Association Between Obesity and Lower Short- and Long-Term Mortality in Coronary Care Unit Patients: A Cohort Study of the MIMIC-III Database

The obesity paradox and 90 day mortality in chronic critically ill patients: a cohort study using a large clinical database

BACKGROUND

This study investigates the obesity paradox, where obesity is linked to lower mortality in certain patient groups, focusing on its impact on long-term mortality in chronic critically ill (CCI) patients.

METHODS

We retrospectively analyzed CCI patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database's Intensive Care Unit, categorizing them into six groups based on Body Mass Index (BMI). Using stepwise multivariable Cox regression and restricted cubic spline models, we examined the association between BMI and 90 day mortality, accounting for confounding variables through subgroup analyses.

RESULTS

The study included 1996 CCI patients, revealing a 90 day mortality of 34.12%. Overweight and obese patients exhibited significantly lower mortality compared to normal-weight individuals. Adjusted analysis showed lower mortality risks in overweight and obese groups (HRs 0.60 to 0.72, p < 0.001). The cubic spline model indicated a negative correlation between BMI and 90 day mortality, with subgroup analyses highlighting interactions with age.

CONCLUSION

Our findings confirm the obesity paradox in CCI patients, especially among the elderly (65-85 years) and very elderly (≥ 85 years). The results suggest a beneficial association of higher BMI in older CCI patients, though caution is advised for those under 45.

Mortality risk in patients with obesity and COVID-19 infection: a systematic review and meta-analysis

Obesity is a risk factor for severe respiratory diseases, including COVID-19 infection. Meta-analyses on mortality risk were inconsistent. We systematically searched 3 databases (Medline, Embase, CINAHL) and assessed the quality of studies using the Newcastle-Ottawa tool (CRD42020220140). We included 199 studies from US and Europe, with a mean age of participants 41.8-78.2 years, and a variable prevalence of metabolic co-morbidities of 20-80 %. Exceptionally, one third of the studies had a low prevalence of obesity of <20 %. Compared to patients with normal weight, those with obesity had a 34 % relative increase in the odds of mortality (p-value 0.002), with a dose-dependent relationship. Subgroup analyses showed an interaction with the country income. There was a high heterogeneity in the results, explained by clinical and methodologic variability across studies. We identified one trial only comparing mortality rate in vaccinated compared to unvaccinated patients with obesity; there was a trend for a lower mortality in the former group. Mortality risk in COVID-19 infection increases in parallel to an increase in BMI. BMI should be included in the predictive models and stratification scores used when considering mortality as an outcome in patients with COVID-19 infections. Furthermore, patients with obesity might need to be prioritized for COVID-19 vaccination.

Adiposity trajectories and cardiovascular disease risk in women: a population-based cohort study with a focus on menopausal status

Objectives

A single measurement of adiposity indices could predict the incidence of cardiovascular disease (CVD); nonetheless their long-term pattern and its association with incident CVD are rarely studied. This study aimed to determine distinct trajectories of adiposity indices among participants of Tehran Lipid and Glucose Study (TLGS) and their association with incident CVD. Furthermore, this study aimed to investigate whether this association differed among individuals according to their menopausal status.

Method

A total of 6840 women participated in TLGS, aged 20 years and older were included in this study; they were followed for a median of 16 years. Body mass index (BMI), waist circumference (WC), conicity index (CI) and body roundness index (BRI) were included in the analysis as adiposity indices. The cohort outcome panel of medical specialists identified the CVD outcomes. Trajectory analyses were used to identify homogeneous distinct clusters of adiposity indices trajectories. The association between the trajectory group membership and incident CVD were explored by Cox proportional hazard models, with unadjusted and adjusted model for baseline age, physical activity, smoking status, menopause and family history of CVD.

Results

Three BMI trajectory groups of low, medium, and high and two trajectories for WC, BRI and CI were identified. Adjusted cox proportional hazard models revealed significant associations between the hazard of CVD experience and the high trajectory group of the BMI (HR: 2.06, 95% CI: 1.38-3.07), WC (HR: 2.71, 95% CI: 1.98-3.70), CI (HR: 1.87, 95% CI: 1.26-2.77) and BRI (HR: 1.55-95% CI: 1.12-2.15), compared to the low trajectory group. Subgroup analysis based on the menopausal status of participants showed that the HR of CVD incidences for all of trajectories adiposity indices, except BMI, was statistically significant. Adjusted cox proportional hazard models, in those women not reached menopause during study, revealed that the HR (95% CI) of CVD incidences for high trajectory of BMI, WC, CI and BRI were 2.80 (1.86-7.05); 2.09 (1.40-6.16); 1.72 (1.42-5.61), and 3.09 (1.06-9.01), respectively. These values for those were menopause at the initiation of the study were 1.40 (1.11, 2.53); 1.65 (1.04-2.75); 1.69 (1.01-2.87), and 1.61 (0.98-2.65), respectively.

Conclusion

Our findings suggest that adiposity trajectories, particularly central adiposity index of CI, could precisely predict the CVD risk. Consequently, preventive strategies should be tailored accordingly.

Dyslipidemia versus obesity as predictors of ischemic stroke prognosis: a multi-center study in China

BACKGROUND

This multicenter observational study aimed to determine whether dyslipidemia or obesity contributes more significantly to unfavorable clinical outcomes in patients experiencing a first-ever ischemic stroke (IS).

METHODS

The study employed a machine learning predictive model to investigate associations among body mass index (BMI), body fat percentage (BFP), high-density lipoprotein (HDL), triglycerides (TG), and total cholesterol (TC) with adverse outcomes in IS patients. Extensive real-world clinical data was utilized, and risk factors significantly linked to adverse outcomes were identified through multivariate analysis, propensity score matching (PSM), and regression discontinuity design (RDD) techniques. Furthermore, these findings were validated via a nationwide multicenter prospective cohort study.

RESULTS

In the derived cohort, a total of 45,162 patients diagnosed with IS were assessed, with 522 experiencing adverse outcomes. A multifactorial analysis incorporating PSM and RDD methods identified TG (adjusted odds ratio (OR) = 1.110; 95% confidence interval (CI): 1.041-1.183; P <  0.01) and TC (adjusted OR = 1.139; 95%CI: 1.039-1.248; P <  0.01) as risk factors. However, BMI, BFP, and HDL showed no significant effect. In the validation cohort, 1410 controls and 941 patients were enrolled, confirming that lipid levels are more strongly correlated with the prognosis of IS patients compared to obesity (TC, OR = 1.369; 95%CI: 1.069-1.754; P <  0.05; TG, OR = 1.332; 95%CI: 1.097-1.618; P <  0.01).

CONCLUSION

This study suggests that dyslipidemia has a more substantial impact on the prognosis of IS patients compared to obesity. This highlights the importance of prioritizing dyslipidemia management in the treatment and prevention of adverse outcomes in IS patients.

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

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.