Body mass index and all-cause readmissions following acute heart failure hospitalization

Risk factors for readmission after sepsis and its association with mortality

BACKGROUND

Sepsis is associated with an approximately 20 % 30-day readmission rate and with subsequent mortality.

OBJECTIVES

To determine the demographics, comorbidities that had been documented prior to sepsis onset, processes of care, commonly administered laboratory tests measured near discharge, and post-sepsis infections that may be associated with readmission and, secondarily, whether readmission is an independent risk factor for 90-day mortality.

METHODS

Using a database of patients who met Sepsis-3 criteria divided into Construction and Validation groups, we used logistic regression to estimate the factors independently associated with readmission within 30 days after discharge and proportional hazard regression to estimate the factors independently associated with 90-day mortality.

RESULTS

Of the 30,798 patients ≥ 18 years at our combined referral and community hospital and were discharged alive who met Sepsis-3 criteria between July 10, 2009 and September 7, 2019, 5943 (19 %) were readmitted within 30 days. Thirteen thousand, four hundred forty-four (44 %) of the patients were female, 25,293 (82 %) White, 3523 (11 %) Black, and the mean age was 59 ± 17 years. Among the readmitted patients, 894 (15 %) died within 90 days from the original discharge compared to 11 % (p < 0.001) who had not been readmitted. Seven comorbidities, five processes of care (presepsis platelet transfusion, postsepsis platelet transfusion, operation, ICU length of stay, and hospital length of stay), five culture results, two discharge laboratory values, and discharge location were associated with readmission. The model had good discrimination, 0.770 ± 0.004 (Construction Group) and 0.748 ± 0.006 (Validation Group) and good relevancy (area under the precision recall curve), 0.390 ± 0.004 (Construction group) and 0.476 ± 0.005 (Validation group). Readmission within 30 days was independently associated with a 56 % higher risk of death (HR=1.562, 95 % CI=1.434, 1.703, p < 0.001) within 90 days from discharge.

CONCLUSIONS

Comorbidities, abnormal laboratory values, processes of care, and post-sepsis onset culture results, but not demographic characteristics, were associated with 30-day readmission. Readmission was associated with 90-day mortality.

Association between triglyceride glucose-body mass index and long-term adverse outcomes of heart failure patients with coronary heart disease

BACKGROUND

The triglyceride glucose-body mass index (TyG-BMI) is recognized as a reliable surrogate for evaluating insulin resistance and an effective predictor of cardiovascular disease. However, the link between TyG-BMI index and adverse outcomes in heart failure (HF) patients remains unclear. This study examines the correlation of the TyG-BMI index with long-term adverse outcomes in HF patients with coronary heart disease (CHD).

METHODS

This single-center, prospective cohort study included 823 HF patients with CHD. The TyG-BMI index was calculated as follows: ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI. To explore the association between the TyG-BMI index and the occurrences of all-cause mortality and HF rehospitalization, we utilized multivariate Cox regression models and restricted cubic splines with threshold analysis.

RESULTS

Over a follow-up period of 9.4 years, 425 patients died, and 484 were rehospitalized due to HF. Threshold analysis revealed a significant reverse "J"-shaped relationship between the TyG-BMI index and all-cause mortality, indicating a decreased risk of all-cause mortality with higher TyG-BMI index values below 240.0 (adjusted model: HR 0.90, 95% CI 0.86-0.93; Log-likelihood ratio p = 0.003). A distinct "U"-shaped nonlinear relationship was observed with HF rehospitalization, with the inflection point at 228.56 (adjusted model: below: HR 0.95, 95% CI 0.91-0.98; above: HR 1.08, 95% CI 1.03-1.13; Log-likelihood ratio p < 0.001).

CONCLUSIONS

This study reveals a nonlinear association between the TyG-BMI index and both all-cause mortality and HF rehospitalization in HF patients with CHD, positioning the TyG-BMI index as a significant prognostic marker in this population.

Relationship between BMI and prognosis of chronic heart failure outpatients in Vietnam: a single-center study

Background

Insufficient data exists regarding the relationship between body mass index (BMI) and the prognosis of chronic heart failure (CHF) specifically within low- and middle-income Asian countries. The objective of this study was to evaluate the impact of BMI on adverse outcomes of ambulatory patients with CHF in Vietnam.

Methods

Between 2018 and 2020, we prospectively enrolled consecutive outpatients with clinically stable CHF in an observational cohort, single-center study. The participants were stratified according to Asian-specific BMI thresholds. The relationships between BMI and adverse outcomes (all-cause death and all-cause hospitalization) were analyzed by Kaplan-Meier survival curves and Cox proportional-hazards model.

Results

Among 320 participants (age 63.5 ± 13.3 years, 57.9% male), the median BMI was 21.4 kg/m2 (IQR 19.5-23.6), and 10.9% were underweight (BMI <18.50 kg/m2). Over a median follow-up time of 32 months, the cumulative incidence of all-cause mortality and hospitalization were 5.6% and 19.1%, respectively. After multivariable adjustment, underweight patients had a significantly higher risk of all-cause mortality than patients with normal BMI (adjusted hazard ratios = 3.03 [95% CI: 1.07-8.55]). Lower BMI remained significantly associated with a worse prognosis when analyzed as a continuous variable (adjusted hazard ratios = 1.27 [95% CI: 1.03-1.55] per 1 kg/m2 decrease for all-cause mortality). However, BMI was not found to be significantly associated with the risk of all-cause hospitalization (p > 0.05).

Conclusion

In ambulatory patients with CHF in Vietnam, lower BMI, especially underweight status (BMI < 18.5 kg/m2), was associated with a higher risk of all-cause mortality. These findings suggest that BMI should be considered for use in risk classification, and underweight patients should be managed by a team consisting of cardiologists, nutritionists, and geriatricians.

Obesity Metabolic Phenotypes and Unplanned Readmission Risk in Diabetic Kidney Disease: An Observational Study from the Nationwide Readmission Database

BACKGROUND AND AIM

Obesity is a potentially modifiable factor for reducing readmissions, with heterogeneity that varies according to the metabolic status. Our objective was to examine the independent or mutual relationship between obesity and metabolic abnormalities and diabetic kidney disease (DKD)-related hospitalizations.

METHODS

493,570 subjects with DKD were enrolled in the 2018 Nationwide Readmission Database (NRD, United States). The at-risk population was reclassified into refined obesity subtypes based on the body mass index (BMI) classification of metabolic abnormalities (hypertension and/or dyslipidemia) to investigate the 180 d readmission risk and hospitalization costs related to DKD.

RESULTS

The overall readmission rate was 34.1%. Patients with metabolic abnormalities, regardless of obesity, had a significantly higher risk of readmission compared to non-obese counterparts (adjusted HR, 1.11 [95% CI, 1.07-1.14]; 1.12 [95% CI, 1.08-1.15]). Hypertension appeared to be the only metabolic factor associated with readmission among individuals with DKD. Obesity without metabolic abnormalities was independently associated with readmission (adjusted HR,1.08 [1.01,1.14]), especially among males and those >65 years (adjusted HR,1.10 [1.01-1.21]; 1.20 [1.10-1.31]). Women or those ≤65 years with metabolic abnormalities (all p <0.050) had elevated readmission rates, regardless of obesity; however, no such trend was observed in obese subjects without metabolic abnormalities (adjusted HR, 1.06 [0.98,1.16]). Additionally, obesity and metabolic abnormalities were associated with elevated hospitalization costs (all p <0.0001).

CONCLUSIONS

Increased BMI and hypertension are positively associated with readmissions and related costs among patients with DKD, which should be considered in future studies.

Rates, Reasons, and Independent Predictors of Readmissions in Portal Venous Thrombosis Hospitalizations in the USA

BACKGROUND

Portal vein thrombosis (PVT), generally considered rare, is becoming increasingly recognized with advanced imaging. Limited data exist regarding readmissions in PVT and its burden on the overall healthcare cost. This study aimed to outline the burden of PVT readmissions and identify the modifiable predictors of readmissions.

METHODS

The National Readmission Database (NRD) was used to identify PVT admissions from 2016 to 2019. Using the patient demographic and hospital-specific variables within the NRD, we grouped patient encounters into two cohorts, 30- and 90-day readmission cohorts. We assessed comorbidities using the validated Elixhauser comorbidity index. We obtained inpatient mortality rates, mean length of hospital stay (LOS), total hospital cost (THC), and causes of readmissions in both 30- and 90-day readmission cohorts. Using a multivariate Cox regression analysis, we identified the independent predictors of 30-day readmissions.

RESULTS

We identified 17,971 unique index hospitalizations, of which 2,971 (16.5%) were readmitted within 30 days. The top five causes of readmissions in both 30-day and 90-day readmission cohorts were PVT, sepsis, hepatocellular cancer, liver failure, and alcoholic liver cirrhosis. The following independent predictors of 30-day readmission were identified: discharge against medical advice (AMA) (adjusted hazard ratio (aHR) 1.86; P = 0.002); renal failure (aHR 1.44, P = 0.014), metastatic cancer (aHR 1.31, P = 0.016), fluid and electrolyte disorders (aHR 1.20, P = 0.004), diabetes mellitus (aHR 1.31, P = 0.001) and alcohol abuse (aHR 1.31, P ≤ 0.001).

CONCLUSION

The readmission rate identified in this study was higher than the national average and targeted interventions addressing these factors may help reduce the overall health care costs.

The Relationship Between Body Mass Index and In-hospital Survival in Patients Admitted With Acute Heart Failure

Background

The association between Body Mass Index (BMI) and clinical outcomes following acute heart failure (AHF) hospitalization is debated in the literature. Our objective was to study the real-world relationship between BMI and in-hospital mortality in patients who were admitted with AHF.

Methods

In this retrospective, multi-center study, we utilized the National Inpatient Sample (NIS) database to identify a sampled cohort of patients who were hospitalized with AHF between October 2015 and December 2016. Outcomes of interest included in-hospital mortality and length of stay (LOS). Patients were divided into 6 BMI (kg/m²) subgroups according to the World Health Organization (WHO) classification: (1) underweight ≤ 19, (2) normal weight 20–25, (3) overweight 26–30, (4) obese I 31–35, (5) obese II 36–39, and (6) extremely obese ≥40. A multivariable logistic regression model was used to identify predictors of in-hospital mortality and to identify predictors of LOS.

Results

A weighted total of 219,950 hospitalizations for AHF across the US were analyzed. The mean age was 66.3 ± 31.5 years and most patients (51.8%) were male. The crude data showed a non-linear complex relationship between BMI and AHF population outcomes. Patients with elevated BMI exhibited significantly lower in-hospital mortality compared to the underweight and normal weight study participants (5.5, 5,5, 2,8, 1.6, 1.4, 1.6% in groups by BMI ≤ 19, 20–25, 26–30, 31–35, 36–39, and, ≥40 respectively, p < 0.001) and shorter LOS. In the multivariable regression model, BMI subgroups of ≤ 25kg/m² were found to be independent predictors of in-hospital mortality. Age and several comorbidities, and also the Deyo Comorbidity Index, were found to be independent predictors of increased mortality in the study population.

Conclusion

A reverse J-shaped relationship between BMI and mortality was documented in patients hospitalized for AHF in the recent years confirming the “obesity paradox” in the real-world setting.

The Association Between Obesity and Key Health or Psychosocial Outcomes Among Autistic Adults: A Systematic Review

Obesity is linked with health and psychosocial outcomes among many populations. However, it is unclear the extent to which obesity is linked with these outcomes among autistic adults. We searched seven research databases for articles examining the association between obesity and autistic adults' health and psychosocial outcomes. Three studies found that obesity was associated with health outcomes, including: in-hospital mortality, risk of type II diabetes, cardiovascular disease, and number of co-occurring medical conditions. One study found no significant association between autism diagnosis, mental health conditions, and body mass index. Obesity increases the risk of in-hospital mortality and some chronic conditions among autistic adults, highlighting the need for clinicians trained to promote weight management among autistic adults.

Pulmonary Artery Pressure Monitoring Effectively Guides Management to Reduce Heart Failure Hospitalizations in Obesity

OBJECTIVES

This study sought to determine the impact of therapy guided by pulmonary artery (PA) pressure monitoring in patients with heart failure (HF) and obesity.

BACKGROUND

Obesity is prevalent in HF and associated with volume retention, but it complicates clinical assessment of congestion.

METHODS

The CardioMEMS Post Approval Study was a prospective, multicenter, open-label trial in 1,200 patients with New York Heart Association functional class III HF and prior HF hospitalization (HFH) within 12 months. Patients with a body mass index (BMI) >35 kg/m² were required to have a chest circumference <65 inches. Therapy was guided by PA pressure monitoring at sites, and HFHs were adjudicated 1 year before implantation and throughout follow-up. This analysis stratified patients according to ejection fraction (EF) <40% or ≥40% and by BMI <35 kg/m² or ≥35 kg/m².

RESULTS

Baseline PA diastolic pressure was higher in patients with BMI ≥35 kg/m² regardless of EF, but all PA pressures were reduced at 12 months in each cohort (P < 0.0001). HFH rate was reduced by >50% in both cohorts for EF <40% (BMI <35 kg/m² [HR: 0.48; 95% CI: 0.41-0.55] and ≥35 kg/m² [HR: 0.40; 95% CI: 0.31-0.53]) and EF ≥40% (BMI <35 kg/m² [HR: 0.42; 95% CI: 0.35-0.52] and ≥35 kg/m² [HR: 0.34; 95% CI: 0.25-0.45]; P < 0.0001). There was a nonsignificant trend toward greater reduction with more obesity. The all-cause hospitalization rate was also significantly reduced during monitoring (P < 0.01).

CONCLUSIONS

Management guided by PA pressure monitoring effectively reduced pressures, HFH, and all-cause hospitalization in patients with obesity regardless of EF. (CardioMEMS HF System Post Approval Study; NCT02279888).

[Deterioration of gas exchange in subjects with an increase in body mass index at an altitude of 2,240 meters above sea level]

Introducción

Las alteraciones del intercambio gaseoso se han reconocido en la obesidad mórbida; sin embargo, no se conoce su comportamiento conforme se incrementa el índice de masa corporal.

Objetivo

Conocer el comportamiento del intercambio gaseoso a la altura de la Ciudad de México en el desarrollo de obesidad mórbida.

Métodos

Mediante un diseño transversal analítico se estudió a sujetos pareados por género y edad de cuatro grupos diferentes de índice de masa corporal (kg/m2): normal (18.5-24.9), sobrepeso (25-29.9), obesidad (30-39.9) y obesidad mórbida (≥ 40). Se obtuvieron sus antecedentes patológicos y demográficos, variables de gasometría arterial y espirometría simple. Las variables se determinaron de acuerdo con las características de la muestra; las diferencias entre grupos se realizaron mediante Anova de una vía con ajuste de Bonferroni, así como la correlación de Pearson para las variables relacionadas. Una p < 0.05 se consideró con significación estadística.

Resultados

Se estudió a 560 pacientes en cuatro grupos. La edad promedio fue de 49 ± 11 años. La mayor frecuencia de diabetes mellitus (34.29%), hipertensión arterial (50%) e hiperlipidemia (36.43%) se registró en el grupo de obesidad, y la de roncador (73.57%) en la obesidad mórbida. Se identificaron diferencias desde el grupo normal respecto de la obesidad mórbida: PaCO2 31.37 ± 2.08 vs. 38.14 ± 5.10 mmHg; PaO2 68.28 ± 6.06 vs. 59.86 ± 9.28 mmHg y SaO2 93.51 ± 1.93 vs. 89.71 ± 5.37%, todas con p = 0.0001. Correlación IMC-PaCO2: 0.497, e IMC-PaO2: -0.365, p = 0.0001, respectivamente.

Conclusiones

A la altitud de la Ciudad de México y con índice de masa corporal > 30 kg/m2, las variables relacionadas con el intercambio gaseoso y espirometría simple comienzan a deteriorarse; son evidentes con IMC > 40 kg/m2.

Introduction

Alterations of gas exchange have been recognized in morbid obesity, however, it is not known how their behavior would be as the body mass index increases.

Objective

To know the behavior of gas exchange at the level of Mexico City in the development of morbid obesity.

Methods

Through analytical design, subjects matched by gender and age were studied from four different groups of body mass index (kg/m2), normal (18.5-24.9), overweight (25-29.9), obesity (30-39.9) and morbid obesity (≥ 40). Their pathological and demographic antecedents, arterial blood gas and simple spirometry variables were obtained. The variables were shown according to their sample characteristic. The differences between groups were made using one way Anova with Bonferroni adjustment, as well as Pearson’s correlation for the related variables. Statistical significance was considered with p < 0.05.

Results

560 subjects were studied in 4 groups. The average age 49 ± 11 years old. The highest frequency of diabetes mellitus (34.29%), arterial hypertension (50%) and hiperlipidemia (36.43%) was in the obesity group, and being snoring (73.57%) in morbid obesity. There were differences from the normal group versus. morbid obesity: PaCO2 31.37 ± 2.08 versus. 38.14 ± 5.10 mmHg; PaO2 68.28 ± 6.06 versus. 59.86 ± 9.28 mmHg and SaO2 93.51 ± 1.93 versus. 89.71 ± 5.37%, all with p = 0.0001. The IMC-PaCO2 correlation: 0.497, and IMC-PaO2: −0.365, p = 0.0001 respectively.

Conclusions

At the altitude of Mexico City and body mass index > 30 kg/m2 the variables related to gas exchange and simple spirometry begin to deteriorate; are evident with BMI > 40 kg/m2.