Relative peak exercise oxygen pulse is related to sudden cardiac death,cardiovascular and all-cause mortality in middle-aged men

Abstract

Background

Preliminary evidence suggests that peak exercise oxygen pulse – peak oxygen uptake/heart rate-, a variable obtained during maximal cardiopulmonary exercise testing and a surrogate of stroke volume, is a predictor of mortality. We aimed to assess the associations of peak exercise oxygen pulse with sudden cardiac death, fatal coronary heart disease and cardiovascular disease and all-cause mortality.

Design

A prospective study.

Methods

Peak exercise oxygen pulse was assessed in a maximal cycling test at baseline in 2227 middle-aged men of the Kuopio Ischaemic Heart Disease cohort study using expired gas variables and electrocardiograms. Relative peak exercise oxygen pulse was obtained by dividing the absolute value by body weight.

Results

During a median follow-up of 26.1 years 1097 subjects died; there were 220 sudden cardiac deaths, 336 fatal coronary heart diseases and 505 fatal cardiovascular diseases. Relative peak exercise oxygen pulse (mean 19.5 (4.1) mL per beat/kg/10²) was approximately linearly associated with each outcome. Comparing extreme quartiles of relative peak exercise oxygen pulse, hazard ratios (95% confidence intervals) for sudden cardiac death, fatal coronary heart disease and cardiovascular disease, and all-cause mortality on adjustment for cardiovascular risk factors were 0.55 (0.36–0.83), 0.58 (0.42–0.81), 0.60 (0.46–0.79) and 0.59 (0.49–0.70), respectively (P < 0.001 for all). The hazard ratios were unchanged on further adjustment for C-reactive protein and the use of beta-blockers. The addition of relative peak exercise oxygen pulse to a cardiovascular disease mortality risk prediction model significantly improved risk discrimination (C-index change 0.0112; P = 0.030).

Conclusion

Relative peak exercise oxygen pulse measured during maximal exercise was linearly and inversely associated with fatal cardiovascular and all-cause mortality events in middle-aged men. In addition, relative peak exercise oxygen pulse provided significant improvement in cardiovascular disease mortality risk assessment beyond conventional risk factors.

Keywords

Peak exercise oxygen pulse cardiopulmonary exercise testing risk prediction sudden cardiac death cardiovascular diseases all-cause mortality

Introduction

Cardiorespiratory or aerobic fitness, as measured by peak oxygen uptake (VO₂), has been one of the most widely examined cardiopulmonary exercise testing (CPX) variables, particularly as it relates to functional capacity and human performance.^1,2 In previous cohort studies, peak VO₂ has been shown to be inversely and independently associated with incident cardiovascular disease (CVD) events, cardiovascular and total mortality.^3–7 Evidence also suggests that peak VO₂ adds additional prognostic value beyond established risk factors in predicting vascular disease and mortality risk.^3,8,9

Stroke volume response is one of the most important measures of cardiac performance during exercise.^10,11 Exercise oxygen pulse, a surrogate for stroke volume, has emerged as an important variable which is obtained during CPX. Peak exercise oxygen pulse (peO₂p) is expressed as oxygen consumed per heart beat at maximal CPX and it is related to the risk of cardiovascular events.¹²

There is evidence to show that a high peO₂p is inversely related to all-cause mortality.^10,13 However, data on the value of utilising peO₂p as a risk assessment tool for serious and specific adverse events such as sudden cardiac death (SCD) and fatal coronary heart disease (CHD) are lacking. Although in the literature, peO2p is often expressed by its absolute value (i.e. mL/beat), its magnitude is obviously related to body dimensions. Thus, ideally, similarly to peak VO₂, it should be expressed in relative form, that is, by dividing its absolute value by body weight.¹¹ Given the relative ease in which this exercise testing variable can be assessed non-invasively using expired gases analysis, it will be clinically relevant to know if relative peO₂p is a significant risk marker for fatal cardiovascular events and if it adds additional information beyond well-established cardiovascular risk factors. Our primary aim was to assess the nature and magnitude of the associations of relative peO₂p with the risk of SCD, fatal CHD and CVD events, and all-cause mortality using a population-based prospective cohort study. A secondary aim was to evaluate whether the addition of relative peO2p measurements to conventional cardiovascular risk factors could improve the prediction of CVD mortality.

Methods

Study population

The strengthening the reporting of observational studies in epidemiology (STROBE) guidelines for reporting observational studies in epidemiology were used in this study (Supplementary Appendix).¹⁴ Data analysis was undertaken in participants of the Finnish Kuopio Ischemic Heart Disease (KIHD) risk factor study, a prospective general population-based cohort study which aimed to study related risk factors for atherosclerotic CVD and other related chronic disease outcomes to aerobic performance. A detailed description of the study design, objectives and sampling strategy has previously been reported.¹⁵ The KIHD cohort was recruited from a representative sample of 3433 men aged 42–61 years who were living in the city of Kuopio (Finland) and its surrounding communities. Of this number, 3235 men were found to be eligible for inclusion and 2682 (82.9%) volunteered to participate in the study. Baseline examinations were performed between March 1984 and December 1989. For the current analysis, 2227 men with complete information on relative peO₂p, relevant covariates and fatal outcomes were included. The medical ethics committee of the University of Eastern Finland approved the study protocol, which was conducted in accordance with the Declaration of Helsinki. All study participants provided written informed consent.

Assessment of peak oxygen pulse

All participants underwent a morning symptom-limited cycling exercise testing.¹⁶ with breath-by-breath respiratory gas analysis (Medical Graphics, USA). Peak VO₂ was assessed as previously described^5,16 and peO₂p was calculated by dividing the measured peak VO₂ by the maximum exercise heart rate, obtained from electrocardiogram, and was expressed in mL/beat. To remove the influence of body weight on the magnitude of peO₂p, values of peO₂p were then divided by weight in kilograms to yield relative peO₂p. All results were multiplied by 100 for easier readability, as previously described.^11,17 To ensure safety, all tests were supervised by an experienced physician and nurse.

Assessment of covariates

Baseline data were obtained by history, questionnaire administration, physical examinations and measurements as detailed elsewhere.^18,19 Fasting cholesterol contents of serum lipoprotein fractions, triglycerides, plasma glucose and serum high sensitivity C-reactive protein (hsCRP) were obtained from analysis of blood samples. Smoking, prevalent diseases and regular and current use of medications were assessed by standardised self-administered questionnaires.¹⁸ Alcohol consumption was assessed using the Nordic alcohol consumption inventory. Resting blood pressure was measured before the CPX with a random-zero sphygmomanometer. The history of CHD was based on a previous myocardial infarction, angina pectoris, use of nitroglycerin for chest pain once a week or more frequently or typical chest pain. The amount of physical activity was assessed from a 12-month physical activity history modified from the Minnesota leisure-time physical activity questionnaire,²⁰ and expressed in kJ/day.¹⁶

Ascertainment of outcomes

All SCD, fatal CHD and CVD, and all-cause mortality events were ascertained from hospital documents, discharge lists, death certificates, informant interviews, health practitioner questionnaires, study electrocardiograms, medico-legal reports and vital statistics offices from study enrollment through to the end of 2014. The diagnostic classification of SCDs was based on symptoms, electrocardiographic findings, cardiac enzyme elevations, autopsy findings and history of CHD plus clinical findings and information from hospital and paramedic staff, details of which have previously been described.^5,19,21 CVD deaths were coded using the tenth International Classification of Diseases codes. Documents were cross-checked in detail by two physicians.

Statistical analysis

The baseline characteristics of study participants were summarised using descriptive statistics (i.e. means, medians and percentages). Cross-sectional associations of relative peO₂p with risk markers were assessed by calculating age-adjusted partial correlation coefficients. Hazard ratios (HRs) with 95% confidence intervals (CIs) for SCD, fatal CHD and CVD events, and all-cause mortality were calculated using Cox proportional hazard models after confirmation of the proportionality-hazards assumption using Schoenfeld residuals. The shape of the association between relative peO₂p and each fatal outcome was characterised by calculating the HRs within quartiles of baseline relative peO₂p and plotting these against the mean values of relative peO₂p within each quartile using floating variances as described previously.^22,23 We modelled our exposure as both continuous (per standard deviation (SD) increase) and categorical (quartiles) variables. HRs were progressively adjusted for: (a) age (model 1); (b) systolic blood pressure (SBP), total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking status, alcohol consumption, prevalent CHD, history of diabetes mellitus and amount of physical activity (model 2); and (c) hsCRP and use of beta-blockers (model 3). Subgroup analyses were performed using interaction tests to assess statistical evidence of effect modification by relevant clinical characteristics. To assess whether adding information on relative peO₂p to documented established risk factors is associated with an improvement in prediction of CVD mortality risk, we calculated measures of discrimination for censored time-to-event data (Harrell’s C-index)²⁴ and reclassification.^25,26 To investigate the change in C-index, we added relative peO₂p to a CVD mortality risk prediction model (i.e. age, SBP, history of diabetes, total cholesterol, HDL-cholesterol and smoking). Reclassification analysis was restricted to the first 10 years and was assessed using the net reclassification improvement (NRI).^25,26 Given that we used CVD mortality as the outcome, we followed European guidelines²⁷ to determine clinically meaningful risk categories. Reclassification analyses were based on predicted 10-year CVD mortality risk categories of low (<1%), intermediate (1 to <5%) and high (≥5%) risk. All statistical analyses were conducted using Stata version 14 (Stata Corp, College Station, USA).

Results

Baseline characteristics and correlates of relative peO2p

The baseline mean (SD) age and relative peO₂p were 53 (5) years and 19.5 (4.1) mL per beat/kg/10², respectively (Table 1). Relative peO₂p was weakly to moderately inversely correlated with age, alcohol consumption, physical measurements (body mass index, blood pressure and resting heart rate), lipids (total cholesterol and triglycerides), fasting plasma glucose and hsCRP. There was a relatively weak positive correlation of relative peO₂p with regular physical activity (r = 0.08) and HDL-cholesterol (r = 0.22) (Table 1). Values of relative peO₂p were lower in the presence of a history of CHD, hypertension, diabetes, current smoking and the use of antihypertensives.

Table 1.

Baseline participant characteristics and correlates of relative peak exercise oxygen pulse.

	Mean (SD), median (IQR), or n (%)	Partial correlation r (95% CI)^a	Absolute difference (95% CI) in values of relative peO₂p per 1 SD higher or compared to reference category of correlate^b
Peak exercise oxygen pulse (mL/beats)	15.5 (3.4)	–	–
Relative peO₂p (mL per beat/kg/10²)	19.5 (4.1)	–	–
Questionnaire/prevalent conditions
Age at survey (years)	53 (5)	–0.15 (–0.19, –0.11)***	–0.62% (–0.79, –0.46)***
Alcohol consumption (g/week)	74.3 (122.2)	–0.10 (–0.14, –0.06)***	–0.40% (–0.56, –0.23)
History of diabetes
No	2149 (96.5)	–	Ref
Yes	78 (3.5)	–	–1.92% (–2.83, –1.00)***
Smoking status
Other	1530 (68.7)	–	Ref
Current	697 (31.3)	–	–0.64% (–1.00, –0.28)**
History of hypertension
No	1568 (70.4)	–	Ref
Yes	659 (29.6)	–	–0.68% (–1.05, –0.31)**
History of CHD
No	1701 (76.4)	–	Ref
Yes	526 (23.6)	–	–1.38% (–1.78, –0.98)***
Use of antihypertensives
No	1762 (79.1)	–	Ref
Yes	465 (20.9)	–	–0.67% (–1.09, –0.26)*
Use of beta-blockers
No	1847 (82.9)	–	Ref
Yes	380 (17.1)	–	–0.13% (–0.59, 0.32)
Physical measurements
BMI (kg/m²)	26.9 (3.4)	–0.33 (–0.37, –0.29)***	–1.33% (–1.49, –1.17)***
Weight (kg)	80.3 (11.8)	–0.31 (–0.34, –0.27)***	–1.24% (–1.40, –1.08)***
SBP (mmHg)	134 (17)	–0.17 (–0.21, –0.13)***	–0.68% (–0.85, –0.52)***
DBP (mmHg)	89 (10)	–0.19 (–0.23, –0.15)***	–0.77% (–0.93, –0.60)***
Physical activity (kj/day)	1545 (1408)	0.08 (0.04, 0.12)**	0.33% (0.17, 0.50)***
Heart rate (beats/min)	62.4 (10.8)	–0.38 (–0.42, –0.34)***	–1.54% (–1.71, –1.38)***
Lipid markers
Total cholesterol (mmol/l)	5.91 (1.07)	–0.05 (–0.10, –0.01)*	–0.22% (–0.39, –0.05)*
HDL-cholesterol (mmol/l)	1.29 (0.30)	0.22 (0.18, 0.26)***	0.89% (0.72, 1.05)***
Triglycerides (mmol/l)	1.09 (0.79–1.54)	–0.25 (–0.29, –0.21)***	–1.02% (–1.18, –0.85)***
Metabolic, renal markers, and inflammatory markers
Fasting plasma glucose (mmol/l)	5.33 (1.20)	–0.17 (–0.21, –0.12)***	–0.67% (–0.83, –0.50)***
Serum creatinine (µmol/1)	89.7 (21.7)	–0.02 (–0.07, 0.02)	–0.09% (–0.27, 0.08)
Estimated GFR (ml/min/1.73 m²)	87.1 (17.2)	–0.03 (–0.08, 0.01)	–0.14% (–0.32, 0.04)
High sensitivity CRP	1.25 (0.69–2.37)	–0.27 (–0.31, –0.23)***	–1.10% (–1.26, –0.94)***

CI: confidence interval; BMI: body mass index; CHD: coronary heart disease; CRP: C-reactive protein; DBP: diastolic blood pressure; GFR: glomerular filtration rate; HDL: high-density lipoprotein; IQR: interquartile range; peO₂p: peak exercise oxygen pulse; SD: standard deviation; SBP: systolic blood pressure.

Partial correlation coefficients between relative peO₂p and the row variables.

Absolute change in values of relative peO₂p per 1 SD increase in the row variable (or for categorical variables, the absolute difference in mean values of relative peO₂p for the category vs. the reference) adjusted for age.

Asterisks indicate the level of statistical significance: *P < 0.05; **P < 0.01; ***P < 0.001.

Relative peO2p and mortality

During a median (interquartile range) follow-up of 26.1 (19.1–28.1) years 1097 subjects died (49.2% of the study sample), with a total of 220 SCDs, 336 fatal CHDs and 505 fatal CVDs. In analyses adjusted for several established risk factors (age, SBP, total cholesterol, HDL-cholesterol, smoking status, alcohol consumption, prevalent CHD, history of diabetes mellitus and physical activity), relative peO₂p was approximately linearly and inversely associated with SCD, fatal CHD, fatal CVD and all-cause mortality (P < 0.001) (Figure 1). Table 2 summarises the HRs (95% CIs) of relative peO₂p with each fatal outcome assessed. In age-adjusted analysis, the HRs (95% CIs) for SCD, fatal CHD, fatal CVD and all-cause mortality per 1 SD increase in relative peO₂p were 0.63 (0.54–0.73), 0.63 (0.56–0.71), 0.66 (0.60–0.73) and 0.73 (0.68–0.78) (P < 0.001), respectively. The associations (HRs) remained consistent and significant after adjustment for several established cardiovascular risk factors plus hsCRP and the use of beta-blockers: 0.76 (0.65–0.89), 0.75 (0.66–0.86), 0.77 (0.70–0.86) and 0.80 (0.74–0.86), respectively. Alternatively, comparing the top versus the bottom quartile of relative peO₂p, the age-adjusted HRs (95% CIs) for SCD, fatal CHD, fatal CVD and all-cause mortality were 0.35 (0.24–0.53), 0.39 (0.28–0.53), 0.42 (0.33–0.54) and 0.49 (0.41–0.58) (P < 0.001), respectively, and were also significant after adjustment for several established cardiovascular risk factors with hsCRP and the use of beta-blockers. The corresponding HRs were 0.54 (0.36–0.82), 0.57 (0.41–0.80), 0.61 (0.47–0.80) and 0.61 (0.51–0.73), respectively (Table 2). The associations were generally not modified by several clinically relevant characteristics (Figures 2 and 3), except for the suggestion of effect modification by a history of CHD for the association of relative peO₂p with SCD. Although the associations were in the same direction, stronger protective associations were observed in presence of a history of CHD. peO₂p was associated with SCD, fatal CHD, fatal CVD and all-cause mortality among men who were not using beta-blockers as well as among those who were using beta-blockers, as shown in Figures 2 and 3, and this relationship was not modified by the use of beta-blockers.

Table 2.

Associations of relative peak exercise oxygen pulse with sudden cardiac death, fatal coronary heart disease, fatal cardiovascular disease, and all-cause mortality.

Models Relative peak oxygen pulse (mL per beat/kg/10²)	Sudden cardiac death		Fatal coronary heart disease		Fatal cardiovascular disease		All-cause mortality
	220 cases		336 cases		505 cases		1097 cases
	Hazard ratio (95% CI)	P value	Hazard ratio (95% CI)	P value	Hazard ratio (95% CI)	P value	Hazard ratio (95% CI)	P value
Model
Per 1 SD increase	0.63 (0.54–0.73)	<0.001	0.63 (0.56–0.71)	<0.001	0.66 (0.60–0.73)	<0.001	0.73 (0.68–0.78)	<0.001
Quartile 1 (6.4–16.8)	1 [Ref]		1 [Ref]		1 [Ref]		1 [Ref]
Quartile 2 (16.8–19.3)	0.62 (0.44–0.87)	0.005	0.65 (0.50–0.86)	0.002	0.65 (0.52–0.81)	<0.001	0.70 (0.60–0.82)	<0.001
Quartile 3 (19.3–21.9)	0.47 (0.32–0.68)	<0.001	0.43 (0.32–0.59)	<0.001	0.47 (0.37–0.60)	<0.001	0.60 (0.51–0.71)	<0.001
Quartile 4 (21.9–42.7)	0.35 (0.24–0.53)	<0.001	0.39 (0.28–0.53)	<0.001	0.42 (0.33–0.54)	<0.001	0.49 (0.41–0.58)	<0.001
Model 2
Per 1 SD increase	0.77 (0.66–0.90)	0.001	0.76 (0.67–0.86)	<0.001	0.77 (0.69–0.85)	<0.001	0.79 (0.74–0.85)	<0.001
Quartile 1 (6.4–16.8)	1 [Ref]		1 [Ref]		1 [Ref]		1 [Ref]
Quartile 2 (16.8–19.3)	0.71 (0.51–1.01)	0.054	0.75 (0.57–0.99)	0.041	0.72 (0.58–0.91)	0.005	0.74 (0.63–0.86)	<0.001
Quartile 3 (19.3–21.9)	0.63 (0.44–0.92)	0.016	0.57 (0.42–0.79)	0.001	0.60 (0.46–0.77)	<0.001	0.69 (0.59–0.82)	<0.001
Quartile 4 (21.9–42.7)	0.55 (0.36–0.83)	0.005	0.58 (0.42–0.81)	0.001	0.60 (0.46–0.79)	<0.001	0.59 (0.49–0.70)	<0.001
Model 3
Per 1 SD increase	0.76 (0.65–0.89)	0.001	0.75 (0.66–0.86)	<0.001	0.77 (0.70–0.86)	<0.001	0.80 (0.74–0.86)	<0.001
Quartile 1 (6.4–16.8)	1 [Ref]		1 [Ref]		1 [Ref]		1 [Ref]
Quartile 2 (16.8–19.3)	0.73 (0.52–1.02)	0.067	0.76 (0.58–1.00)	0.047	0.74 (0.59–0.93)	0.009	0.76 (0.65–0.89)	0.001
Quartile 3 (19.3–21.9)	0.63 (0.43–0.92)	0.016	0.57 (0.42–0.78)	<0.001	0.60 (0.47–0.77)	<0.001	0.70 (0.60–0.83)	<0.001
Quartile 4 (21.9–42.7)	0.54 (0.36–0.82)	0.004	0.57 (0.41–0.80)	0.001	0.61 (0.47–0.80)	<0.001	0.61 (0.51–0.73)	<0.001

Model 1: adjusted for age.

Model 2: model 1 plus systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, alcohol consumption, prevalent coronary heart disease, history of diabetes mellitus, and physical activity.

Model 3: model 2 plus high sensitivity C-reactive protein and use of beta-blockers.

Figure 1.

Hazard ratios (HRs) for sudden cardiac death, fatal coronary heart disease (CHD), fatal cardiovascular disease (CVD), and all-cause mortality by quartiles of relative peak exercise oxygen pulse (peO₂p). HRs were adjusted for age, body mass index, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, alcohol consumption, prevalent CHD, a history of diabetes mellitus and physical activity. CI: confidence interval.

Figure 2.

Hazard ratios (HRs) per one standard deviation (SD) change (4.1 mL per beat/kg/10²) in relative peak exercise oxygen pulse (peO₂p) for sudden cardiac death and fatal coronary heart disease (CHD) by several participant characteristics. HRs were adjusted for age, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking status, alcohol consumption, prevalent CHD, a history of diabetes mellitus and physical activity. *P value for interaction; cut-offs for age, body mass index, systolic blood pressure, total cholesterol and HDL-cholesterol are based on median values. CI: confidence interval.

Figure 3.

Hazard ratios (HRs) per one standard deviation (SD) change (4.1 mL per beat/kg/10²) in relative peak exercise oxygen pulse (peO₂p) for cardiovascular and all-cause mortality by several participant characteristics. HRs were adjusted for age, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking status, alcohol consumption, prevalent coronary heart disease (CHD), a history of diabetes mellitus and physical activity. *P value for interaction; cut-offs for age, body mass index, systolic blood pressure, total cholesterol and HDL-cholesterol are based on median values. CI: confidence interval; CVD: cardiovascular disease.

Relative peO2p and CVD mortality risk prediction

A CVD mortality risk prediction model containing established risk factors yielded a C-index of 0.7009 (95% CI 0.6784–0.7234). After the addition of information on relative peO₂p, the C-index changed to 0.7121 (95% CI 0.6899–0.7344), representing a significant increase of 0.0112 (95% CI 0.0011–0.0214; P = 0.030). However, there was no improvement in the classification of participants into predicted 10-year CVD mortality risk categories (NRI 4.18%, –3.24 to 11.61%; P = 0.269).

In an approach to compare the predictive ability of relative peO₂p with peak VO_2, which has been consistently shown to improve CVD risk prediction above that of traditional cardiovascular risk factors,^3,8,28 peak VO₂ measurements was added to the CVD mortality prognostic model. There was a C-index change of 0.0348 (95% CI 0.0199–0.0497; P < 0.001) and it yielded a NRI of 16.40% (8.21 to 24.59%; P < 0.001) for the predicted 10-year CVD mortality risk categories.

Furthermore, in a prediction model containing established risk factors plus peak VO₂, the C-index change was 0.0028 (95% CI –0.0011–0.0068; P = 0.161), on the addition of information on relative peO₂p and NRI it was 1.15% (–3.17 to 5.48%; P = 0.601).

Discussion

In this population-based prospective cohort study of apparently healthy Finnish men with a median follow-up period of over 25 years, we found approximately significant, linear and inverse associations of relative peO₂p with distinct fatal cardiovascular and all-cause mortality outcomes. The associations were independent of several established and emerging cardiovascular risk factors. The magnitude and directions of the associations were generally consistent across several clinically relevant subgroups including the use of beta-blockers (yes vs. no), except by the possible effect modification by a history of CHD on the relative peO₂p and SCD association. The stronger inverse association between relative peO₂p and SCD risk in men with a prevalent history of CHD may corroborate existing evidence that exercise training has more beneficial effects on adverse outcomes in individuals with pre-existing cardiometabolic disease.²⁹ Furthermore, findings from the assessments of improvements in risk discrimination indicate that relative peO₂p provides a significant improvement in CVD mortality risk prediction but not beyond that provided by established cardiovascular risk factors and peak VO₂. Further analyses showed that the improvement provided by peak VO₂ assessment in the prediction of CVD mortality risk was better than that of relative peO₂p, which further confirms the superiority of peak VO₂ as a prognostic tool.

The concept of oxygen pulse is more than 100 years old.³⁰ Notwithstanding this, studies on the associations of peO₂p with cardiovascular and mortality outcomes are limited and have been based on populations with smaller sample sizes or with pre-existing disease, and have rarely taken into account the body weight, that is, the relative peO₂p. In a French study that compared the long-term prognostic value of peO₂p and peak VO₂ in 178 patients with chronic heart failure, peO₂p was found to have a lower prognostic value for survival compared with peak VO₂.¹² However, in a larger sample of 998 heart failure patients,³¹ the age-predicted peO₂p (an indirect way to adjust peO₂p per body weight) has complemented peak O₂ in the prediction of risk for mortality, while Lavie et al.³² studied 209 patients with mild to moderate heart failure and found that peO₂p/lean body mass outperforms peak oxygen. These apparently contradictory findings may be explained by different ways to analyse peO₂p data, either as an absolute value or in the same way related to body weight or lean body mass. Our data have shown that relative peO₂p is independently associated with several long-term cause-specific cardiovascular mortality outcomes as well as all-cause mortality in a general middle-aged population. In addition, we showed that relative peO₂p provided prognostic value for CVD mortality beyond established risk factors, although there was no significant improvement beyond that of peak VO₂. Considering that these two CPX variables are mathematically related and that both improve with exercise training,³³ these relatively similar results are not surprising. Indeed, whether relative peO₂p or peak VO₂ will be a better prognostic indicator may vary according to the characteristics of the subjects being studied and the outcomes that are being examined.^34,35 Considering the ease of determining relative peO₂p from expired gas analysis, it seems quite logical to include this result in CPX reports.

There is growing evidence on the clinical usefulness of CPX variables, as supported by several guidelines.^36,37 Notwithstanding, the incorporation of these CPX variables in clinical practice is still limited. Currently, peak VO₂, VO₂ at ventilatory/anaerobic threshold and ventilatory efficiency (i.e. the minute ventilation/carbon dioxide production relationship) are the only three CPX variables that have been consistently proved to show prognostic significance.³⁸ peO₂p is gaining attention as a clinically useful variable and can easily be obtained during CPX and computed as the ratio of maximum values of VO₂ and heart rate. In addition, the interpretation of exercise oxygen pulse curves could also be clinically relevant, as abnormal and flat oxygen pulse curves during CPX have been shown to reflect left ventricular dysfunction³⁹ and myocardial ischaemia^40,41 or fibrosis.⁴² The prognostic utility of the peO₂p curves deserves further study.

Strengths and limitations

We have reported the first prospective evaluation of the associations of relative peO₂p, that is, peO₂p/body weight, with the risk of major fatal cardiovascular events and all-cause mortality outcomes in a general population setting. The KIHD cohort was characterised by a high participation rate, and no losses to follow-up were recorded, which minimised potential selection bias. In addition, outcomes were confirmed and validated.^5,8 We have utilised comprehensive analysis, which included adjustment for several lifestyle and biological markers, assessment of the dose–response relationships, subgroup analyses and risk prediction analyses. Oxygen pulse is an indicator of stroke volume response to exercise that might be influenced by body dimensions and heart size,⁴³ and adjustments for body size and/or weight should ideally be included in studies on peO₂p, especially if data from male and female subjects are to be compared in different populations. The lack of control for confounding variables such as body weight might have limited the interpretation of previous reports.^10,41 In our analyses, we used a relative peO₂p which took into account body weight, thus strengthening the validity of the results.

When interpreting the results, some limitations should be considered. The KIHD study included middle-aged Caucasian men from eastern Finland, so extrapolation to other populations and age groups, and particularly for women, might not be valid and more research is needed in this regard. Although we adjusted for a comprehensive panel of covariates, residual confounding remains a potential alternative explanation for our findings, due to the observational design of the study. According to the Fick equation, oxygen pulse equals the product of stroke volume and arteriovenous oxygen difference, while oxygen pulse tends to exhibit a quasi-linear increase throughout maximal exercise.¹¹ We have previously shown that left ventricular diastolic and systolic diameter are directly associated with peO₂p.¹⁰ Even though direct measurements of stroke volume were not available in the current study, there is convincing evidence that oxygen pulse correlates well with direct measurements of stroke volume during submaximal and maximal exercise in healthy and unhealthy subjects of different age groups.^39,43–45

In conclusion, the findings of this large prospective cohort study in middle-aged Finnish men with long-term follow-up indicate strong linear and inverse associations of relative peO₂p with fatal cardiovascular and all-cause mortality events. In addition, the incorporation of relative peO₂p during a maximal cycling CPX provides a significant improvement in CVD mortality risk assessment beyond several conventional risk factors.

Supplemental Material

Supplemental material for Relative peak exercise oxygen pulse is related to sudden cardiac death, cardiovascular and all-cause mortality in middle-aged men

Supplemental material for Relative peak exercise oxygen pulse is related to sudden cardiac death, cardiovascular and all-cause mortality in middle-aged men by Jari A Laukkanen, Claudio Gil S Araú jo, Sudhir Kurl, Hassan Khan, Sae Y Jae, Marco Guazzi and Setor K Kunutsor in European Journal of Preventive Cardiology

Footnotes

Author contribution

JAL, CGA and SKK contributed to the conception or design of the work. JAL, CGA, SK and SKK contributed to the acquisition, analysis, or interpretation of data for the work. JAL and SK drafted the manuscript. JAL, CGA, SK, HK, SYJ, MG and SKK critically revised the manuscript. All authors gave final approval and agree to be accountable for all aspects of the work ensuring integrity and accuracy.

Acknowledgements

The authors thank the staff of the Kuopio Research Institute of Exercise Medicine and the Research Institute of Public Health and University of Eastern Finland, Kuopio, Finland for the data collection in the study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: this work was supported by the Finnish Foundation for Cardiovascular Research, Helsinki, Finland.

References

Harber

Kaminsky

Arena

et al.

Impact of cardiorespiratory fitness on all-cause and disease-specific mortality: advances since 2009. Prog Cardiovasc Dis 2017; 60: 11–20.

Ross

Blair

Arena

et al.

Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign: a scientific statement from the American Heart Association. Circulation 2016; 134: e653–e699.

Kodama

Saito

Tanaka

et al.

Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA 2009; 301: 2024–2035.

Hagnas

Kurl

Rauramaa

et al.

The value of cardiorespiratory fitness and exercise-induced ST segment depression in predicting death from coronary heart disease. Int J Cardiol 2015; 196: 31–33.

Laukkanen

Makikallio

Rauramaa

et al.

Cardiorespiratory fitness is related to the risk of sudden cardiac death: a population-based follow-up study. J Am Coll Cardiol 2010; 56: 1476–1483.

Laukkanen

Zaccardi

Khan

et al.

Long-term change in cardiorespiratory fitness and all-cause mortality: a population-based follow-up study. Mayo Clin Proc 2016; 91: 1183–1188.

Khan

Jaffar

Rauramaa

et al.

Cardiorespiratory fitness and nonfatalcardiovascular events: a population-based follow-up study. Am Heart J 2017; 184: 55–61.

Laukkanen

Kurl

Salonen

et al.

The predictive value of cardiorespiratory fitness for cardiovascular events in men with various risk profiles: a prospective population-based cohort study. Eur Heart J 2004; 25: 1428–1437.

Gupta

Rohatgi

Ayers

et al.

Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality. Circulation 2011; 123: 1377–1383.

10.

Laukkanen

Kurl

Salonen

et al.

Peak oxygen pulse during exercise as a predictor for coronary heart disease and all cause death. Heart 2006; 92: 1219–1224.

11.

Oliveira

Myers

Araujo

. Long-term stability of the oxygen pulse curve during maximal exercise. Clinics (Sao Paulo) 2011; 66: 203–209.

12.

Cohen-Solal

Barnier

Pessione

et al.

Comparison of the long-term prognostic value of peak exercise oxygen pulse and peak oxygen uptake in patients with chronic heart failure. Heart 1997; 78: 572–576.

13.

Oliveira

Myers

Araujo

et al.

Maximal exercise oxygen pulse as a predictor of mortality among male veterans referred for exercise testing. Eur J Cardiovasc Prev Rehabil 2009; 16: 358–364.

14.

von Elm

Altman

Egger

et al.

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61: 344–349.

15.

Salonen

. Is there a continuing need for longitudinal epidemiologic research? The Kuopio Ischaemic Heart Disease Risk Factor Study. Ann Clin Res 1988; 20: 46–50.

16.

Lakka

Venalainen

Rauramaa

et al.

Relation of leisure-time physical activity and cardiorespiratory fitness to the risk of acute myocardial infarction. N Engl J Med 1994; 330: 1549–1554.

17.

Perim

Signorelli

Myers

et al.

The slope of the oxygen pulse curve does not depend on the maximal heart rate in elite soccer players. Clinics (Sao Paulo) 2011; 66: 829–835.

18.

Salonen

Nyyssonen

Korpela

et al.

High stored iron levels are associated with excess risk of myocardial infarction in eastern Finnish men. Circulation 1992; 86: 803–811.

19.

Kunutsor

Khan

Laukkanen

. Gamma-glutamyltransferase and risk of sudden cardiac death in middle-aged Finnish men: a new prospective cohort study. J Am Heart Assoc 2016; 5(pii): e002858–e002858.

20.

Taylor

Jacobs

Jr Schucker

et al.

A questionnaire for the assessment of leisure time physical activities. J Chronic Dis 1978; 31: 741–755.

21.

Kunutsor

Kurl

Zaccardi

et al.

Baseline and long-term fibrinogen levels and risk of sudden cardiac death: a new prospective study and meta-analysis. Atherosclerosis 2016; 245: 171–180.

22.

Kunutsor

Bakker

James

et al.

Serum paraoxonase-1 activity and risk of incident cardiovascular disease: the PREVEND study and meta-analysis of prospective population studies. Atherosclerosis 2015; 245: 143–154.

23.

Kunutsor

Bakker

Kootstra-Ros

et al.

Circulating gamma glutamyltransferase and prediction of cardiovascular disease. Atherosclerosis 2014; 238: 356–364.

24.

Harrell

Jr Lee

Mark

. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15: 361–387.

25.

Pencina

D’Agostino

Sr D’Agostino

Jr et al.

Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157–172; discussion 207–112.

26.

Pencina

D’Agostino

Sr Steyerberg

. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011; 30: 11–21.

27.

Graham

Atar

Borch-Johnsen

et al.

European guidelines on cardiovascular disease prevention in clinical practice: executive summary. Fourth Joint Task Force of the European Society of Cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of nine societies and by invited experts). Eur J Cardiovasc Prev Rehabil 2007; 14(Suppl 2): E1–E40.

28.

Kunutsor

Kurl

Khan

et al.

Associations of cardiovascular and all-cause mortality events with oxygen uptake at ventilatory threshold. Int J Cardiol 2017; 236: 444–450.

29.

Kokkinos

Doumas

Myers

et al.

A graded association of exercise capacity and all-cause mortality in males with high-normal blood pressure. Blood Press 2009; 18: 261–267.

30.

Henderson

Prince

. The oxygen pulse and the systolic discharge. Am J Physiol 1914; 35: 106–115.

31.

Oliveira

Myers

Araujo

et al.

Does peak oxygen pulse complement peak oxygen uptake in risk stratifying patients with heart failure?

Am J Cardiol 2009; 104: 554–558.

32.

Lavie

Milani

Mehra

. Peak exercise oxygen pulse and prognosis in chronic heart failure. Am J Cardiol 2004; 93: 588–593.

33.

Huang

Wang

Chen

et al.

Dose-response relationship of cardiorespiratory fitness adaptation to controlled endurance training in sedentary older adults. Eur J Prev Cardiol 2016; 23: 518–529.

34.

Kato

Suzuki

Uejima

et al.

The relationship between resting heart rate and peak VO₂: a comparison of atrial fibrillation and sinus rhythm. Eur J Prev Cardiol 2016; 23: 1429–1436.

35.

Fernberg

Fernstrom

Hurtig-Wennlof

. Arterial stiffness is associated to cardiorespiratory fitness and body mass index in young Swedish adults: the Lifestyle, Biomarkers, and Atherosclerosis study. Eur J Prev Cardiol 2017; 24: 1809–1818.

36.

Balady

Arena

Sietsema

et al.

Clinician’s guide to cardiopulmonary exercise testing in adults: a scientific statement from the American Heart Association. Circulation 2010; 122: 191–225.

37.

American Thoracic Society and American College of Chest Physicians. ATS/ACCP Statement on cardiopulmonary exercise testing. Am J Respir Crit Care Med 2003; 167: 211–277.

38.

Guazzi

Arena

Halle

et al.

2016 Focused update: clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. Eur Heart J 2016.

39.

Klainman

Fink

Lebzelter

et al.

The relationship between left ventricular function assessed by multigated radionuclide test and cardiopulmonary exercise test in patients with ischemic heart disease. Chest 2002; 121: 841–845.

40.

Belardinelli

Lacalaprice

Carle

et al.

Exercise-induced myocardial ischaemia detected by cardiopulmonary exercise testing. Eur Heart J 2003; 24: 1304–1313.

41.

Munhoz

Hollanda

Vargas

et al.

Flattening of oxygen pulse during exercise may detect extensive myocardial ischemia. Med Sci Sports Exerc 2007; 39: 1221–1226.

42.

De Lorenzo

da Silva

Souza

FCC

et al.

Clinical, scintigraphic, and angiographic predictors of oxygen pulse abnormality in patients undergoing cardiopulmonary exercise testing. Clin Cardiol 2017; 40: 914–918. DOI: 10.1002/clc.22747.

43.

Whipp

Higgenbotham

Cobb

. Estimating exercise stroke volume from asymptotic oxygen pulse in humans. J Appl Physiol (1985) 1996; 81: 2674–2679.

44.

Bhambhani

Norris

Bell

. Prediction of stroke volume from oxygen pulse measurements in untrained and trained men. Can J Appl Physiol 1994; 19: 49–59.

45.

Legendre

Richard

Pontnau

et al.

Usefulness of maximal oxygen pulse in timing of pulmonary valve replacement in patients with isolated pulmonary regurgitation. Cardiol Young 2016; 26: 1310–1318.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.14 MB