Operative Risk

Excerpt

One of the main challenges in surgery has long been to elaborate safe, effective, and technically feasible procedures for the best possible outcomes. Continuous progress in science and technology combined with cumulative experience in the field have refined indications for surgical treatment, prompted standardization of modern surgical techniques, and established comprehensive protocols in perioperative care. The most complex interventions can now be implemented with significantly reduced intraoperative trauma by using modern instruments and minimally invasive approaches. Surgical procedures became faster and safer, but complications are still prevalent, even in experienced hands.

Surgeons are challenged by another conundrum: to accurately select the best candidates for surgical treatment. While technical aspects of surgery are still crucial, an accurate prediction of immediate and long-term outcomes becomes an important part of an elective procedure that guides preoperative testing. Failure to identify patients at a high operative risk may be associated with inappropriate postoperative care and significantly increase in-hospital mortality. Preoperative risk factors and surgical complexity are predictive of treatment costs. Also, operative risk serves as a solid foundation for a future patient-surgeon relationship. Having the same understanding of the goals of surgical treatment and bearing the most realistic expectations about postoperative recovery and possible complications is important in a shared decision-making process.

The selection of patients for surgical treatment is still largely influenced by a surgeon’s personal experience and judgment. However, estimation of an individual risk/benefit ratio for a specific surgical procedure can help to more objectively adopt a nonoperative management strategy or select the best surgical procedure at the most appropriate point of time. This article aims to discuss the problem of operative risk, review common risk factors and available statistical models to predict adverse events after surgery, and speculate about some practical aspects of the operative risk assessment.