Body Mass Index and 90-Day Mortality Among 35,406 Danish Patients Hospitalized for Infection

Evaluating the association of body mass index with COVID-19 severity and mortality using Japanese administrative claims data

INTRODUCTION

Obesity is a risk factor for aggravation of and mortality from coronavirus disease 2019 (COVID-19). We aimed to investigate the relationship between COVID-19 and Body Mass Index (BMI) in the Japanese population.

METHODS

We used administrative claims data from an advanced treatment hospital in Japan and extracted data from patients hospitalized for COVID-19. The exposure variable was BMI measured at the time of admission, and the study outcomes were progression to critical illness and death. Analyses were performed for each age group.

RESULTS

Overall, 58,944 patients met the inclusion criteria. The risk of critical illness increased monotonically with higher BMI. In contrast, the relationship between BMI and mortality follows a J-shaped curve; being underweight and obese are risk factors for mortality. When stratified by age, similar trends were observed for both critical illness and mortality.

CONCLUSION

A higher BMI is a risk factor for the progression of COVID-19 severity, whereas both lower and higher BMIs are risk factors for mortality in the Japanese population.

Associations between obesity and severity of coronavirus disease 2019 in Brazilian inpatients: A 2021 secondary data analysis

In the backdrop of the global obesity pandemic, recognized as a notable risk factor for coronavirus disease 2019 (COVID-19) complications, the study aims to explore clinical and epidemiological attributes of hospitalized COVID-19 patients throughout 2021 in Brazil. Focused on four distinct age cohorts, the investigation scrutinizes parameters such as intensive care unit (ICU) admission frequency, invasive mechanical ventilation (IMV) usage, and in-hospital mortality among individuals with and without obesity. Using a comprehensive cross-sectional study methodology, encompassing adult COVID-19 cases, data sourced from the Influenza Epidemiological Surveillance Information System comprises 329 206 hospitalized patients. Of these individuals, 26.3% were affected by obesity. Analysis reveals elevated rates of ICU admissions, increased dependence on IMV, and heightened in-hospital mortality among the individuals with obesity across all age groups (p < .001). Logistic regression, adjusting for confounding variables, underscores a progressively rising odds ratio for mortality in younger age brackets: 1.2 (95%CI 1.1-1.3) for those under 50 years, 1.1 (95%CI 1.0-1.2) for the 50-59 age group, and 1.1 (95%CI 1.0-1.2) for the 60-69 age group. Conversely, no significant mortality difference is observed for patients over 70 years (OR: 0.972, 95%CI 0.9-1.1). In summary, hospitalized COVID-19 patients with obesity, particularly in younger age groups, exhibit elevated rates of ICU admission, IMV requirement, and in-hospital mortality compared with the control group. Notably, the 'obesity paradox' is not evident among hospitalized COVID-19 patients in 2021.

Development and validation of an interpretable machine learning for mortality prediction in patients with sepsis

Introduction

Sepsis is a leading cause of death. However, there is a lack of useful model to predict outcome in sepsis. Herein, the aim of this study was to develop an explainable machine learning (ML) model for predicting 28-day mortality in patients with sepsis based on Sepsis 3.0 criteria.

Methods

We obtained the data from the Medical Information Mart for Intensive Care (MIMIC)-III database (version 1.4). The overall data was randomly assigned to the training and testing sets at a ratio of 3:1. Following the application of LASSO regression analysis to identify the modeling variables, we proceeded to develop models using Extreme Gradient Boost (XGBoost), Logistic Regression (LR), Support Vector Machine (SVM), and Random Forest (RF) techniques with 5-fold cross-validation. The optimal model was selected based on its area under the curve (AUC). Finally, the Shapley additive explanations (SHAP) method was used to interpret the optimal model.

Results

A total of 5,834 septic adults were enrolled, the median age was 66 years (IQR, 54-78 years) and 2,342 (40.1%) were women. After feature selection, 14 variables were included for developing model in the training set. The XGBoost model (AUC: 0.806) showed superior performance with AUC, compared with RF (AUC: 0.794), LR (AUC: 0.782) and SVM model (AUC: 0.687). SHAP summary analysis for XGBoost model showed that urine output on day 1, age, blood urea nitrogen and body mass index were the top four contributors. SHAP dependence analysis demonstrated insightful nonlinear interactive associations between factors and outcome. SHAP force analysis provided three samples for model prediction.

Conclusion

In conclusion, our study successfully demonstrated the efficacy of ML models in predicting 28-day mortality in sepsis patients, while highlighting the potential of the SHAP method to enhance model transparency and aid in clinical decision-making.

Integrating classification and regression learners with bioimpedance methods for estimating weight status in infants and juveniles from the southern Cuba region

OBJECTIVE

The search for other indicators to assess the weight and nutritional status of individuals is important as it may provide more accurate information and assist in personalized medicine. This work is aimed to develop a machine learning predictions of weigh status derived from bioimpedance measurements and other physical parameters of healthy younger volunteers from Southern Cuba Region.

METHODS

A pilot random study at the Pediatrics Hospital was conducted. The volunteers were selected between 2002 and 2008, ranging in age between 2 and 18 years old. In total, 776 female and male volunteers are studied. Along the age and sex in the cohort, volunteers with class I obesity, overweight, underweight and with normal weight are considered. The bioimpedance parameters are obtained by measuring standard tetrapolar whole-body configuration. The bioimpedance analyser is used, collecting fundamental bioelectrical and other parameters of interest. A classification model are performed, followed by a prediction of the body mass index.

RESULTS

The results derived from the classification leaner reveal that the size, body density, phase angle, body mass index, fat-free mass, total body water volume according to Kotler, body surface area, extracellular water according to Kotler and sex largely govern the weight status of this population. In particular, the regression model shows that other bioparameters derived from impedance measurements can be associated with weight status estimation with high accuracy.

CONCLUSION

The classification and regression predictive models developed in this work are of the great importance to assist the diagnosis of weigh status with high accuracy. These models can be used for prompt weight status evaluation of younger individuals at the Pediatrics Hospital in Santiago de Cuba, Cuba.

Association of anthropometric z score with complications and length of hospital stay in children with severe pneumonia aged 3 months to 5 years

BACKGROUND

Severe pneumonia in children accounts for a significant healthcare burden, involving prolonged hospitalization and increased risk of complications. The prognosis is closely related to the child's nutrition status. Anthropometric z scores are preferred to evaluate growth levels in children. This study aimed to investigate the association of anthropometric z scores with complications and length of hospital stay (LOS) in children with severe pneumonia.

METHODS

This study included 361 hospitalized children aged 3 months to 5 years with severe pneumonia in Tianjin, China. Anthropometry was performed, and anthropometric z scores were calculated. Blood laboratory indices were assessed, and complications and LOS were recorded.

RESULTS

The average anthropometric z scores were -0.10 ± 1.15 (body mass index for age z score), 0.00 ± 0.97 (upper arm circumference for age z score [ACAZ]), and -0.14 ± 1.00 (triceps skinfold thickness for age z score [TSAZ]). The prevalence of complications was 73.96% (n = 267), including 82 children with only respiratory complications, 71 with only extrapulmonary complications, and 114 with both. After adjusting for confounding factors, compared with the noncomplication group, only the extrapulmonary complication group had a lower TSAZ (odds ratio [OR] = 0.597; 95% CI = 0.405-0.880; P < 0.05), whereas the respiratory and extrapulmonary complication group had a lower ACAZ (OR = 0.674; 95% CI = 0.469-0.969; P < 0.05) and TSAZ (OR = 0.573; 95% CI = 0.389-0.843; P < 0.05). ACAZ (β = -0.368; 95% CI = -0.720 to 0.016; P < 0.05) and TSAZ (β = -1.123; 95% CI = -1.470 to -0.777; P < 0.05) were negatively correlated with LOS.

CONCLUSION

ACAZ and TSAZ were associated with complications and LOS of severe pneumonia in children aged 3 months to 5 years.

Association of body mass index with long-term outcomes in older adults hospitalized for COVID-19: an observational study

Both underweight and obesity have been associated with poor prognosis in COVID-19. In an older populations of patients hospitalized for SARS-CoV-2 infection, we aimed to evaluate the association between body mass index (BMI) and short and long-term prognosis. Among 434 consecutive patients aged ≥ 70 years and hospitalized for suspected COVID-19 at a university hospital, 219 patients (median age of 83 years, 53% male) testing positive for COVID-19 and for whom BMI was recorded at admission, agreed to participate. Among them, 39 had a BMI < 20 kg/m2, 73 had a BMI between 20 and 24.9 kg/m2 and 107 had a BMI ≥ 25 kg/m2. After adjustment for confounders, BMI < 20 kg/m2 was associated with a higher risk of one-year mortality (hazard ratio (HR) [95% confidence interval]: 1.75 [1.00-3.05], p = 0.048), while BMI ≥ 25 kg/m2 was not (HR: 1.04 [0.64-1.69], p = 0.9). However, BMI was linearly correlated with both in-hospital acute respiratory failure (p = 0.02) and cardiovascular events (p = 0.07). In this cohort of older patients hospitalized for COVID-19, low BMI, rather than high BMI, appears as an independent risk factor for death after COVID-19. The pathophysiological patterns underlying this excess mortality remain to be elucidated.

Does the "Obesity Paradox" Have an Expiration Date? A Retrospective Cohort Study

(1) Background: The "obesity paradox" refers to a protective effect of higher body mass index (BMI) on mortality in acute infectious disease patients. However, the long-term impact of this paradox remains uncertain. (2) Methods: A retrospective study of patients diagnosed with community-acquired acute infectious diseases at Shamir Medical Center, Israel (2010-2020) was conducted. Patients were grouped by BMI: underweight, normal weight, overweight, and obesity classes I-III. Short- and long-term mortality rates were compared across these groups. (3) Results: Of the 25,226 patients, diverse demographics and comorbidities were observed across BMI categories. Short-term (90-day) and long-term (one-year) mortality rates were notably higher in underweight and normal-weight groups compared to others. Specifically, 90-day mortality was 22% and 13.2% for underweight and normal weight respectively, versus 7-9% for others (p < 0.001). Multivariate time series analysis revealed underweight individuals had a significantly higher 5-year mortality risk (HR 1.41 (95% CI 1.27-1.58, p < 0.001)), while overweight and obese categories had a reduced risk (overweight-HR 0.76 (95% CI 0.72-0.80, p < 0.001), obesity class I-HR 0.71 (95% CI 0.66-0.76, p < 0.001), obesity class II-HR 0.77 (95% CI 0.70-0.85, p < 0.001), and obesity class III-HR 0.79 (95% CI 0.67-0.92, p = 0.003)). (4) Conclusions: In this comprehensive study, obesity was independently associated with decreased short- and long-term mortality. These unexpected results prompt further exploration of this counterintuitive phenomenon.

Underweight status and development of end-stage kidney disease: A nationwide population-based study

BACKGROUND

Underweight status increases the risk of cardiovascular disease and mortality in the general population. However, whether underweight status is associated with an increased risk of developing end-stage kidney disease is unknown.

METHODS

A total of 9 845 420 participants aged ≥20 years who underwent health checkups were identified from the Korean National Health Insurance Service database and analysed. Individuals with underweight (body mass index [BMI] < 18.5 kg/m2 ) and obesity (BMI ≥ 25 kg/m2 ) were categorized according to the World Health Organization recommendations for Asian populations.

RESULTS

During a mean follow-up period of 9.2 ± 1.1 years, 26 406 participants were diagnosed with end-stage kidney disease. After fully adjusting for other potential predictors, the moderate to severe underweight group (<17 kg/m2 ) had a significantly higher risk of end-stage kidney disease than that of the reference (normal) weight group (adjusted hazard ratio, 1.563; 95% confidence interval, 1.337-1.828), and competing risk analysis to address the competing risk of death also showed the similar results (adjusted hazard ratio, 1.228; 95% confidence interval, 1.042-1.448). Compared with that of the reference BMI group (24-25 kg/m2 ), the adjusted hazard ratios for end-stage kidney disease increased as the BMI decreased by 1 kg/m2 . In the sensitivity analysis, sustained underweight status or progression to underweight status over two repeated health checkups, when compared with normal weight status, had a higher hazard ratio for end-stage kidney disease.

CONCLUSIONS

Underweight status is associated with an increased risk of end-stage kidney disease, and this association gradually strengthens as BMI decreases.

Precedence of Bone Loss Accompanied with Changes in Body Composition and Body Fat Distribution in Patients with Type 2 Diabetes Mellitus

Methods

A total of 596 patients with T2DM, including 308 male and 288 female patients, were included in the follow-up study; the median follow-up time was 2.17 years. We calculated the difference between the endpoint and the baseline of each body composition index and the annual rate. The research participants were divided into the increased body mass index (BMI) group, stable BMI group, and decreased BMI group. Some confounding factors were adjusted, such as BMI, fat mass index (FMI), muscle mass index (MMI), muscle/fat mass ratio (M/F), trunk fat mass index (TFMI), appendicular skeletal muscle mass index (ASMI), and appendicular skeletal muscle mass/trunk fat mass ratio (A/T).

Results

The linear analysis showed that ΔFMI and ΔTFMI were negatively correlated with the change in femoral neck BMD (ΔFNBMD) and ΔMMI, ΔASMI, ΔM/F, and ΔA/T were positively correlated with ΔFNBMD. The risk of FNBMD reduction in patients with increased BMI was 56.0% lower than that in patients with decreased BMI; also, the risk in patients with stable M/F was 57.7% lower than that in patients with decreased M/F. The risk in the A/T increase group was 62.9% lower than that in the A/T decrease group.

Conclusions

A reasonable muscle/fat ratio is still beneficial to maintaining bone mass. Maintaining a certain BMI value is conducive to maintaining FNBMD. Simultaneously, increasing the proportion of muscle mass and reducing fat accumulation can also prevent FNBMD loss.

COVID-19-associated AKI in hospitalized US patients: incidence, temporal trends, geographical distribution, risk factors and mortality

Background

Acute kidney injury (AKI) is associated with mortality in patients hospitalized with COVID-19, however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied.

Methods

Electronic health record data were obtained from 53 health systems in the United States (US) in the National COVID Cohort Collaborative (N3C). We selected hospitalized adults diagnosed with COVID-19 between March 6th, 2020, and January 6th, 2022. AKI was determined with serum creatinine (SCr) and diagnosis codes. Time were divided into 16-weeks (P1-6) periods and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality.

Results

Out of a total cohort of 306,061, 126,478 (41.0 %) patients had AKI. Among these, 17.9% lacked a diagnosis code but had AKI based on the change in SCr. Similar to patients coded for AKI, these patients had higher mortality compared to those without AKI. The incidence of AKI was highest in P1 (49.3%), reduced in P2 (40.6%), and relatively stable thereafter. Compared to the Midwest, the Northeast, South, and West had higher adjusted AKI incidence in P1, subsequently, the South and West regions continued to have the highest relative incidence. In multivariable models, AKI defined by either SCr or diagnostic code, and the severity of AKI was associated with mortality.

Conclusions

Uncoded cases of COVID-19-associated AKI are common and associated with mortality. The incidence and distribution of COVID-19-associated AKI have changed since the first wave of the pandemic in the US.

A nomogram to predict prolonged stay of obesity patients with sepsis in ICU: Relevancy for predictive, personalized, preventive, and participatory healthcare strategies

Objective

In an era of increasingly expensive intensive care costs, it is essential to evaluate early whether the length of stay (LOS) in the intensive care unit (ICU) of obesity patients with sepsis will be prolonged. On the one hand, it can reduce costs; on the other hand, it can reduce nosocomial infection. Therefore, this study aimed to verify whether ICU prolonged LOS was significantly associated with poor prognosis poor in obesity patients with sepsis and develop a simple prediction model to personalize the risk of ICU prolonged LOS for obesity patients with sepsis.

Method

In total, 14,483 patients from the eICU Collaborative Research Database were randomized to the training set (3,606 patients) and validation set (1,600 patients). The potential predictors of ICU prolonged LOS among various factors were identified using logistic regression analysis. For internal and external validation, a nomogram was developed and performed.

Results

ICU prolonged LOS was defined as the third quartile of ICU LOS or more for all sepsis patients and demonstrated to be significantly associated with the mortality in ICU by logistic regression analysis. When entering the ICU, seven independent risk factors were identified: maximum white blood cell, minimum white blood cell, use of ventilation, Glasgow Coma Scale, minimum albumin, maximum respiratory rate, and minimum red blood cell distribution width. In the internal validation set, the area under the curve was 0.73, while in the external validation set, it was 0.78. The calibration curves showed that this model predicted probability due to actually observed probability. Furthermore, the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical net benefit.

Conclusion

In obesity patients with sepsis, we created a novel nomogram to predict the risk of ICU prolonged LOS. This prediction model is accurate and reliable, and it can assist patients and clinicians in determining prognosis and making clinical decisions.

Obesity paradox in joint replacement for osteoarthritis - truth or paradox?

Obesity is associated with an increased risk of cardiovascular disease (CVD) and other adverse health outcomes. In patients with pre-existing heart failure or coronary heart disease, obese individuals have a more favourable prognosis compared to individuals who are of normal weight. This paradoxical relationship between obesity and CVD has been termed the 'obesity paradox'. This phenomenon has also been observed in patients with other cardiovascular conditions and diseases of the respiratory and renal systems. Taking into consideration the well-established relationship between osteoarthritis (OA) and CVD, emerging evidence shows that overweight and obese individuals undergoing total hip or knee replacement for OA have lower mortality risk compared with normal weight individuals, suggesting an obesity paradox. Factors proposed to explain the obesity paradox include the role of cardiorespiratory fitness ("fat but fit"), the increased amount of lean mass in obese people, additional adipose tissue serving as a metabolic reserve, biases such as reverse causation and confounding by smoking, and the co-existence of older age and specific comorbidities such as CVD. A wealth of evidence suggests that higher levels of fitness are accompanied by prolonged life expectancy across all levels of adiposity and that the increased mortality risk attributed to obesity can be attenuated with increased fitness. For patients about to have joint replacement, improving fitness levels through physical activities or exercises that are attractive and feasible, should be a priority if intentional weight loss is unlikely to be achieved.

Influence of Overweight and Obesity on Morbidity and Mortality among Hospitalized Patients in Sri Lanka: A Single-Center Analysis

BACKGROUND

Current evidence regarding the association between overweight and obesity and in-hospital morbidity and mortality is inconsistent and South Asian populations are underrepresented.

METHODS

Data relevant to anthropometry, hospital outcomes, complications, and medical diagnoses of all acute medical admissions to the National Hospital of Sri Lanka were collected over a period of 3 months. Analysis was performed with WHO international (ICs) and Asian obesity cut-offs (ACs).

RESULTS

Sample size was 2,128 (median age: 57 years [IQR: 42, 67], males: 49.7%). High prevalence of overweight (23.5%), generalized obesity (10.4%), central obesity (28.5%), and underweight (15.4%) was observed (ICs). Patients with either generalized or central obesity had significantly higher in-hospital mortality (4.8% versus 2.5%, p = 0.031) and acute kidney injury (AKI) (3.9% versus 1.2%) (p = 0.001) compared to normal weight. With ACs, overweight and obesity prevalence increased, without any significant increment in morbidity and mortality, but median length of hospital stay was significantly reduced in patients with generalized obesity compared to normal (3 [IQR: 2, 5] versus 4 [IQR: 2, 6], p = 0.014). Infections (44.4%) and cardiovascular diseases (CVDs) (25.9%) were the most common causes of admission. Overweight and generalized obesity or central obesity were associated with increased prevalence of acute CVDs and CVD risk factors and lower prevalence of acute infections, whilst underweight showed an inverse association.

CONCLUSION

A double burden of malnutrition and diseases were noted among hospital admissions, with obesity being a risk factor for in-hospital all-cause mortality and AKI. Overweight and obesity were associated with increased CVDs and reduced infections. Larger prospective studies are required to characterize these associations among South Asians.

Association of body mass index with Clostridioides difficile infection among older patients with pneumonia in Japan

AIM

Obesity is reported to be a risk factor for Clostridioides difficile infection. However, obesity rarely occurs in older Asian patients, and the effects of obesity on health and disease are different in Asian and Western countries. This study aimed to assess the association between body mass index and C. difficile infection risk among older patients with pneumonia in Japan.

METHODS

This retrospective observational cohort study used data from the nationwide database of acute hospital inpatients' data in Japan between July 2014 and March 2016. All patients aged ≥65 years admitted with a primary diagnosis of pneumonia were enrolled. Risk factors for C. difficile infection were determined by logistic regression analysis, including known risks as covariates.

RESULTS

Among 221 242 pneumonia patients, 611 developed C. difficile infection. Underweight patients (body mass index <18.5 kg/m² ) showed higher odds for C. difficile infection (odds ratio 1.38, 95% confidence interval 1.17-1.62, P < 0.001) than normal weight patients (body mass index 18.5-24.9 kg/m² ), whereas overweight patients (body mass index ≥25 kg/m² ) showed lower odds (odds ratio 0.63, 95% confidence interval 0.45-0.89, P < 0.01).

CONCLUSIONS

Body mass index was associated with C. difficile infection in older pneumonia patients in Japan. Underweight was a risk factor, whereas overweight was a protective factor for C. difficile infection. Geriatr Gerontol Int 2021; ••: ••-••.

Reconciling the obesity paradox: Obese patients suffer the highest critical illness associated mortality rates

The obesity paradox refers to the observation that obese patients admitted to intensive care units (ICU) have lower case fatality as compared to healthy weight patients. However, selection bias could explain the apparent paradox. Our objective was to assess whether obese people have a different overall burden of critical illness associated mortality. A retrospective population-based cohort study was conducted in North Brisbane ICUs during 2017-2019. Patients were classified as underweight, healthy weight, overweight, and obese according to BMIs <18.5, 18.5-24.9, 25-29.9, and ≥ 30 kg/m², respectively. ICU admission incidence rates were 245.6, 138.2, 178.9, and 421.9 per 100,000 population; 90-day all cause case fatalities were 24.0%, 17.0%, 18.1%, and 16.0%; and critical illness associated mortality rates were 58.8, 23.4, 32.4, and 67.7 per 100,000 population among underweight, healthy weight, overweight, and obese patients, respectively. As compared to patients of healthy weight, those who were underweight (relative risk; RR 2.51; 95% CI, 1.79-3.44), overweight (RR 1.38; 95% CI, 1.16-1.65), and obese (RR 2.89; 2.43-3.43) were each at significantly higher risk for critical illness associated mortality. While obese patients have lower case fatality they are at much higher risk for ICU admission and as result suffer the highest burden of critical illness associated mortality in our region.