Hip Fracture Surgery: Most Sophisticated Mortality Predictor Yet?

A team from Stanford University and the US Department of Veterans Affairs (VA) set out to enhance surgeons’ ability to form a treatment plan for frail patients who are at high risk of complications and death after hip fracture surgery.

Their work, “A Tool to Estimate Risk of 30-day Mortality and Complications After Hip Fracture Surgery: Accurate Enough for Some but Not All Purposes? A Study From the ACS-NSQIP Database,” appears in the December 2022 edition of Clinical Orthopaedics and Related Research.

Citing issues with existing tools for predicting postoperative mortality and complications, the Stanford-VA team developed and validated a new tool, estimated the accuracy of risk prediction models for 30-day mortality and complications after hip fracture surgery, evaluated the accuracy of risk prediction thresholds for identifying very high-risk patients, and put the models in a web calculator.

“Some frail patients with hip fractures have low pre-fracture functioning and may have very high risk of postoperative mortality,” study author Alex H. S. Harris. M.S., Ph.D., told OTW, “making the choice between surgical and nonsurgical management more difficult.”

“For these patients and their families, high-quality informed consent and shared decision-making is essential. We sought to develop a tool to accurately estimate patient-specific risks of 30-day mortality and surgical complications that could inform and improve these processes.”

The team used data from 82,168 patients aged 18 years and older who had surgery for hip fracture in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) between 2011 and 2017. The majority (82%) were at least 70 years old, and 21% were at least 90 years old. The researchers found that 5% (4,260 of 82,168) of patients died within 30 days of surgery, and 8% (6,786 of 82,168) had a major complication.

Complex Risk-Reward Situation

According to the authors, “…the key challenge of prediction lies in identifying patients with very low probability of survival while also not restricting access to surgery for those who choose to take those risks. Although risk models cannot make these decisions, the evaluating accuracy metrics (such as, specificity, false discovery rate) of various thresholds of predicted risk can be described to and used within a shared decision-making process. To our knowledge, information on these tradeoffs is unavailable in any existing hip fracture prediction tool.”

“The models of mortality and complications we developed are accurate enough for personalizing informed consent and shared decision making with patient-specific risk estimates. However, many patients with high risk of mortality survive and therefore may benefit from surgery. Therefore, the models should not be used to restrict access to surgery for high-risk patients.”

“Next steps should include testing whether specific methods of providing model predictions, such as personalized informed consent, clinical decision support tools, and shared decision making that includes patient-specific risk estimates, can improve decision-making quality and patient outcomes.”