Why the study?
Senior surgeon presence is vital for high-risk emergency surgery, but 24-hour consultant cover is inefficient, creating a need for a user-friendly toolbox to guide senior surgeon involvement.
Does a risk assessment toolbox accurately predict mortality and morbidity to direct senior surgeons' involvement in emergency general surgery?
Does a risk assessment toolbox accurately predict mortality and morbidity to direct senior surgeons' involvement in emergency general surgery?
A simple risk assessment tool using ASA score, age, and BUN can accurately predict mortality in emergency general surgery to guide senior surgeon involvement.
Supports mortality prediction with ASA, age, and BUN in emergency surgery; leaves open effects on morbidity or directing senior involvement.
BACKGROUND: Having a senior surgeon present for high-risk patients is an important safety measure in emergency surgery, but 24-h consultant cover is not efficient. We aimed to develop a user-friendly toolbox (risk identification, outcome prediction and patient stratification) to support when to involve a senior surgeon. MATERIALS AND METHODS: We included 11,901 general surgery patients (10.0% emergencies) in a multicenter prospective cohort in China (2015-2016). Patient information and surgeons' seniority were compared between emergency and elective surgery with the same procedure codes. Risk indicators common in these two surgical timings and specific to emergency surgery were identified, and their clinical importance was evaluated by a working group of 48 experienced surgeons. Predictive models for mortality and morbidity were built using logistic regression models. Stratification rules were created to balance patients' risk and surgeons' caseload with an Acute Call Team (ACT) model. RESULTS: Emergency patients had significantly higher risks of mortality (3.6% vs 0.6%) and morbidity (7.8% vs 4.3%) than elective patients, but disproportionally fewer senior surgeons (59.9% vs 91.4%) were present. Using three risk indicators (American Society of Anesthesiologists score, age, blood urea nitrogen), C-statistic (95% CI) for prediction of emergency mortality was high [0.90 (0.84-0.96)]. It was less complex but equally accurate as two existing and validated models (0.86 [0.79-0.93] and 0.86 [0.77-0.95]). Using five indicators, C-statistic (95% CI) was moderate for prediction of overall morbidity [0.77 (0.72-0.83)], but high for severe morbidity [0.92 (0.88-0.97)]. Based on stratification rules of the ACT model, patient mortality and morbidity were 0.5% and 5.3% in the low-risk stratum (composing 64.6% of emergency caseload), and 15.9% and 29.0% in the very high-risk stratum (6.9% of caseload). CONCLUSION: These findings show the practical feasibility of using a risk assessment tool to direct senior surgeons' involvement in emergency general surgery.
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Yu et al. (2020) studied this question.
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