Affiliation:
1. Department of Surgery John Hunter Hospital Newcastle New South Wales Australia
2. School of Medicine and Public Health University of Newcastle Newcastle New South Wales Australia
3. Hunter Medical Research Institute Newcastle New South Wales Australia
4. Medical School University of Western Australia Crawley Western Australia Australia
5. School of Biomedical Sciences and Pharmacy University of Newcastle New South Wales Australia
Abstract
AbstractBackgroundRisk assessment for emergency laparotomy (EL) is important for guiding decision‐making and anticipating the level of perioperative care in acute clinical settings. While established tools such as the American College of Surgeons National Surgical Quality Improvement Program calculator (ACS‐NSQIP), the National Emergency Laparotomy Audit Risk Prediction Calculator (NELA) and the Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity calculation (P‐POSSUM) are accurate predictors for mortality, there has been increasing recognition of the benefits from including measurements for frailty in a simple and quantifiable manner. Psoas muscle to 3rd lumbar vertebra area ratio (PM:L3) measured on CT scans was proven to have a significant inverse association with 30‐, 90‐ and 365‐day mortality in EL patients.MethodsA retrospective analysis was conducted of 500 patients admitted to four Australian hospitals who underwent EL during 2016–2017, and had contemporaneous abdomino‐pelvic CT scans. Radiological sarcopenia was measured as PM:L3 ratios. ASC‐NSQIP, NELA and P‐POSSUM were retrospectively calculated. Univariate and multivariate logistic regression modelling was used to assess these ratios and scores, as well as American Society of Anaesthesiologists (ASA) classification separated into ASA I‐III and IV/V (simplified ASA), as potential predictors of 30‐, 90‐ and 365‐day mortality.ResultsPM:L3, simplified ASA, ACS‐NSQIP, NELA and P‐POSSUM were each statistically significant predictors of 30‐day, 90‐day and 365‐day mortality (P < 0.001). Logistic regression models of 30‐, 90‐ and 365‐day mortality combining PM:L3 (P = 0.001) and simplified ASA (P < 0.001) exhibited AUCs of 0.838 (0.780, 0.896), 0.805 (0.751, 0.860) and 0.775 (0.729, 0.822), respectively, which were comparable to that of ACS‐NSQIP and NELA.ConclusionCombining the semi‐physiological parameter ASA classification with PM:L3 provides a quick and simple alternative to the more complex established risk assessment scores and is superior to PM:L3 alone.