A team of researchers, including Professor Monty Mythen, has identified two predictors of short-term mortality that could help clinicians and patients to make better decisions about surgery.
The study, published in October issue of Anesthesiology, looks for the ‘best’ risk stratification tool so patients make the most informed surgical decision.
Having the right tool to estimate surgical risk in patients at high risk for complications and death during and after surgery is crucially important. The team evaluated many tools, identifying two as most accurate predictors of short-term mortality, but both have limitations.
“Understanding the risk of a surgical procedure is essential so that patient consent can be fully informed and clinical teams can tailor perioperative care to the individual needs of each patient,” said Dr Suneetha Ramani Moonesinghe, Director of the UCL/UCLH Surgical Outcomes Research Centre and a Consultant in Anaesthetics and Intensive Care. “While there are many systems available to estimate surgical risk, few have been rigorously tested for accuracy, and even the best systems have limitations.”
Risk stratification tools are mathematical equations that offer the most widely available and resource-efficient means of predicting patient risk. The information gathered from these tools should be shared with patients so they can make the most informed decision about their surgery. For example, if a patient is at high risk for kidney failure during surgery, they need to be aware that they could be on dialysis for the rest of their life. Additionally, if there is high risk for a major complication or death, the patient may want to still proceed with the surgery, but may also want to discuss advanced directives and health care plans in view of this information.
For high-risk patients, the surgical team can opt to change the planned procedure to a less severe operation, delay surgery until risk factors for poor outcome have been treated, manage the patient after surgery in a critical care unit or possibly even decide to cancel the surgery if the operation was not life-saving (cancer surgery), but life-improving (joint replacement), according to Dr Moonesinghe.
The team researched medical literature to determine which tools were the most accurate predictors, when tested in studies of patient populations undergoing a variety of surgical procedures. Twenty-seven studies evaluating 34 risk stratification tools were identified.
The study found two systems to be the most accurate predictors of short-term mortality: the Portsmouth Physiological and Operative Scoring System for the enUmeration of Morbidity and Mortality (P-POSSUM) and the Surgical Risk Scale. However, the study notes that both systems have limitations. The P-POSSUM system includes some data which are only available during and after surgery, thus limiting its use for preoperative consultation. Also, the Surgical Risk Scale, while it is an entirely preoperative predictor, has only been tested in the United Kingdom.
“The ideal tool would include data which is available in entirety before the surgical procedure, would be simple and quick to use and provide a percentage estimate of the short-term risk of death following surgery, but such a tool remains elusive,” said Dr. Moonesinghe. “As the health care world embraces the concept of ‘shared decision making’ between patients and doctors, a risk stratification tool that enables patients to understand their complete operative risk would be hugely valuable.”
Risk stratification tools are one of many physician anesthesiologists use as the perioperative physician before, during and after surgery in the operating room. Their role includes evaluating the patient before surgery consulting with the surgical team, providing pain control and supporting life functions during surgery, supervising care after surgery and discharging the patient from the recovery unit.
To read Risk Stratification Tools for Predicting Morbidity and Mortality in Adult Patients Undergoing Major Surgery: Qualitative Systematic Review in full click here.
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