5 research outputs found

    Insurance status impacts treatment for hepatocellular carcinoma

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    Introduction and aim: Previous studies have identified treatment disparities in the treatment of hepatocellular carcinoma (HCC) based on insurance status and provider. Recent studies have shown more Americans have healthcare insurance; therefore we aim to determine if treatment disparities based on insurance providers continue to exist. Materials and methods: A retrospective database analysis using the NIS was performed between 2010 and 2013 including adult patients with a primary diagnosis of HCC determined by ICD-9 codes. Multivariable logistic regressions were performed to analyze differences in treatment, mortality, features of decompensation, and metastatic disease based on the patient's primary payer. Results: This study included 62,368 patients. Medicare represented 44% of the total patients followed by private insurance (27%), Medicaid (19%), and other payers (10%). Patients with Medicare, Medicaid, and other payer were less likely to undergo liver transplantation [(OR 0.63, 95% CI 0.47–0.84), (OR 0.23, 95% CI 0.15–0.33), (OR 0.26, 95% CI 0.15–0.45)] and surgical resection [(OR 0.74, 95% CI 0.63–0.87), (OR 0.40, 95% CI 0.32–0.51), (OR 0.42, 95% CI 0.32–0.54)] than patients with private insurance. Medicaid patients were less likely to undergo ablation then patients with private insurance (OR 0.52, 95% CI 0.40–0.68). Patients with other forms of insurance were less likely to undergo transarterial chemoembolization (TACE) compared to private insurance (OR 0.64, 95% CI 0.43–0.96). Conclusion: Insurance status impacts treatment for HCC. Patients with private insurance are more likely to undergo curative therapies of liver transplantation and surgical resection compared to patients with government funded insurance

    Impact of Recipient and Donor Obesity Match on the Outcomes of Liver Transplantation: All Matches Are Not Perfect

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    There is a paucity of literature examining recipient-donor obesity matching on liver transplantation outcomes. The United Network for Organ Sharing database was queried for first-time recipients of liver transplant whose age was ≥18 between January 2003 and September 2013. Outcomes including patient and graft survival at 30 days, 1 year, and 5 years and overall, liver retransplantation, and length of stay were compared between nonobese recipients receiving a graft from nonobese donors and obese recipient-obese donor, obese recipient-nonobese donor, and nonobese recipient-obese donor pairs. 51,556 LT recipients were identified, including 34,217 (66%) nonobese and 17,339 (34%) obese recipients. The proportions of patients receiving an allograft from an obese donor were 24% and 29%, respectively, among nonobese and obese recipients. Graft loss (HR: 1.27; 95% CI: 1.09–1.46; p=0.002) and mortality (HR: 1.38; 95% CI: 1.16–1.65; p<0.001) at 30 days were increased in the obese recipient-obese donor pair. However, 1-year graft (HR: 0.83; 95% CI: 0.74–0.93; p=0.002) and patient (HR: 0.84; 95% CI: 0.74–0.95; p=0.007) survival and overall patient (HR: 0.93; 95% CI: 0.86–1.00; p=0.042) survival were favorable. There is evidence of recipient and donor obesity disadvantage early, but survival curves demonstrate improved long-term outcomes. It is important to consider obesity in the donor-recipient match

    A validated risk model for prediction of early readmission in patients with hepatic encephalopathy

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    Introduction and aim: Hepatic encephalopathy (HE) is a common complication in cirrhotics and is associated with an increased healthcare burden. Our aim was to study independent predictors of 30-day readmission and develop a readmission risk model in patients with HE. Secondary aims included studying readmission rates, cost, and the impact of readmission on mortality. Materials and methods: We utilized the 2013 Nationwide Readmission Database (NRD) for hospitalized patients with HE. A risk assessment model based on index hospitalization variables for predicting 30-day readmission was developed using multivariate logistic regression and validated with the 2014 NRD. Patients were stratified into Low Risk and High Risk groups. Cox regression models were fit to identify predictors of calendar-year mortality. Results: Of 24,473 cirrhosis patients hospitalized with HE, 32.4% were readmitted within 30 days. Predictors of readmission included presence of ascites (OR: 1.19; 95% CI: 1.06–1.33), receiving paracentesis (OR: 1.43; 95% CI: 1.26–1.62) and acute kidney injury (OR: 1.11; 95% CI: 1.00–1.22). Our validated model stratified patients into Low Risk and High Risk of 30-day readmissions (29% and 40%, respectively). The cost of the first readmission was higher than index admission in the 30-day readmission cohort (14,198vs.14,198 vs. 10,386; p-value <0.001). Thirty-day readmission was the strongest predictor of calendar-year mortality (HR: 4.03; 95% CI: 3.49–4.65). Conclusions: Nearly one-third of patients with HE were readmitted within 30 days, and early readmission adversely impacted healthcare utilization and calendar-year mortality. With our proposed simple risk assessment model, patients at high risk for early readmissions can be identified to potentially avert poor outcomes
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