International Journal of Cardiology 181 (2015) 155–159
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International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Exercise cardiac power and the risk of sudden cardiac death in a long-term prospective study Sudhir Kurl a,b,⁎,1, Sae Young Jae c,1, Jussi Kauhanen a,1, Kimmo Ronkainen a,1, Rainer Rauramaa d,1, Jari A. Laukkanen a,b,1 a
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio. Finland Lapland Central Hospital, Rovaniemi, Finland Department of Sports Informatics, College of Arts and Physical Education, University of Seoul, South Korea d Kuopio Research Institute of Exercise Medicine Kuopio, University of Eastern Finland, Kuopio. Finland b c
a r t i c l e
i n f o
Article history: Received 22 October 2014 Accepted 1 December 2014 Available online 3 December 2014 Keywords: Exercise cardiac power Sudden cardiac death Prevention Risk factors
a b s t r a c t Background: Little is known about exercise cardiac power and the risk of sudden cardiac death. The aim of this study was to examine the relationship of exercise cardiac power (ECP), defined as a ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise, with the risk for sudden cardiac death (SCD). Methods: This prospective study was based on 2358 men who participated in exercise stress test at baseline. During an average follow-up of 20 years 205 SCDs occurred. Results: Men with ECP (b 8.2 mL/mm Hg, lowest quartile) had a 4.6-fold (95% CI 2.8–7.5, p b 0.001) increased risk of SCD as compared to with ECP in the highest quartile (N12.8 mL/mm Hg) after adjusting for age and examination years. Men with low ECP (b 8.2 mL/mm Hg) had markedly increased risk of SCD (RR 3.9, 95% CI 2.19–7.14, p b 0.001) after adjustment for conventional risk factors and left ventricular hypertrophy, whereas for progressive adjustment for resting systolic blood pressure, the respective risk among men with lowest ECP was 2.5 (95% CI 1.46– 4.22, p b 0.001). After adding ECP in the multivariate model, the Harrell C-index increased from 0.760 to 0.778 showing the significant incremental value of ECP in predicting SCD. The integrated discrimination improvement was 0.014 (p = 0.004). Conclusions: Low ECP provides a non-invasive and easily available measure for the prediction of SCD and may help in identifying men with high risk for SCD. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Sudden cardiac arrest accounts for one half of all deaths related to coronary heart disease (CHD) and presents as the first manifestation of CHD in about 20% to 30% of the deaths [1–3]. It is suggested that one of the most important risk markers yielded by the exercise test is the measure of exercise capacity [4–7]. Previous population-based studies have looked at the ability of indirectly defined functional capacity to predict total mortality and other cardiovascular events [8–11]. Cardiorespiratory fitness (CRF), when measured directly during exercise, has been shown to have a strong inverse relation to the CHD risk factors [5–7] and sudden cardiac death (SCD) [8]. It has been proposed that measurement of CRF should be included when clinical decisions are being made in patients referred for evaluation of cardiovascular diseases (CVDs). Although CRF is the most accurate indicator of exercise capacity,
⁎ Corresponding author at: Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, P.O. 1627, 70211 Kuopio, Finland. E-mail address: sudhir.kurl@uef.fi (S. Kurl). 1 All the authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
http://dx.doi.org/10.1016/j.ijcard.2014.12.023 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
it does not take into account the differences in cardiovascular resistance and cardiac afterload. A previous study has shown that resting systolic blood pressure (SBP) is a risk factor for SCD [12], whereas both resting SBP and exercise-induced elevation of SBP have been found to be an independent predictor of stroke [9], hypertension [10–14], CHD [15,16] and CVD [17–19]. As exercise cardiac power (ECP) is a function of CRF (VO2max) and peripheral resistance (indicated by SBP) [20], we hypothesized that ECP may provide valuable information in SCD risk stratification. Thus the aim of this study was to investigate the association of ECP during exercise with the risk of SCD in a population based sample of men. 2. Methods 2.1. Subjects Subjects were participants in the Kuopio Ischaemic Heart Disease Risk Factor Study which is a prospective population based study designed to investigate risk factors for CVD, carotid atherosclerosis and related outcomes in a population-based, randomly selected sample of men from eastern Finland [20]. Of the 3433 men aged 42, 48, 54 or 60 who resided in the town of Kuopio or its surrounding rural communities, 198 were excluded because of death, serious disease or migration away from the area. At baseline, examinations were conducted on 2682 men (82.9% of the potential eligible) between March
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1984 and December 1989. The Kuopio ischemic Heart Disease study was approved by the Research Ethics Committee of the University of Kuopio, and each participant gave written informed consent. Complete data on ECP was available on 2358 subjects at baseline in this study. 2.2. Assessment of exercise cardiac power A maximal symptom-limited exercise tolerance test was performed between 8:00 AM and 10:00 AM using an electrically braked cycle ergometer [4]. The standardized testing protocol comprised of an increase in the workload of 20 W/min with the direct analyses of respiratory gases (Medical Graphics, St. Paul, Minnesota). The VO2max was defined as the highest value for or the plateau of oxygen uptake. Blood pressure was measured manually when the exercise test was started and blood pressure was measured every 2 min during the exercise test. The peak SBP was the highest value achieved during the test. The ratio of measured VO2max with peak SBP was defined as ECP [20]. For safety reasons, all tests were supervised by an experienced physician with the assistance of an experienced nurse. Electrocardiography (ECG) was recorded continuously with the Kone 620 electrocardiograph (Kone, Turku, Finland) [8,9]. 2.3. Assessment of other covariates Resting blood pressures was obtained using a random-zero sphygmomanometer after 5 and 10 min of rest in the seated position. The mean of these two values was used as the resting blood pressure. Body mass index was computed as the ratio of weight in kilograms to the square of height in meters. Information on use of medications and diagnosis of diseases was collected at baseline examination by an internist [4]. Alcohol consumption was assessed with the use of the Nordic Alcohol Consumption Inventory [4]. The collection of blood specimens and the measurement of serum lipids, lipoproteins, and insulin, and the definition of type 2 diabetes have been described elsewhere [8,9]. Serum C-reactive protein (CRP) was measured with an immunometric assay (Immulite High Sensitivity Creactive protein Assay, DPC, Los Angeles, CA, U.S.A.).
3. Results 3.1. Baseline characteristics In the beginning of the follow-up, the mean age of the subjects was 52.9 years (range 42.0 to 61. 2 years). The mean ECP was 11.9 mL/ mm Hg (standard deviation, 3.16 mL/mm Hg, range 3.39 to 29.57 mL/ mm Hg). At baseline examination, men with low ECP were older, smoked more, and were less physically active, and they had higher LDL cholesterol, SBP, alcohol consumption, and prevalence of type 2 diabetes, as compared to those with higher ECP (Table 1).
3.2. Associated predictors for sudden cardiac death Age-adjusted predictors for any SCD were ECP (p = 0.002), BMI (p b 0.001), prevalent CHD (p b 0.001), smoking (p b 0.001), type 2 diabetes (p = 0.012), the use of antihypertensive medication (p b 0.01) and alcohol consumption (p = 0.040). One standard deviation (SD) increase in ECP (3.2 mL/mm Hg) was associated with a decreased risk of SCD by 36% (95% CI 47% to 23%). One SD increase in VO2max (635.9 mL/min) was associated with a decreased risk of SCD (RR 0.67, 95% CI 0.55 to 0.81, p b 0.001) after adjustment for risk factors. Change in maximal SBP per one SD (28.1 mm Hg) was related to the risk of SCD (p = 0.010).
2.4. Classification of sudden cardiac death
3.3. Exercise cardiac power and risk for sudden cardiac death in men
All deaths that occurred by the end of 2011 were checked from the hospital documents, wards of health centers and death certificates. The sources of information were interviews with family members, hospital documents, death certificates, autopsy reports and medico-legal reports. There were no losses to follow-up. Deaths were coded using to the Ninth or Tenth International Classification of Diseases codes. The primary outcome was sudden cardiac death. A death was defined as SCD when it occurred either within 1 h after the onset of an abrupt change in symptoms or within 24 h after onset of symptoms when autopsy data did not reveal a non-cardiac cause of sudden death or after successful resuscitation from ventricular tachycardia and/or ventricular fibrillation [8]. SCDs that occurred in- out-of-hospital conditions had been accurately documented [8,9]. The deaths due to aortic aneurysm rupture, cardiac rupture or tamponade, pulmonary embolism, cancer or other non-cardiac co-morbidities were not included as SCD. Diagnostic classification of events was based on symptoms, electrocardiographic findings, cardiac enzyme elevations, autopsy findings (80% of the SCDs) and history of CHD together with clinical and ECG findings. Other cardiac-related deaths were defined as non-SCD. All death-related documents were cross-checked in detail by two physicians. An independent Events Committee blinded to clinical data performed classification of all deaths.
ECP was inversely related to the risk of SCD (Table 2). Men with ECP (b 8.2 mL/mm Hg, lowest quartile) had a 4.6-fold increased risk of SCD as compared to men with high ECP (N 16.1 mL/mm Hg, highest quartile) after adjusting for age and examination years. Low ECP was associated with a 2.9-fold risk of SCD after additional adjustment for the use of antihypertensive medication, cigarette smoking, alcohol consumption, BMI, the energy expenditure of physical activity, type 2 diabetes, CRP, prevalent CHD, and serum LDL and HDL cholesterol (Table 2). After further adjustment for resting SBP or LVH, the respective HRs among men with lowest ECP were 2.5 (95% CI 1.46–4.22, p b 0.001) and 3.9 (95% CI 2.19–7.14, p b 0.001) respectively. The respective risk of SCD was 2.9fold (95% CI 1.73 to 4.80, p b 0.001) among men with low ECP, after additional adjustment for myocardial infarction during the interim period of follow-up. The multivariate adjusted cumulative curves are shown in Fig. 1. Similar results were observed among men free of CHD at baseline. The inclusion of ECP in the model with other previously established risk factors increased the C-index from 0.760 (95% CI 0.727 to 0.795) to 0.778 (95% CI 0.751 to 0.813) indicating an incremental value. The IDI was 0.014 (p = 0.004) and relative IDI was 0.119 showing the significant level of discrimination between men classified with and without the use of ECP duration in addition to other risk factors (Table 3). Consistently, binary R2 increased from 0.121 to 0.134 after adding ECP duration into the multivariable model.
2.5. Statistical analysis Descriptive data are presented as means and percentages. Risk factors for main outcomes were analyzed with a multivariate Cox model. ECP was entered into forced Cox proportional hazards models. Cox models were adjusted for age and other demographic and clinical factors previously reported to be predictive of SCD by considering their clinical relevance. Hazards risks (HRs) with 95% confidence intervals (CIs) were adjusted for clinical risk factors and were estimated as antilogarithms of the coefficients from multivariable models. The fit of the proportional hazards models was examined by plotting the hazard functions in different categories of risk factors over time. The proportional hazards assumption was verified for all variables by inspection of the plots of Schoenfeld residuals for covariates. The linearity assumption was satisfied for all continuous variables, and it was assessed with Martingale residuals for each continuous variable against survival time. Different sets of covariates were used: Model 1) age and examination year; 2) Model 1 + the use of antihypertensive medication, smoking, alcohol consumption, body mass index, the energy expenditure of physical activity, type 2 diabetes, CRP and serum HDL and LDL cholesterol. In subsidiary analysis resting SBP or left ventricular hypertrophy was additionally included into Model 2. All statistical analyses were performed using the SPSS 20.0 Windows software. A p value of b0.05 was considered statistically significant. The cumulative survival from SCD according to the presence of ECP was calculated. On the basis of C-index, the incremental value of ECP in addition to previously documented risk factors and diseases was evaluated [8,21,22]. We also calculated the integrated discrimination index (IDI) for the model with and without ECP, defined as the average increase in predicted risk among cases, plus the analogous average decrease among controls.
3.4. Exercise cardiac power and risk of out-of-hospital sudden cardiac death Low ECP was also associated with an increased risk of out-ofhospital SCD (Table 2). The risk of out-of-hospital SCD among men with low ECP was a 5.9-fold after adjusting for age and examination year and a 3.9-fold (95% CI 2.08–7.40, p b 0.001) after further adjustment for the use of conventional risk factors (Table 2). After additional adjustment for resting SBP, men with low ECP had a 3.21-fold (95% CI 1.66–6.19, p b 0.001) risk. The respective risk was 4.0-fold (95% CI (2.15–7.60), p b 0.001) among men with low ECP, when myocardial infarction during the interim period of follow-up was included in multivariate Model 2.
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Table 1 Characteristics of men at baseline in the quartiles of exercise cardiac power.
Age (years) Cigarette smoking (pack-years)a Serum total cholesterol (mmol/l) Serum LDL cholesterol (mmol/l) Serum triglycerides (mmol/l) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Type 2 diabetes (%) Body mass index (kg/m2) Leisure-time physical activity (kcal/wk) b Serum C-reactive protein (mg/l) Alcohol consumption (g/week)
Mean (SD)
Q1 Mean (SD)
Q2 Mean (SD)
Q3 Mean (SD)
Q4 Mean (SD)
p value
52.8 (5.0) 8.4 (16.3) 5.90 (1.06) 4.04 (1.00) 1.28 (0.82) 134.1 (16.8) 89.1 (10.4) 5.0 26.6 (3.4) 979.8 (1185.7) 2.3 (3.3) 74.3 (121.5)
55.1 (4.0) 11.9 (19.7) 6.06 (1.12) 4.16 (1.07) 1.42 (0.86) 141.1 (19.6) 85.7 (9.0) 9.0 26.8 (3.3) 881.3 (1083.4) 3.2 (4.9) 79.9 (157.8)
53.6 (4.6) 10.5 (11.7) 6.00 (1.06) 4.16 (0.98) 1.30 (0.86) 135.2 (15.6) 88.7 (10.1) 5.0 26.8 (3.4) 794.4 (990.8) 2.3 (2.9) 72.6 (104.8)
52.5 (4.9) 5.5 (13.1) 5.86 (1.05) 4.01 (0.99) 1.22 (0.79) 132.1 (15.3) 89.8 (9.8) 3.0 26.8 (3.2) 999.9 (1338) 1.8 (2.9) 72.6 (111.3)
50.2 (5.3) 5.9 (13.0) 5.70 (0.99) 4.16 (1.07) 1.20 (0.72) 127.9 (13.3) 92.1 (11.4) 3.0 26.3 (3.6) 1243.8(1365) 1.8 (2.5) 72.0 (103.8)
p b 0.001 p b 0.001 p b 0.001 p b0.001 p b 0.001 p b 0.001 p b 0.001 p b 0.001 p = 0.31 p b 0.001 p b 0.001 p = 0.64
Q1 = b8.21 mL/mm Hg, Q2 = 8.12–10.75 mL/mm Hg, Q3 = 10.76–12.74 mL/mm Hg, Q4 N 12.75 mL/mm Hg, (Quintiles). a Pack-years denote the lifelong exposure to smoking which was estimated as a product of years smoked and the number of tobacco products smoked daily at the time of examination, HDL denotes high-density lipoprotein and LDL denotes low-density lipoprotein. b LTPA is defined as the leisure time physical activity using the 12-month leisure-time physical activity questionnaire.
3.5. Exercise cardiac power and risk of all-cause death Low ECP was also associated with an increased risk of all-cause mortality. Men with low ECP had a 2.4-fold (95% CI 2.00–3.02, p b 0.001) risk of all-cause death relative to those with high ECP after adjusting for age and examination years and a 1.9-fold (95% CI 1.60–2.46, p b 0.001) risk after further adjustment for conventional risk factors. After additional adjustment for resting SBP, low ECP was related to the risk of all-cause death (1.81, 95% CI 1.44–2.27, p b 0.001).
4. Discussion Exercise cardiac power, an easily available novel marker of peak cardiac output during exercise, was associated with an increased risk of SCD in a population-based study of men. The association was even stronger for out-of-hospital SCD. The integration of afterload using peak SBP with VO2max emphasizes the role of ergospirometry in the risk prediction of SCD and gives prognostic information in addition to that obtained by conventional methods. To the best of our knowledge, this is the first prospective populationbased follow-up study showing an association between ECP and the risk for SCD. The important finding is that ECP provides incremental prognostic and discriminative power on SCD risk prediction despite taking into account established risk factors such as smoking, lipids, hypertension, left ventricular hypertrophy and type 2 diabetes. A dose–response was observed between ECP and SCD. This study shows that excessive risk of SCD was observed among men with the lowest level of ECP. A continuous change in ECP (3.2 mL/mm Hg) corresponds to a 36% decrease in the risk for SCD among these men. Our previous study showed
that 1-MET increment in CRF reduced the risk of SCD by 22% [8] and stroke risk by 17% [23]. On the basis of our study it seems that ECP may provide a valuable tool for the risk prediction for SCD than CRF alone. It has been suggested that VO2max is a non-invasive measure of cardiac output during physical stress and reflects cardiac preload whereas SBP is a mere indicator of afterload during exercise as cardiac output is dependent both on preload and afterload [20]. In subjects with elevated adrenergic tone and inappropriately constricted arterial bed, cardiac output can be lowered in the presence of disproportionately elevated SBP [24]. Consequently, VO2max may be severely reduced over the years and thus it may underestimate cardiac pumping capacity in a large number of subjects. Cardiac output is a non-invasive descriptor of cardiac function derived from preload, blood pressure and cardiac output [25] and ECP takes into consideration not only the preload but also the afterload that potentially increases its value as a prognostic marker for SCD. The role of ECP can be considered as a modifiable risk factor by increasing CRF and a decrease in blood pressure will help in the prevention of SCD risk. CRF is determined by several physiological, environmental and genetic factors such as age, sex, and physical activity. CRF can be improved by increasing physical activity which ultimately confers long-term benefits on the cardiovascular system. The impairment of coronary blood flow and cardiac function during exercise may be caused by vessel constriction, endothelial dysfunction, spasm and thrombosis [24–26]. A high intraluminal pressure will lead to extensive change in endothelium and smooth muscle function in the arteries. In subjects with preclinical atherosclerotic with elevated SBP, the increased stress on the vessel wall can increase the risk of endothelial injury [27,28], leading to an increased risk of SCD. In our study, extensive adjustment for risk factors did not markedly change the
Table 2 The relative risk of sudden cardiac death in the quartiles of exercise cardiac power (ECP) in men. Risk factor
Sudden cardiac death (n = 205)
Exercise cardiac power (mL/mm Hg)
HR (95% CI)
N12.75 (mL/mm Hg) (1st quarter) n = 589 10.76–12.74 (mL/mm Hg) (2nd quarter) n = 590 8.12-10.75 (mL/mm Hg) (3rd quarter) n = 590 b8.21 (mL/mm Hg) (4th quarter) n = 589
1.00
a
1.31 (0.75-2.29) 2.65 (1.59–4.41) 4.58 (2.80–7.49)
a
p value
HR (95% CI)
Out-of-hospital SCD (n = 151) b
No. of cases
HR (95% CI)a
21
1.00
0.353
31
0.005
59
b0.001
94
1.41 (0.69–2.85) 3.46 (1.85–6.48) 5.90 (3.20–10.8)
p value
1.00 0.338 0.001 b0.001
1.30 (0.74–2.29) 2.08 (1.24–3.51) 2.90 (1.74–4.83)
p value
HR (95% Cl) b
p value
1.00 0.34 b0.001 b0.001
1.42 (0.70–2.89) 2.84 (1.49–5.39) 3.92 (2.08–7.40)
No. of cases 13
0.328
20
0.001
46
b0.001
72
Adjusted for age and examination years. Adjusted for age, examination year, the use of antihypertensive medication, cigarette smoking, alcohol consumption, body mass index, the energy expenditure of physical activity, type 2 diabetes, C reactive protein and serum HDL and LDL cholesterol. HR = Hazards ratio, Cl = confidence interval. b
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of discrimination improvement in IDI when ECP was added with age and risk factors. There were no losses during follow-up. The strength of our study was the availability of autopsy data in 80% of the SCD cases. ECP remained as a risk factor, while taking into account left ventricular hypertrophy in a multivariate model. It is probable that the incidence of SCD can be reduced by a combination of several approaches aimed at preventing its occurrence. A limitation of this study is that it is based on an ethnically homogenic and middle-aged male population that may limit the generalization of our results. Therefore, more studies are needed in different study populations and especially in elderly and in women to confirm our findings. This prospective population-based study provides the first evidence that ECP was associated with an increased risk of SCD. On the basis of our study, ECP provides additional valuable information on the evaluation of SCD risk, although further studies are needed showing the value of ECP as a prognostic measure. Conflict of interest The authors report no relationships that could be construed as a conflict of interest. Fig. 1. The age and examination adjusted survival curves of sudden cardiac death in men according to quartiles of exercise cardiac power.
Relationship with industry and financial disclosure statement None.
association between ECP and risk for SCD, although the adjustment for resting SBP slightly weakened the observed relationship. This is in line with the role of resting SBP as a risk factor for SCD [12]. Additionally, our study showed that ECP is an important predictive factor when antihypertensive medication was taken into account. 5. Strengths and limitations The strengths of this study are that we have a representative population-based sample of middle-aged men with a high participation rate with the assessment of VO2max, which is considered to be a golden standard for measuring CRF [29]. This study showed the significant level Table 3 Effect of adding the exercise cardiac power to traditional risk factors: Reclassification of men between predicted cardiovascular risk categories and comparison of observed and predicted risk of sudden cardiac death. Model with exercise cardiac power (%) 0% to b6%
6% to b20%
N20%
Model without exercise cardiac p (%) Events (n = 205) 0% to b6% n % reclassified 6% to b20% n % reclassified N20% n % reclassified
40 0 7 4.5%
15 9.6% 61 0 1 0.6%
0 0% 11 7.1% 70 0
Non-events (n = 2153) 0% to b6% n % reclassified 6% to b20% n % reclassified N20% n % reclassified
1172 0 99 5.2% 0
146 7.6% 517 0 24 1.3%
0 50 2.6% 145 0
3.3% 6.6% 0
9.3% 10.6% 4.0%
0 18.0% 32.6%
Events/total 0 to b6% 6 to 20% N20%
A total of 168 subjects were reclassified as to risk level: 26 events upward and 8 events downward; 196 non-events upward and 123 non-events downward; net reclassification index (NRI) = 0.054 (p = 0.07), for events NRI was 0.088 (p = 0.002) and for non-events NRI was 0.034 (p = 0.0001).
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Exercise cardiac power and the risk of sudden cardiac death in a long-term prospective study Sudhir Kurl a,b,⁎,1, Sae Young Jae c,1, Jussi Kauhanen a,1, Kimmo Ronkainen a,1, Rainer Rauramaa d,1, Jari A. Laukkanen a,b,1 a
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio. Finland Lapland Central Hospital, Rovaniemi, Finland Department of Sports Informatics, College of Arts and Physical Education, University of Seoul, South Korea d Kuopio Research Institute of Exercise Medicine Kuopio, University of Eastern Finland, Kuopio. Finland b c
a r t i c l e
i n f o
Article history: Received 22 October 2014 Accepted 1 December 2014 Available online 3 December 2014 Keywords: Exercise cardiac power Sudden cardiac death Prevention Risk factors
a b s t r a c t Background: Little is known about exercise cardiac power and the risk of sudden cardiac death. The aim of this study was to examine the relationship of exercise cardiac power (ECP), defined as a ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise, with the risk for sudden cardiac death (SCD). Methods: This prospective study was based on 2358 men who participated in exercise stress test at baseline. During an average follow-up of 20 years 205 SCDs occurred. Results: Men with ECP (b 8.2 mL/mm Hg, lowest quartile) had a 4.6-fold (95% CI 2.8–7.5, p b 0.001) increased risk of SCD as compared to with ECP in the highest quartile (N12.8 mL/mm Hg) after adjusting for age and examination years. Men with low ECP (b 8.2 mL/mm Hg) had markedly increased risk of SCD (RR 3.9, 95% CI 2.19–7.14, p b 0.001) after adjustment for conventional risk factors and left ventricular hypertrophy, whereas for progressive adjustment for resting systolic blood pressure, the respective risk among men with lowest ECP was 2.5 (95% CI 1.46– 4.22, p b 0.001). After adding ECP in the multivariate model, the Harrell C-index increased from 0.760 to 0.778 showing the significant incremental value of ECP in predicting SCD. The integrated discrimination improvement was 0.014 (p = 0.004). Conclusions: Low ECP provides a non-invasive and easily available measure for the prediction of SCD and may help in identifying men with high risk for SCD. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Sudden cardiac arrest accounts for one half of all deaths related to coronary heart disease (CHD) and presents as the first manifestation of CHD in about 20% to 30% of the deaths [1–3]. It is suggested that one of the most important risk markers yielded by the exercise test is the measure of exercise capacity [4–7]. Previous population-based studies have looked at the ability of indirectly defined functional capacity to predict total mortality and other cardiovascular events [8–11]. Cardiorespiratory fitness (CRF), when measured directly during exercise, has been shown to have a strong inverse relation to the CHD risk factors [5–7] and sudden cardiac death (SCD) [8]. It has been proposed that measurement of CRF should be included when clinical decisions are being made in patients referred for evaluation of cardiovascular diseases (CVDs). Although CRF is the most accurate indicator of exercise capacity,
⁎ Corresponding author at: Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, P.O. 1627, 70211 Kuopio, Finland. E-mail address: sudhir.kurl@uef.fi (S. Kurl). 1 All the authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
http://dx.doi.org/10.1016/j.ijcard.2014.12.023 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
it does not take into account the differences in cardiovascular resistance and cardiac afterload. A previous study has shown that resting systolic blood pressure (SBP) is a risk factor for SCD [12], whereas both resting SBP and exercise-induced elevation of SBP have been found to be an independent predictor of stroke [9], hypertension [10–14], CHD [15,16] and CVD [17–19]. As exercise cardiac power (ECP) is a function of CRF (VO2max) and peripheral resistance (indicated by SBP) [20], we hypothesized that ECP may provide valuable information in SCD risk stratification. Thus the aim of this study was to investigate the association of ECP during exercise with the risk of SCD in a population based sample of men. 2. Methods 2.1. Subjects Subjects were participants in the Kuopio Ischaemic Heart Disease Risk Factor Study which is a prospective population based study designed to investigate risk factors for CVD, carotid atherosclerosis and related outcomes in a population-based, randomly selected sample of men from eastern Finland [20]. Of the 3433 men aged 42, 48, 54 or 60 who resided in the town of Kuopio or its surrounding rural communities, 198 were excluded because of death, serious disease or migration away from the area. At baseline, examinations were conducted on 2682 men (82.9% of the potential eligible) between March
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1984 and December 1989. The Kuopio ischemic Heart Disease study was approved by the Research Ethics Committee of the University of Kuopio, and each participant gave written informed consent. Complete data on ECP was available on 2358 subjects at baseline in this study. 2.2. Assessment of exercise cardiac power A maximal symptom-limited exercise tolerance test was performed between 8:00 AM and 10:00 AM using an electrically braked cycle ergometer [4]. The standardized testing protocol comprised of an increase in the workload of 20 W/min with the direct analyses of respiratory gases (Medical Graphics, St. Paul, Minnesota). The VO2max was defined as the highest value for or the plateau of oxygen uptake. Blood pressure was measured manually when the exercise test was started and blood pressure was measured every 2 min during the exercise test. The peak SBP was the highest value achieved during the test. The ratio of measured VO2max with peak SBP was defined as ECP [20]. For safety reasons, all tests were supervised by an experienced physician with the assistance of an experienced nurse. Electrocardiography (ECG) was recorded continuously with the Kone 620 electrocardiograph (Kone, Turku, Finland) [8,9]. 2.3. Assessment of other covariates Resting blood pressures was obtained using a random-zero sphygmomanometer after 5 and 10 min of rest in the seated position. The mean of these two values was used as the resting blood pressure. Body mass index was computed as the ratio of weight in kilograms to the square of height in meters. Information on use of medications and diagnosis of diseases was collected at baseline examination by an internist [4]. Alcohol consumption was assessed with the use of the Nordic Alcohol Consumption Inventory [4]. The collection of blood specimens and the measurement of serum lipids, lipoproteins, and insulin, and the definition of type 2 diabetes have been described elsewhere [8,9]. Serum C-reactive protein (CRP) was measured with an immunometric assay (Immulite High Sensitivity Creactive protein Assay, DPC, Los Angeles, CA, U.S.A.).
3. Results 3.1. Baseline characteristics In the beginning of the follow-up, the mean age of the subjects was 52.9 years (range 42.0 to 61. 2 years). The mean ECP was 11.9 mL/ mm Hg (standard deviation, 3.16 mL/mm Hg, range 3.39 to 29.57 mL/ mm Hg). At baseline examination, men with low ECP were older, smoked more, and were less physically active, and they had higher LDL cholesterol, SBP, alcohol consumption, and prevalence of type 2 diabetes, as compared to those with higher ECP (Table 1).
3.2. Associated predictors for sudden cardiac death Age-adjusted predictors for any SCD were ECP (p = 0.002), BMI (p b 0.001), prevalent CHD (p b 0.001), smoking (p b 0.001), type 2 diabetes (p = 0.012), the use of antihypertensive medication (p b 0.01) and alcohol consumption (p = 0.040). One standard deviation (SD) increase in ECP (3.2 mL/mm Hg) was associated with a decreased risk of SCD by 36% (95% CI 47% to 23%). One SD increase in VO2max (635.9 mL/min) was associated with a decreased risk of SCD (RR 0.67, 95% CI 0.55 to 0.81, p b 0.001) after adjustment for risk factors. Change in maximal SBP per one SD (28.1 mm Hg) was related to the risk of SCD (p = 0.010).
2.4. Classification of sudden cardiac death
3.3. Exercise cardiac power and risk for sudden cardiac death in men
All deaths that occurred by the end of 2011 were checked from the hospital documents, wards of health centers and death certificates. The sources of information were interviews with family members, hospital documents, death certificates, autopsy reports and medico-legal reports. There were no losses to follow-up. Deaths were coded using to the Ninth or Tenth International Classification of Diseases codes. The primary outcome was sudden cardiac death. A death was defined as SCD when it occurred either within 1 h after the onset of an abrupt change in symptoms or within 24 h after onset of symptoms when autopsy data did not reveal a non-cardiac cause of sudden death or after successful resuscitation from ventricular tachycardia and/or ventricular fibrillation [8]. SCDs that occurred in- out-of-hospital conditions had been accurately documented [8,9]. The deaths due to aortic aneurysm rupture, cardiac rupture or tamponade, pulmonary embolism, cancer or other non-cardiac co-morbidities were not included as SCD. Diagnostic classification of events was based on symptoms, electrocardiographic findings, cardiac enzyme elevations, autopsy findings (80% of the SCDs) and history of CHD together with clinical and ECG findings. Other cardiac-related deaths were defined as non-SCD. All death-related documents were cross-checked in detail by two physicians. An independent Events Committee blinded to clinical data performed classification of all deaths.
ECP was inversely related to the risk of SCD (Table 2). Men with ECP (b 8.2 mL/mm Hg, lowest quartile) had a 4.6-fold increased risk of SCD as compared to men with high ECP (N 16.1 mL/mm Hg, highest quartile) after adjusting for age and examination years. Low ECP was associated with a 2.9-fold risk of SCD after additional adjustment for the use of antihypertensive medication, cigarette smoking, alcohol consumption, BMI, the energy expenditure of physical activity, type 2 diabetes, CRP, prevalent CHD, and serum LDL and HDL cholesterol (Table 2). After further adjustment for resting SBP or LVH, the respective HRs among men with lowest ECP were 2.5 (95% CI 1.46–4.22, p b 0.001) and 3.9 (95% CI 2.19–7.14, p b 0.001) respectively. The respective risk of SCD was 2.9fold (95% CI 1.73 to 4.80, p b 0.001) among men with low ECP, after additional adjustment for myocardial infarction during the interim period of follow-up. The multivariate adjusted cumulative curves are shown in Fig. 1. Similar results were observed among men free of CHD at baseline. The inclusion of ECP in the model with other previously established risk factors increased the C-index from 0.760 (95% CI 0.727 to 0.795) to 0.778 (95% CI 0.751 to 0.813) indicating an incremental value. The IDI was 0.014 (p = 0.004) and relative IDI was 0.119 showing the significant level of discrimination between men classified with and without the use of ECP duration in addition to other risk factors (Table 3). Consistently, binary R2 increased from 0.121 to 0.134 after adding ECP duration into the multivariable model.
2.5. Statistical analysis Descriptive data are presented as means and percentages. Risk factors for main outcomes were analyzed with a multivariate Cox model. ECP was entered into forced Cox proportional hazards models. Cox models were adjusted for age and other demographic and clinical factors previously reported to be predictive of SCD by considering their clinical relevance. Hazards risks (HRs) with 95% confidence intervals (CIs) were adjusted for clinical risk factors and were estimated as antilogarithms of the coefficients from multivariable models. The fit of the proportional hazards models was examined by plotting the hazard functions in different categories of risk factors over time. The proportional hazards assumption was verified for all variables by inspection of the plots of Schoenfeld residuals for covariates. The linearity assumption was satisfied for all continuous variables, and it was assessed with Martingale residuals for each continuous variable against survival time. Different sets of covariates were used: Model 1) age and examination year; 2) Model 1 + the use of antihypertensive medication, smoking, alcohol consumption, body mass index, the energy expenditure of physical activity, type 2 diabetes, CRP and serum HDL and LDL cholesterol. In subsidiary analysis resting SBP or left ventricular hypertrophy was additionally included into Model 2. All statistical analyses were performed using the SPSS 20.0 Windows software. A p value of b0.05 was considered statistically significant. The cumulative survival from SCD according to the presence of ECP was calculated. On the basis of C-index, the incremental value of ECP in addition to previously documented risk factors and diseases was evaluated [8,21,22]. We also calculated the integrated discrimination index (IDI) for the model with and without ECP, defined as the average increase in predicted risk among cases, plus the analogous average decrease among controls.
3.4. Exercise cardiac power and risk of out-of-hospital sudden cardiac death Low ECP was also associated with an increased risk of out-ofhospital SCD (Table 2). The risk of out-of-hospital SCD among men with low ECP was a 5.9-fold after adjusting for age and examination year and a 3.9-fold (95% CI 2.08–7.40, p b 0.001) after further adjustment for the use of conventional risk factors (Table 2). After additional adjustment for resting SBP, men with low ECP had a 3.21-fold (95% CI 1.66–6.19, p b 0.001) risk. The respective risk was 4.0-fold (95% CI (2.15–7.60), p b 0.001) among men with low ECP, when myocardial infarction during the interim period of follow-up was included in multivariate Model 2.
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Table 1 Characteristics of men at baseline in the quartiles of exercise cardiac power.
Age (years) Cigarette smoking (pack-years)a Serum total cholesterol (mmol/l) Serum LDL cholesterol (mmol/l) Serum triglycerides (mmol/l) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Type 2 diabetes (%) Body mass index (kg/m2) Leisure-time physical activity (kcal/wk) b Serum C-reactive protein (mg/l) Alcohol consumption (g/week)
Mean (SD)
Q1 Mean (SD)
Q2 Mean (SD)
Q3 Mean (SD)
Q4 Mean (SD)
p value
52.8 (5.0) 8.4 (16.3) 5.90 (1.06) 4.04 (1.00) 1.28 (0.82) 134.1 (16.8) 89.1 (10.4) 5.0 26.6 (3.4) 979.8 (1185.7) 2.3 (3.3) 74.3 (121.5)
55.1 (4.0) 11.9 (19.7) 6.06 (1.12) 4.16 (1.07) 1.42 (0.86) 141.1 (19.6) 85.7 (9.0) 9.0 26.8 (3.3) 881.3 (1083.4) 3.2 (4.9) 79.9 (157.8)
53.6 (4.6) 10.5 (11.7) 6.00 (1.06) 4.16 (0.98) 1.30 (0.86) 135.2 (15.6) 88.7 (10.1) 5.0 26.8 (3.4) 794.4 (990.8) 2.3 (2.9) 72.6 (104.8)
52.5 (4.9) 5.5 (13.1) 5.86 (1.05) 4.01 (0.99) 1.22 (0.79) 132.1 (15.3) 89.8 (9.8) 3.0 26.8 (3.2) 999.9 (1338) 1.8 (2.9) 72.6 (111.3)
50.2 (5.3) 5.9 (13.0) 5.70 (0.99) 4.16 (1.07) 1.20 (0.72) 127.9 (13.3) 92.1 (11.4) 3.0 26.3 (3.6) 1243.8(1365) 1.8 (2.5) 72.0 (103.8)
p b 0.001 p b 0.001 p b 0.001 p b0.001 p b 0.001 p b 0.001 p b 0.001 p b 0.001 p = 0.31 p b 0.001 p b 0.001 p = 0.64
Q1 = b8.21 mL/mm Hg, Q2 = 8.12–10.75 mL/mm Hg, Q3 = 10.76–12.74 mL/mm Hg, Q4 N 12.75 mL/mm Hg, (Quintiles). a Pack-years denote the lifelong exposure to smoking which was estimated as a product of years smoked and the number of tobacco products smoked daily at the time of examination, HDL denotes high-density lipoprotein and LDL denotes low-density lipoprotein. b LTPA is defined as the leisure time physical activity using the 12-month leisure-time physical activity questionnaire.
3.5. Exercise cardiac power and risk of all-cause death Low ECP was also associated with an increased risk of all-cause mortality. Men with low ECP had a 2.4-fold (95% CI 2.00–3.02, p b 0.001) risk of all-cause death relative to those with high ECP after adjusting for age and examination years and a 1.9-fold (95% CI 1.60–2.46, p b 0.001) risk after further adjustment for conventional risk factors. After additional adjustment for resting SBP, low ECP was related to the risk of all-cause death (1.81, 95% CI 1.44–2.27, p b 0.001).
4. Discussion Exercise cardiac power, an easily available novel marker of peak cardiac output during exercise, was associated with an increased risk of SCD in a population-based study of men. The association was even stronger for out-of-hospital SCD. The integration of afterload using peak SBP with VO2max emphasizes the role of ergospirometry in the risk prediction of SCD and gives prognostic information in addition to that obtained by conventional methods. To the best of our knowledge, this is the first prospective populationbased follow-up study showing an association between ECP and the risk for SCD. The important finding is that ECP provides incremental prognostic and discriminative power on SCD risk prediction despite taking into account established risk factors such as smoking, lipids, hypertension, left ventricular hypertrophy and type 2 diabetes. A dose–response was observed between ECP and SCD. This study shows that excessive risk of SCD was observed among men with the lowest level of ECP. A continuous change in ECP (3.2 mL/mm Hg) corresponds to a 36% decrease in the risk for SCD among these men. Our previous study showed
that 1-MET increment in CRF reduced the risk of SCD by 22% [8] and stroke risk by 17% [23]. On the basis of our study it seems that ECP may provide a valuable tool for the risk prediction for SCD than CRF alone. It has been suggested that VO2max is a non-invasive measure of cardiac output during physical stress and reflects cardiac preload whereas SBP is a mere indicator of afterload during exercise as cardiac output is dependent both on preload and afterload [20]. In subjects with elevated adrenergic tone and inappropriately constricted arterial bed, cardiac output can be lowered in the presence of disproportionately elevated SBP [24]. Consequently, VO2max may be severely reduced over the years and thus it may underestimate cardiac pumping capacity in a large number of subjects. Cardiac output is a non-invasive descriptor of cardiac function derived from preload, blood pressure and cardiac output [25] and ECP takes into consideration not only the preload but also the afterload that potentially increases its value as a prognostic marker for SCD. The role of ECP can be considered as a modifiable risk factor by increasing CRF and a decrease in blood pressure will help in the prevention of SCD risk. CRF is determined by several physiological, environmental and genetic factors such as age, sex, and physical activity. CRF can be improved by increasing physical activity which ultimately confers long-term benefits on the cardiovascular system. The impairment of coronary blood flow and cardiac function during exercise may be caused by vessel constriction, endothelial dysfunction, spasm and thrombosis [24–26]. A high intraluminal pressure will lead to extensive change in endothelium and smooth muscle function in the arteries. In subjects with preclinical atherosclerotic with elevated SBP, the increased stress on the vessel wall can increase the risk of endothelial injury [27,28], leading to an increased risk of SCD. In our study, extensive adjustment for risk factors did not markedly change the
Table 2 The relative risk of sudden cardiac death in the quartiles of exercise cardiac power (ECP) in men. Risk factor
Sudden cardiac death (n = 205)
Exercise cardiac power (mL/mm Hg)
HR (95% CI)
N12.75 (mL/mm Hg) (1st quarter) n = 589 10.76–12.74 (mL/mm Hg) (2nd quarter) n = 590 8.12-10.75 (mL/mm Hg) (3rd quarter) n = 590 b8.21 (mL/mm Hg) (4th quarter) n = 589
1.00
a
1.31 (0.75-2.29) 2.65 (1.59–4.41) 4.58 (2.80–7.49)
a
p value
HR (95% CI)
Out-of-hospital SCD (n = 151) b
No. of cases
HR (95% CI)a
21
1.00
0.353
31
0.005
59
b0.001
94
1.41 (0.69–2.85) 3.46 (1.85–6.48) 5.90 (3.20–10.8)
p value
1.00 0.338 0.001 b0.001
1.30 (0.74–2.29) 2.08 (1.24–3.51) 2.90 (1.74–4.83)
p value
HR (95% Cl) b
p value
1.00 0.34 b0.001 b0.001
1.42 (0.70–2.89) 2.84 (1.49–5.39) 3.92 (2.08–7.40)
No. of cases 13
0.328
20
0.001
46
b0.001
72
Adjusted for age and examination years. Adjusted for age, examination year, the use of antihypertensive medication, cigarette smoking, alcohol consumption, body mass index, the energy expenditure of physical activity, type 2 diabetes, C reactive protein and serum HDL and LDL cholesterol. HR = Hazards ratio, Cl = confidence interval. b
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of discrimination improvement in IDI when ECP was added with age and risk factors. There were no losses during follow-up. The strength of our study was the availability of autopsy data in 80% of the SCD cases. ECP remained as a risk factor, while taking into account left ventricular hypertrophy in a multivariate model. It is probable that the incidence of SCD can be reduced by a combination of several approaches aimed at preventing its occurrence. A limitation of this study is that it is based on an ethnically homogenic and middle-aged male population that may limit the generalization of our results. Therefore, more studies are needed in different study populations and especially in elderly and in women to confirm our findings. This prospective population-based study provides the first evidence that ECP was associated with an increased risk of SCD. On the basis of our study, ECP provides additional valuable information on the evaluation of SCD risk, although further studies are needed showing the value of ECP as a prognostic measure. Conflict of interest The authors report no relationships that could be construed as a conflict of interest. Fig. 1. The age and examination adjusted survival curves of sudden cardiac death in men according to quartiles of exercise cardiac power.
Relationship with industry and financial disclosure statement None.
association between ECP and risk for SCD, although the adjustment for resting SBP slightly weakened the observed relationship. This is in line with the role of resting SBP as a risk factor for SCD [12]. Additionally, our study showed that ECP is an important predictive factor when antihypertensive medication was taken into account. 5. Strengths and limitations The strengths of this study are that we have a representative population-based sample of middle-aged men with a high participation rate with the assessment of VO2max, which is considered to be a golden standard for measuring CRF [29]. This study showed the significant level Table 3 Effect of adding the exercise cardiac power to traditional risk factors: Reclassification of men between predicted cardiovascular risk categories and comparison of observed and predicted risk of sudden cardiac death. Model with exercise cardiac power (%) 0% to b6%
6% to b20%
N20%
Model without exercise cardiac p (%) Events (n = 205) 0% to b6% n % reclassified 6% to b20% n % reclassified N20% n % reclassified
40 0 7 4.5%
15 9.6% 61 0 1 0.6%
0 0% 11 7.1% 70 0
Non-events (n = 2153) 0% to b6% n % reclassified 6% to b20% n % reclassified N20% n % reclassified
1172 0 99 5.2% 0
146 7.6% 517 0 24 1.3%
0 50 2.6% 145 0
3.3% 6.6% 0
9.3% 10.6% 4.0%
0 18.0% 32.6%
Events/total 0 to b6% 6 to 20% N20%
A total of 168 subjects were reclassified as to risk level: 26 events upward and 8 events downward; 196 non-events upward and 123 non-events downward; net reclassification index (NRI) = 0.054 (p = 0.07), for events NRI was 0.088 (p = 0.002) and for non-events NRI was 0.034 (p = 0.0001).
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