Fig. 1

The optimal GSEM (model 6) founded on COGO concepts in relation to Pseudomonas and Acinetobacter infection data. Pseudomonas GO and Acinetobacter GO (ovals) are latent variables representing Pseudomonas and Acinetobacter gut overgrowth (GO), respectively. The variables in rectangles are binary predictor variables representing the group-level exposure to the following: a trauma ICU setting (trauma50), mean or median length of ICU stay ≥ 7 days (los7), exposure to a topical anti-septic-based prevention method (a_S), exposure to a TAP-based prevention method (tap), concurrency of a control group with a TAP intervention group (CC), exposure to a non-decontamination-based prevention method (non-D), use of mechanical ventilation for more than 90% of the group (mvp90), or exposure to PPAP (ppap). The circles contain error terms. The three-part boxes represent the count data for Pseudomonas and Acinetobacter VAP (v_ps_n, v_ac_n) and bacteremia (b_ps_n, b_ac_n). These counts are logit transformed with the total number of patients in each group as the denominator using the logit link function in the generalized model of the GSEM. Note that EAP use is confounded by PPAP use and that EAP use when separately entered into model 7 (ESM Fig S14) was non-significant