Key result
The Revised Cardiac Risk Index and ACS NSQIP preoperative risk assessment tools demonstrate variable predictive accuracy and reliability across different surgical oncology patient populations.
Why the study?
Preoperative cardiac risk assessment tools like RCRI and NSQIP sacrifice predictive accuracy in certain surgical subpopulations, creating uncertainty about their reliability in surgical oncology patients.
Are the RCRI and ACS NSQIP preoperative risk assessment tools reliable for predicting major perioperative cardiac outcomes in surgical oncology patients?
Are the RCRI and ACS NSQIP preoperative risk assessment tools reliable for predicting major perioperative cardiac outcomes in surgical oncology patients?
Standard perioperative cardiac risk assessment tools like RCRI and ACS NSQIP may have limited predictive accuracy in certain surgical oncology subpopulations, necessitating tailored risk evaluation.
May limit precision of standard perioperative risk tools in select surgeries; leaves open development of more targeted models.
The Revised Cardiac Risk Index (RCRI) and the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) preoperative risk assessment tools are the most widely used methods for quantifying the risk of major negative perioperative cardiac outcomes that a patient may face during and after noncardiac surgery. However, these tools were created to include as wide a range of surgical factors as possible; thus, some predictive accuracy is sacrificed when it comes to certain surgical subpopulations. In this review, we explore the various surgical oncology patient populations for whom these assessment tools can be reliably applied and for whom they demonstrate poor reliability.
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Johnson et al. (2024) conducted a review in Surgical oncology patients requiring noncardiac surgery. Revised Cardiac Risk Index (RCRI) and ACS NSQIP preoperative risk assessment tools was evaluated. The Revised Cardiac Risk Index and ACS NSQIP preoperative risk assessment tools demonstrate variable predictive accuracy and reliability across different surgical oncology patient populations.
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