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Expert Rev Anti Infect Ther ; 22(6): 423-433, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38743435

ABSTRACT

INTRODUCTION: Hospital-acquired pneumonia (HAP) represents a significant cause of mortality among critically ill patients admitted to Intensive Care Units (ICUs). Timely and precise diagnosis is imperative to enhance therapeutic efficacy and patient outcomes. However, the diagnostic process is challenged by test limitations and a wide-ranging list of differential diagnoses, particularly in patients exhibiting escalating oxygen requirements, leukocytosis, and increased secretions. AREAS COVERED: This narrative review aims to update diagnostic modalities, facilitating the prompt identification of nosocomial pneumonia while guiding, developing, and assessing therapeutic interventions. A comprehensive literature review was conducted utilizing the MEDLINE/PubMed database from 2013 to April 2024. EXPERT OPINION: An integrated approach that integrates clinical, microbiological, and imaging tools is paramount. Progress in diagnostic techniques, including novel molecular methods, the expanding utilization and accuracy of bedside ultrasound, and the emergence of Artificial Intelligence, coupled with an improved comprehension of lung microbiota and host-pathogen interactions, continues to enhance our capability to accurately and swiftly identify HAP and its causative agents. This advancement enables the refinement of treatment strategies and facilitates the implementation of precision medicine approaches.


Subject(s)
Critical Illness , Healthcare-Associated Pneumonia , Intensive Care Units , Pneumonia, Bacterial , Humans , Pneumonia, Bacterial/diagnosis , Pneumonia, Bacterial/microbiology , Pneumonia, Bacterial/drug therapy , Healthcare-Associated Pneumonia/diagnosis , Healthcare-Associated Pneumonia/microbiology , Healthcare-Associated Pneumonia/therapy , Diagnosis, Differential , Host-Pathogen Interactions , Precision Medicine , Cross Infection/microbiology , Cross Infection/diagnosis , Cross Infection/drug therapy , Artificial Intelligence
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