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PARAMETERS OF VANCOMYCIN PHARMACOKINETICS IN POSTOPERATIVE PATIENTS WITH RENAL DYSFUNCTION: COMPARING THE RESULTS OF A PHARMACOKINETIC STUDY AND MATHEMATICAL MODELING
Ramenskaya GV1, Shokhin IE1, Lukina MV2 ^ Andrushchishina TB2, Chukina MA2, Tsarev IL2, Vartanova OA2, Morozova TE2
1 Department of Pharmaceutical and Toxicological Chemistry, Institute of Pharmacy, Sechenov First Moscow State Medical University (Sechenov University), Moscow
2 Department of Clinical Pharmacology and Propaedeutics of Internal Diseases, Faculty of General Medicine Sechenov First Moscow State Medical University (Sechenov University), Moscow
Mathematical modeling of pharmacokinetic (PK) and pharmacodynamic (PD) parameters essential for establishing correct dosing regimens is an alternative to pharmacokinetic studies (PKS) adopted in the clinical setting. The aim of this work was to compare the values of PK parameters for vancomycin obtained in an actual PKS and through MM in postoperative patients with kidney injury. Our prospective study included 61 patients (47 males and 14 females aged 60.59 ± 12.23 years). During PKS, drug concentrations at steady state Ctrough and Cpeak were measured by high-performance liquid chromatography followed by the calculation of the area under the plasma concentkation-time curve AUC24. For mathematical modeling, a single-compartment model was employed; PK parameters were estimated using R 3.4.0. The values of Ctrough measured 48 h after the onset of antibiotic therapy during PKS were significantly lower than those predicted by MM р = 0.004). In a group of patients with acute kidney injury (AKI), AUC24 measured at the end of treatment was significantly higher than its value predicted by MM р = 0.011). The probability of achieving the target AUC24 to MIC ratio of over 400 pg^h /ml is higher in the group of patients with Ctrough = 10-15 pg /ml. Our findings confirm that the use of MM in postoperative patients with renal dysfunction is limited and therapeutic drug monitoring should be used instead.
Keywords: pharmacokinetic study, vancomycin pharmacokinetics, mathematical modeling, acute kidney injury, surgical patients
Acknowledgements: the authors wish to thank Oleg V. Babenko, Chief Physician of the University Clinical Hospital No.1 of Sechenov First Moscow State Medical University for providing an opportunity to carry out our research
gg Correspondence should be addressed: Maria V. Lukina
Bolshaya Pirogovskaya, 2, bl. 4, Moscow, 119435; mari-luk2010@yandex.ru
Received: 16.05.2018 Accepted: 25.08.2018
DOI: 10.24075/brsmu.2018.051
ПАРАМЕТРЫ ФАРМАКОКИНЕТИКИ ВАНКОМИЦИНА У БОЛЬНЫХ С НАРУШЕНИЕМ ФУНКЦИИ ПОЧЕК В ПОСЛЕОПЕРАЦИОННОМ ПЕРИОДЕ: СРАВНЕНИЕ РЕЗУЛЬТАТОВ ФАРМАКОКИНЕТИЧЕСКОГО ИССЛЕДОВАНИЯ И МАТЕМАТИЧЕСКОГО МОДЕЛИРОВАНИЯ
Г. В. Раменская1, И. Е. Шохин1, М. В. Лукина2 Т. Б. Андрущишина2, М. А. Чукина2, И. Л. Царев2, О. А. Вартанова2, Т. Е. Морозова2
1 Кафедра фармацевтической и токсикологической химии имени А. П. Арзамасцева, Институт фармации,
Первый Московский государственный медицинский университет имени И. М. Сеченова (Сеченовский Университет), Москва
2 Кафедра клинической фармакологии и пропедевтики внутренних болезней, лечебный факультет,
Первый Московский государственный медицинский университет имени И. М. Сеченова (Сеченовский Университет), Москва
В клинической практике возможной альтернативой фармакокинетическим исследованиям (ФКИ) является методика математического моделирования (ММ) фармакокинетических (ФК) и фармакодинамических (ФД) параметров для расчета доз антибактериальных препаратов. Целью исследования было сравнение параметров ФК ванкомицина, полученных на основе ФКИ и ММ, у пациентов с нарушением функции почек в послеоперационном периоде. В проспективное исследование был включен 61 пациент (47 мужчин и 14 женщин, возраст 60,59 ± 12,23 лет). В ходе ФКИ методом высокоэффективной жидкостной хроматографии определяли Ctrou h, Cpeak, с последующим расчетом площади под фармакокинетической кривой (ПФК24). Расчет параметров Фк при ММ9 проводили с помощью программы R 3.4.0 на основе однокомпартментной модели. По данным ФКИ значения равновесных С h через 48 ч от начала антибактериальной терапии были достоверно ниже значений, полученных при ММ р = 0,004). В группе пациентов с острым почечным повреждением (ОПП) на момент завершения терапии значения ПФК24 по данным ФКИ были достоверно выше р = 0,011). Вероятность достижения целевого отношения ПФК24 / МПК > 400 мкг^ч /мл выше в группе пациентов, где Ctrou h составляет 10-15 мкг/мл. Таким образом, результаты исследования подтверждают, что у больных с нарушением^функции почек в послеоперационном периоде применение ММ имеет ряд ограничений и необходимо проведение терапевтического лекарственного мониторинга (ТЛМ).
Ключевые слова: фармакокинетическое исследование, фармакокинетика ванкомицина, математическое моделирование, острое почечное повреждение, пациенты хирургического профиля
Благодарности: авторы благодарят Бабенко Олега Васильевича, главного врача УКБ № 1 Первого МГМУ им. И. М. Сеченова, за предоставленную возможность проведения фармакокинетического исследования.
gg Для корреспонденции: Мария Владимировна Лукина
ул. Большая Пироговская, 2, стр. 4, Москва, 119435; mari-luk2010@yandex.ru
Статья получена: 16.05.2018 Статья принята к печати: 25.08.2018
DOI: 10.24075/vrgmu.2018.051
To deliver safe and effective treatment, a pharmacokinetic study (PKS) or therapeutic drug monitoring (TDM) can be recommended for patients receiving antibacterial drugs with a narrow therapeutic index. According to the international guidelines, vancomycin TDM should include measurements of its trough concentrations (Ctrough) at steady state, the area under the time-concentration curve (AUC24), and the ratio of AUC24 to the minimum inhibitory concentration (MIC) of the prescribed drug. There are a few limitations to the use of TDM in clinical routine often arising from the failure to obtain the sufficient number of blood samples to calculate AUC24 [1, 2].
In some clinical circumstances, TDM can be replaced with the mathematical modeling (MM) of drug pharmacokinetics. For a number of antibiotics, including vancomycin, aminoglycosides, and colistin, a starting dosing regimen can be generated by medical calculators exploiting mathematic modeling [3, 4]. The medical calculator for vancomycin is based on a single-compartment pharmacokinetic model and can predict the ratio of pharmacokinetic to pharmacodynamic parameters and the minimum inhibitory concentration (MIC) necessary to calculate an adequate drug dose considering the patient's age, sex, weight, and renal function [5, 6]. The use of different types of mathematical modeling in clinical routine reduces the need for TDM.
There is little information about the use of MM for predicting drug pharmacokinetics in different groups of patients. It is impossible to predict the biotransformation dynamics, the volume of distribution and the elimination rate of antibacterial drugs in patients with acute kidney injury in the early postoperative period. Among other important MM drawbacks are high equipment and software costs [7, 8].
The literature analysis does not allow firm conclusions as to whether MM can be safely used instead of TDM in different clinical circumstances because too few research works have been carried out to compare these two methods.
Therefore, to improve the method of pharmacokinetic MM, pharmacokinetic studies need to be carried out in different groups of patients. The data yielded by such research works
Table 1. Clinical characteristics of patients included in the study
will help to improve the efficacy and safety of vancomycin-based therapy.
The aim of this work was to compare the results of a pharmacokinetic study and mathematical modeling of vancomycin pharmacokinetics in surgical patients with acute kidney injury.
METHODS
This prospective observational study was carried out at the facilities of the University Clinical Hospital No. 1 of Sechenov First Moscow State Medical University in September 2016 through January 2018. The study protocol was approved by the local Ethics Committee (Protocol No. 05-16 dated May 18, 2016).
The study included 61 postoperative patients (47 males and 14 females) with septic complications. Their mean age was 60.59 ± 12.23 years. The patients were distributed into two groups depending on the presence of acute kidney injury (AKI) [9]: group 1 included patients with AKI (n = 35; 66.6%), group 2 included patients without AKI (the controls; n = 26; 33.4%). In group 1, mild and moderate kidney injury prevailed: stage 1 AKI was diagnosed in 19 (31.1%) patients; stage 2, in 13 (21.3%) patients; stage 3, in 3 (4.9%) patients. Details are presented in Table 1. The groups were comparable in terms of main clinical characteristics, but the patients representing the group with AKI were significantly older p = 0.004). In the postoperative period, those patients had higher albumin levels than the controls p = 0.047).
Vancomycin regimen
All patients with infectious complications received vancomycin (marketed as Edicin by Sandoz; Slovenia). The dosing regimen was 15 to 20 mg per 1 kg of body weight, as recommended by the clinical practice guidelines, with due account of the patients' kidney function as estimated by the Cockroft-Gault equation (creatinine clearance rate Cl , ml/min). The maximum
Clinical characteristics Total n = 61 Without AKI n = 26 (44.8%) With AKI n = 35 (55.7%) P
М ± SD М ± SD М ± SD
Age, years 60.59 ± 12.23 55.46 ± 12.89 64.4 ± 10.33 0.004*
BMI, kg/m2 27.4 ± 5.2 27.12 ± 6.1 27.29 ± 4.5 0.726
EF0, % 59.02 ± 7.86 62.53 ± 6.74 56.89 ± 7.83 0.018*
ClCr 0, ml/min 96.48 ± 29.01 96.26 ± 24.76 96.64 ± 32.16 0.96
ClCr ,, ml/min 61.5 ± 27.2 81.51 ± 23.54 46.64 ± 19.1 < 0.0001*
ClCr 2, ml/min 85.98 ± 32.33 87.37 ± 33.52 84.95 ± 31.86 0.776
Albumin0, mg/dl 41.21 ± 4.2 42.46 ± 4.35 40.29 ± 3.97 0.447
Albumin,, mg/dl 33.56 ± 1.52 32.21 ± 2.84 44.57 ± 1.61 0.047*
Hospital stay, days 25.07 ± 15.069 26.77 ± 4.27 23.8 ± 1.17 0.451
MV, days 3.30 ± 1.75 3.00 ± 1.29 3.51 ± 0.887 0.736
Intensive care, days. 6.46 ± 1.187 6.5 ± 2.27 6.43 ± 1.23 0.977
Blood loss, ml 653.44 ± 604.65 512.1 ± 258.8 758.00 ± 754.66 0.118
Mortality, % 11 (18%) 4 (36.4%) 7 (63.6%) 0.454
Note: * significant differences, pvalue < 0.05; BMI — body mass index; ClCr — creatinine clearance rate (Cockroft-Gault equation); ClCr 0 — before the surgery; ClCr 1 — 2-3 days after the surgery; ClCr — 7-10 days after the surgery; MV — mechanical ventilation; EF — ejection fraction.
daily dose of the drug did not exceed 2 g. Vancomycin was administered by intravenous drips for 60 min every 12 h [10]. Dosing adjustments were done 24 to 48 h later based on the estimated Cl .
cr
The patients with AKI received significantly lower daily doses of vancomycin in comparison with the patients without kidney disfunction (928.6 ± 275 mg and 1637.9 ± 515.8 mg, respectively; р < 0.0001). Therapy duration was 9.61 ± 3.8 days. It depended on the severity and site of infection, results of microbiological tests, and individual patient's tolerability. Therapy duration did not differ significantly between the groups and was 9.17 ± 3.6 and 10.19 ± 4 days for groups 1 and 2, respectively (p = 0.353).
Parameters of vancomycin pharmacokinetics measured by high-performance liquid chromatography during the pharmacokinetic study
Blood samples for the PKS were collected from all patients included in the study as recommended by the guidelines for vancomycin TDM [1]. To measure Cpeak (60 min after the infusion) and Ctrough (60 min before administering the next dose), blood samples were collected 48 hours after the onset of therapy (1) and upon its completion (2) [11].
Proteins contained in the samples were precipitated using methanol. Quantitative measurements were done on the high-performance liquid chromatography system Agilent 1260 equipped with a gradient pump, a degasser, an autosampler, and the tandem mass spectrometer Agilent 6460 (AgilentTechnologies; USA). For separation, the ZorbaxEclipse Plus-C18 2.1 x 50 mm 1.8 pm column and the Zorbax Eclipse Plus C18 12.5 x 2.1 mm 1.8 pm guard column were used.
AUC_„ was calculated from the obtained values of C
24 peak
and C
trough
at steady state as a sum of different phases of drug
pharmacokinetics using the trapezoidal rule [12]:
auc24 =
(Lintrap + Logtrap) x 24
where Lintrap is the area under the time-concentration curve during the linear phase of drug infusion:
Lintrap
(C h + C J x t
v trough peak inf 2
where Tnf is infusion time (h).
Logtrap is the area under the "logarithmic" phase of drug elimination:
(C „ - C h)r- T,
v peak trough inf .
Logtrap =
where ris time between the infusions (h)
C
in CP8* trough
Method of mathematical modeling
Mathematic modeling was done in R 4.3.0 [12]. We estimated the values of Cpeak, Ctrough and AUC24 using the equations describing the pharmacokinetic dynamics for the single-compartment model 48 h after the onset of therapy (1) and upon its completion (2) [13]:
n H --T .x K
C
Dosex 1 -e
peak -Tx K
Tn x x Kei x (l - e )
C = C X e
trough peak
-K„X (T- TJ
infusion time (h), t is time between the infusions (h), Kel is the predicted elimination rate (h~1), and is the apparent volume of distribution (l/kg):
= 0.7 x M ;
where M is the absolute weight of a patient (kg).
To calculate the predicted elimination rate, the following equation was used [14]:
Kel = 0.00083 x ClCr + 0.0044 ;
where ClCr is creatinine clearance (ml/min) determined by the Cockroft-Gault formula:
[140 - age] x body weight (kg) x (10.05 for women or 10.23 for men)
Cl Cr =
/ iimol \
blood plasma creatinine (—i—)
To calculate AUC the trapezoidal rule was applied:
AUC24 =
(Lintrap + Logtrap) x 24
where Dose is a single dose of vancomycin (mg), T f is
Statistical processing was done in IBMSPSS Statistics 18.0. and R 3.4.0. In this work continuous variables with normal distribution are presented as a mean (M) and a mean square deviation (SD). Categorical data are presented as a median (Me) and an interquartile range (IQR). Departure from normality was estimated using the Shapiro-Wilk test. The significance of frequency differences was assessed using Fisher's exact test. The significance of differences in arithmetic means between the groups was tested by ANOVA. Apart from ANOVA, nonparametric tests were applied; differences in mean ranks were compared using the Mann-Whitney-Wilcoxon test. The differences were considered significant at p < 0.05. To establish correlations between clinically significant pharmacokinetic parameters Ctrough and AUC24, Spearman's correlation was applied.
RESULTS
The actual values of Kel1 yielded by the PKS (samples collected 48 h after the onset of therapy and upon its completion) were significantly higher than values predicted by MM (0.109 (0.08-0.15) and 0.06 (0.04-0.072), respectively; p < 0.0001). The actual values of Ctrough1 at steady state were significantly lower than the values predicted by MM (11.32 (8.1-16.4) and 16.59 (14.03-24.8), respectively; p = 0.004). At the same time, the values of Ctrough2 measured by HPLC and those predicted by MM did not differ significantly. The actual and predicted values of AUC24 did not differ significantly 48 h after the onset of antibacterial therapy (p = 0.715). Upon therapy completion, the actual values of AUC242 were significantly higher than its predicted values (564.04 (<409.5-751.9) and 347.03 (267.43479.99) respectively; p = 0.011) (Table. 2).
Parameters of vancomycin pharmacokinetics measured by HPLC and predicted by MM did not differ significantly between group 1 and group 2, except for the actual values of Kel1 (p = 0.037) that was significantly higher in the patients with kidney injury (Table 2).
Parameters of vancomycin pharmacokinetics obtained through real measurements demonstrate the variability of Ctrough and AUC24 both at the onset of therapy and upon its completion (Fig. 1). This can be explained by the specifics of vancomycin pharmacokinetics in the studied sample, given standard dosing regimens. However, the obtained range of PK values predicted by MM and the significant difference from the actual values mean that the use of MM in patients with acute kidney injury is limited.
Table 2. Vancomycin pharmacokinetics evaluated by HPLC and MM in the groups of patients with and without AKI 48 h after the onset of therapy and at the time of its completion
PK parameter TDM ММ Mann-Whltney-Wllcoxon test; P TDM (n= 61) Mann-Whltney-Wllcoxon test; P ММ (n = 61) Mann-Whltney-Wllcoxon test; P
(n = 61) (n = 61) AKI+ (n = 35) AKI- AKI + AKI-
Ме [IQR] Ме [IQR] Ме [IQR]
Kel1 (hour -1) 0.109 [0.08-0.15] 0.06 [0.04-0.072] < 0.0001 0.12 [0.1-0.14] 0.1 [0.06-0.131] 0.037 0.04 [0.04-0.07] 0.06 [0.06-0.077] 0.117
Kel2 (hour -1) 0.08 [0.05-0.14] 0.08 [0.063-0.102] 0.274 0.06 [0.05-0.15] 0.11 [0.07-0.13] 0.412 0.08 [0.05-0.15] 0.09 [0.07-0.11] 0.709
trough1 (Mg/mO 11.32 [8.1-16.4] 16.59 [14.03-24.8] 0.004 9.6 [6.9-15.0] 12.08 [8.8-18.27] 0.197 16.2 [14.2-19.7] 14.03 [13.24-18.04] 0.54
Ctrough (Mg/ml) 12.59 [8.5-22.8] 8.65 [5.9-12.06] 0.092 15.7 [6.6-25.8] 12.59 [9.1-21.7] 0.776 8.3 [6.08-11.6] 10.14 [5.7-12.5] 0.765
Cpeak1 (Mg/mO 35.6 [31.2-37.2] 27.3 [24.2-32.2] 0.019 35.1 [30.9-37.8] 23.8 [21.3-31.4] 0.502 26.2 [15.8-27.2] 28.2 [26.6-32.8] 0.502
Cpeak2 (HQ/ml) 22.5 [18.6-30.7] 34.8 [31.7-41.9] 0.002 35.6 [31.9-40.7] 23.8 [21.3-31.4] 0.263 26.23 [24.11-28.1] 34.8 [30.1-43.1] 0.263
AUC241 (Hg x h/ml) 484.08 [404.5-604.4] 459.72 [433.6-556.01] 0.715 465.7 [399.5-605.3] 530.8 [480.2-603.4] 0.263 462.8 [450.4-548.5] 458.38 [413.8-553.5] 0.709
AUC242 (Hg x h/ml) 564.04 [409.5-751.9] 347.03 [267.43-479.99] 0.011 551.2 [397.02-786.6] 564.04 [421.9-721.58] 0.765 345.4 [255.5-393.2] 386.8 [273.8-481.5] 0.502
Note: 1 — 48 h after the onset of therapy; 2 — at the time of its completion.
First test
Second test
о
ZD <
900 -
800 -
700 -
600 -
500 -
400 -
500 1,000 1,500
Modeled AUC24 (|jg-h/ml)
2,000
О
ZD <
900
800
700
600
500
400
500 1,000 1,500
Modeled AUC24 (|jg-h/ml)
2,000
Fig. 1. The range of AUC24 values obtained through MM and high-performance liquid chromatography in postoperative patients with acute kidney injury 48 hours after the onset of therapy and upon its completion
In the patients with Ctrough of 10-15 pg/ml at steady state,
AUC24 was above 400
|jg x h/ml both 48 h after the onset of therapy (Fig. 2) and at the time of its completion (Fig. 3). The correlation analysis revealed a positive correlation between the values of Ctrough and AUC24 at steady state (r = 0.964; p < 0.001).
MIH equals 1 pg/ml (for Staphylococcus aureus). The exception is the group of patients in which Ctrough is below 10 pg/ml; in this group the target PK/PD ratio was observed in 55% of patients. If MIC increases to 1.5 or 2 pg/ml, the probability of reaching the desired PK/PD ratio in the group of patients
with Ct with C
Predicting the probability of reaching the target PK/PD ratio
The values of AUC24 obtained through HPLC suggest that the target PK/PD ratio (AUC24/MIC > 400) is highly probable if
trough trough
10-15 pg/ml is reduced to 30%, and in the group 15-20 pg/ml, to 70% (Table 3). Hypothetically, the
desired PK/PD ratio can be achieved at MIC = 2 pg/ml only if ^trough reaches 20 pg/ml or higher (Table 3).
The analysis of the predicted AUC24 to MIC ratio revealed that upon therapy completion the target PK/PD ratio of > 400 was observed mostly in the patients with Ctrough above 10-15 pg/ml (Table 4).
DISCUSSION
Our study shows that if a standard approach to vancomycin dosing is applied in surgical patients with acute kidney injury, the actual values of C . measured by HPLC 48 h after the
trough 3
onset of therapy are significantly different from the values predicted by MM (11.32 (8.1-16.4) and 16.59 (14.03-24.8) pg/ml, respectively; p = 0.004).
The obtained results are consistent with the findings of other researchers who observed the high variability of pharmacokinetic parameters and the ratio of AUC24/MIC > 400 in the patients of intensive care units treated with standard doses of vancomycin [15, 16].
The differences in the results yielded by PKS and MM can be explained by the drawbacks of the majority of mathematical models. A single-compartment model exploits a fixed mean value of 0.7 l/kg. Pharmacokinetic studies demonstrate that this value can range from 0.2 to 1.25 l/kg and depends on the volume of circulating blood, albumin levels, etc. Kel is
calculated based on the clearance rate Cl estimated by the
cr J
Cockroft-Gault equation. At present there is no perfect formula for estimating the rate of drug elimination based on the levels of endogenous creatinine [17, 18].
Some authors believe that the use of standard nomograms and MM for predicting drug pharmacokinetics has a number of limitations. First, the majority of these methods were validated on the limited population of healthy volunteers or stable patients. Second, the target values of steady-state C . were thought
trough
to fall within the range of 5-10 pg/ml. At present, the range of these values has risen to 15-20 pg/ml as demonstrated by a number of microbiological studies [19, 20].
It is debatable whether high C . concentrations and
trough
AUC24/MIC of 400 or above really need to be achieved. Local microbiological monitoring demonstrates that at MIC of 1 pg/ml or below Ctrough does not have to be as high as 15-20 pg/ml [21].
Our retrospective study demonstrates that over 30% of patients reached the target ratio AUC24/MIC of > 400 even at Ctrough below 15 pg/ml. Regression analysis reveals that
First test
1,000
900
o
ZD <
800
700
600
500
400
300
Concentration C J at steady state (ig/ml) Fig. 2. Dependency of AUC241 on the levels of steady-state C J 48 hours after the onset of antibacterial treatment (HPLC)
Second test
1,000
900
C
ZD <
800
700
600
500
400
300
10
15
Concentration C
20 25
h2 at steady state (ig/ml)
30
35
Fig. 3. Dependency of AUC242 on the levels of steady-state C troh2 at the time of therapy completion (HLPC)
5
Table 3. Prediction of the AUC24/ MIC ratio for Staphylococcus aureus 48 hours after the onset of vancomycin therapy
Value of C ., ug/ml trough' AUC24, |jg-h/ml AUC24/MIC > 400
М min max MIC 1 pg/ml (%) MIC 1.5 pg/ml (%) MIC 2 pg/ml (%)
< 10 401.9753 365.676 484.0849 55 0 0
10-15 530.8875 459.4124 645.6017 100 30 0
15-20 603.4062 549.4891 605.2955 100 70 0
> 20 780.6152 676.4806 884.7498 100 100 50
Table 4. Prediction of the AUC24/ MIC ratio for Staphylococcus aureus at the time of vancomycin therapy completion
Value of C ., ug/ml trough' ^^ AUC24, pg^h/ml AUC24/MIC > 400
М min max MIC 1 pg/ml (%) MIC 1.5 pg/ml (%) MIC 2 pg/ml (%)
< 10 395.1776 361.2053 421.9468 16 0 0
10-15 517.7069 502.5894 564.0411 100 0 0
15-20 650.2483 578.911 721.5856 100 50 0
> 20 783.8409 667.7073 910.8016 100 100 38
Ctrough = 10.8 pg/ml is a predictor of the target AUC24/MIC value above 400 [22].
In our study the patients treated with standard doses of vancomycin responded positively to treatment although their Ctrough was 10-15 pg/ml (Table 2). The fact that they reached the target AUC24/MIC ratio of > 400 can be explained by the microbiological monitoring carried out in our hospital (S. aureus, MIC of vancomycin < 1 pg/ml in 60-70% cases).
As MIC rises to 1.5 or 2 pg/ml, the efficacy of vancomycin treatment decreases in 30% or 70% of case, respectively.
The obtained data suggest that dosing adjustments aided by MM based on the results of the pharmacokinetic study involving measurements of C , C and AUC were more
trough peak 24
beneficial for the patients than dosing regimens based solely on the monitoring of Ctrough [23].
Pharmacokinetic studies carried out in specific groups of patients are especially important in the development of a good mathematical model of vancomycin pharmacokinetics
and selecting optimal dosing regimens. On a larger scale, the results of such studies can be used to build population models, which in turn requires more pharmacokinetic studies involving different cohorts of patients [24, 25].
CONCLUSIONS
Our study demonstrates that the predicted and actual values of vancomycin pharmacokinetics vary. The differences indicate the necessity of therapeutic drug monitoring in postoperative patients with kidney injury. Information about the actual Ctrough values ensures better safety of vancomycin-based therapy in patients with acute kidney injury. The efficacy of the antibacterial treatment is constrained by the sensitivity of the infectious agent (MIC). For a better outcome, the AUC24/MIC ratio should be calculated. Further pharmacokinetic studies of vancomycin are necessary to improve the method of mathematical modeling for postoperative patients with acute kidney injury.
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7. Al-Kofide H, Zaghloul I, Al-Naim L. Pharmacokinetics of vancomycin in adult cancer patients. J Oncol Pharm Pract. 2010 Dec 16; 16 (4): 245-250.
8. Burton ME, Gentle DL, Vasko MR. Evaluation of a Bayesian
method for predicting vancomycin dosing. DICP. 1989; 23 (4): 294-300.
9. Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012; 120 (4): 179-84.
10. Instrukciya po medicinskomu primeneniyu [internet]. Available from: http://grls.rosminzdrav.ru/Grls_View_v2.aspx?routingGuid= 80390ff0-c656-4e1b-a33e-a30232cccf1d&t=.
11. Hammett-Stabler CA, Johns T. Laboratory guidelines for monitoring of antimicrobial drugs. Clin Chem. 1998 May; 44 (5): 1129-40.
12. Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2017 Available from: https://www.R-project.org.
13. Bauer LA. Applied clinical pharmacokinetics. New York: McGraw-Hill, 2001.p. 26-49.
14. Matzke GR, McGory RW, Halstenson CE, Keane WF. Pharmacokinetics of vancomycin in patients with various degrees of renal function. Antimicrob Agents Chemother. 1984 Apr;25(4):433-7.
15. Patel N, Pai MP, Rodvold KA, Lomaestro B, Drusano GL, Lodise TP. Vancomycin: we can't get there from here. Clin Infect Dis. 2011 Apr 15; 52 (8): 969-74.
16. Bel KA, Bourguignon L, Marcos M, Ducher M, Goutelle S. Is trough concentration of vancomycin predictive of the area under the curve? A clinical study in elderly patients. Ther Drug Monit.
2017 Feb; 39 (1): 83-7. 21.
17. Moise-Broder PA, Forrest A, Birmingham MC, et al. Pharmacodynamics of vancomycin and other antimicrobials in patients with Staphylococcus aureus lower respiratory tract infections. Clin Pharmacokinet. 2004; 43 (13): 925-42. 22.
18. Paglialunga S, Offman E, Ichhpurani N, Marbury TC, Morimoto BH. Update and trends on pharmacokinetic studies in patients with impaired renal function: practical insight into application of the 23. FDA and EMA guidelines. Expert review of clinical pharmacology. 2017; 10 (3): 273-83.
19. Prybylski JP. Vancomycin Trough Concentration as a Predictor 24. of Clinical Outcomes in Patients with Staphylococcus aureus Bacteremia: A Meta-analysis of Observational Studies. Pharmacotherapy. 2015 Oct; 35 (10): 889-98.
20. Murphy JE, Gillespie DE, Bateman CV. Predictability of vancomycin 25. trough concentrations using seven approaches for estimating pharmacokinetic parameters. Am J Health Syst Pharm. 2006
Dec 1; 63 (23): 2365-70.
del Mar Fernández de Gatta Garcia M, Revilla N, Calvo MV, Domínguez-Gil A, Sánchez Navarro A. Pharmacokinetic/ pharmacodynamic analysis of vancomycin in ICU patients. Intensive Care Med. 2007 Feb; 33 (2): 279-85. Neely MN, Youn G, Jones B, Jelliffe RW, Drusano GL, Rodvold KA, et al. Are vancomycin trough concentrations adequate for optimal dosing? Antimicrob Agents Chemother. 2014; 58 (1): 309-16. Pai MP, Neely M, Rodvold KA, Lodise TP. Innovative approaches to optimizing the delivery of vancomycin in individual patients. Adv Drug Deliv Rev. 2014 Nov 20;77:50-7.
Purwonugroho TA, Chulavatnatol S, Preechagoon Y, Chindavijak B, Malathum K, Bunuparadah P. Population pharmacokinetics of vancomycin in Thai patients. The Scientific World Journal. 2012;2012:762649. DOI: 10.1100/2012/762649. Zalloum N, Saleh MI, Al Haj M, Balbisi M, Al-Ghazawi M. Population pharmacokinetics of vancomycin in Jordanian patients Tropical Journal of Pharmaceutical Research. 2018; 17 (2): 351-58.
Литература
1. Rybak M, Lomaestro B, Rotschafer JC, Moellering R, Craig W, 15. Billeter M, et al. Therapeutic monitoring of vancomycin in adult patients: a consensus review of the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, 16. and the Society of Infectious Diseases. Am J Health Syst Pharm. 2009 Jan 1; 66 (1): 82-98.
2. Ye ZK, et al. Therapeutic drug monitoring of vancomycin: a guideline of the Division of Therapeutic Drug Monitoring. J 17. Antimicrob Chemother. 2016 Nov 11; 71 (11): 3020-25.
3. Бондарева И. Б. Программное обеспечение для анализа данных ФК/ФД исследований. Клиническая фармакокинетика. 2005; 2 (3): 9-13. 18.
4. Brendel K, Dartois C, Comets E, et al. Are population pharmacokinetic and/or pharmacodynamic models adequately evaluated? A survey of the literature from 2002 to 2004. Clin Pharmacokinet. 2007; 46 (3): 221-34.
5. Clinical Calculators [интернет]. Available from: http://clincalc. 19. com/Vancomycin
6. Lake KD, Peterson CD. A simplified dosing method for initiating vancomycin therapy. Pharmacotherapy. 1985 Nov-Dec; 5 (6): 340-44. 20.
7. Al-Kofide H, Zaghloul I, Al-Naim L. Pharmacokinetics of vancomycin in adult cancer patients. J Oncol Pharm Pract. 2010 Dec 16; 16(4): 245-250.
8. Burton ME, Gentle DL, Vasko MR. Evaluation of a Bayesian 21. method for predicting vancomycin dosing. DICP. 1989; 23 (4): 294-300.
9. Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012; 120 (4): 179-84. 22.
10. Инструкция по медицинскому применению [интернет]. Доступно по ссылке: http://grls.rosminzdrav.ru/Grls_View_v2.aspx?routingGuid= 80390ff0-c656-4e1b-a33e-a30232cccf1d&t=
11. Hammett-Stabler CA, Johns T. Laboratory guidelines for 23. monitoring of antimicrobial drugs. Clin Chem. 1998 May; 44 (5): 1129-40.
12. Core Team. R: A language and environment for statistical 24. computing. R Foundation for Statistical Computing, Vienna, Austria. 2017 Available from: https://www.R-project.org
13. Bauer LA. Applied clinical pharmacokinetics. New York: McGraw-
Hill, 2001. р. 26-49. 25.
14. Matzke GR, McGory RW, Halstenson CE, Keane WF. Pharmacokinetics of vancomycin in patients with various degrees of renal function. Antimicrob Agents Chemother. 1984 Apr; 25 (4): 433-7.
Patel N, Pai MP, Rodvold KA, Lomaestro B, Drusano GL, Lodise TP. Vancomycin: we can't get there from here. Clin Infect Dis. 2011 Apr 15; 52 (8): 969-74.
Bel KA, Bourguignon L, Marcos M, Ducher M, Goutelle S. Is trough concentration of vancomycin predictive of the area under the curve? A clinical study in elderly patients. Ther Drug Monit. 2017 Feb; 39 (1): 83-7.
Moise-Broder PA, Forrest A, Birmingham MC, et al. Pharmacodynamics of vancomycin and other antimicrobials in patients with Staphylococcus aureus lower respiratory tract infections. Clin Pharmacokinet. 2004; 43 (13): 925-42. Paglialunga S, Offman E, Ichhpurani N, Marbury TC, Morimoto BH. Update and trends on pharmacokinetic studies in patients with impaired renal function: practical insight into application of the FDA and EMA guidelines. Expert review of clinical pharmacology. 2017; 10 (3): 273-83.
Prybylski JP. Vancomycin Trough Concentration as a Predictor of Clinical Outcomes in Patients with Staphylococcus aureus Bacteremia: A Meta-analysis of Observational Studies. Pharmacotherapy. 2015 Oct; 35 (10): 889-98. Murphy JE, Gillespie DE, Bateman CV. Predictability of vancomycin trough concentrations using seven approaches for estimating pharmacokinetic parameters. Am J Health Syst Pharm. 2006 Dec 1; 63 (23): 2365-70.
del Mar Fernández de Gatta Garcia M, Revilla N, Calvo MV, Domínguez-Gil A, Sánchez Navarro A. Pharmacokinetic/ pharmacodynamic analysis of vancomycin in ICU patients. Intensive Care Med. 2007 Feb; 33 (2): 279-85. Neely MN, Youn G, Jones B, Jelliffe RW, Drusano GL, Rodvold KA, et al. Are vancomycin trough concentrations adequate for optimal dosing? Antimicrob Agents Chemother. 201 4; 58 (1 ): 309-16.
Pai MP, Neely M, Rodvold KA, Lodise TP. Innovative approaches
to optimizing the delivery of vancomycin in individual patients. Adv
Drug Deliv Rev. 2014 Nov 20; 77: 50-7.
Purwonugroho TA, Chulavatnatol S, Preechagoon Y, Chindavijak B,
Malathum K, Bunuparadah P. Population pharmacokinetics
of vancomycin in Thai patients. The Scientific World Journal.
2012;2012:762649. DOI: 10.1100/2012/762649.
Zalloum N, Saleh MI, Al Haj M, Balbisi M, Al-Ghazawi M. Population
pharmacokinetics of vancomycin in Jordanian patients Tropical
Journal of Pharmaceutical Research. 2018; 17 (2): 351-58.
