Characteristics of the learning curve in robotic thoracic surgery in an emerging country.

Abstract

It is notestablishedwhich factors impact the learning curve (LC) in robotic thoracic surgery (RTS), especially in emerging countries. The aim of this study is to analyze LC in RTS in Brazil and identify factors that can accelerate LC. We selected the firstcasesof two Brazilian surgeons who started their LC. We used CUSUM and the Lowess technique to measure LC for each surgeon and Poisson regression to assess factors associated with shorter console time (CT). 58 patients were operated by each surgeon andincluded in the analysis. Surgeries performed weredifferent: Surgeon I (SI) performed 54 lobectomies (93.11%), whereas Surgeon II (SII) had a varied mix of cases. SI was proctored in hisfirst 10 cases (17.24%), while SIIin hisfirst 41 cases (70.68%). The mean interval between surgeries was 8days for SI and 16days for SII.There were differences in the LC phases of the two surgeons, mainlyregarding complications and conversions. There wasshorterCT by 30% in the presence of aproctor, and by 20% with the Da Vinci Xi. Mix of cases did not seem to contribute to faster LC. Higher frequency between surgeries seems to be associated with a faster curve. Presence of proctorand use of bolder technologiesreduced console time. We wonder ifin phase 3 itisnecessary to keep a proctoron complex cases to avoid serious complications. More studies are necessaryto understandwhich factors impact theLC.