What Is Acute Kidney Injury (AKI)?

Acute kidney injury (AKI) is a subset of acute kidney diseases and disorders (AKD), that encompasses all acute renal conditions and is contrasted by chronic kidney disease (CKD).1
Approximately 1.7 million deaths per year worldwide can be attributed to AKI. In addition to long lengths of hospital stays (LOS), severe AKI sequelae can range from life-long dialysis to kidney transplantation.1
A sudden decrease in renal function, indicated by renal failure and/or a decline in glomerular filtration rate (GFR), is considered an AKI.

Figure 1. Key elements involved in AKI. Adapted from KDIGO Clinical Practice Guidelines for Acute Kidney Injury1

The diagnostic criteria and severity classifications for AKI use serum creatinine (SCr) and urine output (UO) as surrogate parameters (Figure 1).2 However, in a study by Chertow et al., modest changes in SCr were significantly correlated with mortality, LOS, and hospital costs. This correlation remained even after adjustment for a variety of factors such as age, gender, admission by the International Classification of Diseases (ICD), modification diagnosis, severity of illness (diagnosis-related group weight), and CKD status. An increase in SCr greater than 0.5 mg/dL was associated with a 6.5-fold (95% CI [5.0, 8.5]) increase in the odds of death (Figure 2), a 3.5-day increase in LOS, and nearly $7500 excess in hospital costs (Figure 3).3

Why is Bayesian Modeling the Method of Choice to Estimate AUC?

New 2020 IDSA vancomycin dosing guidelines published in March recommend monitoring the pharmacodynamic index AUC/MIC to predict the safety and efficacy of vancomycin therapy in patients with serious MRSA infection. This recommendation is based on compelling evidence showing that a vancomycin AUC/MIC ratio of 400 to 600 mg*h/L optimizes clinical efficacy and reduces vancomycin-related nephrotoxicity [1,2]. AUC calculation can be accomplished using either a Bayesian dosing software or a formula-based approach, such as the trapezoidal model. Manual AUC calculation is cumbersome and time-consuming, as it requires more computing efforts and pharmacokinetic sampling (at least two serum levels). The Bayesian approach is the preferred method to estimate AUC, as it provides several advantages compared to traditional PK calculation:

1. Dynamic models that employ continuous machine learning
2. Requires limited pharmacokinetic sampling (as little as one serum level) for precise Bayesian modeling
3. Cost-saving, highly efficient and less biased dosing strategy

The image above depicts the comparison between typical measurements of predicted vancomycin concentrations using Bayesian method and formula-based methods. From this, we see that Bayesian method results in more accurate predictions.

Why Should You Consider PrecisePK?

The transition from trough-based dosing to area-under-the-curve based dosing protocols can be challenging. Clinical decision support software can facilitate this change by performing the complex Bayesian calculations that aide in the optimal dosing recommendation for each patient. PrecisePK is a user-friendly EHR integrated Therapeutic Drug Monitoring (TDM) Precision Dosing platform driven by Bayesian Analytics. It has been used in numerous hospitals worldwide for over 30 years and was validated by a third-party to give the most accurate and least biased vancomycin AUC results. [3] We use research-based population-specific data and advanced Bayesian analytics to adjust the population values of pharmacokinetic parameters (F, Vd, CL, CF, etc.) and serum level data. Upon entering the patient's demographic information, the program will automatically select the best population model (i.e critically-ill, obese, pediatric, etc) derived from current peer-reviewed literature that is most representative for the patient. Advanced users can also choose to modify the model selection or PK parameters (i.e Vd, CL) that best describe the patient based on their personal experience and clinical judgement. Using our program, users can quickly calculate AUC between two pre-selected time points, analyze dose efficacy, and simulate possible dosage regimen. PrecisePK projects serum level charts that help users predict what the next dose should be using as little as a single serum level.

What Do Pharmacists Like About PrecisePK?

Many of our clinical pharmacist users have come to love the software’s ease of use and the reliable pharmacokinetic monitoring it provides. PrecisePK has become an indispensable component in their practice including daily clinical activities, making dosing recommendations, and research activities related to AUC vancomycin dosing. Jennifer Le, an ID pharmacist specialist, co-author of the new 2020 vancomycin consensus guideline, and UCSD professor of Clinical Pharmacy said “The new version is amazing visually and user-friendly too, requiring minimal training. The unique features of this platform that I find especially helpful for patient care are flexibility in selecting neonatal, pediatric, and adult models to ensure you select the best Bayesian prior for your patient population.” Lauren Dea Pharm. D., used PrecisePK extensively as a PGY2 Infectious Disease resident and commented “The program has helped my research become vastly more efficient due to the ease of inputting patient information and determining dosing recommendations. I would not have been able to retrospectively collect 4 years of vancomycin orders within a condensed residency year without the streamlined efficiency of entering info into their program. They also developed a unique Bayesian model for our unique patient population with a specific set of Bayesian priors.”

Interested in trying out PrecisePK's Bayesian precision dosing software? Book a demo with us today to explore our wide range of features and to see how PrecisePK can help streamline your clinical workflow.