Relevance of the LOEM Classification in Chronic Rhinosinusitis Management: A Retrospective Analysis of Surgical Outcomes

ABSTRACT Background The lack of a standardized framework for defining endoscopic sinus surgery (ESS) in chronic rhinosinusitis (CRS) has led to ambiguity and inconsistency in surgical descriptions. This study evaluates the recently described lamella ostium extent mucosa (LOEM) classification's usefulness, aiming to solidify its role in enhancing clinical decision‐making and the reproducibility of surgical studies. Methods A nonrandomized retrospective study compared CRS patients who underwent ESS, categorized into four groups based on LOEM. Baseline characteristics, disease severity, and QoL were compared at baseline and 2 years postsurgery. Predictors of clinically meaningful improvements in QoL were assessed using linear and logistic regression models, analyzing changes in the Sinonasal Outcome Test (SNOT)‐22. Additionally, a subgroup analysis evaluated QoL outcomes specific to different clinical phenotypes and the ESS type (t) performed. Results 305 patients were analyzed, with significant baseline differences across ESS groups, showing increasing disease severity and comorbidities from t1 to t4 surgeries. The t4 ESS showed the greatest postoperative improvements in SNOT‐22, nasal polyp score, and Lund Mackay scale. Multivariate regression confirmed t4 ESS as a significant predictor of greater QoL improvements and higher responder rates (OR = 8.49, p = 0.036). Subgroup analyses found that prior ESS negatively impacted outcomes, while t4 ESS was more effective across CRS phenotypes, except in exclusive atopy, where t3 ESS proved superior. Conclusions The LOEM classification correlates surgical complexity with disease burden. The t4 ESS demonstrated superior clinical outcomes, particularly in CRS patients with poorly controlled asthma, severe N‐ERD, or several prior ESS. These findings underscore the importance of personalized surgical planning and the potential utility of the LOEM system in optimizing patient outcomes.