A novel machine learning model substantially improved our ability to predict IBD-related hospitalization and outpatient steroid use. This model could be used at point of care to distinguish patients at high and low risk for disease flare, allowing individualized therapeutic management.

IMPORTANCE Inflammatory bowel disease (IBD) is commonly treated with corticosteroids and anti-tumor necrosis factor (TNF) drugs; however, medications have well-described adverse effects. Prior work suggests that anti-TNF therapy may reduce all-cause mortality compared with prolonged corticosteroid use among Medicare and Medicaid beneficiaries with IBD.

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We utilized a multicompartment model to describe the effects of changes in tidal volume (VT) and positive end‐expiratory pressure (PEEP) on lung emptying during passive deflation before and after experimental lung injury. Expiratory time constants (τ E) were determined by partitioning the expiratory flow–volume (trueV˙ EV) curve into multiple discrete segments and individually calculating τ E for each segment. Under all conditions of PEEP and VT, τ E increased throughout expiration both before and after injury. Segmented τ E values increased throughout expiration with a slope that was different than zero (P < 0. 01). On average, τ E increased by 45.08 msec per segment. When an interaction between injury status and τ E segment was included in the model, it was significant (P < 0.05), indicating that later segments had higher τ E values post injury than early τ E segments. Higher PEEP and VT values were associated with higher τ E values. No evidence was found for an interaction between injury status and VT, or PEEP. The current experiment confirms previous observations that τ E values are smaller in subjects with injured lungs when compared to controls. We are the first to demonstrate changes in the pattern of τ E before and after injury when examined with a multiple compartment model. Finally, increases in PEEP or VT increased τ E throughout expiration, but did not appear to have effects that differed between the uninjured and injured state.

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