Probabilistic clinical studies and deterministic physiology: building a Monte Carlo bridge with the "Frank" project

ABSTRACT Objective: To resolve the apparent paradox between deterministic physiological laws and probabilistic clinical outcomes by framing clinical variability as epistemic uncertainty within a complex, non-linear system, demonstrating how deterministic mechanisms can account for empirical distributions and outcome heterogeneity.

Methods

We developed the "Frank" project, a 0-dimensional computational agent-based model (ABM) of human cardiovascular hemodynamics implemented in Julia (Agents.jl). Using Monte Carlo simulations (n=100), myocardial infarction was modeled by varying initial conditions, specifically sampling the infarction area from a Gaussian distribution along with systemic compliance. Cardiogenic shock was defined by a systolic arterial pressure <90mmHg and a cardiac index <2.2L/min/m2, with parameters evaluated via grid search against literature incidence benchmarks (5-10%).