Effect of Undernutrition and Obesity on Clinical Outcomes in Adults with Community-Acquired Pneumonia

Socio-demographic and comorbid risk factors for poor prognosis in patients hospitalized with community-acquired bacterial pneumonia in southeastern US

BACKGROUND

How socio-demographic characteristics and comorbidities affect bacterial community-acquired pneumonia (CAP) prognosis during/after hospitalization is important in disease management.

OBJECTIVES

To identify predictors of medical intensive care unit (MICU) admission, length of hospital stay (LOS), in-hospital mortality, and bacterial CAP readmission in patients hospitalized with bacterial CAP.

METHODS

ICD-9/10 codes were used to query electronic medical records to identify a cohort of patients hospitalized for bacterial CAP at a tertiary hospital in Southeastern US between 01/01/2013-12/31/2019. Adjusted accelerated failure time and modified Poisson regression models were used to examine predictors of MICU admission, LOS, in-hospital mortality, and 1-year readmission.

RESULTS

There were 1956 adults hospitalized with bacterial CAP. Median (interquartile range) LOS was 11 days (6-23), and there were 26 % (513) MICU admission, 14 % (266) in-hospital mortality, and 6 % (117) 1-year readmission with recurrent CAP. MICU admission was associated with heart failure (RR 1.38; 95 % CI 1.17-1.62) and obesity (RR 1.26; 95 % CI 1.04-1.52). Longer LOS was associated with heart failure (adjusted time ratio[TR] 1.27;95 %CI 1.12-1.43), stroke (TR 1.90;95 %CI 1.54,2.35), type 2 diabetes (TR 1.20;95 %CI 1.07-1.36), obesity (TR 1.50;95 %CI 1.31-1.72), Black race (TR 1.17;95 %CI 1.04-1.31), and males (TR 1.24;95 %CI 1.10-1.39). In-hospital mortality was associated with stroke (RR 1.45;95 %CI 1.03-2.04) and age ≥65 years (RR 1.34;95 %CI 1.06-1.68). 1-year readmission was associated with COPD (RR 1.55;95 %CI 1.05-2.27) and underweight BMI (RR 1.74;95 %CI 1.04-2.90).

CONCLUSIONS

Comorbidities and socio-demographic characteristics have varying impacts on bacterial CAP in-hospital prognosis and readmission. More studies are warranted to confirm these findings to develop comprehensive care plans and inform public health interventions.

Model-Informed Approaches to Support Drug Development for Patients With Obesity: A Regulatory Perspective

Obesity, which is defined as having a body mass index of 30 kg/m2 or greater, has been recognized as a serious health problem that increases the risk of many comorbidities (eg, heart disease, stroke, and diabetes) and mortality. The high prevalence of individuals who are classified as obese calls for additional considerations in clinical trial design. Nevertheless, gaining a comprehensive understanding of how obesity affects the pharmacokinetics (PK), pharmacodynamics (PD), and efficacy of drugs proves challenging, primarily as obese patients are seldom selected for enrollment at the early stages of drug development. Over the past decade, model-informed drug development (MIDD) approaches have been increasingly used in drug development programs for obesity and its related diseases as they use and integrate all available sources and knowledge to inform and facilitate clinical drug development. This review summarizes the impact of obesity on PK, PD, and the efficacy of drugs and, more importantly, provides an overview of the use of MIDD approaches in drug development and regulatory decision making for patients with obesity: estimating PK, PD, and efficacy in specific dosing scenarios, optimizing dose regimen, and providing evidence for seeking new indication(s). Recent review cases using MIDD approaches to support dose selection and provide confirmatory evidence for effectiveness for patients with obesity, including pediatric patients, are discussed. These examples demonstrate the promise of MIDD as a valuable tool in supporting clinical trial design during drug development and facilitating regulatory decision-making processes for the benefit of patients with obesity.

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.

Implications of obesity and adiposopathy on respiratory infections; focus on emerging challenges

Obesity is characterized by excessive adipose tissue accumulation, which impacts physiological, metabolic, and immune functions. Several respiratory infections, including bacterial pneumonia, influenza, and coronavirus disease 2019, appear to be linked to unfavorable results in individuals with obesity. These may be attributed to the direct mechanical/physiological effects of excess body fat on the lungs’ function. Notably, adipose tissue dysfunction is associated with a low-grade chronic inflammatory status and hyperleptinemia, among other characteristics. These have all been linked to immune system dysfunction and weakened immune responses to these infections. A better understanding and clinical awareness of these risk factors are necessary for better disease outcomes.

Are Undernutrition and Obesity Associated with Post-Discharge Mortality and Re-Hospitalization after Hospitalization with Community-Acquired Pneumonia?

Undernutrition is associated with increased mortality after hospitalization with community-acquired pneumonia (CAP), whereas obesity is associated with decreased mortality in most studies. We aimed to determine whether undernutrition and obesity are associated with increased risk of re-hospitalization and post-discharge mortality after hospitalization. This study was nested within the Surviving Pneumonia cohort, which is a prospective cohort of adults hospitalized with CAP. Patients were categorized as undernourished, well-nourished, overweight, or obese. Undernutrition was based on diagnostic criteria by the European Society for Clinical Nutrition and Metabolism. Risk of mortality was investigated using multivariate logistic regression and re-hospitalization with competing risk Cox regression where death was the competing event. Compared to well-nourished patients, undernourished patients had a higher risk of 90-day (OR 3.0, 95% CI 1.0; 21.4) mortality, but a similar 30-day and 180-day mortality risk. Obese patients had a similar re-hospitalization and mortality risk as well-nourished patients. In conclusion, among patients with CAP, undernutrition was associated with increased risk of mortality. Undernourished patients are high-risk patients, and our results indicate that in-hospital screening of undernutrition should be implemented to identify patients at mortality risk. Studies are required to investigate whether nutritional therapy after hospitalization with CAP would improve survival.

Moderate-to-Severe Malnutrition Identified by the Controlling Nutritional Status (CONUT) Score Is Significantly Associated with Treatment Failure of Periprosthetic Joint Infection

The prevalence and role of malnutrition in periprosthetic joint infection (PJI) remain unclear. This study aimed to use measurable nutritional screening tools to assess the prevalence of malnutrition in PJI patients during two-stage exchange arthroplasty and to explore the association between malnutrition and treatment failure. Our study retrospectively included 183 PJI cases who underwent 1st stage exchange arthroplasty and had available nutritional parameters, of which 167 proceeded with 2nd stage reimplantation. The recently proposed Musculoskeletal Infection Society (MSIS) Outcome Reporting Tool was used to determine clinical outcomes. The Controlling Nutritional Status (CONUT), Nutritional Risk Index (NRI), and Naples Prognostic Score (NPS) were used to identify malnutrition at 1st and 2nd stage exchange, respectively. Multivariate logistic regression analyses were performed to determine the association between malnutrition and treatment failure. Restricted cubic spline models were further used to explore the dose−response association. Additionally, risk factors for moderate-to-severe malnutrition were evaluated. Malnourished patients identified by CONUT, NPS, and NRI accounted for 48.1% (88/183), 98.9% (181/183), and 55.7% (102/183) of patients at 1st stage, and 9.0% (15/167), 41.9% (70/167), and 43.1% (72/167) at 2nd stage, indicating a significant improvement in nutritional status. We found that poorer nutritional status was a predictor of treatment failure, with CONUT performing best as a predictive tool. Moderate-to-severe malnutrition at 1st stage identified by CONUT was significantly related to treatment failure directly caused by PJI (odds ratio [OR] = 5.86), while the OR was raised to 12.15 at 2nd stage (OR = 12.15). The linear dose−response associations between them were also confirmed (P for nonlinearity at both 1st and 2nd stage > 0.05). As for total treatment failure, moderate-to-severe malnutrition as determined by CONUT was associated with a 1.96-fold and 8.99-fold elevated risk at the 1st and 2nd stages, respectively. Age ≥ 68 years (OR = 5.35) and an increased number of previous surgeries (OR = 2.04) may be risk factors for moderate-to-severe malnutrition. Overall, the prevalence of malnutrition in PJI patients is very high. Given the strong association between moderate-to-severe malnutrition identified by CONUT and PJI treatment failure, COUNT could be a promising tool to evaluate the nutritional status of PJI patients to optimize treatment outcomes.