Effects of Sleep hours and Fatigue on Performance in Laparoscopic Surgery Simulators

Amine Chellali, PhD, Ganesh Sankaranarayanan, PhD, Likun Zhang, MSc, Caroline G.L. Cao, PhD, Suvranu De, ScD, Daniel B Jones, MD, Benjamin Schneider, MD

Cambridge Health Alliance, Harvard Medical School, Rensselaer Polytechnic Institute, Tufts University, Wright State University, Beth Israel Deaconess Medical Center

INTRODUCTION
Previous studies have demonstrated that residents who were sleep deprived post call make more errors when performing on a virtual reality (MIST VR) surgical simulator. Today, work hour restrictions assure enough sleep time for residents throughout the week. In this new context, the objective of this study was to assess the effects of perceived fatigue, sleep time and experience on surgical performance. We hypothesized that the performance of residents would decrease with less sleep and with fatigue, and increase with experience despite sleep deprivation and fatigue.

METHODS AND PROCEDURES
Twenty two surgical residents, fellows and attendings performed a peg transfer task on two surgical simulators: the Fundamentals of Laparoscopic Skills (FLS) trainer, and the Virtual Basic Laparoscopic Surgical Trainer (VBLaST), a virtual version of the FLS. The expertise level (EL) for residents was determined by the post-graduate year (PGY-1 to PGY-5), while level 6 was attributed to fellows and attendings. Participants completed questionnaires to assess their fatigue level (FL) using a 5-point Likert scale (varying from (1) well rested to (5) really tired), and sleep hours (SH) during the night preceding the test. Each subject performed 10 trials on each simulator. The order of simulators was counterbalanced. Subjects’ performance on each simulator was measured using the FLS normalized scores, and analyzed using a multiple regression model.

RESULTS
The results from the questionnaire and the performance scores are summarized in Table 1.

Table 1: questionnaire answers and performance scores

Table 1: questionnaire answers  and performance scores

The multiple regression analysis, using the Akaike Information Criterion (AIC) to choose the best-fit model, showed that sleep hours and perceived fatigue were not covariates. No correlation was found between experience level and sleep hours or fatigue. The factor coefficients for each model are summarized in Table 2.

Table 2: Multiple regression model coefficients

The resulting models are as follow:

FLSscore= (90.13)-(4.70*FL)+(3.33*EL)
VBLaSTscore= (47.96)+(5.65*EL)

Sleep hours and fatigue did not appear to affect performance, while expertise level was the most significant determinant of performance in both FLS and VBLaST.

CONCLUSION
In restricting work-hour for residents, the presumed increase in available sleep time is expected to lead to lower fatigue and better clinical performance. Our study shows that, on two different surgical simulators, resident and surgeon performance of the peg transfer task was not affected by sleep hours or perceived fatigue level. Rather, experience level was the most significant indicator of performance. Further investigation is needed to provide evidence to examine the complex relationship between sleep, fatigue, and clinical performance, and to support the practice of work-hour restriction for residents.


Session: Poster Presentation

Program Number: P158

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