Abstract

Background: Perioperative mortality is 2-4 times higher in patients with cirrhosis compared to patients without cirrhosis due to cirrhosis-related factors such as portal hypertension and impaired hepatic synthetic function. Currently no models exist that accurately estimate peri-operative mortality and morbidity in patients with cirrhosis. Our overarching aim is to develop and validate a Cirrhosis-specific Surgical Risk Calculator (C- SuRC) that accurately estimates perioperative mortality and complications in patients with cirrhosis. Significance/Impact: Use of C-SuRC in routine pre-operative assessment of cirrhotic patients will optimize the selection of patients with cirrhosis for surgical procedures, improve access to elective surgery for patients with cirrhosis with low operative mortality, prevent surgeries in patients with prohibitively high operative mortality, and reduce emergency surgical presentations in patients who can safely undergo surgery electively. Innovation: • C-SuRC will be the first surgical risk calculator specifically designed for patients with cirrhosis that incorporates all three major classes of predictors that contribute to operative mortality in patients with cirrhosis, that is cirrhosis-related, surgery-related and comorbidity-related predictors. • C-SuRC will be developed using a unique dataset that we developed by merging VASQIP and CDW data. This is a nationally representative VA dataset of cirrhotic patients undergoing surgical procedures with prospectively collected baseline characteristics and surgical outcomes. • We will develop both traditional logistic regression models as well as novel machine learning (ML) models for C-SuRC and compare their discrimination, calibration and overall accuracy. • We will apply user-centered design to develop a web-based tool that executes C-SuRC. Specific Aims: SA1. Develop and internally validate a predictive model (the Cirrhosis-specific Surgical Risk Calculator or C-SuRC) that accurately estimates 30-day postoperative mortality in patients with cirrhosis using routinely available cirrhosis-related, comorbidity-related and surgery-related predictors. SA2. a. Compare the performance characteristics of C-SuRC to those of the existing VASQIP, NSQIP and Mayo Clinic surgical risk calculators, and b. Externally validate C-SuRC using a dataset of cirrhotic patients at the Mayo clinic. SA3. a. Develop a web-based tool that executes C-SuRC to estimate 30-day mortality in cirrhotic patients undergoing surgery, and b. Apply best practices in user-centered design to improve the user interface. Methodology: We will use conventional logistic regression models as well as novel machine learning models for C-SuRC development. We will formally test the discrimination, calibration and accuracy of C-SuRC, externally validate it and compare it to existing surgical risk calculators. We will use best practices in user- centered design to develop a web-based tool that executes C-SuRC for use in routine clinical practice. Next Steps/Implementation: We will solicit support from all important VA stakeholders, many of whom have already endorsed this proposal, and disseminate our findings and the web-based C-SuRC tool in the VA nationally as a routine instrument in the pre-operative assessment of patients with cirrhosis.

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DRA: Digestive Diseases, Other Conditions

DRE: Prognosis, TRL - Applied/Translational, Treatment - Implementation

Keywords: Data Management, Healthcare Algorithms, Surveillance

MeSH Terms: None at this time.