Impact of first-assistant experience on surgical efficiency in uni-port mediastinoscopic-assisted transhiatal esophagectomy

BACKGROUND: Uni-port mediastinoscopic-assisted transhiatal esophagectomy (UMATHE) is increasingly applied in minimally invasive esophageal cancer surgery, particularly for patients unsuitable for transthoracic procedures. This study aimed to quantitatively assess the independent impact of first-assistant experience on surgical efficiency and outcomes in UMATHE. METHODS: We retrospectively analyzed 179 consecutive UMATHE procedures performed by a single surgeon with 2 fixed assistants. Joinpoint regression identified the learning-curve inflection point. To explore temporal synchrony between assistant experience and surgical performance, we applied Seasonal-Trend decomposition using LOESS (STL) and cross-correlation analysis. Assistant experience (cumulative case count), identity, and surgeon learning phase were then incorporated into linear mixed-effects models (LMMs) and robust linear regression models (RLMs) to evaluate their effects on operative time and blood loss. RESULTS: Joinpoint regression identified a learning curve inflection at case 42. STL and cross-correlation analyses demonstrated synchronized improvement between assistant experience and operative performance. Assistant experience consistently predicted shorter operative time, with significance emerging in the basic model (P =.012) and strengthening after adjustment for learning phase and clinical covariates (P