Association of Ventilator Settings With Mortality in Pediatric Patients Treated With Extracorporeal Life Support for Respiratory Failure.

Extracorporeal life support (ECLS) is a treatment for acute respiratory failure that can provide extracorporeal gas exchange, allowing lung rest. However, while most patients remain mechanically ventilated during ECLS, there is a paucity of evidence to guide the choice of ventilator settings. We studied the associations between ventilator settings 24 hours after ECLS initiation and mortality in pediatric patients using a retrospective analysis of data from the Extracorporeal Life Support Organization Registry. 3497 patients, 29 days to 18 years of age, treated with ECLS for respiratory failure between 2015 and 2021, were included for analysis. 93.3% of patients on ECLS were ventilated with conventional mechanical ventilation. Common settings included positive end-expiratory pressure (PEEP) of 10 cm H 2 O (45.7%), delta pressure (ΔP) of 10 cm H 2 O (28.3%), rate of 10-14 breaths per minute (55.9%), and fraction of inspired oxygen (FiO 2 ) of 0.31-0.4 (30.3%). In a multivariate model, PEEP >10 cm H 2 O ( versus PEEP < 8 cm H 2 O, odds ratio [OR]: 1.53, 95% CI: 1.20-1.96) and FiO 2 ≥0.45 ( versus FiO 2 < 0.4; 0.45 ≤ FiO 2 < 0.6, OR: 1.31, 95% CI: 1.03-1.67 and FiO 2 ≥ 0.6, OR: 2.30; 95% CI: 1.81-2.93) were associated with higher odds of mortality. In a secondary analysis of survivors, PEEP 8-10 cm H 2 O was associated with shorter ECLS run times ( versus PEEP < 8 cm H 2 O, coefficient: -1.64, 95% CI: -3.17 to -0.11), as was ΔP >16 cm H 2 O ( versus ΔP < 10 cm H 2 O, coefficient: -2.72, 95% CI: -4.30 to -1.15). Our results identified several categories of ventilator settings as associated with mortality or ECLS run-time. Further studies are necessary to understand whether these results represent a causal relationship.

Distribution of Ventilation Measured by Electrical Impedance Tomography in Critically Ill Children.

BACKGROUND: Electrical impedance tomography (EIT) is a noninvasive, portable lung imaging technique that provides functional distribution of ventilation. We aimed to describe the relationship between the distribution of ventilation by mode of ventilation and level of oxygenation impairment in children who are critically ill. We also aimed to describe the safety of EIT application. METHODS: A prospective observational study of EIT images obtained from subjects in the pediatric ICU. Images were categorized by whether the subjects were on intermittent mandatory ventilation (IMV), continuous spontaneous ventilation, or no positive-pressure ventilation. Images were categorized by the level of oxygenation impairment when using [Formula: see text]/[Formula: see text]. Distribution of ventilation is described by the center of ventilation. RESULTS: Sixty-four images were obtained from 25 subjects. Forty-two images obtained during IMV with a mean ± SD center of ventilation of 55 ± 6%, 14 images during continuous spontaneous ventilation with a mean ± SD center of ventilation of 48.1 ± 11%, and 8 images during no positive-pressure ventilation with a mean ± SD center of ventilation of 47.5 ± 10%. Seventeen images obtained from subjects with moderate oxygenation impairment with a mean ± SD center of ventilation of 59.3 ± 1.9%, 12 with mild oxygenation impairment with a mean ± SD center of ventilation of 52.6 ± 2.3%, and 4 without oxygenation impairment with a mean ± SD center of ventilation of 48.3 ± 4%. There was more ventral distribution of ventilation with IMV versus continuous spontaneous ventilation (P = .009), with IMV versus no positive-pressure ventilation (P = .01) cohorts, and with moderate oxygenation impairment versus cohorts without oxygenation impairment (P = .009). There were no adverse events related to the placement and use of EIT in our study. CONCLUSIONS: Children who had worse oxygen impairment or who received controlled modes of ventilation had more ventral distribution of ventilation than those without oxygen impairment or the subjects who were spontaneously breathing. The ability of EIT to detect changes in the distribution of ventilation in real time may allow for distribution-targeted mechanical ventilation strategies to be deployed proactively; however, future studies are needed to determine the effectiveness of such a strategy.