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. 2021 Feb 12:11:611435.
doi: 10.3389/fendo.2020.611435. eCollection 2020.

Association Between Obesity and Short-And Long-Term Mortality in Patients With Acute Respiratory Distress Syndrome Based on the Berlin Definition

Affiliations

Association Between Obesity and Short-And Long-Term Mortality in Patients With Acute Respiratory Distress Syndrome Based on the Berlin Definition

Wei Zhang et al. Front Endocrinol (Lausanne). .

Abstract

Purpose: Acute respiratory distress syndrome (ARDS) is one of the most common causes of death in intensive care units (ICU). Previous studies have reported the potential protective effect of obesity on ARDS patients. However, these findings are inconsistent, in which less was reported on long-term prognosis and diagnosed ARDS by Berlin definition. This study aimed to investigate the relationship between obesity and short-term and long-term mortality in patients with ARDS based on the Berlin Definition.

Methods: This is a retrospective cohort study from the Medical Information Mart for Intensive Care III (MIMIC-III) database, in which all the patients were diagnosed with ARDS according to the Berlin definition. The patients were divided into four groups according to the WHO body mass index (BMI) categories. The multivariable logistic regression and Cox regression analysis were used to investigate the relationship between BMI and short-term and long-term mortality.

Result: A total of 2,378 patients with ARDS were enrolled in our study. In-hospital mortality was 27.92%, and 1,036 (43.57%) patients had died after 1-year follow-up. After adjusting for confounders, the in-hospital and 1-year mortality risks of obese patients were significantly lower than those of normal weight (OR 0.72, 95%CI 0.55-0.94, P=0.0168; HR 0.80, 95%CI 0.68-0.94 P=0.0084; respectively), while those mortality risks of underweight patients were higher than normal weight patients (P=0.0102, P=0.0184; respectively). The smooth curve showed that BMI, which was used as a continuous variable, was negatively correlated with in-hospital and 1-year mortality. The results were consistent after being stratified by age, gender, race, type of admission, severity of organ dysfunction, and severity of ARDS. The Kaplan-Meier survival curves showed that obese patients had significant lower 1-year mortality than normal weight patients.

Conclusion: We found that obesity was associated with decreased risk of short-term and long-term mortality in patients with ARDS.

Keywords: 1-year mortality; 28-day mortality; ARDS; body mass index; obesity.

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Conflict of interest statement

YW was employed by the company Ruibiao (Wuhan) Biotechnology Co. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of the current study.
Figure 2
Figure 2
A smooth curve fitting for the relationship between BMI and the risk of ICU and in-hospital mortality. (A) Association between BMI and ICU mortality for patients with ARDS. (B) association between BMI and in-hospital for patients with ARDS. The resulting figures show the risk of mortality in the y-axis and the BMI (continuous variable) in the x-axis. A negative relationship between BMI and the risk of short-term mortality was observed after adjusting for age, gender, ethnicity, admission type, ICU type, sepsis, chronic pulmonary disease, renal failure, liver disease, metastatic cancer, chronic heart disease, cerebrovascular disease, Elixhauser comorbidity score, vital signs within 24h after ICU admission, SAPSII, SOFA, OASIS, arterial pH, lactic acid, renal replacement therapy and vasopressor by spline smoothing plot.
Figure 3
Figure 3
Kaplan-Meier (K-M) survival curves of 1-year mortalities by BMI categorical.
Figure 4
Figure 4
General additive models demonstrate the relationship between BMI and the risk of 1-year mortality in ARDS patients. The resulting figures show the predicted log(relative risk) in the y-axis and the BMI in the x-axis. The model was adjusted for age, gender, ethnicity, admission type, ICU type, sepsis, chronic pulmonary disease, renal failure, liver disease, metastatic cancer, chronic heart disease, cerebrovascular disease, Elixhauser comorbidity score, vital signs within 24h after ICU admission, SAPSII, SOFA, OASIS, arterial pH, lactic acid, renal replacement therapy and vasopressor.

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