exercise group. Pa for treatment × time interaction with repeated-measures ANOVA. Pb for univariate general linear model. ⁎ Analysis of these variables was adjusted for nitrate medication.

400.6 383.6 281.8 37.6

(151.1) (64.5) (75.7) (26.4)

396.0 385.5 288.9 34.9

(159.1) (84.6) (92.2) (24.5)

Pa

Difference (95% CI) at final assessment

.067 1.95 (−0.56 to .028 −0.47 (−1.53 to .175 −0.38 (−1.71 to .460 0.60 (−0.63 to

4.46) 0.60) 0.95) 1.83)

Pb

.125 .385 .569 .331

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Supplementary Table IV. Changes in dietary intake (per-protocol analysis) Exercise group (n = 34)

Dietary intake Energy (kcal) Carbohydrates (g) Protein (g) Total fat (g) Saturated fat (g) Monounsaturated fat (g) Polyunsaturated fat (g) Cholesterol (mg) n-3 fatty acid (g) n-6 fatty acid (g) Total fiber (g) Calcium (mg) Sodium (g)

Control group (n = 44)

Baseline mean (SD)

Final mean (SD)

Baseline mean (SD)

Final mean (SD)

Pa

1626.5 (372.6) 188.2 (48.0) 81.4 (19.2) 50.6 (20.4) 12.7 (5.5) 19.1 (7.2) 8.9 (7.1) 204.3 (70.7) 0.6 (0.5) 7.5 (7.0) 15.0 (5.2) 729.5 (305.9) 1.4 (0.5)

1586.1 (376.3) 173.3 (36.1) 80.1 (20.6) 49.9 (18.7) 13.4 (7.3) 18.5 (5.8) 8.7 (6.2) 203.7 (64.5) 0.6 (0.4) 7.1 (5.9) 13.4 (4.8) 666.2 (261.9) 1.6 (1.0)

1673.2 (489.7) 193.2 (58.8) 84.5 (27.0) 50.3 (22.9) 13.0 (9.1) 20.5 (9.6) 7.4 (2.8) 213.0 (88.6) 0.6 (0.6) 5.9 (2.7) 14.9 (5.7) 779.4 (481.6) 1.4 (0.6)

1558.5 (390.8) 175.6 (43.6) 78.7 (19.0) 46.9 (16.5) 12.0 (6.5) 18.0 (6.5) 7.2 (2.8) 209.5 (66.0) 0.5 (0.3) 5.6 (2.7) 13.9 (5.2) 680.3 (285.5) 1.4 (0.5)

.378 .741 .362 .692 .501 .294 .998 .871 .854 .888 .629 .623 .549

Positive and negative differences are in favor of the exercise group. Pa for treatment × time interaction with repeated-measures ANOVA. Pb for univariate general linear model.

Difference (95% CI) at final assessment

27.53 −0.01 1.45 0.06 0.20 0.05 0.08 −5.79 0.002 0.18 −0.52 −14.14 0.04

(−147.36 to 202.41) (−0.11 to 0.10) (−7.51 to 10.40) (−0.10 to 0.23) (−0.20 to 0.60) (−0.12 to 0.21) (−0.13 to 0.30) (−35.51 to 23.92) (−0.11 to 0.11) (−0.14 to 0.51) (−2.80 to 1.77) (−139.42 to 111.13) (−0.16 to 0.24)

Pb

.755 .921 .748 .468 .332 .565 .453 .699 .975 .261 .653 .823 .690