Hypoalbuminaemia and decreased midazolam clearance in terminally ill adult patients, an inflammatory effect?

Franken, L; Masman, Anniek D.; Winter, Brenda C M de; Baar, Frans P. M.; Tibboel, Dick; Gelder, Teun van; Koch, Birgit C. P.; Mathôt, Ron A. A.

doi:10.1111/bcp.13259

Cited by 26 publications

(47 citation statements)

References 41 publications

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“…We did not find a similar effect on V 1 , which one would expect if the correlation were due to protein binding. A possible explanation could be that the reduced CL/F is caused by an underlying inflammatory response, as described previously . Hypoalbuminaemia can be an expression of inflammation, which can result in reduced CYP3A activity .…”

Section: Discussionmentioning

confidence: 83%

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Andrews

Hesselink

Schaik

et al. 2019

Brit J Clinical Pharma

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Aims The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient. Methods Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. Results A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h−1, clearance was 23.0 l h–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dose0.25em()mg=2220.25emng0.25emnormalh0.25emml–1*0.5em22.50.25emnormall0.25emnormalh–1*[](),1.0if0.25emCYP3normalA5*3/*30.25emor0.25em(),1.62if0.25emCYP3normalA5*1/*30.25emor0.25emCYP3normalA5*1/*1*[](),1.0if0.25emCYP3normalA4*10.25emor unknown0.25emor0.25em(),0.814if0.25emCYP3normalA4*22*Age56−0.50*BSA1.930.72/1000 Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model. Conclusions For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

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Section: Discussionmentioning

confidence: 83%

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Andrews

Hesselink

Schaik

et al. 2019

Brit J Clinical Pharma

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“…Within the DINO study midazolam plasma samples were analyzed using liquid chromatography–tandem mass spectroscopy with electrospray ionization in the positive ionization mode. The lower limit of quantification for midazolam was 4 µg/L …”

Section: Methodsmentioning

confidence: 99%

Recently Registered Midazolam Doses for Preterm Neonates Do Not Lead to Equal Exposure: A Population Pharmacokinetic Model

Völler

Flint

Beggah

et al. 2019

The Journal of Clinical Pharma

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Although midazolam is a frequently used sedative in neonatal intensive care units, its use in preterm neonates has been off‐label. Recently, a new dosing advice for midazolam for sedation on intensive care units has been included in the label (0.03 mg/[kg·h] for preterm neonates <32 weeks and 0.06 mg/[kg·h] for neonates >32 weeks). Concentration‐time data of a prospective multicenter study (29 patients, median gestational age 26.7 [range 24.0‐31.1 weeks]) were combined with previously published data (26 patients, median gestational age 28.1 [range 26.3‐33.6 weeks]), and a population pharmacokinetic model describing the maturation of midazolam pharmacokinetics was developed in NONMEM 7.3. Clearance was 73.7 mL/h for a neonate weighing 1.1 kg and changed nonlinearly with body weight (exponent 1.69). Volume of distribution increased linearly with body weight and was 1.03 L for a neonate weighing 1.1 kg. Simulations of the newly registered dosing show considerable differences in steady‐state concentrations in preterm neonates. To reach similar steady‐state concentrations of 400 µg/mL (±100 µg/mL), a dose of 0.03 mg/(kg·h) is adequate for neonates ≥1 kg and ≤2 kg but would have to be reduced to 0.02 mg/(kg·h) (−33%) in neonates <1 kg and increased to 0.04 mg/(kg·h) (+33%) in neonates weighing >2 kg and ≤2.5 kg. The impact of the observed differences in exposure is difficult to assess because no target concentrations have yet been defined for midazolam, but the current analysis shows that one should be cautious in giving dosage advice based on historical data with a lack of reliable pharmacokinetic and effect data.

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“…The design of the study and study population are presented in detail in the article of Franken et al . in which the population PK model of midazolam is described . Parts of the methods are briefly mentioned in this article when relevant.…”

Section: Methodsmentioning

confidence: 99%

“…Sparse blood samples were collected at random time points during both the preterminal and terminal stage of the disease. Using these samples, midazolam and its two major metabolites, 1‐hydroxymidazolam (1‐OH‐M) and 1‐hydroxymidazolam glucuronide (1‐OH‐MG) were determined by an liquid chromatography–tandem mass spectrometry method described before . Blood samples for clinical chemistry were taken at the same time and serum levels of albumin, creatinine, urea, bilirubin, γ‐glutamyl transpeptidase, alkaline phosphatase, alanine transaminase, aspartate transaminase and C‐reactive protein were determined.…”

Section: Methodsmentioning

confidence: 99%

“…A more individualized dose could therefore potentially lead to more adequate sedation in these patients. To investigate this, a population pharmacokinetic (PK) model was developed which demonstrated large interindividual variability (IIV) on clearance of both midazolam and its metabolites with values ranging from 49 to 61% . It also showed that IIV could be significantly reduced if patients' serum albumin levels and estimated glomerular filtration rate (eGFR) were to be taken into account.…”

Section: Introductionmentioning

confidence: 99%

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Population pharmacodynamic modelling of midazolam induced sedation in terminally ill adult patients

Franken

Winter

Masman

et al. 2017

Brit J Clinical Pharma

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AimsMidazolam is the drug of choice for palliative sedation and is titrated to achieve the desired level of sedation. A previous pharmacokinetic (PK) study showed that variability between patients could be partly explained by renal function and inflammatory status. The goal of this study was to combine this PK information with pharmacodynamic (PD) data, to evaluate the variability in response to midazolam and to find clinically relevant covariates that may predict PD response.MethodA population PD analysis using nonlinear mixed effect models was performed with data from 43 terminally ill patients. PK profiles were predicted by a previously described PK model and depth of sedation was measured using the Ramsay sedation score. Patient and disease characteristics were evaluated as possible covariates. The final model was evaluated using a visual predictive check.ResultsThe effect of midazolam on the sedation level was best described by a differential odds model including a baseline probability, Emax model and interindividual variability on the overall effect. The EC50 value was 68.7 μg l–1 for a Ramsay score of 3–5 and 117.1 μg l–1 for a Ramsay score of 6. Comedication with haloperidol was the only significant covariate. The visual predictive check of the final model showed good model predictability.ConclusionWe were able to describe the clinical response to midazolam accurately. As expected, there was large variability in response to midazolam. The use of haloperidol was associated with a lower probability of sedation. This may be a result of confounding by indication, as haloperidol was used to treat delirium, and deliria has been linked to a more difficult sedation procedure.

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Hypoalbuminaemia and decreased midazolam clearance in terminally ill adult patients, an inflammatory effect?

Cited by 26 publications

References 41 publications

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Recently Registered Midazolam Doses for Preterm Neonates Do Not Lead to Equal Exposure: A Population Pharmacokinetic Model

Population pharmacodynamic modelling of midazolam induced sedation in terminally ill adult patients

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