Dexmedetomidine pharmacokinetics in the obese

Cortínez, Luis Ignacio; Anderson, Brian J.; Holford, Nick; Puga, Valentina A.; Fuente, Natalia de la; Auad, Hernán; Solari, Sandra; Allende, Fidel; Ibacache, Mauricio

doi:10.1007/s00228-015-1948-2

Cited by 49 publications

(31 citation statements)

References 38 publications

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“…The analysis found no relationship between C ss and CL. Sparse sampling could have precluded the identification of the non-linearity in DMED clearance as a function of DMED concentrations ( C ss at the highest DMED infusion was well below the IC 50 reported by Dutta et al; 2.3 vs. 1.3 ng/mL)Cortínez (2015) [40]Obese and non-obese laparoscopic surgery patients20 obese/20 non-obese21 v samples during ( n = 10) and after ( n = 11) DMED infusion360 min34/40 years115/75 kg165/166 cm0.5 µg/kg/h for 10 minutes followed by 0.25 µg/kg/h or 0.5 µg/kg/hAge, WGT, FFM, normal fat mass, intra-operative2-compartment model with FFM as a covariate on clearance, Q 2 , V 1 and V 2 . With FAT as a covariate on clearance and intra-operative state as a covariate on V 1 and V 2 DMED was administered at the same time as propofol and remifentanil.…”

Section: Population Pharmacokinetic Modelingmentioning

confidence: 99%

“…To describe the observed variability in dexmedetomidine pharmacokinetics across and within subjects, different covariate models have been suggested. The central and/or peripheral volumes of distribution ( V 1 , V 2 , V 3 ) were found to correlate with a subject’s age [29, 41], body weight [41, 42], fat free mass [40], serum albumin level [24, 32] and/or whether or not a subject was undergoing surgery [40]. The elimination and/or distributional clearance (CL, Q 2 , Q 3 ) was found to vary significantly according to height [21, 39], body weight [24, 42], or fat (free) mass [40], age [32], cardiac output [26, 32], plasma albumin level [29] and/or alanine aminotransferase activity [41].…”

Section: Population Pharmacokinetic Modelingmentioning

confidence: 99%

“…According to Iirola et al 80-year-old patients have a significantly reduced dexmedetomidine clearance compared with 20-year-old patients, resulting in a 2.1-fold higher C ss . However, when age was tested by other investigators in Asian [39] as well as non-Asian populations [21, 24, 32, 38, 40, 42], it was never retained in the final covariate model. Current evidence thus suggests it is unlikely that age has a significant influence on dexmedetomidine pharmacokinetics.…”

Section: Population Pharmacokinetic Modelingmentioning

confidence: 99%

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Clinical Pharmacokinetics and Pharmacodynamics of Dexmedetomidine

et al. 2017

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Dexmedetomidine is an α2-adrenoceptor agonist with sedative, anxiolytic, sympatholytic, and analgesic-sparing effects, and minimal depression of respiratory function. It is potent and highly selective for α2-receptors with an α2:α1 ratio of 1620:1. Hemodynamic effects, which include transient hypertension, bradycardia, and hypotension, result from the drug’s peripheral vasoconstrictive and sympatholytic properties. Dexmedetomidine exerts its hypnotic action through activation of central pre- and postsynaptic α2-receptors in the locus coeruleus, thereby inducting a state of unconsciousness similar to natural sleep, with the unique aspect that patients remain easily rousable and cooperative. Dexmedetomidine is rapidly distributed and is mainly hepatically metabolized into inactive metabolites by glucuronidation and hydroxylation. A high inter-individual variability in dexmedetomidine pharmacokinetics has been described, especially in the intensive care unit population. In recent years, multiple pharmacokinetic non-compartmental analyses as well as population pharmacokinetic studies have been performed. Body size, hepatic impairment, and presumably plasma albumin and cardiac output have a significant impact on dexmedetomidine pharmacokinetics. Results regarding other covariates remain inconclusive and warrant further research. Although initially approved for intravenous use for up to 24 h in the adult intensive care unit population only, applications of dexmedetomidine in clinical practice have been widened over the past few years. Procedural sedation with dexmedetomidine was additionally approved by the US Food and Drug Administration in 2003 and dexmedetomidine has appeared useful in multiple off-label applications such as pediatric sedation, intranasal or buccal administration, and use as an adjuvant to local analgesia techniques.

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Section: Population Pharmacokinetic Modelingmentioning

confidence: 99%

Section: Population Pharmacokinetic Modelingmentioning

confidence: 99%

Section: Population Pharmacokinetic Modelingmentioning

confidence: 99%

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Clinical Pharmacokinetics and Pharmacodynamics of Dexmedetomidine

et al. 2017

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“…A negative value for Ffat suggests organ dysfunction associated with fat in which may be the case in the morbidly obese. Dexmedetomidine was noted to have a negative value for Ffat CL in morbidly obese adults . Although we might anticipate that Ffat increases with lipid solubility, this has not been demonstrated.…”

Section: Popular Size Metrics In Anesthesiamentioning

confidence: 99%

What is the best size predictor for dose in the obese child?

Anderson

Holford

2017

Pediatric Anesthesia

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SummaryLean body mass is commonly proposed for anesthesia maintenance drug dosing calculations. However, total body mass used with allometric scaling has been shown to be better for propofol in obese adults and children. Fat-free mass has also been used instead of lean body mass. Fat-free mass is essentially the same as lean body mass but excludes a small percentage of mass of lipids in cell membranes, CNS, and bone marrow. Normal fat mass is a size descriptor that partitions total body mass into fat-free mass and fat mass calculated from total body mass minus fat-free mass.The relative influence of fat mass compared with fat-free mass is described by the fraction of fat mass that makes fat equivalent to fat-free mass in terms of allometric size. This fraction (Ffat) will differ for each drug and each parameter affected by body size (eg, clearance and volume of distribution). This fraction is based on the concept of theory-based allometric size. The normal fat mass based on allometric theory and partition of body mass into fat and fat-free components provides a principle-based approach explaining size and body composition effects on pharmacokinetics of all drugs in children and in adults. 1 This speculation is difficult to test because of the well-known biologically driven relationship between body structure and function driven by body mass. 2 In order to evaluate the influence of obesity, it is necessary to find a means to distinguish between size and the independent effects of obesity.We have proposed using a theory-based relationship between body mass and size-related differences in clearance to distinguish between size and age-related effects in early life that reflect maturation of organ function. 3 This approach has proved useful for describing glomerular filtration rate and clearance of many drugs. 4We have also suggested using a similar theory-based approach to distinguish the influence of fat and fat-free components of body mass used to predict clearance and volume of distribution. 5 In this review, we expand on these concepts to develop a framework for determining if there is an influence of obesity on pharmacokineticparameters. We also demonstrate how pharmacokinetic parameters may be predicted using fat mass with application to drug dosing in children and adults.

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“…This was due to volume of distribution increases dependent on lean body tissue, and a reduced clearance. 99 …”

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confidence: 99%