AUTHOR=Yang Boshen , Xu Sixuan , Wang Di , Chen Yu , Zhou Zhenfa , Shen Chengxing 

TITLE=ACEI/ARB Medication During ICU Stay Decrease All-Cause In-hospital Mortality in Critically Ill Patients With Hypertension: A Retrospective Cohort Study Based on Machine Learning

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 8 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2021.787740

DOI=10.3389/fcvm.2021.787740

ISSN=2297-055X

ABSTRACT=Background:
Hypertension is a rather common comorbidity among critically ill patients and hospital mortality might be higher among critically ill patients with hypertension (SBP ≥ 140mmHg and/or DBP ≥ 90mmHg). The aim of this study was to explore the association between ACEI/ ARB medication during ICU stay and all-cause in-hospital mortality in these patients.
Methods:
A retrospective cohort study was performed based on data from Medical Information Mart for Intensive Care IV (MIMIC-IV) database, which consisted of more than 40,000 patients in ICU between 2008 to 2019 at Beth Israel Deaconess Medical Center. Adults diagnosed with hypertension on admission and those had high blood pressure (SBP ≥ 140mmHg and/ or DBP ≥ 90mmHg) during ICU stay were included. The primary outcome was all-cause in-hospital mortality. Patients were divided into ACEI/ARB treated and non-treated group during ICU stay. Propensity score matching (PSM) was used to adjust potential confounders. Nine machine learning models were developed and validated based on 37 clinical and laboratory features of all patients. The model with best performance was selected based on area under the receiver operating characteristic curve (AUC) followed by 5-fold cross-validation. After hyperparameter optimization using Grid and random hyperparameter search, a final LightGBM model was developed, and Shapley Additive exPlanations (SHAP) values were calculated to evaluate feature importance of each feature. The features closely associated with hospital mortality were presented as significant features.
Results:	
A total of 15352 patients were enrolled in this study, among whom 5193 (33.8%) patients were treated with ACEI/ARB. A significant lower all-cause in-hospital mortality was observed among patients treated with ACEI/ARB (3.9% vs. 12.7%) as well as a lower 28-day mortality (3.6% vs. 12.2%). The outcome remained consistent after a propensity score matching. Among nine machine learning models, the LightGBM model had the highest AUC=0.9935. The SHAP plot was employed to make the model interpretable based on LightGBM model after hyperparameter optimization, showing that ACEI/ARB use was among the top five significant features, which were associated with hospital mortality. 
Conclusions:
The use of ACEI/ARB in critically ill patients with hypertension during ICU stay is related to lower all-cause in-hospital mortality.