Dataset Information

Association between obesity and short- and medium-term mortality in critically ill patients with atrial fibrillation: a retrospective cohort study.

ABSTRACT:

Background

There has been controversy about how obesity affects the clinical prognosis for patients with atrial fibrillation (AF), and the relationship between obesity and outcomes in critically ill patients with AF remains unclear. The purpose of this study was to explore the association between obesity and short- and medium-term mortality in critically ill patients with AF.

Methods

The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retrospective cohort analysis on 9282 critically ill patients with AF. Patients were categorized into four groups based on their body mass index (BMI) values: underweight, normal-weight, overweight, and obese. The outcomes of this study were 30-day, 90-day, and 1-year all-cause mortality. Cox proportional-hazards models and restricted cubic spline analyses were performed to investigate the association between BMI and mortality.

Results

For 30-day mortality, after adjustment for all confounding factors, the hazard ratio (HR) with 95% confidence interval (CI) for the underweight, overweight, and obese categories were 1.58 (1.21, 2.07), 0.82 (0.72, 0.93), and 0.79 (0.68, 0.91), respectively, compared to the normal-weight category. Using multivariable-adjusted restricted cubic spline analysis, an "L-shaped" correlation was observed between BMI and 30-day mortality. For each 1 kg/m² increase in BMI when BMI was less than 30 kg/m², the risk of 30-day mortality decreased by 6.4% (HR, 95% CI: 0.936 [0.918, 0.954]; P < 0.001); however, this relationship was not present when BMI was greater than or equal to 30 kg/m². Similar results were observed for 90-day and 1-year mortality.

Conclusions

There was a nonlinear relationship between BMI and all-cause mortality among critically ill patients with AF. All-cause mortality and the BMI were negatively correlated when the BMI was less than 30 kg/m².

SUBMITTER: Yang D

PROVIDER: S-EPMC10037857 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Association between obesity and short- and medium-term mortality in critically ill patients with atrial fibrillation: a retrospective cohort study.

Yang Duo D Ye Shujun S Zhang Kaihong K Huang Zhiliang Z Zhang Longsheng L

BMC cardiovascular disorders 20230323 1

<h4>Background</h4>There has been controversy about how obesity affects the clinical prognosis for patients with atrial fibrillation (AF), and the relationship between obesity and outcomes in critically ill patients with AF remains unclear. The purpose of this study was to explore the association between obesity and short- and medium-term mortality in critically ill patients with AF.<h4>Methods</h4>The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retro ...[more]

PMID: 36959537

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Project description:Atrial fibrillation has been associated with increased mortality in critically ill patients. We sought to determine whether atrial fibrillation in the ICU is an independent risk factor for death. A secondary objective was to determine if patients with new-onset atrial fibrillation have different risk factors or outcomes compared with patients with a previous history of atrial fibrillation.Prospective observational cohort study.Medical and general surgical ICUs in a tertiary academic medical center.One thousand seven hundred seventy critically ill patients requiring at least 2 days in the ICU.None.Demographics, medical history, development of atrial fibrillation, fluid balance, echocardiographic findings, medication administration, and hospital mortality were collected during the first 4 days of ICU admission. Atrial fibrillation occurred in 236 patients (13%) (Any AF). Of these, 123 patients (7%) had no prior atrial fibrillation (New-onset AF) while the remaining 113 (6%) had recurrent atrial fibrillation (Recurrent AF). Any AF was associated with male gender, Caucasian race, increased age, cardiac disease, organ failures, and disease severity. Patients with Any AF had increased mortality compared with those without atrial fibrillation (31% vs 17%; p < 0.001), and Any AF was independently associated with death (odds ratio, 1.62; 95% CI, 1.14-2.29; p = 0.007) in multivariable analysis controlling for severity of illness and other confounders. The association of atrial fibrillation with death was magnified in patients without sepsis (odds ratio, 2.92; 95% CI, 1.52-5.60; p = 0.001). Treatment for atrial fibrillation had no effect on hospital mortality. New-onset AF and Recurrent AF were each associated with increased mortality. New-onset AF, but not Recurrent AF, was associated with increased diastolic dysfunction and vasopressor use and a greater cumulative positive fluid balance.Atrial fibrillation in critical illness, whether new-onset or recurrent, is independently associated with increased hospital mortality, especially in patients without sepsis.

Project description:Sepsis is defined by life-threatening organ dysfunction during infection and is the leading cause of death in hospitals. During sepsis, there is a high risk that new onset of atrial fibrillation (AF) can occur, which is associated with significant morbidity and mortality. Consequently, early prediction of AF during sepsis would allow testing of interventions in the intensive care unit (ICU) to prevent AF and its severe complications. In this paper, we present a novel automated AF prediction algorithm for critically ill sepsis patients using electrocardiogram (ECG) signals. From the heart rate signal collected from 5-min ECG, feature extraction is performed using the traditional time, frequency, and nonlinear domain methods. Moreover, variable frequency complex demodulation and tunable Q-factor wavelet-transform-based time-frequency methods are applied to extract novel features from the heart rate signal. Using a selected feature subset, several machine learning classifiers, including support vector machine (SVM) and random forest (RF), were trained using only the 2001 Computers in Cardiology data set. For testing the proposed method, 50 critically ill ICU subjects from the Medical Information Mart for Intensive Care (MIMIC) III database were used in this study. Using distinct and independent testing data from MIMIC III, the SVM achieved 80% sensitivity, 100% specificity, 90% accuracy, 100% positive predictive value, and 83.33% negative predictive value for predicting AF immediately prior to the onset of AF, while the RF achieved 88% AF prediction accuracy. When we analyzed how much in advance we can predict AF events in critically ill sepsis patients, the algorithm achieved 80% accuracy for predicting AF events 10 min early. Our algorithm outperformed a state-of-the-art method for predicting AF in ICU patients, further demonstrating the efficacy of our proposed method. The annotations of patients' AF transition information will be made publicly available for other investigators. Our algorithm to predict AF onset is applicable for any ECG modality including patch electrodes and wearables, including Holter, loop recorder, and implantable devices.

Project description:BackgroundIncreased or decreased blood pressure variability may affect the perfusion of tissues and organs, leading to acute kidney injury and death. This study was conducted to explore the relationship between mean arterial pressure variability and short- and long-term mortality in critically ill patients.MethodsWe used patient data from the MIMIC-III database for cohort study. According to the recorded mean arterial pressure during the first 24 h in the intensive care unit, we calculated each patient's two variability parameters -coefficient of variation and average real variability. The primary outcome was in-hospital mortality and the secondary outcomes were 28-day mortality and 1-year mortality. We conducted smooth spline models to examine the possible nonlinear associations between blood pressure variability and mortality. According to the smoothing curve, we further developed a two-piecewise linear regression model to find out the threshold effect. Multivariable logistic regression or Cox proportional hazards model was used to evaluate the relationship. Kaplan-Meier survival analysis for 28-day and 1-year mortality was performed. Subgroup analysis explored the factors modifying the relationship between them.ResultsA total of 12,867 patients were enrolled in the study, 1,320 in-hospital death, 1,399 28-day death, and 2,734 1-year death occurred. The smooth spline showed death risk was the lowest when average real variability was around 7.2 mmHg. After adjusting for covariates, logistic or Cox regression showed the highest MAP variability level was strongly associated with increased mortality in the hospital (odds ratio: 1.44; 95% CI, 1.21∼1.72), at 28 days (hazard ratio: 1.28; 95% CI, 1.1∼1.5), and at 1 year (hazard ratio: 1.27; 95% CI, 1.14∼1.42) compared with the second level of average real variability group. The survival curve plot showed patients with higher average real variability had a higher risk of 28-day and 1-year mortality. This relationship remained remarkable in patients with low or high Sequential Organ Failure Assessment scores in the sensitivity analysis. The two-piecewise linear regression model showed that lower ARV was a risk factor for 28-day (HR 0.72, 95% CI, 0.57∼0.91) and 1-year mortality (HR 0.81, 95% CI, 0.68∼0.96) when ARV was less than 7.2 mmHg, higher ARV was a risk factor for 28-day mortality (HR 1.1, 95% CI, 1.04∼1.17) and 1-year mortality (HR 1.07, 95% CI, 1.02∼1.12) when ARV was greater than 7.2 mmHg.ConclusionBlood pressure variability predicts mortality in critically ill patients. Individuals with higher or lower mean arterial pressure average real variability during the first day in ICU may have an increased risk of death.

Project description:BackgroundThe stress hyperglycemia ratio (SHR) was developed to mitigate the influence of long-term chronic glycemic factors on stress hyperglycemia levels, which are associated with adverse clinical events, particularly cardiovascular events. However, studies examining the SHR index and its prognostic significance in patients with atrial fibrillation (AF) are lacking. This study aims to evaluate the relationship between the SHR index and all-cause mortality in critically ill patients with AF upon Intensive Care Unit admission.MethodsThe patients' data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. All patients were categorized into four groups based on the SHR index. The outcomes include both primary and secondary endpoints, with the primary endpoints being 30-day and 365-day all-cause mortality, and the secondary endpoints being 90-day and 180-day all-cause mortality. The SHR index was analyzed using quartiles, and the Kaplan-Meier curve was employed to compare the outcomes across groups. Cox proportional-hazards regression and restricted cubic splines (RCS) were used to assess the relationship between the SHR index and the outcomes.ResultsOut of a total of 1,685 participants, the average age was 63.12 years (range: 40.17 to 101.49), with 1,004 (59.58%) being male. Higher levels of the SHR index were associated with an increased risk of all-cause mortality at 30 days, 90 days, 180 days, and 365 days, as indicated by the Kaplan-Meier curves (log-rank P < 0.01). Additionally, Cox proportional-hazards regression analysis revealed that the risk of mortality at these time points was significantly higher in the highest quartile of the SHR index. Restricted cubic splines (RCS) analysis demonstrated U-shaped relationships between the SHR index and all-cause mortality, with inflection points at 0.73 for 30-day mortality and 0.76 for 365-day mortality. Compared to patients with SHR levels below these inflection points, those with higher levels had a 69.9% increased risk for 30-day all-cause mortality (hazard ratio [HR] 1.699; 95% confidence interval [CI] 1.336 to 2.159) and a 61.6% increased risk for 365-day all-cause mortality (HR 1.616; 95% CI 1.345 to 1.942).ConclusionIn critically ill patients with AF, higher levels of the SHR index are significantly associated with an increased risk of all-cause mortality at 30 days, 90 days, 180 days, and 365 days. The SHR index may serve as a valid indicator for assessing the severity and guiding the treatment of AF patients in the ICU.

Dataset Information

Association between obesity and short- and medium-term mortality in critically ill patients with atrial fibrillation: a retrospective cohort study.

Background

Methods

Results

Conclusions

Publications

Association between obesity and short- and medium-term mortality in critically ill patients with atrial fibrillation: a retrospective cohort study.

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