Abstract:

Ventilator-associated pneumonia（VAP） is one of the most severe complications in ICU patients undergoing orotracheal intubation mechanical ventilation，significantly prolonging hospital stay，increasing medical costs，and elevating mortality rates. Standardized oral care can effectively reduce the incidence of VAP，current clinical practice still faces three core challenges：the inadequate applicability of traditional assessment tools for ICU patients，the controversy regarding the efficacy and safety of chlorhexidine solution concentration selection，and the generally low clinical implementation rate of oral care. To address these issues，this article systematically integrates evidence from the past decade literature，reviews the research progress in four dimensions of oral care for mechanical ventilation patients—“assessment，tool，solution，frequency”，and summarizes a three-step progressive clinical decision-making pathway termed “assessment-matching-adjustment.” This pathway integrates artificial intelligence visual recognition system and Intensive Care Oral Care Frequency Assessment Scale（ICOCFAS） to achieve precise assessment，matches nursing tools and solutions based on risk stratification and resource conditions，and dynamically adjusts the frequency of care via ICOCFAS scores. It aims to provide a structured，individualized practical strategy for clinical practice，promoting the transition of oral care toward standardization and precision. However，the overall efficacy of this decision-making pathway and its adaptability across different healthcare resource environments still require further validation and optimization through large-sample，multicenter real-world clinical studies.

Key words: Intensive Care Units, Oral Care, Pneumonia, Ventilator-Associated, Decision-Making Pathway, Artificial Intelligence, Review Literature as Topic