Predictive Ability of Preoperative Multidomain Risk Stratification for Inpatient Outcomes in Older Patients With Acute Cholecystitis Undergoing Cholecystectomy (
PRIOC
): Retrospective Prognostic Stu
Kate Wylde, Leon Flicker, Sally Burrows, Dieter Weber, Nicholas Chatman, Krystyna Drewniak, Mayura Iddagoda ABSTRACT
Background
The most common indication for cholecystectomy is acute cholecystitis, a condition associated with significant morbidity and mortality. Several tools are in practice to aid pre‐operative risk stratification. However, these scores have limited predictive ability in older, comorbid patients. The aim of this study was to investigate the predictive capability of the novel preoperative Multi Domain Risk Stratification (pMDRS) model in older patients with acute cholecystitis.
Methods
Two hundred consecutive patients admitted to a tertiary surgical unit with a diagnosis of acute cholecystitis and underwent a cholecystectomy were analysed. The pMDRS‐model was applied retrospectively; patients were risk stratified to low, moderate and high‐risk groups. Selected post‐operative outcomes of interest were analysed against the risk groups using regression models.
Results
Multivariate analysis (adjusted for age, sex, comorbidities and surgical‐approach) demonstrated prolonged hospital stay for the high‐risk group, incidence rate ratio (IRR) 2.67, (95% CI 1.38–5.17) and for the moderate‐risk group, (IRR) 1.90, (95% CI 1.16–3.11) compared with the low‐risk group. There were more medical complications in the high‐risk group, odds ratio (OR, 95% CI) 5.37, (1.05–28.03) and moderate group 2.73, (1.27–6.45) and more surgical complications in the high (OR, 95% CI) 1.60, (0.40–6.38) and moderate 1.65, (0.65–4.16) groups compared to low‐risk group. Medical Emergency Team calls (METc) demonstrated similar results in both high and moderate‐risk groups (OR, 95% CI 24.28, 2.96–198.93 and 7.10, 1.29–38.96).
Conclusion
The pMDRS model positively correlated with LOS, medical complications and METc. Surgical complications failed to demonstrate a significant relationship after adjustment for variables. A larger sample is required to evaluate the model's ability to predict mortality and functional outcomes.