Correlations of kinematic data with robotic experience and duration of practice on complications and readmissions

Abstract

Robotic surgery is increasingly prevalent in thoracic surgery. Studies of specific kinematic data on outcomes are missing. The object of this study was to examine correlations between years in practice, robotic experience, and kinematic (motion) data on complications and readmissions. Kinematic data from the first lymph node dissection of anatomic robotic lung resections were combined with data from a prospectively maintained single institution database. Kinematic data included arm movement speed, economy of motion, and camera movement. Lobectomies and segmentectomies were matched and propensity-score weighted with inverse-probability treatment weights. Pearson's correlations, between years in practice, robotic experience, and kinematic data; and logistic regression; between years in practice and robotic experience on complications and readmissions were done. Lobectomies, 42, and segmentectomies, 31, from 2022 to 2023 were included. After matching, lymph nodes sampled were greater with lobectomies than segmentectomies, but other data were well matched; nodes sampled with lobes 13.4 vs 7.6 with segments, p < 0.001. Years in practice and robotic experience were not correlated with complications or readmissions. Significant correlations were noted between kinematic data and robotic experience. Length of stay had a negative correlation with robotic experience, -0.16, p < 0.001. No odds ratios were significant. In this small series, decreased length of stay was correlated with increased robotic experience which was a stronger outcome determinant than practice years. The complications and readmissions were not correlated with either measure. Increasing robotic experience may help optimize patient care but additional data are needed to establish usefulness of specific kinematic data.

Keywords: Correlations; Kinematics; Outcomes; Thoracic surgery.