The Flexible Accumulation Model for High Density Temporal Exposures

TL;DR

This paper introduces the FLAME model and tools to analyze how the number and duration of episodic exposures influence disease risk, demonstrated through a case study on hypotension during cardiac surgery and AKI risk.

Contribution

The paper presents the FLAME model and R package for flexible analysis of high-density temporal exposure data, addressing a key scientific question about exposure patterns and disease risk.

Findings

Longer hypotensive episodes significantly increase AKI risk.

The model quantifies risk accumulation as a function of exposure duration and frequency.

Results guide intraoperative hemodynamics management strategies.

Abstract

Emerging technologies enable continuous monitoring of temporal exposures to disease risk factors, leading to complex structures in the exposure process that consists of a subject-specific number and duration of exposure episodes. A key scientific question is how does the number and duration of episodic exposure affect disease risk. We address this question by introducing the FLexible Accumulation ModEl (FLAME) and the associated inferential tools, whose finite sample performance is evaluated through comprehensive simulations. FLAME is motivated by and applied to quantifying the association between hypotensive exposure during cardiac surgery and acute kidney injury (AKI). Our results characterize the AKI risk accumulation pattern as a function of hypotensive duration and shows that while 60 one-minute episodes is associated with an AKI probability of 0.23, a single sustained sixty-minute hypotensive episode raises that probability to 0.32, a 37\% increase despite the same total duration. These results offer direct guidance for improving hemodynamics risk management strategies during intraoperative care. Our method is accompanied by the R package flame.