Exercise capacity in diabetes mellitus is predicted by activity status and cardiac size rather than cardiac function: a case control study

Abstract

BackgroundThe reasons for reduced exercise capacity in diabetes mellitus (DM) remains incompletely understood, although diastolic dysfunction and diabetic cardiomyopathy are often favored explanations. However, there is a paucity of literature detailing cardiac function and reserve during incremental exercise to evaluate its significance and contribution. We sought to determine associations between comprehensive measures of cardiac function during exercise and maximal oxygen consumption (peak), with the hypothesis that the reduction in exercise capacity and cardiac function would be associated with co-morbidities and sedentary behavior rather than diabetes itself.MethodsThis case–control study involved 60 subjects [20 with type 1 DM (T1DM), 20 T2DM, and 10 healthy controls age/sex-matched to each diabetes subtype] performing cardiopulmonary exercise testing and bicycle ergometer echocardiography studies. Measures of biventricular function were assessed during incremental exercise to maximal intensity.ResultsT2DM subjects were middle-aged (52 ± 11 years) with a mean T2DM diagnosis of 12 ± 7 years and modest glycemic control (HbA1c 57 ± 12 mmol/mol). T1DM participants were younger (35 ± 8 years), with a 19 ± 10 year history of T1DM and suboptimal glycemic control (HbA1c 65 ± 16 mmol/mol). Participants with T2DM were heavier than their controls (body mass index 29.3 ± 3.4 kg/m2 vs. 24.7 ± 2.9, P = 0.001), performed less exercise (10 ± 12 vs. 28 ± 30 MET hours/week, P = 0.031) and had lower exercise capacity (peak = 26 ± 6 vs. 38 ± 8 ml/min/kg, P < 0.0001). These differences were not associated with biventricular systolic or left ventricular (LV) diastolic dysfunction at rest or during exercise. There was no difference in weight, exercise participation or peak in T1DM subjects as compared to their controls. After accounting for age, sex and body surface area in a multivariate analysis, significant positive predictors of peak were cardiac size (LV end-diastolic volume, LVEDV) and estimated MET-hours, while T2DM was a negative predictor. These combined factors accounted for 80% of the variance in peak (P < 0.0001).ConclusionsExercise capacity is reduced in T2DM subjects relative to matched controls, whereas exercise capacity is preserved in T1DM. There was no evidence of sub-clinical cardiac dysfunction but, rather, there was an association between impaired exercise capacity, small LV volumes and sedentary behavior.

Type 2 diabetes and reduced exercise tolerance: a review of the literature through an integrated physiology approach

“…Importantly, reduced VO 2peak was associated with S' and E' and also to cardiac magnetic resonance assessed myocardial fibrosis [44]. However, other studies did not observe impaired Doppler indices, but reported LV size as a predictor of reduced oxygen uptake [45]. Finally, cardiac index reserve, a variable expressed by the combination of chronotropic index and SV index reserve, appears related to VO 2max as well [46], thus strengthening the possibility of causal link between subclinical diabetic cardiac myopathy and reduced exercise capacity in T2DM.…”

The importance of return to work: How to achieve optimal reintegration in ACS patients

“…additionally influence the overall estimation of a patient s physical capacity and the return to work rate. 21…”

Exercise as A Potential Therapeutic Target for Diabetic Cardiomyopathy: Insight into the Underlying Mechanisms

“…If biomarkers or non-invasive imaging modalities could be used for early identification of high-risk patients [46,140], it would be feasible to prescribe personalized exercise programs based on risk stratification. Since exercise may not only mitigate cardiac dysfunction but also improve the outcome of T2DM [36,134,[141][142][143], a therapeutic approach with a tailored exercise prescription would positively impact DCM management in the future. To this end, the development of tools for early diagnosis and optimization of risk stratification models would be pivotal and in conjunction with well-designed clinical trials could provide the evidence to facilitate timely implementation.…”