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. 2024 Jul 26;14(1):17179.
doi: 10.1038/s41598-024-68223-y.

Predicting the occurrence of minor adverse events in cardiac rehabilitation using physical variables

Affiliations

Predicting the occurrence of minor adverse events in cardiac rehabilitation using physical variables

Maria Júlia Lopez Laurino et al. Sci Rep. .

Abstract

The safety of exercise practice by individuals with cardiovascular disease is due to a good clinical evaluation to identify patients with a higher risk of adverse events, thus the study of simple variables capable of predicting the rate of events during exercise is relevant and may provide better screening tools to be applied in the clinical practice. The study aimed to evaluate if clinical and physical parameters can predict the rate of adverse events during exercise-based cardiac rehabilitation. This was a cohort study that followed 73 patients during 24 sessions of exercise. Were registered 217 simple adverse events, at a rate of 2.5 events per hour of exercise. We found that higher adiposity, worse pulmonary function, lower functional capacity, and reduced heart rate variability were significant and acceptable predictors of adverse events during exercise, according to the ROC curve analysis. We state that these simple physical parameters may be useful for cardiac risk stratification in cardiac rehabilitation programs with low resources, contributing to its safety.

Keywords: Acute events; Cardiac rehabilitation; Cardiovascular diseases; Exercise; Risk factors.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Participants flow chart. N number, HRV heart rate variability, WHR waist-to-hip ratio, rMSSD root square of the mean of the square of the differences between adjacent normal RR intervals of the series, SDNN standard deviation of the mean of all normal RR intervals in the series, LF low-frequency spectral component, HF high-frequency spectral component, LF/HF the ratio between low- and high-frequency components, SD1 dispersion of the points perpendicular to the line with the smallest diameter of the ellipse, SD2 dispersion of the points perpendicular to the line with the largest diameter of the ellipse, SD1/SD2 ratio between the short- and long-term components of RR intervals, ms milliseconds, ms2 milliseconds squared, u.n. standardised units, HR resting heart rate, SBP systolic blood pressure, MEP maximal expiratory pressure, FVC forced vital capacity, FEV1 forced expiratory volume in the 1st second.
Figure 2
Figure 2
Characteristic of the occurrence of events. Representation of the absolute number of events recorded during exercise and recovery (A) and absolute number of participants stratified by the number of events recorded over the follow-up period (B). N/A not applicable.
Figure 3
Figure 3
Univariable logistic regression, cutoff value, and number of events associated with the observed risk of adverse events. OR odds ratio, 95% CI 95% confidence interval, BMI body mass index, Kg/m2 kilogram per square meter, 6MWT 6 min walk test, m meters, HR heart rate, bpm beats per minute, % percentage, bpm beats per minute, N Newton, MEP maximal expiratory pressure, FVC forced vital capacity, FEV1 forced expiratory volume in the 1st second, L liters, LF low-frequency spectral component, LF/HF ratio between low- and high-frequency components, n.u. normalized units. *Cutoff defined by the 3rd quartile, †Cutoff defined by the median, §Cutoff defined by the 33% percentile.

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