ABSTRACT
Vancomycin is a first-line agent used in the treatment of methicillin-resistant Staphylococcus aureus; however, vancomycin is associated with acute kidney injury (AKI). Previous literature demonstrates decreased incidence of AKI using 24-h area under the concentration-time curve (AUC24) monitoring, but its safety is unknown in obese populations. Patients ≥18 years, with body mass indices (BMI) ≥30 kg/m2, admitted between August 2015 and July 2017 or October 2017 and September 2019, who received vancomycin for ≥72 h and had level(s) drawn within 96 h of initiation were included. The primary outcome was incidence of AKI. Secondary outcomes included inpatient mortality rate, median inpatient length of stay, median vancomycin trough concentration, and median vancomycin AUC24. AKI was identified using the highest serum creatinine value compared with the value immediately prior to vancomycin initiation based on Kidney Disease Improving Global Outcomes (KDIGO) criteria. Overall, 1,024 patients met inclusion criteria, with 142 out of 626 patients in the trough group and 65 out of 398 patients in the AUC24 group meeting criteria for AKI (22.7% versus 16.3%, P = 0.008). Logistic regression of the data to account for confounding factors maintained significance for the reduction in incidence of AKI with AUC24 monitoring compared to trough monitoring (P = 0.010). Monitoring of vancomycin with AUC24 was associated with a decreased risk of AKI when compared with trough monitoring in obese patients.
KEYWORDS: vancomycin, therapeutic drug monitoring, nephrotoxicity, acute kidney injury, obesity
INTRODUCTION
Vancomycin is a commonly used intravenous antimicrobial for both empiric and definitive therapy for methicillin-resistant Staphylococcus aureus (MRSA) infections. However, it is well documented that vancomycin use has been associated with the development of acute kidney injury (AKI) ranging from 5% to 43% (1–7).
Vancomycin trough monitoring was the previously recommended method for assessing safety and efficacy. A trough goal of 15 to 20 mg/liter was recommended as a surrogate marker for 24-h area under the curve (AUC24) to MIC ratio of ≥400 mg·hr/liter for Staphylococcus aureus (8). However, it was subsequently found that vancomycin trough values of 15–20 mg/liter, which are considered to be within the goal range, may not necessarily correlate with AUC24 of 400–600 mg·hr/liter, which is considered to be the therapeutic range (9–11). Compared with trough monitoring, AUC24 monitoring using a Bayesian approach or equation-based methodology with two concentrations produced lower trough values. Additionally, it was found that direct AUC24 monitoring produced AUC24 values in the range of 400–600 mg·hr/liter more frequently than trough monitoring (12, 13). In 2020, the Infectious Diseases Society of America (IDSA), American Society of Health-System Pharmacists (ASHP), Society of Infectious Disease Pharmacists (SIDP), and Pediatric Infectious Disease Society (PIDS) released updated vancomycin guidelines that recommend AUC24 monitoring of vancomycin with a goal AUC24 to MIC ratio of 400–600 mg·hr/liter for serious MRSA infections. Trough-only monitoring is no longer recommended except in limited, specific situations which are outside the scope of this study (14).
Obese patients have been noted to have an increased vancomycin volume of distribution (Vd) and increased clearance (Cl) (15). Despite these noted differences, vancomycin dosing in obese patients remains challenging, without definitive guideline recommendations as the current vancomycin guidelines recommend dosing vancomycin based on actual body weight for most patients. For obese patients, it is recommended to give loading doses of 20–25 mg/kg of vancomycin based on actual body weight, and initial maintenance doses can be computed using population pharmacokinetic data to calculate estimated vancomycin clearance (14). Additionally, the guidelines recommend a maximum loading dose of 3,000 mg for obese patients, and that early and frequent monitoring of AUC24 be utilized for dose adjustments, especially when maintenance doses exceed 4,000 mg/day (13). In studies which utilized vancomycin trough levels, the impact of an increased body weight on renal outcomes in obese patients on vancomycin therapy is not consistent, with some showing no difference in incidence of AKI between obese and nonobese patients (6), while others show increased risk of AKI associated with increased weight and/or BMI (1, 3, 16, 17).
Current literature suggests decreased incidence of AKI using AUC24 monitoring (12, 13), but the safety and efficacy of this method is unknown in obese patients. This study aims to determine the impact of BMI on incidence of AKI with AUC24 versus trough monitoring.
RESULTS
Overall, 1,024 patients met inclusion criteria for analysis and were evaluated (Fig. 1) with 516 patients classified as Class I obesity (BMI 30.0 to 35.0 kg/m2), 237 patients as Class II obesity (BMI 35.1 to 40.0 kg/m2), and 271 patients as Class III obesity (BMI > 40.0 kg/m2). There were 626 patients in the trough group and 398 patients in the AUC24 group.
FIG 1.
Flowchart of exclusion criteria.
The majority of patients were male (54.0%) and Caucasian (93.6%) (Table 1). Baseline characteristics were similar between the two groups, but patients in the trough group had a higher incidence of history of myocardial infarction (15.3% versus 8.7%, P = 0.002), history of renal disease (8.8% versus 4.3%, P = 0.007), and history of cancer (13.9% versus 8.1%, P = 0.005). The baseline Charlson Comorbidity Index score was 3 (interquartile range [IQR], 1–6) for the trough group and 3 (IQR, 1–4) for the AUC24 group (P = 0.009).
TABLE 1.
Baseline demographics
| Trough group (n = 626) | AUC24 group (n = 398) | P value | |
|---|---|---|---|
| Age (yrs)a | 52 [40–61] | 52 [40–61] | 0.836 |
| wt (kg)a | 105.9 [92.2–122] | 103.3 [92.5–119.4] | 0.384 |
| BMI (kg/m2)a | 35 [32.1–41.1] | 34.9 [31.9–40.1] | 0.797 |
| SCr (mg/dl)a | 0.84 [0.69–1.06] | 0.85 [0.69–0.99] | 0.587 |
| CrCl (ml/min)a | 99.1 [74.0–126.2] | 99.3 [78.5–121.4] | 0.766 |
| Albumina | 2.80 [2.30–3.20] | 2.70 [2.30–3.20] | 0.899 |
| Gender (male)b | 347 (55.4%) | 206 (51.8%) | 0.250 |
| Race (white)b | 585 (93.5%) | 373 (93.7%) | 0.865 |
| Charlson Comorbidity Indexa | 3 [1–6] | 3 [1–4] | 0.009 |
| History of myocardial infarctionb | 96 (15.3%) | 34 (8.7%) | 0.002 |
| History of congestive heart failureb | 114 (18.2%) | 56 (14.2%) | 0.099 |
| History of peripheral vascular diseaseb | 68 (10.9%) | 39 (9.9%) | 0.634 |
| History of dementiab | 14 (2.2%) | 9 (2.3%) | 0.955 |
| History of COPDb | 185 (29.6%) | 103 (26.2%) | 0.249 |
| History of rheumatic diseaseb | 25 (4.0%) | 12 (3.1%) | 0.435 |
| History of peptic ulcer diseaseb | 9 (1.4%) | 6 (1.5%) | 0.909 |
| History of mild liver diseaseb | 97 (15.5%) | 62 (15.8%) | 0.904 |
| History of moderate to severe liver diseaseb | 33 (5.3%) | 15 (3.8%) | 0.286 |
| History of diabetes without complicationsb | 282 (45.0%) | 153 (38.9%) | 0.055 |
| History of diabetes with complicationsb | 104 (16.6%) | 76 (19.3%) | 0.267 |
| History of hemiparaplegiab | 50 (8.0%) | 21 (5.3%) | 0.107 |
| History of renal diseaseb | 55 (8.8%) | 17 (4.3%) | 0.007 |
| History of cancerb | 87 (13.9%) | 32 (8.1%) | 0.005 |
| History of metastatic cancerb | 34 (5.4%) | 17 (4.3%) | 0.431 |
| History of AIDS/HIVb | 1 (0.2%) | 4 (1.0%) | 0.056 |
Median [IQR].
Number (%).
For the primary outcome of AKI using KDIGO criteria, 142 patients in the trough group and 65 patients in the AUC24 group met the predetermined criteria for AKI (22.7% versus 16.3%, P = 0.008, absolute risk reduction [ARR] of 6.4%). AKI rates were also calculated among obesity classes (Table 2). The lowest incidence of AKI was found within the group of patients with a BMI > 40.0 kg/m2 who were monitored via AUC24, with an incidence of AKI of 28.7% in the trough group and 11.0% in the AUC24 group (P = 0.008, ARR 17.7%). Comparatively, 20.6% in the trough group experienced AKI versus 11.5% in the AUC24 group (P = 0.27, ARR 9.1%) in patients with a BMI of 35.1 to 40.0 kg/m2, and 20.4% versus 21.3% (P = 0.63, ARR −0.9%) in patients with a BMI of 30.0 to 35.0 kg/m2.
TABLE 2.
Primary outcome (AKI) for entire study population (BMI ≥ 30.0 kg/m2) and for subgroups by obesity class
| BMI | Trough | AUC24 | P |
|---|---|---|---|
| ≥30.0 kg/m2 (all patients) | 142/626 (22.7%) | 65/398 (16.3%) | 0.048 |
| 30.0 to 35.0 kg/m2 (n = 516) | 64/314 (20.4%) | 43/202 (21.3%) | 0.628 |
| 35.1 to 40.0 kg/m2 (n = 237) | 29/141 (20.6%) | 11/96 (11.5%) | 0.268 |
| >40.0 kg/m2 (n = 271) | 49/171 (28.7%) | 11/100 (11.0%) | 0.008 |
As a secondary outcome, incidence of AKI was measured using RIFLE criteria (22). Using the RIFLE definition of AKI, 147 patients in the trough group and 71 patients in the AUC24 group met criteria for AKI (23.5% versus 17.8%, P = 0.049).
The median daily vancomycin dose among patients in the AUC24 group was significantly lower during the second day (4,500 mg in the trough group [IQR, 3,500 mg–6,000 mg] versus 4,000 mg in the AUC24 group [IQR, 3,000 mg–5,250 mg], P = 0.004) and third day (4,250 mg [IQR, 2,750 mg–5,500 mg] versus 3,750 mg [IQR, 2,750 mg–5,000 mg], P = 0.016) of vancomycin therapy (Table 3). In addition, the median vancomycin trough values were significantly lower in the AUC24 group (15.82 μg/ml [IQR, 15.00–17.86] versus 15.02 μg/ml [IQR, 13.09–16.75], P = 0.0006). Median AUC24 within the AUC24 group was found to be 540.8 mg·hr/liter (IQR, 430–689 mg·hr/liter). Patients in the AUC24 group were significantly more likely to receive a loading dose (≥20 mg/kg) (13.6% versus 35.2%, P = 0.0001). Median length of stay was found to be not statistically different between groups (10 days in the AUC24 group [IQR, 5–18 days] versus 9 days in the trough group [IQR, 5–17 days], P = 0.45). All-cause inpatient mortality was significantly lower in the AUC24 group (6.5% versus 3.5%, P = 0.036) along with ICU length of stay (8 days [IQR, 4–14 days] versus 7 days [IQR, 3–12 days], P = 0.035). AKI was also examined by AUC24 (Table 4). AKI rate was highest in patients with AUC24 >600 mg·hr/liter.
TABLE 3.
Secondary outcomes
| Variable | Trough | AUC24 | P |
|---|---|---|---|
| Vancomycin dose, 0 h to 24 h (mg)a | 3,750 [3,000–4,750] | 4,000 [3,000–5,000] | 0.296 |
| Vancomycin dose, 24 h to 48 h (mg)a | 4,500 [3,500–6,000] | 4,000 [3,000–5,250] | 0.004 |
| Vancomycin dose, 48 h to 72 h (mg)a | 4,250 [2,750–5,500] | 3,750 [2,750–5,000] | 0.016 |
| Vancomycin trough (ug/ml)a | 15.82 [15.00–17.86] | 15.02 [13.09–16.75] | <0.001 |
| Loading dose (initial dose ≥ 20 mg/kg)b | 85 (13.6%) | 140 (35.2%) | <0.001 |
| Length of stay (days)a | 8 [4–14] | 10 [5–18] | 0.446 |
| All-cause inpatient mortalityb | 41 (6.5%) | 14 (3.5%) | 0.036 |
Median [IQR].
Number of patients (%).
TABLE 4.
Incidence of AKI (based on KDIGO criteria) by AUC24
| AUC24 (mg·hr/liter) | AKI rate |
|---|---|
| <400 (n = 334) | 13.5% |
| 400 to 500 (n = 321) | 17.1% |
| 501 to 600 (n = 263) | 16.0% |
| >600 (n = 325) | 25.9% |
Variables included in the regression models were age, weight, number of days of beta-lactam therapy, Charlson Comorbidity Index score, CrCl, number of days on other nephrotoxic medications, renal disease, receipt of vancomycin loading dose, vancomycin trough value, number of days of vancomycin, days of ICU stay, days of hospital stay, number of days on other nephrotoxic medications, gender, race, BMI >40 kg/m2, history of myocardial infarction, inpatient mortality rate, and vancomycin dose for the first day, second day, and third day. Variables found to be significant on multivariate binary logistic regression predicting AKI included CrCl, days of hospital stay, renal disease, vancomycin trough value, and number of days on other nephrotoxic medications (Table 5). After logistic regression using a backwards elimination method, AUC24 monitoring remained associated with a significantly lower incidence of AKI using KDIGO criteria (OR 0.61; 95% CI, 0.42–0.89; P = 0.010).
TABLE 5.
Variables found to be significant on multivariate binary logistic regression
| Variable | Odds ratio (OR) | 95% CI | P |
|---|---|---|---|
| CrCl | 1.01 | 1.00–1.02 | <0.001 |
| Length of stay | 1.07 | 1.04–1.10 | <0.001 |
| Renal disease | 3.88 | 2.17–6.91 | <0.001 |
| Vancomycin trough concentration | 1.05 | 1.02–1.07 | <0.001 |
| No. of days on other nephrotoxic medications | 1.28 | 1.08–1.50 | 0.004 |
| AUC24 monitoring | 0.61 | 0.42–0.89 | 0.010 |
DISCUSSION
Multiple studies have shown an association between increased risk of nephrotoxicity and increased weight and/or higher BMI, but it was unknown whether AUC24 monitoring might reduce this risk in obese patients when compared with trough monitoring (1, 3, 16, 17). Within our study, fewer obese patients with AUC24 monitoring of vancomycin experienced AKI compared with patients with trough monitoring with incidence of AKI of 22.7% and 16.3% for trough and AUC24, respectively (ARR 6.4%). A multivariate regression to account for confounding factors showed a continued association between AUC24 monitoring of vancomycin and decreased incidence of AKI. To the authors’ knowledge, there are no other studies available investigating incidence of AKI using AUC24 monitoring versus trough monitoring in obese patients.
The decrease in AKI with AUC24 monitoring appeared to be driven primarily by patients with a BMI > 40.0 kg/m2 within our study. Interestingly, we saw the lowest incidence of AKI within the group of patients with a BMI > 40.0 kg/m2 who were monitored via AUC24 (28.7% versus 11.0%, ARR 17.7%, P = 0.008). Comparatively, 20.6% in the trough group experienced AKI versus 11.5% in the AUC24 group (ARR 9.1%, P = 0.27) in patients with a BMI of 35.1 to 40.0 kg/m2, and 20.4% versus 21.3% (ARR −0.9%, P = 0.63) in patients with a BMI of 30.0 to 35.0 kg/m2. The lower incidence of AKI in the BMI > 40.0 kg/m2 group monitored with AUC24 could also be affected by the relatively small number of patients within this group (271 patients total). We also saw a decrease in incidence of AKI within the group of patients with a BMI of 35.1 to 40.0 kg/m2, although this decrease was not statistically significant. Due to the significant decrease in AKI seen in patients with BMI >40.0 kg/m2 and decrease seen in patients with a BMI of 35.1 to 40.0 kg/m2, our data suggest that an AUC24 based monitoring may be most beneficial to those patients with a higher BMI.
Additionally, we found a median vancomycin AUC24 of 540.8 mg·hr/liter (IQR, 430–689 mg·hr/liter) in our group of patients with BMI ≥ 30.0 kg/m2 which is near the recommended range of 400–600 mg·hr/liter. This would suggest appropriate initial dosing in this patient population.
We also saw a reduction in median total daily dose (TDD) of vancomycin on days 2 and 3 of vancomycin therapy of approximately 500 mg with AUC24 monitoring. These findings are consistent with other studies that examined reduction in TDD and found a decrease of 250–500 mg of vancomycin per day in patients with normal body weight (12, 13) and 500–750 mg in patients who were obese (16) when utilizing AUC24 monitoring. There was likely no difference on the first day due to the greater utilization of loading doses in the AUC24 group. It has been previously noted in the literature that doses over 4,000 mg of vancomycin a day are associated with higher rates of nephrotoxicity, although the patients studied were not necessarily obese and other literature has not been consistent with this finding (1). It is possible that some of the reduction in AKI seen in our study could be related to decreased total daily doses of vancomycin with AUC24 monitoring. The reduction in AKI may also be related to more accurate targeting of an AUC24 range of 400–600 mg·hr/liter and minimizing supratherapeutic exposures as median vancomycin trough values were seen to be lower with AUC24 monitoring. This is supported by previous literature that found lower trough concentrations utilizing AUC24 monitoring than trough monitoring (13). Additionally, a mortality benefit was seen between AUC24 monitoring and trough monitoring for our patient population. As AKI has been shown to be a predictor of inpatient mortality (23–25), it is possible that the decrease in incidence of AKI with AUC24 monitoring contributed to the mortality benefit demonstrated in this study. A multivariate regression would be needed to assess what factors might be contributing to this benefit.
This study is not without limitations. First, although we utilized a multivariate analysis to consider factors that may influence incidence of AKI, there could be factors not assessed that may have contributed. Additionally, due to the retrospective cohort nature of this study and the implementation of AUC24 monitoring at a specific time point, it is possible that dosing strategies for vancomycin changed over time outside of the change in monitoring strategy. For example, the number of patients who received a loading dose (≥20 mg/kg) of vancomycin within our study was higher in the group with AUC24 monitoring (13.6% versus 35.2%, P = 0.0001), which may have influenced our outcomes. The patient population of our institution may also have changed over time, although based on the experience of the authors, this is unlikely. Additionally, our study required patients to have a true trough concentration to be included in the trough monitoring group and to have two levels for inclusion into the AUC24 monitoring group. In practice, this may only represent a subset of patients as levels may not be appropriately drawn on all patients consistently, and short course empiric therapy may not require levels in all patients. Time to event for AKI was also outside of the scope of this study, which is a study limitation. Finally, previous studies have examined nephrotoxicity of vancomycin in terms of a 0.5 mg/dl increase in serum creatinine. As our study examined AKI based on KDIGO and RIFLE criteria, incidence of AKI may not be directly comparable to studies using other definitions of AKI.
In summary, AUC24 monitoring of vancomycin demonstrated lower incidence of AKI in patients with a BMI of ≥30 kg/m2 when compared with trough monitoring. The largest difference in nephrotoxicity may be in morbidly obese patients (BMI > 40.0 kg/m2). A potential mortality benefit with AUC24 monitoring was also found, with need for further studies to assess contributing factors. Further validation of these results is warranted but in obese patients receiving vancomycin therapy, AUC24 monitoring should be utilized.
MATERIALS AND METHODS
This retrospective, single-center cohort study utilized clinical data extracted from the University of Kentucky Center for Clinical and Translational Science Enterprise Data Trust. The study was approved by the University of Kentucky Institutional Review Board.
Vancomycin AUC24 monitoring was implemented at University of Kentucky HealthCare in September 2017. All adults admitted to the hospital who received vancomycin for at least 72 h with vancomycin level(s) drawn within 96 h of initiation and had a BMI ≥30 kg/m2 during the period of August 2015–July 2017 (pre-implementation group) and October 2017–September 2019 (post-implementation group) were included for analysis. Both groups had to have a trough level within 2 h prior to administration of a vancomycin dose and patients in the AUC24 group (post-implementation group) were also required to have a random level drawn within 2 h to 5 h after administration of a vancomycin dose for inclusion. BMI was calculated using the World Health Organization’s equation (18). AUC24 monitoring was performed using 2-level pharmacokinetic equations that have been described previously (19).
Patients were excluded if they had a diagnosis of cystic fibrosis, chronic kidney disease Stage 3–5, history of a kidney transplant, or were pregnant while receiving vancomycin. Patients were also excluded if they had a creatinine clearance (CrCl) ≤30 ml/min using the corrected Cockcroft-Gault equation at the time of vancomycin initiation (20). Patients were also excluded if they experienced AKI during their hospitalization prior to initiation of vancomycin, within 48 h of initiation of vancomycin, or 7 or more days after vancomycin was discontinued as AKI in these patients was unlikely to be caused by vancomycin.
The primary outcome of AKI was based on the Kidney Disease Improving Global Outcomes (KDIGO) 2012 Clinical Practice Guidelines definition using the serum creatinine criteria and excluding the urine output criteria and presence of CRRT due to limitations on data extraction (21). The staging criteria for AKI is as follows:
I. Stage 1
a. Change from baseline serum creatinine where 1.5 ≤ × < 2.0, or any 2 creatinine levels collected within 48 hours of each other (after the first 48 hours of vancomycin therapy and within 7 days after vancomycin therapy was stopped) that show an increase of ≥0.3 mg/dl.
II. Stage 2
a. Change from baseline where 2.0 ≤ × <3.0.
III. Stage 3
a. Change from baseline where × ≥3.0 (21).
To calculate the change in serum creatinine from baseline, the following formula was used:
The initial serum creatinine was the serum creatinine value immediately prior to vancomycin initiation. If no serum creatinine value was available prior to initiation of vancomycin, the first available serum creatinine value was used. For the highest serum creatinine, the maximum serum creatinine within 48 h after vancomycin initiation and up to 7 days after vancomycin was discontinued was used. If the patient’s change in serum creatinine values did not meet the previously mentioned AKI criteria, the patient was classified as having no AKI.
Secondary outcomes were all-cause inpatient mortality (defined as death during admission or transfer to hospice), median length of stay, median intensive care unit (ICU) length of stay, median vancomycin trough concentration, median vancomycin AUC24, and median daily dose of vancomycin. Median values were used as measures of central tendency for these variables due to concern for potential outliers that might influence mean values. Additionally, AKI based on RIFLE criteria using serum creatinine was also examined as a secondary outcome (22).
Data collected included age, sex, weight, height, comorbidities, serum creatinine measurements during hospitalization, length of hospitalization, serum vancomycin concentrations, and all medications administered, with dosing and administration dates and times. A patient was classified as receiving vancomycin for a particular day if they received at least one dose of vancomycin within a 24-h period.
Patient demographics were analyzed using a Student's t test or Wilcoxon rank sum test for continuous variables. Nominal variables were analyzed using a chi-square or Fisher’s exact test, as appropriate. A multivariate logistic regression was then completed using a backward elimination model. Analyses were conducted using SAS software.
ACKNOWLEDGMENTS
The project described was supported by the NIH National Center for Advancing Translational Sciences through grant number UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
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