Heart Rate Changes in Response to an Exercise Test and to a High Intensity Interval Training Session in Subjects With Normoglycaemic, Prediabetes, and Type 2 Diabetes Mellitus State
Phase: NA
Conditions: Type2 Diabetes Mellitus, Hyperglycemia, Heart Rate, Exercise Training
Sponsor: Universidad de Los Lagos

 
Heart rate changes in response to an exercise test and to a high intensity interval 
training session in subjects with normoglycaemic, prediabetes, and type 2 diabetes 
mellitus state 
 
ID: RP010317 
 
Date: Apri1 10, 2019 
 
Study documents 
Scientific background: Exercise training is a cornerstone for the prevention [1-
3] and treatment of metabolic disorders and associated cardiometabolic complications 
such as type 2 diabetes mellitus (T2D) and hypertension [4-7]. Similar to the beneficial 
health effects after performing conventional continuous exercise modalities, high 
intensity interval training (HIIT) has been reported as an effective alternative exercise-
modality to improve glucose homeostasis in both prediabetes subjects and individuals 
with T2D diagnosed [5]. In this regard, although multiple HIIT-based interventions 
commonly report acute and long term benefits on body composition, cardiorespiratory 
fitness and insulin sensitivity in metabolically compromised subjects, little is known 
about the acute cardiovascular response (i.e., at heart rate level) during HIIT in subjects 
with different glucose control. HIIT is described as performing brief periods of exercise 
at vigorous or maximal intensity, interspersed with inactive or low intensity recovery 
phases of variable duration[8]. In order to characterize different HIIT-based protocols, 
exercise intensity is usually defined as relative percentages of individual maximal 
cardiorespiratory fitness (VO2max) or relative maximal power output values. 
Nevertheless, the need for specific technological equipment to assess these parameters 
usually limit the prescription and recommendations of HIIT in clinical settings and other 
public health contexts at massive level. Additionally, the use of self-perceived exertion 
scales [9] and heart rate (HR) variations upon HIIT [4, 10] have been demonstrating to 
be accessible and feasible strategies to regulate exercise intensity during HIIT. For 
example, it was reported that HR and self-perceived exertion scores increased 
progressively in T2D subjects, parallel to the oxygen consumption rate throughout an 
acute HIIT session performed on cycle ergometer [5]. Consequently, it is conceivable to 

hypothesize that determining HR variations during HIIT might optimize the 
recommendation of this training methodology in metabolically compromised subjects as 
those at risk or with T2D diagnosed. Design: An experimental, and randomized control 
clinical study. Methods: This cross-sectional study will use a non-probabilistic sample 
of 75 adult subjects, characterized as healthy normoglycaemic and with disturbed glucose 
homeostasis subjects, all referred by a physician to the exercise programme of our 
research centre. All volunteers will read and signed an informed consent. The inclusion 
criteria will be; a) aged 18-60 y; b) previously screened by physician professional; c) 
diagnosed with normoglycaemic, prediabetes or T2D state; d) and living in Temuco city. 
The exclusion criteria will be; a) low maximal cardiorespiratory fitness (defined as 
VO2max ≤21 ml/kg-1/min-1) below the expected value for the subject's sex and age 11; b) 
not receiving pharmacologic hypotensive treatment with β-blockers; and c) having no 
musculoskeletal limitations to perform exercise cycling. The study will be completed in 
accordance with the Declaration of Helsinki and was approved by the Ethical Committee 
of the Physical Activity and Sports Sciences, of the Universidad de Los Lagos.  
 
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Statistical Analysis Plan (SAP): We will apply 2 main forms of statistical 
analyses a) to report the pre-post changes in mean terms, and b) to report the results 
according with the inter-individual responses based on the technical error criteria, where 
according with the error calculated in the three previous measurements registered by the 
sample that was voluntary. Graphpad Prisma statistical software 5.0 (San Diego, CA, 
USA) will be used. The normal distribution of all the variables were tested using the 
D'Agostino-Pearson test. All the continuous variables were expressed as mean ± standard 

deviation (SD). The differences between quantitative variables were analysed by 
ANOVA and Tukey's post-test for multiple comparisons or Kruskal-Wallis and Dunn's 
post-test. The level of significance used in all the comparisons was P<0.05. Secondly,  
we will classify the subjects in responders and non-responders by the technical error of 
measurement, and additionally, we will classify the subjects according with a responder 
and non-responder clinical criteria, where we will classify as responders to all subjects 
who can be able of changing an initial adverse clinical altered profile for a healthy new 
classification. Thus, the specific statistical methods that we hope to apply for each 
analysis are; test of normality and homoscedasticity assumptions using Shapiro-Wilk and 
Levene’s tests, the Student’s t test for the identification of differences at baseline. An 
ANCOVA will be conducted (for potential confounders outcomes) in those altered 
baseline differences outcomes. We also hope to apply the repeated measures of two-way 
(group, time) to assess occurrence of an actual training effect [i.e., p <0.05 for the 
interaction (group × time) for the different study outcomes]. Among the specific statistical 
methods we hope to apply the Bonferroni post hoc test we hope to apply when we can be 
seen test differences among groups. Similarly, we hope to apply the Cohen’s d test in 
order to detect effect size, using the threshold values of 0.20, 0.60, 1.2, and 2.0 for small, 
moderate, large, and very large effects, respectively [14], with 95% confidence intervals 
(CI). The alpha level was fixed at P<0.05 for statistical significance.