scholarly journals Searching for an optimal AUC estimation method: a never-ending task?

2014 ◽  
Vol 41 (6) ◽  
pp. 655-673 ◽  
Author(s):  
Wojciech Jawień
2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S645-S646
Author(s):  
Justin Spivey ◽  
Jenny Shroba ◽  
Connor Deri ◽  
Cara Nys ◽  
Rebekah Wrenn ◽  
...  

Abstract Background Recent guidelines recommend a transition from trough-based to area-under the curve-based (AUC) monitoring for vancomycin for serious invasive methicillin-resistant Staphylococcus aureus infections. Due to the challenges of performing AUC monitoring in clinical practice, this study sought to compare the accuracy of an AUC calculated from two points using trapezoidal calculations and from a single steady-state trough combined with population assumptions. Methods This prospective cohort analysis included hospitalized patients with stable renal function from 10.2020 to 12.2020 with two vancomycin concentrations obtained at steady-state during a single dosing interval. For each patient, AUC was calculated via trapezoidal equations utilizing peak and trough concentrations (P/T) and using the trough concentration (T) combined with population volume of distribution. Appropriate concentrations were defined as a peak at least 2 hours after the end of the infusion and a trough within one hour of the next dose. The percent and actual differences were calculated between the P/T and T AUC assessments for each patient. A patient level review was independently conducted by two clinical pharmacists to evaluate if a change in dosing would have been made according to AUC estimation methodology. Results Thirty-one patients had appropriate steady-state P/T obtained. Baseline demographics are shown in Table 1 with the majority of patients being overweight with normal renal function. The mean calculated AUC for both groups was similar, P/T 544.8 and T 549.8. The mean and median percent differences were 1.85% and 0.65%, with a standard deviation of 7.3% and an apparent normal distribution (Figure 1, p = 0.94 by Shapiro’s test). The median absolute difference in AUC was 25.82 mg*h/L between methodologies. Both methods would have resulted in the same modification to the vancomycin regimen based on patient level chart review. Conclusion The single-trough method performed similarly to the more laborious P/T method. No patient would have received a dose adjustment based on the two different AUC estimation methods. The single-trough method may represent a resource and workflow conscious AUC estimation method for patients meeting population assumptions. Disclosures All Authors: No reported disclosures


1995 ◽  
Author(s):  
Nagykaldi Csaba ◽  
Manohar Singh Badhan
Keyword(s):  

2018 ◽  
Vol 1 (1) ◽  
pp. 21-37
Author(s):  
Bharat P. Bhatta

This paper analyzes and synthesizes the fundamentals of discrete choice models. This paper alsodiscusses the basic concept and theory underlying the econometrics of discrete choice, specific choicemodels, estimation method, model building and tests, and applications of discrete choice models. Thiswork highlights the relationship between economic theory and discrete choice models: how economictheory contributes to choice modeling and vice versa. Keywords: Discrete choice models; Random utility maximization; Decision makers; Utility function;Model formulation


2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.


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