학술논문

Proactive screening algorithm for early onset pneumonia in patients with out-of-hospital cardiac arrest: a before-after implementation study
Document Type
Academic Journal
Source
Shock. Mar 25, 2024
Subject
Language
English
ISSN
1073-2322
Abstract
INTRODUCTION: Early Onset Pneumonia (EOP) occurs in around 50% of critically ill patients with out-of-hospital cardiac arrest (OHCA), and is associated with increased morbidity. Prompt diagnosis of EOP in these patients is difficult because of targeted temperature management and the post-cardiac arrest syndrome. We hypothesized that an algorithm for proactive screening of EOP would improve patient outcomes. METHODS: We conducted a single-center observational study comparing the outcomes of mechanically-ventilated adult patients with OHCA, before (study period 1) and after (study period 2) implementation of an algorithm for proactive diagnosis of EOP, including an early distal pulmonary specimen. An inverse probability treatment weighted (IPTW) multivariable regression was performed to identify independent parameters associated with duration of mechanical ventilation. A subgroup analysis was conducted in patients alive on day 5 after ICU admission. RESULTS: Over the 4-year study period, 190 patients (99 and 91 for study periods 1 and 2, respectively) were enrolled. The overall incidence of EOP was 57.4% and was similar between both study periods. Although there was no difference in the time-interval to antibiotic initiation, study period 2 was independently associated with higher SpO2/FiO2 ratios on days 3 and 4. We also observed a decrease in mechanical ventilation time in study period 2 (4.5 [1 – 11.3] versus 3 [2 – 5.8] days; p = 0.07), and this reached statistical significance in the subgroup analysis of patients alive at day 5 (10 [5 – 17] versus 5 [3 – 9] days, p = 0.01). CONCLUSION: In critically ill patients with OHCA, proactive diagnosis of EOP was not associated with a significant change in the time to antibiotic initiation. Further research is warranted to better define optimal diagnosis and management of EOP in this setting.