A value-based budget impact model for dronedarone compared with other rhythm control strategies

Aim: The budgetary consequences of increasing dronedarone utilization for treatment of atrial fibrillation were evaluated from a US payer perspective. Materials & methods: A budget impact model over a 5-year time horizon was developed, including drug-related costs and risks for long-term clinical outcomes (LTCOs). Treatments included antiarrhythmic drugs (AADs; dronedarone, amiodarone, sotalol, propafenone, dofetilide, flecainide), rate control medications, and ablation. Direct comparisons and temporal and non-temporal combination scenarios investigating treatment order were analyzed as costs per patient per month (PPPM). Results: By projected year 5, costs PPPM for dronedarone versus other AADs decreased by $37.69 due to fewer LTCOs, treatment with dronedarone versus ablation or rate control medications + ablation resulted in cost savings ($359.94 and $370.54, respectively), and AADs placed before ablation decreased PPPM costs by$242 compared with ablation before AADs. Conclusion Increased dronedarone utilization demonstrated incremental cost reductions over time

Predictive performance of ten equations for estimating creatinine clearance in cardiac patients

OBJECTIVE: The predictive performance of 10 equations used to estimate creatinine clearance (Clcr) was assessed retrospectively from data collected on 420 patients. DESIGN: This study is a retrospective data analysis of information collected on hemodynamically stable patients awaiting coronary angiography during the Iohexol Cooperative Study. SETTING: The Iohexol Cooperative Study was a multicenter study that compared nephrotoxicity of high- and low-osmolar contrast media in patients undergoing coronary angiography. Data used for this analysis were preangiography 24-hour urine collections that were primarily collected in hospitalized patients. PATIENTS: Patients selected from the Iohexol Cooperative Study database for analysis were participants categorized into one or more of six subgroups: elderly (n = 222), hypoalbuminemic (n = 25), chronic renal insufficiency (n = 128), low serum creatinine (n = 115), obese (n = 208), and diabetic (n = 191) who had baseline urine collections of at least 24 hours. OUTCOME MEASURES: Predictive performance was assessed using bias, precision, slopes, and y-intercepts. RESULTS: The Salazar–Corcoran equation was unbiased in the entire group as well as in five of the subgroups. The Cockcroft–Gault equation was unbiased in three of the subgroups. All other equations were biased in predicting Clcr in the entire group as well as in at least four of the subgroups. Precision was generally poor. All slopes were significantly different than one and all y-intercepts were significantly different than zero (p \u3c 0.01). Correlation coefficients were between 0.63 and 0.79 with the exceptions of the low serum creatinine subgroup (r values 0.35–0.64) and the Davis–Chandler equation (r values 0.35–0.71 across groups). CONCLUSIONS: Of the equations studied, Salazar–Corcoran and Cockcroft–Gault appear to be the best for predicting Clcr