Preoperative risk prediction tools that predict morbidity risk in adults undergoing surgery: An Evidence Review

Background and Context

Ahead of surgery, clinicians use risk prediction tools to assess the risks of the operation and plan the right level of care for each patient. Importantly, accurate risk prediction can help identify patients who can be safely treated in hubs designed for low-risk procedures. However, there are many risk prediction tools available with little guidance on their use across different surgical specialties and settings. 

Aims

We aimed to explore the evidence for 14 risk prediction tools currently used in Wales before planned (non-emergency) surgery for adults. We wanted to focus on the tools most suitable for selecting patients fit for surgery in low-risk settings. 

Strategy

We searched studies published between 1999 and 2024. We reviewed the performance of the 14 identified tools and selected the ones most relevant to the Welsh population for further analysis.

Outcomes

We found no evidence for two of the tools. For the remaining 12, we identified 118 studies across various specialties. The studies reported outcomes and measured performance differently, making it difficult to compare tools directly. None of the studies looked at the use of risk prediction tools in low-risk settings. 

We selected the ACS NSQIP, P-POSSUM, RCRI, and ASA tools for detailed analysis as they were felt to be most relevant to the Welsh population. We identified 76 studies for review. None of the four tools accurately predicted risks across all types of surgery, with performance varying by specialty. These findings are limited by the small number of studies looking at each type of surgery.

Impact

No one tool accurately predicted risks across all specialties, suggesting that some are better suited for assessing certain procedures than others. Also, there is no evidence on using risk prediction tools to identify patients suitable for surgery in low-risk settings. More research using consistent methods is needed to understand which tools work best for different surgical specialties and settings. 

Author: Praveena Pemmasani, Public Partnership Group Member

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