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1.
Dig Dis Sci ; 60(10): 3124-9, 2015 Oct.
Article in English | MEDLINE | ID: mdl-25986524

ABSTRACT

BACKGROUND: Clostridium difficile infection (CDI) is an important public health problem in hospitalized patients. Patients with cirrhosis are particularly at risk of increased associated morbidity, mortality, and healthcare utilization from CDI. AIM: The aim of this study was to assess the pharmacoeconomic impact of CDI screening on hospitalized patients with cirrhosis. METHODS: A Markov model was used to compare costs and outcomes of two strategies for the screening of CDI. The first strategy consisted of screening all patients for CDI and treating if detected (screening). In the second strategy, only patients found to have symptomatic CDI were treated (no screening). The probability of underlying CDI prevalence, symptomatic CDI infection, and likelihood of recurrent infection were varied in a sensitivity analysis. The costs of antibiotics and hospitalization were also assessed. Differences in outcome were expressed in ratio of the total costs associated with screening to the total costs associated without screening. RESULTS: The results of our model showed that screening for CDI was consistently associated with improved healthcare outcomes and decreased healthcare utilization across all variables in the one- and two-way sensitivity analyses. Using baseline assumptions, the costs associated with the no screening strategy were 3.54 times that of the screening strategy. Moreover, the mortality for symptomatic CDI was lower in the screening strategy than the no screening strategy. CONCLUSION: The screening strategy results in less healthcare utilization and improved clinical outcomes. Screening for CDI measures favorably.


Subject(s)
Clostridioides difficile/isolation & purification , Clostridium Infections/epidemiology , Cost Savings , Liver Cirrhosis/epidemiology , Markov Chains , Mass Screening/economics , Aged , Analysis of Variance , Cost-Benefit Analysis , Cross Infection/prevention & control , Cross-Sectional Studies , Female , Hospitalization/statistics & numerical data , Humans , Incidence , Length of Stay/economics , Liver Cirrhosis/diagnosis , Liver Cirrhosis/therapy , Male , Mass Screening/methods , Middle Aged , Risk Assessment
2.
Liver Int ; 35(1): 164-70, 2015 Jan.
Article in English | MEDLINE | ID: mdl-24313970

ABSTRACT

BACKGROUND & AIMS: It is controversial if obesity has an impact on overall survival after liver transplantation (LT). The goal of this study was to determine if obesity impacts liver transplant recipient survival. Through subgroup analysis, we also evaluated different body mass index (BMI) thresholds and the confounding effect of ascites on survival. METHODS: A systematic literature search from 1990 until July 2013. The main outcome was to evaluate the impact of obesity on survival in adult LT recipients. Dochotomous outcomes were reported as relative risk (RR) with 95% confidence intervals (CI). RESULTS: Thirteen studies with a total 2275 obese and 72 212 non obese patients were included in the analysis. The combined analysis showed no difference in mortality between control and increased weight patients (RR = 0.97, 95% CI [0.82, 1.13], P = 0.66) at last follow-up. Moreover, no differences in mortality were noted in subgroup analysis comparing different BMI thresholds. There was also no differences in survival when BMI was adjusted for ascites or in studies where the liver disease severity was similar. Obese patients had worse survival than nonobese patients in pooled analysis of studies which had similar causes of liver disease (RR = 0.69, 95% CI [0.52, 0.92], P = 0.01). CONCLUSION: The results of our pools analysis suggest that BMI does not specifically impact patient survival. However, obese patients have worse survival when analysis was performed in studies whose cohorts of obese and nonobese patients had similar causes of liver disease.


Subject(s)
Liver Transplantation/mortality , Obesity/complications , Transplant Recipients/statistics & numerical data , Adult , Ascites/pathology , Body Mass Index , Humans , Middle Aged , Risk , Survival Analysis
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