Andrea Cardoni

Background: The Macklin effect recently demonstrated a high positive predictive value for barotrauma in the COVID-19 ARDS population. However, there was less evidence available regarding the ARDS population without SARS-CoV-2 infection. We aim to analyze COVID-19 and non-COVID-19 ARDS subjects to assess the sensitivity and specificity of the Macklin effect in predicting the development of barotrauma in both groups. Methods: We retrospectively analyzed subjects with ARDS admitted to our center from January 2018 to November 2022. Experienced radiologists examined the presence of the Macklin effect on chest computed tomography scans. Subjects were then divided into two groups based on the presence or absence of the Macklin effect to assess its predictive power regarding barotrauma. Finally, we analyzed the impact of the Macklin effect and barotrauma on Intensive Care Unit and in-hospital mortality. Results: We analyzed 225 patients; the Macklin effect was observed in 44 subjects. In our cohort, the Macklin effect exhibited a sensitivity of 44.6% and a specificity of 90.6% in predicting barotrauma. After excluding the COVID-19 ARDS cases, the Macklin effect showed a sensitivity of 34.7% and a specificity of 93.6%. Nonetheless, in our population, the presence of the Macklin effect or the occurrence of barotrauma did not lead to increased ICU or in-hospital mortality. Conclusions: Our analysis highlighted that the Macklin effect demonstrates high specificity in predicting barotrauma but a low sensitivity; moreover, the development of barotrauma did not impact mortality, possibly due to the exclusion of mild to moderate ARDS and the inclusion of a significant number of ECMO recipients. Finally, the Macklin effect appears early during ARDS and may serve as an early indicator of lung frailty, potentially becoming an additional criterion for referral to centers for advanced ARDS treatment.

Background: Mechanical ventilation significantly improves patient survival but is associated with complications, increasing healthcare costs and morbidity. Identifying optimal weaning times is paramount to minimize these risks, yet current methods rely heavily on clinical judgment, lacking specificity. Methods: This study introduces a novel multiparametric predictive score, the MUSVIP (MUltiparametric Score for Ventilation discontinuation in Intensive care Patients), aimed at accurately predicting successful extubation. Conducted at Santo Stefano Hospital’s ICU, this single-center, observational, prospective cohort study will span over 12 months, enrolling adult patients undergoing invasive mechanical ventilation. The MUSVIP integrates variables measured before and during a spontaneous breathing trial (SBT) to formulate a predictive score. Results: Preliminary analyses suggest an Area Under the Curve (AUC) of 0.815 for the MUSVIP, indicating high predictive capacity. By systematically applying this score, we anticipate identifying patients likely to succeed in weaning earlier, potentially reducing ICU length of stay and associated healthcare costs. Conclusion: This study’s findings could significantly influence clinical practices, offering a robust, easy-to-use tool for optimizing weaning processes in ICUs.