1091. Validation of an Allometrically Scaled Body Weight Equation to Predict Vancomycin Clearance and Guide 24-Hour Vancomycin AUC Dosing in Obese Patients

Abstract Background Accurately determining empiric vancomycin (VAN) doses in obese patients represents a clinical challenge. A recent population pharmacokinetic (PK) study provided an equation to estimate vancomycin clearance (CL) based on age, sex, serum creatinine (Scr), and allometrically scaled body weight. The purpose of this study was to validate this equation in a population of obese adults treated with vancomycin at eight community-based hospitals and use the CL estimate to guide empiric VAN dosing. Methods The study period was November 1, 2020 and March 30, 2021. Patients were included if they were ≥ 18-year-old with a body mass index (BMI) ≥ 30 kg/m2, had an empiric dose targeting an AUC24 determined using the above referenced equation, and had a calculated AUC24. Only the first vancomycin course and AUC calculation for each patient were included. Patients with a creatinine clearance < 30ml/min and pregnant women were excluded. AUC24 and other PK parameters were calculated using two levels and noncompartmental analysis. Observed versus predicted CL and AUC24 were plotted to determine correlation. Results Sixty patients were included, of which 60% were male and 33% had a confirmed methicillin-resistant Staphylococcus aureus infection. The mean age, BMI, and baseline Scr were 61.8 years, 37.8 kg/m2, and 0.99 mg/dL, respectively. Fifty-three (88%) patients received a loading dose, with a mean dose of 20.3mg/kg. The mean initial total daily maintenance dose was 2397.9mg. The mean predicted AUC24 was 476.4mg*h/L while the mean observed AUC24 was 556.3mg*h/L. For CL, the correlation between observed and predicted values was R2=0.38 (Figure 1). The correlation between predicted and observed AUC24 values was R2=0.08 (Figure 2). The percent of patients with observed AUC24 values of < 400mg*h/L, 400-600mg*h/L, and >600mg*h/L were 23%, 40%, and 37%, respectively. The relationship between calculated minimum concentrations (Cmin) and AUC24 is shown in Figure 3. 65% of patients with a therapeutic AUC achieved it with a Cmin < 15mg/L while 4.5% of patients with a supratherapeutic AUC had a Cmin < 15mg/L. Figure 1. Observed versus Predicted Clearance (CL) of Vancomycin Figure 2. Observered versus Predicted 24 hour Vancomycin Area Under the Curve (AUC24) Figure 3. Calculated 24 hour Vancomycin Area Under the Curve (AUC24) versus Calculated minimal concentration (Cmin) Conclusion The correlation between observed and predicted CL was 0.38. Using these CL estimates to guide empiric VAN dosing resulted in only 40% of patients achieving a therapeutic AUC24. Disclosures All Authors: No reported disclosures


Session: P-62. PK/PD Studies
Background. Recent vancomycin (VAN) guidelines recommend targeting an area under the curve (AUC) concentration of 400-600 for treatment of methicillin resistant Staphylococcus aureus infections. Multiple strategies for calculating AUC exist, including first order pharmacokinetic (foPK) equations and Bayesian models. Most clinical applications of foPK assume unchanged patient status and project ideal administration times to estimate exposure. Bayesian modeling provides the best estimate of true drug exposure and can incorporate changing patient covariates and exact doses. We compared two commonly used foPK methods to Bayesian estimates of VAN AUC.
Methods. First order equations were performed using population PK estimates (foPOPPK) to estimate steady state (SS) AUC and initial doses. Two concentrations after first dose were used to estimate SS AUC (foFDPK). A 2-compartment Bayesian model allometrically scaled for weight and adjusted for creatinine clearance was used to determine 24-48 hour AUCs. Differences between AUCs were compared using a mixed-effects analysis, and correlation of foPK equations to Bayesian estimates was described using Spearman's correlation. Patient results from each method were classified as below (< 400), within (400-600), or above ( >600) targets.
Conclusion. AUCs calculated by the three methods did not differ on average, but dosing recommendations for foPK at the patient level varied substantially compared to the Bayesian method. This difference is because Bayesian estimation incorporates actual patient exposures while foPK equations rely on idealized dose timing to predict AUCs. Disclosures

Validation of an Allometrically Scaled Body Weight Equation to Predict Vancomycin Clearance and Guide 24-Hour Vancomycin AUC Dosing in Obese Patients
Brent Footer, PharmD, BCPS 1 ; Arthur Nguyen, PharmD 1 ; Meagan Greckel, PharmD 1 ; Colton Taylor, PharmD 2 ; Alyssa Christensen, PharmD, BCIDP 2 ; Gregory Tallman, PharmD, BCIDP, BCPS 3 ; 1 Providence Portland Medical Center, Portland, Oregon; 2 Providence Saint Vincent Medical Center, Portland, Oregon; 3 School of Pharmacy, Pacific University, Portland, Oregon Session: P-62. PK/PD Studies Background. Accurately determining empiric vancomycin (VAN) doses in obese patients represents a clinical challenge. A recent population pharmacokinetic (PK) study provided an equation to estimate vancomycin clearance (CL) based on age, sex, serum creatinine (Scr), and allometrically scaled body weight. The purpose of this study was to validate this equation in a population of obese adults treated with vancomycin at eight community-based hospitals and use the CL estimate to guide empiric VAN dosing.
Methods. The study period was November 1, 2020 and March 30, 2021. Patients were included if they were ≥ 18-year-old with a body mass index (BMI) ≥ 30 kg/m 2 , had an empiric dose targeting an AUC24 determined using the above referenced equation, and had a calculated AUC24. Only the first vancomycin course and AUC calculation for each patient were included. Patients with a creatinine clearance < 30ml/min and pregnant women were excluded. AUC24 and other PK parameters were calculated using two levels and noncompartmental analysis. Observed versus predicted CL and AUC24 were plotted to determine correlation.
Results. Sixty patients were included, of which 60% were male and 33% had a confirmed methicillin-resistant Staphylococcus aureus infection. The mean age, BMI, and baseline Scr were 61.8 years, 37.8 kg/m 2 , and 0.99 mg/dL, respectively. Fifty-three (88%) patients received a loading dose, with a mean dose of 20.3mg/kg. The mean initial total daily maintenance dose was 2397.9mg. The mean predicted AUC24 was 476.4mg*h/L while the mean observed AUC24 was 556.3mg*h/L. For CL, the correlation between observed and predicted values was R 2 =0.38 (Figure 1). The correlation between predicted and observed AUC24 values was R 2 =0.08 (Figure 2). The percent of patients with observed AUC24 values of < 400mg*h/L, 400-600mg*h/L, and >600mg*h/L were 23%, 40%, and 37%, respectively. The relationship between calculated minimum concentrations (C min ) and AUC24 is shown in Figure 3. 65% of patients with a therapeutic AUC achieved it with a C min < 15mg/L while 4.5% of patients with a supratherapeutic AUC had a C min < 15mg/L. Conclusion. The correlation between observed and predicted CL was 0.38. Using these CL estimates to guide empiric VAN dosing resulted in only 40% of patients achieving a therapeutic AUC24.
Disclosures. All Authors: No reported disclosures

Background.
Obesity is a significant global health problem and has been associated with altered pharmacokinetics (PK) and pharmacodynamics (PD) of many drugs. Cephalexin is a commonly prescribed antibiotic as an oral drug for the treatment of mild to moderate infections; however, little is known regarding cephalexin pharmacokinetics in obese patients. The objective of this study was to investigate the population PK of cephalexin in non-obese and obese patients.
Methods. Hospitalized patients who were 18 years or older with a suspected or documented infection were studied. Patients weighing < 120 kg were defined as non-obese patients whereas those weighing ≥ 120 kg as obese. All included patients received cephalexin 1000 mg every 6 hours orally. After ≥ 3 days of therapy, serial blood samples were collected. Ultrafiltration was used to separate the unbound drug from the protein-bound fractions, and both total and unbound serum concentrations were determined by HPLC. The concentration-time data for cephalexin were analyzed by a non-linear mixed effects modeling approach using NONMEM.
Results. Overall, 255 serum concentrations from 19 patients (10 males, 4 in an ICU) were included; ten patients were non-obese (total body weight [TBW] < 120 kg) and nine were obese (TBW ≥ 120 kg). A 1-compartment model with first-order absorption, absorption lag-time, first-order elimination, and linear protein binding best fit the concentration-time data. Creatinine clearance (CrCl) was the only covariate significantly associated with cephalexin PK, specifically systemic clearance (CL): CL (L/h) = 12.3 + [0.0837*(CRCL -81.8)]. No other covariates significantly affected the model-derived PK parameters including CL, volume of distribution (V), first-order absorption rate constant (K a ), unbound fraction (f u ) with the fixed estimate of 0.776, and absorption lag-time (T lag ).
Conclusion. In conclusion, cephalexin PK is comparable between non-obese and obese patients. Dosing adjustments based solely on body size may not be necessary. Further analyses are warranted to suggest optimal cephalexin dosages in obesity through large-scale population PK-PD modeling and simulation.
Disclosures. Background. Patient interview, penicillin skin testing (PST) and/or an oral challenge can be used to evaluate penicillin allergies. Programs favor PST prior to oral challenge, but there is interest in bypassing PST and directly oral challenging for logistical and financial reasons. Data on the safety and efficacy of a direct challenge in the inpatient setting when the index reaction is moderate to severe (e.g. swelling of throat, angioedema, anaphylaxis) is lacking.
Methods. Adult patients (≥18 years) admitted with a penicillin allergy were evaluated for eligibility between September 2019 and June 2021. Pregnant patients were excluded, while critically ill patients and those on anti-histamine medications were evaluated if clinical need was high. Institutional protocols allowing for patients to be challenged without PST if reaction was more than 10 years ago were used. Data collected included the number of patients challenged and delabeled, number of patients who had moderate to severe index reactions, number of patients who were relabeled without cause, and number of patients who declined further testing.
Results. Two hundred twenty-five patients were evaluated; 11 patients declined testing. Two hundred four patients were delabeled (95%) among those fully evaluated. One hundred twelve patients were delabeled by interview and chart review alone (52%), 99 by oral challenge (46%), and 2 by PST and oral challenge (1%). Twenty-nine patients with moderate to severe reactions were challenged and 27 were delabeled. Ten patients could not be delabeled due to mild or delayed reactions to challenge or subsequent treatment, including 2 patients with severe index reactions who had mild challenge reactions and required no rescue medications. No patients required epinephrine during challenge. Five patients were relabeled and then delabeled again as no new reaction had occurred.