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DOI 10.21203/rs.3.rs-3848514/v1

Медицинская библиотека · Research square · 2024

Predicting Acute Brain Injury in Venoarterial Extracorporeal Membrane Oxygenation Patients with Tree-Based Machine Learning: Analysis of the Extracorporeal Life Support Organization Registry.

Kalra Andrew, Bachina Preetham, Shou Benjamin L, Hwang Jaeho, Barshay Meylakh, Kulkarni Shreyas, Sears Isaac, Eickhoff Carsten, Bermudez Christian A, Brodie Daniel, Ventetuolo Corey E, Kim Bo Soo, Whitman Glenn J R, Abbasi Adeel, Cho Sung-Min

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Аннотация

OBJECTIVE

To determine if machine learning (ML) can predict acute brain injury (ABI) and identify modifiable risk factors for ABI in venoarterial extracorporeal membrane oxygenation (VA-ECMO) patients.

DESIGN

Retrospective cohort study of the Extracorporeal Life Support Organization (ELSO) Registry (2009-2021).

SETTING

International, multicenter registry study of 676 ECMO centers.

PATIENTS: Adults (≥18 years) supported with VA-ECMO or extracorporeal cardiopulmonary resuscitation (ECPR).

INTERVENTIONS: None.

MEASUREMENTS AND MAIN

RESULTS

Our primary outcome was ABI: central nervous system (CNS) ischemia, intracranial hemorrhage (ICH), brain death, and seizures. We utilized Random Forest, CatBoost, LightGBM and XGBoost ML algorithms (10-fold leave-one-out cross-validation) to predict and identify features most important for ABI. We extracted 65 total features: demographics, pre-ECMO/on-ECMO laboratory values, and pre-ECMO/on-ECMO settings.Of 35,855 VA-ECMO (non-ECPR) patients (median age=57.8 years, 66% male), 7.7% (n=2,769) experienced ABI. In VA-ECMO (non-ECPR), the area under the receiver-operator characteristics curves (AUC-ROC) to predict ABI, CNS ischemia, and ICH was 0.67, 0.67, and 0.62, respectively. The true positive, true negative, false positive, false negative, positive, and negative predictive values were 33%, 88%, 12%, 67%, 18%, and 94%, respectively for ABI. Longer ECMO duration, higher 24h ECMO pump flow, and higher on-ECMO PaO2 were associated with ABI.Of 10,775 ECPR patients (median age=57.1 years, 68% male), 16.5% (n=1,787) experienced ABI. The AUC-ROC for ABI, CNS ischemia, and ICH was 0.72, 0.73, and 0.69, respectively. The true positive, true negative, false positive, false negative, positive, and negative predictive values were 61%, 70%, 30%, 39%, 29% and 90%, respectively, for ABI. Longer ECMO duration, younger age, and higher 24h ECMO pump flow were associated with ABI.

CONCLUSIONS

This is the largest study predicting neurological complications on sufficiently powered international ECMO cohorts. Longer ECMO duration and higher 24h pump flow were associated with ABI in both non-ECPR and ECPR VA-ECMO.

Для цитирования: Kalra Andrew, Bachina Preetham, Shou Benjamin L, Hwang Jaeho, Barshay Meylakh, Kulkarni Shreyas, Sears Isaac, Eickhoff Carsten, Bermudez Christian A, Brodie Daniel, Ventetuolo Corey E, Kim Bo Soo, Whitman Glenn J R, Abbasi Adeel, Cho Sung-Min. Predicting Acute Brain Injury in Venoarterial Extracorporeal Membrane Oxygenation Patients with Tree-Based Machine Learning: Analysis of the Extracorporeal Life Support Organization Registry.. Research square. 2024. DOI: 10.21203/rs.3.rs-3848514/v1.
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