BREATHE: Bridging Registry Evidence to Assess the Postoperative Health Effects of Air Pollution - Air pollution, driven by both wildfire smoke and other ambient sources, is an increasingly significant public health concern in the United States. Despite recognition that air pollution dries adverse medical events, its acute effects on surgical outcomes remains largely unknown. Fine Particulate Matter (PM2.5), which is particularly elevated during wildfire events but also present from various human (ambient) sources, is a potent trigger of cardiopulmonary and inflammatory complications. These effects may overlap with the body’s physiological response to surgical stress, potentially increasing the risk of postoperative complications. Prior observational studies, including our own preliminary results at the University of Utah, indicate an increased risk of major postoperative morbidity from exposure to elevated PM2.5. Yet these studies largely do not distinguish between various types of surgeries and they examined a heterogenous mix of outcomes and exposures, such as chronic PM2.5 and proximity to roadways. This Early-Stage Investigator R01 therefore seeks to evaluate how short-term PM2.5 exposure, from both ambient and wildfire-attributed sources, influences postoperative cardiopulmonary outcomes across a national cohort of over 30 million surgical patients. Our long-term goal is to understand and mitigate the risk of PM2.5 exposure in surgical populations. Using the Multicenter Perioperative Outcomes Group (MPOG) registry, a large national registry from a diverse set of US states covering nearly all types of surgery, we plan to link PM2.5 exposure estimates to elective surgical cases in over 70 medical centers across the United States. This work will involve first using city-level exposure estimates, replicating landmark studies in air pollution epidemiology, and then to enhance the registry with patient ZIP Code level exposure and geographic contextual elements using a HIPAA compliant process in partnership with MPOG leadership. Thus, this research will dramatically improve the ability to perform environmental and social epidemiology research in the MPOG registry. In Aim 1, we will quantify the exposure- response thresholds using distributed lag-models and causal inference methods for both ambient and wildfire- attributed PM2.5. Aim 2 will identify key modifiers of this risk across a suite of related social and environmental modifiers, including rural status, surgical types, and pharmacological and demographic factors. Aim 3 will then develop an interpretable machine learning risk model for PM2.5 associated surgical complications, enabling translation into decision support tools. This project will deliver the first large-scale evidence of the acute effects of PM2.5, both from ambient and wildfire-attributed sources, on perioperative risks. The findings will inform future investigations on the potential for clinical risk counseling and could guide strategies such as dynamic scheduling or mitigation measures, including therapeutics. The work directly supports NHLBI’s mission by addressing environmental determinants of heart, lung, and blood complications in surgical patients, a high-risk and understudied population.
