PREOPERATIVE WALKING RECOMMENDATION FOR NON-CARDIAC SURGERY PATIENTS TO REDUCE THE LENGTH OF HOSPITAL STAY: A RANDOMIZED CONTROL TRIAL
Background: Even though the importance of preparing patients for a surgical event is recognized, there are still gaps about the benefit of improving functional capacity by walking during the waiting time among patients scheduled for non-cardiac surgery. This study aimed to evaluate the impact of pre-surgical walking in-hospital length of stay, early ambulation, and the appearance of complications after surgery among patients scheduled for non-cardiac surgery. Methods: A two-arm, single-blinded randomized controlled trial was developed from May 2016 to August 2017. Eligible outpatients scheduled for non-cardiac surgery, capable of walking, were randomized (2:1 ratio) to receive a prescription of walking 150 minutes/week during the whole pre-surgical waiting time (n = 249) or conventional care (n = 119). The primary outcome was the difference in hospital length of stay. Secondary results were time to the first ambulation during hospitalization, description of ischemic events during hospitalization, six months of hospital discharge, and the walking continuation. We performed an intention to treat analysis and compared length of stay between both groups by Kaplan-Meier estimator (log-rank test). Results: There were no significant differences in the length of hospital stay between both groups (log-rank test p = 0.367) and no differences in the first ambulation time during hospitalization (log-rank test p=0.299). Similar rates of postoperative complications were observed in both groups, but the intervention group patients continued to practice walking six months after discharge (p<0.001). Conclusion: Our study is the first clinical trial evaluating the impact of walking before non-cardiac surgery in the length of stay, early ambulation, and complications after surgery. Prescription of walking for patients before non-cardiac surgery had no significant effect in reducing the length of stay, early ambulation, and complications but promoted the walking up six months after discharge. The results become a crucial element for further investigation.
Steps to reproduce
Continuous variables were described using means (standard deviation) or medians (interquartile range) when non-normally distributed. Alternatively, we performed a logarithmic transformation to reduce said asymmetry. Discrete variables were described as counts (percentages). The Student's t-test was used to evaluate differences in means of continuous variables between study groups or the non-parametric Kruskal-Wallis test to contrast variables whose distribution was not expected. We used the chi-squared test or the Fisher's exact test to assess differences in the distribution of discrete variables whenever the count expected in any cell of the contingency tables was <5 observations. Finally, a time-to-event analysis was performed, employing the Kaplan-Meier estimator and the log-rank test to determine differences in the hospital stay or the first walk between the intervention and the conventional group