Impact of Noninvasive Respiratory Support in Patients With COVID-19 Requiring Veno-Venous Extracorporeal Membrane Oxygenation: A Question of Time?

Presti, Federica Lo; Santo, Luca Salvatore De; Esquinas, António M.

doi:10.1097/mat.0000000000001773

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…These patients also spent more time on ECMO, which likely influenced oxygenator lifespan and led to increased circuit and oxygenator exchanges. A number of other factors may have contributed to mortality in this study that were not directly accounted for, including time of cannulation throughout the pandemic, [17][18][19][20] SARS-CoV-2 variant strain, days spent on non-invasive respiratory support, 21,22 and others. Interestingly, of the three patients who did not demonstrates signs of RV failure and underwent empiric VP cannulation, mortality was only 33%.…”

Section: Discussionmentioning

confidence: 99%

Physiologic benefits of veno-pulmonary extracorporeal membrane oxygenation for COVID-19 ARDS: A single center experience

Grotberg,

Greenberg,

Sullivan

et al. 2024

Int J Artif Organs

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Background: A subset of patients with COVID-19 acute respiratory distress syndrome (ARDS) require extracorporeal membrane oxygenation (ECMO). Veno-pulmonary (VP) ECMO provides support to the right ventricle and decreased risk of recirculation. Methods: A retrospective analysis of patients with COVID-19 ARDS and VP ECMO was performed. Patients were separated into groups by indication (1) “right ventricular (RV) failure,” (2) “refractory hypoxemia,” and (3) “recurrent suck-down events (SDEs).” Pre- and post-configuration vasoactive inotropic scores (VIS), fraction of inspired oxygen (FIO2), and resolution of SDEs were reported. A 90-day mortality was computed for all groups. Patients were also compared to those who underwent conventional venovenous (VV) ECMO. Results: Forty-seven patients underwent VP ECMO configuration, 18 in group 1, 16 in group 2, and 8 in group 3. Ninety-day mortality was 66% for the entire cohort and was 77.8%, 81.3% and 37.5% for groups 1, 2, and 3, respectively. Mean VIS decreased in group 1 (8.3 vs 2.9, p = 0.005), while mean FIO2 decreased in the group 2 and was sustained at 72 h (82.5% vs 52.5% and 47.5%, p < 0.001). Six of the eight (75%) of patients with recurrent SDEs had resolution of these events after configuration to VP ECMO. Patients with VP ECMO spent more days on ECMO (33 days compared to 18 days, p = 0.004) with no difference in mortality (66% compared to 55.1%, p = 0.28). Conclusion: VP ECMO in COVID-19 ARDS improves hemodynamics in patients with RV failure, improves oxygenation in patients with refractory hypoxemia and improves the frequency of SDEs.

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Section: Discussionmentioning

confidence: 99%

Physiologic benefits of veno-pulmonary extracorporeal membrane oxygenation for COVID-19 ARDS: A single center experience

Grotberg,

Greenberg,

Sullivan

et al. 2024

Int J Artif Organs

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“…We thank Lo Presti et al 1 for their letter related to our examination of the impact of duration of noninvasive respiratory support (RS) in patients with COVID-19 supported with extracorporeal membrane oxygenation (ECMO). The points raised highlight the challenges faced in the retrospective analysis of a complex disease process.…”

Section: To the Editormentioning

confidence: 99%

Duration of Noninvasive Respiratory Support and Extracorporeal Membrane Oxygenation Outcomes: Connecting the Dots

et al. 2022

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Multi-horizon predictive models for guiding extracorporeal resource allocation in critically ill COVID-19 patients

Xue

Shah

Yang

et al. 2022

Journal of the American Medical Informatics Association

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Objective Extracorporeal membrane oxygenation (ECMO) resource allocation tools are currently lacking. We developed machine learning (ML) models for predicting COVID-19 patients at risk of receiving ECMO to guide patient triage and resource allocation. Material and methods We included COVID-19 patients admitted to intensive care units for >24 hours from March 2020 to October 2021, divided into training and testing development and testing only holdout cohorts. We developed ECMO-deployment timely prediction model ForecastECMO using Gradient Boosting Tree (GBT), with pre-ECMO prediction horizons from 0-48 hours, compared to PaO2/FiO2 (PF) ratio, Sequential Organ Failure Assessment (SOFA) score, PREdiction of Survival on ECMO Therapy-Score (PRESET) score, logistic regression (LR), and 30 pre-selected clinical variables GBT Clinical GBT models, with area under the receiver operator curve (AUROC) and precision recall curve (AUPRC) metrics. Results ECMO prevalence was 2.89% and 1.73% in development and holdout cohorts. ForecastECMO had the best performance in both cohorts. At the 18-hour prediction horizon, a potentially clinically actionable pre-ECMO window, ForecastECMO had the highest AUROC (0.94 & 0.95) and AUPRC (0.54 & 0.37) in development and holdout cohorts in identifying ECMO patients without data 18-hours prior to ECMO. Discussion and conclusion We developed a multi-horizon model, ForecastECMO, with high performance in identifying patients receiving ECMO at various prediction horizons. This model has potential to be used as early alert tool to guide ECMO resource allocation for COVID-19 patients. Future prospective multi-center validation would provide evidence for generalizability and real-world application of such models to improve patient outcomes.

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Impact of Noninvasive Respiratory Support in Patients With COVID-19 Requiring Veno-Venous Extracorporeal Membrane Oxygenation: A Question of Time?

Cited by 3 publications

References 5 publications

Physiologic benefits of veno-pulmonary extracorporeal membrane oxygenation for COVID-19 ARDS: A single center experience

Physiologic benefits of veno-pulmonary extracorporeal membrane oxygenation for COVID-19 ARDS: A single center experience

Duration of Noninvasive Respiratory Support and Extracorporeal Membrane Oxygenation Outcomes: Connecting the Dots

Multi-horizon predictive models for guiding extracorporeal resource allocation in critically ill COVID-19 patients

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