Role of cardiopulmonary interactions in development of ventilator-induced lung injury-Experimental evidence and clinical Implications

The place of positive end expiratory pressure in ventilator-induced lung injury generation

PURPOSE OF REVIEW

Describe the rationale for concern and accumulating pathophysiologic evidence regarding the adverse effects of high-level positive end expiratory pressure (PEEP) on excessive mechanical stress and ventilator-induced lung injury (VILI).

RECENT FINDINGS

Although the inclusion of PEEP in numerical estimates of mechanical power may be theoretically debated, its potential to increase stress, strain, and mean airway pressure are not. Recent laboratory data in a variety of animal models demonstrate that higher levels of PEEP coupled with additional fluids needed to offset its impediment of hemodynamic function are associated with increased VILI. Moreover, counteracting end-tidal hyperinflation by external chest wall pressure may paradoxically improve respiratory mechanics, indicating that lower PEEP helps protect the small 'baby lung' of advanced acute respiratory distress syndrome (ARDS).

SUMMARY

The potentially adverse effects of PEEP on VILI can be considered in three broad categories. First, the contribution of PEEP to total mechanical energy expressed through mechanical power, raised mean airway pressure, and end-tidal hyperinflation; second, the hemodynamic consequences of altered cardiac loading, heightened pulmonary vascular stress and total lung water; and third, the ventilatory consequences of compromised carbon dioxide eliminating efficiency. Minimizing ventilation demands, optimized body positioning and care to avoid unnecessary PEEP are central to lung protection in all stages of ARDS.

Prognostic value of oxygen saturation index trajectory phenotypes on ICU mortality in mechanically ventilated patients: a multi-database retrospective cohort study

BACKGROUND

Heterogeneity among critically ill patients undergoing invasive mechanical ventilation (IMV) treatment could result in high mortality rates. Currently, there are no well-established indicators to help identify patients with a poor prognosis in advance, which limits physicians' ability to provide personalized treatment. This study aimed to investigate the association of oxygen saturation index (OSI) trajectory phenotypes with intensive care unit (ICU) mortality and ventilation-free days (VFDs) from a dynamic and longitudinal perspective.

METHODS

A group-based trajectory model was used to identify the OSI-trajectory phenotypes. Associations between the OSI-trajectory phenotypes and ICU mortality were analyzed using doubly robust analyses. Then, a predictive model was constructed to distinguish patients with poor prognosis phenotypes.

RESULTS

Four OSI-trajectory phenotypes were identified in 3378 patients: low-level stable, ascending, descending, and high-level stable. Patients with the high-level stable phenotype had the highest mortality and fewest VFDs. The doubly robust estimation, after adjusting for unbalanced covariates in a model using the XGBoost method for generating propensity scores, revealed that both high-level stable and ascending phenotypes were associated with higher mortality rates (odds ratio [OR]: 1.422, 95% confidence interval [CI] 1.246-1.623; OR: 1.097, 95% CI 1.027-1.172, respectively), while the descending phenotype showed similar ICU mortality rates to the low-level stable phenotype (odds ratio [OR] 0.986, 95% confidence interval [CI] 0.940-1.035). The predictive model could help identify patients with ascending or high-level stable phenotypes at an early stage (area under the curve [AUC] in the training dataset: 0.851 [0.827-0.875]; AUC in the validation dataset: 0.743 [0.709-0.777]).

CONCLUSIONS

Dynamic OSI-trajectory phenotypes were closely related to the mortality of ICU patients requiring IMV treatment and might be a useful prognostic indicator in critically ill patients.