Regional Planning for Extracorporeal Membrane Oxygenation Allocation During Coronavirus Disease 2019

Prekker, Matthew E.; Brunsvold, Melissa E.; Bohman, J. Kyle; Fischer, Gwenyth; Gram, Kendra L.; Litell, John M.; Saavedra-Romero, Ramiro; Hick, John L.

doi:10.1016/j.chest.2020.04.026

Cited by 40 publications

(39 citation statements)

References 12 publications

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“… 15 Additionally, the fundamental clinical presentation of patients with COVID-19 during the pandemic has been respiratory symptoms associated with hypoxia, often leading to subsequent respiratory failure and requiring ventilator support, extracorporeal membrane oxygenation, or both. 16 Our finding that a patient's minimum oxygen saturation value during their encounter was the strongest predictive feature of mortality is in line with global epidemiological observations that respiratory failure is the most common feature of critical illness and death in patients with COVID-19. 17 , 18 …”

Section: Discussionsupporting

confidence: 87%

Clinical features of COVID-19 mortality: development and validation of a clinical prediction model

Yadaw

Bose

et al. 2020

The Lancet Digital Health

247

229

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Background The COVID-19 pandemic has affected millions of individuals and caused hundreds of thousands of deaths worldwide. Predicting mortality among patients with COVID-19 who present with a spectrum of complications is very difficult, hindering the prognostication and management of the disease. We aimed to develop an accurate prediction model of COVID-19 mortality using unbiased computational methods, and identify the clinical features most predictive of this outcome. Methods In this prediction model development and validation study, we applied machine learning techniques to clinical data from a large cohort of patients with COVID-19 treated at the Mount Sinai Health System in New York City, NY, USA, to predict mortality. We analysed patient-level data captured in the Mount Sinai Data Warehouse database for individuals with a confirmed diagnosis of COVID-19 who had a health system encounter between March 9 and April 6, 2020. For initial analyses, we used patient data from March 9 to April 5, and randomly assigned (80:20) the patients to the development dataset or test dataset 1 (retrospective). Patient data for those with encounters on April 6, 2020, were used in test dataset 2 (prospective). We designed prediction models based on clinical features and patient characteristics during health system encounters to predict mortality using the development dataset. We assessed the resultant models in terms of the area under the receiver operating characteristic curve (AUC) score in the test datasets. Findings Using the development dataset (n=3841) and a systematic machine learning framework, we developed a COVID-19 mortality prediction model that showed high accuracy (AUC=0·91) when applied to test datasets of retrospective (n=961) and prospective (n=249) patients. This model was based on three clinical features: patient's age, minimum oxygen saturation over the course of their medical encounter, and type of patient encounter (inpatient vs outpatient and telehealth visits). Interpretation An accurate and parsimonious COVID-19 mortality prediction model based on three features might have utility in clinical settings to guide the management and prognostication of patients affected by this disease. External validation of this prediction model in other populations is needed. Funding National Institutes of Health.

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Section: Discussionsupporting

confidence: 87%

Clinical features of COVID-19 mortality: development and validation of a clinical prediction model

Yadaw

Bose

et al. 2020

The Lancet Digital Health

247

229

View full text Add to dashboard Cite

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“…Dear Editor, We would like to present a case of successful implementation of venovenous extracorporeal membrane oxygenation (ECMO) in a COVID-19 convalescent. Many experts suggest that during a pandemic ECMO should be applied in strictly defined cases for COVID-19 patients, mainly because of the resource-consuming nature of extracorporeal therapy [1,2]. Current guidelines state that ECMO is contraindicated after seven days of mechanical ventilation, including in critically ill COVID-19 patients [3].…”

Section: Implementation Of Veno-venous Extracorporeal Membrane Oxygenmentioning

confidence: 99%

Implementation of veno-venous extracorporeal membrane oxygenation in a COVID-19 convalescent

Gawda¹,

Marszalski²,

Molsa³

et al. 2020

ait

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“…In addition, a vast majority of COVID-19 patients develop a procoagulant state due to marked inflammatory response, responsible for venous thromboses and/or pulmonary embolism (13)(14)(15)(16), which in turn could induce thrombotic complications of ECMO and complicate the anticoagulation management of these patients (9). Finally, in the context of pandemic with limited ECMO services, patients with ARDS eligible for ECMO should be carefully selected (17)(18)(19)(20).…”

Section: Introductionmentioning

confidence: 99%

Use of Venovenous Extracorporeal Membrane Oxygenation in Critically-Ill Patients With COVID-19

et al. 2020

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Acute respiratory distress syndrome (ARDS) related to Coronavirus disease (COVID-19) is associated with high mortality. It has been suggested that venovenous extracorporeal membrane oxygenation (ECMO) was suitable in this indication, albeit the effects of ECMO on the mechanical respiratory parameters have been scarcely described. In this case-series, we prospectively described the use of venovenous ECMO and its effects on mechanical respiratory parameters in eleven COVID-19 patients with severe ARDS. Implantation of ECMO occurred 6 [3–11] days after the onset of mechanical ventilation. At the time of ECMO implantation, all patients received neuromuscular blocking agents, three (27%) received inhaled nitric oxide and prone positioning was performed in all patients with 4 [3−5] sessions of PP per patient. Under ECMO, the tidal volume was significantly decreased from 6.1 [4.0–6.3] to 3.4 [2.5–3.6] mL/kg of predicted body weight and the positive end-expiratory pressure level was increased by 25 ± 27% whereas the driving pressure and the mechanical power decreased by 33 ± 25% and 71 ± 27%, respectively. The PaO2/FiO2 ratio significantly increased from 68 [58–89] to 168 [137–218] and the oxygenation index significantly decreased from 28 [26–35] to 13 [10–15]. The duration of ECMO was 12 [8–25] days. Nine (82%) patients experienced ECMO-related complications and the main complication was major bleeding requiring blood transfusions. Intensive care unit mortality rate was 55% but no patient died from ECMO-related complications. In COVID-19 patients with severe ARDS, venovenous ECMO allowed ultra-protective ventilation, improved oxygenation and should be considered in highly selected patients with the most severe ARDS.

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Regional Planning for Extracorporeal Membrane Oxygenation Allocation During Coronavirus Disease 2019

Cited by 40 publications

References 12 publications

Clinical features of COVID-19 mortality: development and validation of a clinical prediction model

Clinical features of COVID-19 mortality: development and validation of a clinical prediction model

Implementation of veno-venous extracorporeal membrane oxygenation in a COVID-19 convalescent

Use of Venovenous Extracorporeal Membrane Oxygenation in Critically-Ill Patients With COVID-19

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