High-Load and Low-Load Resistance Exercise in Patients with Coronary Artery Disease: Feasibility and Safety of a Randomized Controlled Clinical Trial.
Tim KambičNejc ŠarabonVedran HadžićMitja LainscakPublished in: Journal of clinical medicine (2022)
Resistance exercise (RE) remains underused in cardiac rehabilitation; therefore, there is insufficient evidence on safety, feasibility, and hemodynamic adaptations to high-load (HL) and low-load (LL) RE in patients with coronary artery disease (CAD). This study aimed to compare the safety, feasibility of HL-RE and LL-RE when combined with aerobic exercise (AE), and hemodynamic adaptations to HL and LL resistance exercise following the intervention. Seventy-nine patients with CAD were randomized either to HL-RE (70-80% of one-repetition maximum [1-RM]) and AE, LL-RE (35-40% of 1-RM) and AE or solely AE (50-80% of maximal power output) as a standard care, and 59 patients completed this study. We assessed safety and feasibility of HL-RE and LL-RE and we measured 1-RM on leg extension machine and hemodynamic response during HL- and LL-RE at baseline and post-training. The training intervention was safe, well tolerated, and completed without any adverse events. Adherence to RE protocols was excellent (100%). LL-RE was better tolerated than HL-RE, especially from the third to the final mesocycle of this study (Borgs' 0-10 scale difference: 1-2 points; p = 0.001-0.048). Improvement in 1-RM was greater following HL-RE (+31%, p < 0.001) and LL-RE (+23%, p < 0.001) compared with AE. Participation in HL-RE and LL-RE resulted in a decreased rating of perceived exertion during post-training HL- and LL-RE, but in the absence of post-training hemodynamic adaptations. The implementation of HL-RE or LL-RE combined with AE was safe, well tolerated and can be applied in the early phase of cardiac rehabilitation for patients with stable CAD.
Keyphrases
- high intensity
- physical activity
- randomized controlled trial
- healthcare
- coronary artery disease
- clinical trial
- end stage renal disease
- virtual reality
- quality improvement
- newly diagnosed
- machine learning
- double blind
- deep learning
- open label
- ejection fraction
- skeletal muscle
- prognostic factors
- phase iii
- phase ii
- pain management
- patient reported