Machine learning can help personalize opioid-sparing strategies for outpatient surgeries.

• In a study of 223 patients, 42% required opioids, using a median of 4 doses post-surgery.
• The machine learning model identified key risk factors like active cancer and age, achieving an AUC of 0.674, with 70% sensitivity and 68% specificity.

Adoption of this model could refine pain management plans in surgical practice, reducing reliance on opioids and minimizing risks of dependence.

Surgical trainees show significant gaps in understanding critical cancer surgery standards, impacting surgical outcomes.

• Only 30% of trainees received formal training on CoC operative standards.
• Correct response rates were just 30% for CoC standards versus 50% for core cancer principles.

Incorporating education on these standards is crucial for improving surgical quality and documentation practices.

• 71% of residents actively contribute to operative documentation but lack foundational knowledge of standards.

A new embalming method offers superior realism for laparoscopic surgery training.

• Residents and experts rated laparoscopic procedures positively, especially TEP, with scores of “good” to “very good.”
• Novices rated lifelike tissue manipulation significantly higher than experts (p < 0.001).

This model may improve surgical education, leading to better outcomes for patients.

• Tissue quality and color also rated highly (p = 0.014 and p = 0.046).

Effective teamwork in the operating room significantly influences patient safety and surgical outcomes.

• Surgeons scored highest in teamwork and leadership, while circulating staff excelled in checklist completion and communication.
• Gender dynamics affected teamwork scores; male surgeons received lower ratings when their respondents were female.

Longer surgeries (over 3 hours) correlated with lower teamwork and communication scores.

Targeted education could enhance collaboration and reduce bias in surgical teams.