QUANTITATIVE RISK ASSESSMENT IN PERIOPERATIVE SURGERY: A BIOMATHEMATICAL APPROACH TO ENHANCED RECOVERY AND PATIENT-CENTERED OUTCOMES

Abstract

The dynamic aspects of surgical stress, physiological response and recovery still complicate perioperative risk assessment especially when patient-centered outcomes are considered more important than fixed endpoints. A biomathematical model of perioperative trajectory is presented involving the combination of surgical stress, inflammatory dynamics and physiologic reserve into a time-resolved dynamical system. Enhanced Recovery After Surgery (ERAS) adherence is implemented as a continuous control input, which allows measuring quantitatively the effect of interventions on the risk of complications, recovery time, and quality-of-recovery measures. The hazard-based formulation of the time-varying physiological states is used to map time-varying physiological states to postoperative risk, and cumulative complication probability to vary with the current recovery processes. The simulations have shown that higher levels of ERAS adherence lead to faster inflammatory resolutions, maintenance of physiologic reserve and a significant decrease in individual and population-wide complication risk. Virtual cohort analyses also indicate that ERAS compliance changes risk distributions and reduces patient recovery time with heterogeneous patient groups, and inter-patient variability should be considered. Recovery measures compared to complication measures alone are more sensitive to intervention intensity, and recovery time and quality-of-recovery measures are more sensitive than complication measures. The suggested framework gives a mechanistic basis to quantitative perioperative decision support and sets the course of direction towards individual and adaptive recovery plans that are based on systems-level modeling.