Towards personalized care in minimally invasive esophageal surgery: An adverse events prediction model

This letter addressed the impactful study by Zhong et al, which introduced a risk prediction and stratification model for surgical adverse events following minimally invasive esophagectomy. By identifying key risk factors such as chronic obstructive pulmonary disease and hypoalbuminemia, the model demonstrated strong predictive accuracy and offered a pathway to personalized perioperative care. This correspondence highlighted the clinical significance, emphasizing its potential to optimize patient outcomes through tailored interventions. Further prospective validation and application across diverse settings are essential to realize its full potential in advancing esophageal surgery practices.