Absorption

The first step in modeling exposure is to quantify the relationship between drug dosage administered and the amount of drug that reaches the systemic circulation. This relationship is known as the drug’s bioavailability. IV administration provides 100% bioavailability, whereas this value can be considerably less for other routes. Oral ingestion is the most common route of administration in the general population and remains useful in many critically ill patients. Bioavailability through oral administration is usually less than 100% and is a function of two main factors: (1) absorption, which is the intrinsic ability of the drug to cross the gastrointestinal tract, and (2) presystemic metabolism, also known as the first-pass effect, which occurs primarily in the liver, and to a lesser extent in the intestinal lumen. Drugs that undergo extensive hepatic metabolism may have large first-pass effects and thus low bioavailability compared to IV administration. Similarly, drugs that are poorly absorbed will have low bioavailability.

Factors that determine absorption from the gastrointestinal (GI) tract include drug characteristics such as lipid solubility, ionization, and molecular size, in addition to physiologic factors such as gastric emptying rate, intestinal blood flow, motility, gastric and intestinal pH, gut wall permeability, and whether the dose is administered during the fasted or fed state.¹ Most drugs are orally absorbed through passive diffusion; although carrier-mediated absorption can also be important. The most important sites of absorption are the upper and lower segments of the small intestine.² The stomach regulates absorption through gastric emptying but is not an important site for absorption. Similarly, little drug absorption occurs in the colon with the exception of extended-release products.¹ Drugs with low oral bioavailability will require larger doses administered orally to produce equivalent exposure to that obtained from IV administration. Some drugs (e.g., vancomycin) have such poor bioavailability after oral administration that they cannot be used to treat the same disease processes as the IV formulations. Bioavailability is an important consideration when converting between oral and IV routes. For example, a patient who takes furosemide 80 mg orally at home would need only 40 mg given intravenously because this drug has 50% bioavailability on average. Other routes of administration include subcutaneous (SC) and intramuscular injection, transdermal absorption, buccal absorption, and inhalation. Many drugs that are available as IV preparations are amenable to SC and intramuscular administration. However, some IV drugs have characteristics that preclude administration by routes other than large-bore catheters. These drugs include those with very basic or acidic pH, or those that act as vesicants and therefore need diluents added to maintain solubility. Drugs with adequate lipid solubility are amenable to transdermal and buccal administration.

Distribution

After reaching the systemic circulation an administered dose then distributes throughout the body to produce a peak concentration. The relationship between the dose administered and the peak concentration observed after accounting for bioavailability is termed the volume of distribution (Vd). Vd estimates the size of the compartment into which the drug distributes. Total plasma volume in the average adult is 3 to 4 L.¹ However, the Vd for most drugs is much greater than this value. The discrepancy between plasma volume and a drug’s Vd is accounted for by the extent that drugs concentrate in various tissues. The main determinants of Vd are the drug’s lipid solubility, degree of protein binding, and extent of tissue binding.¹ High lipid solubility increases Vd through improved passage across cell membranes. Avid tissue binding also increases Vd as this concentrates drug outside the vascular space. Conversely, because only unbound drug can cross cell membranes and bind to tissue, high protein binding decreases Vd.

The simplest conceptualization of Vd is to view the body as a bucket—one large compartment where drug rapidly equilibrates between plasma and tissue and has uniform distribution (Fig. 20.3A). The one-compartment assumption is useful for drugs with small to intermediate Vds, such as aminoglycoside antibiotics, because these drugs have a short distribution phase owing to their limited tissue penetration. Drugs with large Vds, such as fentanyl and amiodarone, require longer periods of time to achieve equilibrium between serum and tissue and thus have a prolonged distribution phase. As a result, the one-compartment assumption fails to accurately describe large Vd drugs. An alternative is to view the body as multiple compartments: a central compartment composed of blood, extracellular fluid, and highly perfused tissues; and one or more peripheral compartments composed of tissue beds with lower perfusion and drug binding affinity (Fig. 20.4A). The number of peripheral compartments required will be determined by the differential distribution rate in each tissue. Two-compartment models adequately describe most large Vd drugs; however, a three-compartment model can be useful for agents that act in the central nervous system because of slower distribution as a result of the blood-brain barrier.

Clearance

Drug elimination begins immediately upon entry into the body and can be divided into two main components: metabolism and excretion. Metabolism occurs mainly in the liver via enzymatic degradation, although it occurs to lesser extents in other tissues such as the kidney, lung, small intestine and skin and via enzymes found in the serum. Nonenzymatic metabolism also occurs in the serum, as is the case for cisatracurium, which undergoes spontaneous degradation in the serum through ester hydrolysis. Excretion occurs primarily in the kidney, bile, and feces. Some drugs are eliminated predominantly by a single mechanism. For example, more than 95% of elimination for the aminoglycoside antibiotics occurs through excretion in the kidneys. Other drugs, such as ceftriaxone, are removed through multiple pathways. Regardless of pathway, the degree of protein binding exhibited by a drug is an important determinant of elimination rate, as only unbound drug can be eliminated from the serum.

The rate of drug removal via all routes of elimination is termed clearance, which is expressed as the volume of plasma cleared per unit of time. This value is assumed to be constant for most drugs. Defining total body clearance in terms of volume has important implications. If the volume of blood cleared per unit of time is constant, it then holds that the amount of drug cleared per unit of time must change in proportion to serum concentration. An increase in the rate of drug administration will lead to an increase in serum concentration, which in turn leads to commensurate increases in the rate of drug removal. Serum and tissue concentrations will accumulate until the rate of elimination is in equilibrium with the rate of administration, at which time the system is said to be at “steady state” (Figs. 20.2 and 20.5). Accumulation follows a linear pattern for most drugs, meaning that increases in dose are always matched by proportional increases in elimination, thus producing proportional changes in serum concentration (see Fig. 20.5). Drugs that follow this pattern of accumulation are said to have first-order kinetics. However, some drugs exhibit saturable elimination. These drugs follow linear accumulation until the saturation point for elimination is reached. Once elimination is saturated, small changes in dose can produce substantial increases in concentration (see Fig. 20.5). Drugs that follow this pattern of accumulation have zero-order kinetics. Examples of drugs used in critically ill patients that have saturable elimination include phenytoin, heparin, propranolol, and verapamil.

Half-Life

Once clearance is known the clinician can estimate the time needed for a given dose to be eliminated. Elimination time is commonly expressed in terms of half-life, which is the period of time required for the amount of drug to decrease by 50%. Half-life is calculated from the elimination rate constant:

ke can be further transformed into half-life:

For any system that follows exponential decay, half-life can be used to estimate the amount of elimination that has occurred: after 5 half-lives more than 90% is eliminated. Elimination approaches 100% after 7 half-lives. The time required for a dosing regimen to reach steady state is also an exponential function and thus can be estimated using half-life. This “5-7” rule of thumb is useful at the bedside. Dosing regimens approach maximal effects after 5-7 half-lives. Similarly, drug effects are usually completely dissipated after 5-7 half-lives. Using this rule, it can be predicted that drugs with long half-lives may take several days to produce target effects. This is less than ideal in the critically ill population when effective treatment is needed rapidly. As a result, loading doses are frequently used to hasten the time to steady state. Loading doses can be calculated by multiplying the target steady-state peak concentration by the patient’s Vd. Recommendations for effective loading doses of most long half-life drugs are provided in the package labeling as applicable.

It is important to note that the time needed to eliminate a given dose is not only dependent on the clearance rate, but also on the drug’s Vd. It is intuitive that half-life will be affected by changes in elimination pathways (e.g., renal failure). However, changes in Vd can have equally important effects on half-life, which can lead to higher than expected drug accumulation independent of changes in drug clearance. This effect has important implications for critically ill patients in whom Vd can be significantly altered.

β-Lactams

Alexander Fleming first discovered penicillin in 1928, marking the dawn of the antibiotic era. It was more than 2 decades later when Harry Eagle first noted that penicillin’s effect could be modulated by dosing regimen. Specifically, he observed that penicillin’s ability to kill bacteria was dependent on the amount of time that the drug was maintained at or above the bacteria’s MIC.⁶ Later experiments confirmed time above MIC (T > MIC), as the PD index that predicts bacterial killing for penicillin and other β-lactam agents.⁴ The T > MIC required for optimal response varies among the different β-lactams and is likely related to differences in the rate of bacterial killing and presence of PAE. Cephalosporins require the highest T > MIC (50-70%), followed by the penicillins (30-50%) and the carbapenems (20-40%). The importance of T > MIC has gained increasing attention in the last decade as a result of increasing bacterial resistance. Resistant bacteria have elevated MICs, making it more difficult to achieve adequate T > MIC (Fig. 20.7). In addition, PK studies conducted in critically ill patients have shown that standard β-lactam dosing regimens may produce unacceptably low serum concentrations, resulting in diminished T > MIC.^7,8 Although failure to achieve adequate T > MIC has been shown to predict outcome in numerous animal models,⁹ there have been relatively few data in humans until recently. One study of patients with gram-negative bacteremia found mortality rates to double as the MIC increased from 4 mg/L to 8 mg/L in patients who were treated with cefepime.¹⁰ The importance of this finding is magnified when one considers that an MIC of 8 mg/L is considered to be within the susceptible range for cefepime. A similar increase in mortality rate was found in patients with bacteremia due to Pseudomonas aeruginosa: the relative risk of 30-day mortality was increased nearly fourfold when standard doses of piperacillin were used to treat isolates with elevated MICs to piperacillin.¹¹ Although serum concentrations were not measured in these studies, the data provide indirect evidence that links reduced T > MIC to poor clinical outcome. In another study of gram-negative infection treated with cefepime, actual T > MIC was calculated using serum concentration data. The study showed that likelihood of achieving bacterial eradication was significantly correlated with T > MIC.¹²

The inability to achieve adequate T > MIC has led to the investigation of alternative dosing regimens. Simple dose escalation strategies are hampered by increasing the risk for toxicity. One alternative is to change the shape of the concentration-time curve using continuous or extended infusions. As seen in Figure 20.7, extending the infusion duration changes the shape of the concentration-time curve to promote longer T > MIC. Several PK studies have confirmed that these alternative dosing strategies can increase T > MIC without increasing the size of the dose. One study found that T > MIC following a 2-g dose of meropenem was increased 15% by extending the infusion duration from 0.5 hour to 3 hours.¹³ Although there are no outcome data in humans comparing extended infusions to continuous infusions, PK studies suggest a similar probability of target attainment.¹⁴

An additional theoretical consideration when comparing the extended and continuous strategies is the risk of selecting resistant bacteria. Mathematical modeling of bacterial growth dynamics suggests that a constant rate of bacterial killing creates more opportunity for generating resistant mutants than does a fluctuating kill rate.¹⁵ This effect has been demonstrated in an in vitro model of ceftazidime continuous infusion, when maintenance of steady-state serum concentrations slightly above the bacteria’s MIC resulted in the emergence of resistant bacteria subpopulations.¹⁶ This has led some investigator to recommend serum concentration monitoring if continuous infusions are used, with adjustment of the infusion rate to ensure steady-state concentrations are adequate.¹⁷ Although extended infusions produce more consistent concentrations compared to standard infusions, they produce greater fluctuation compared to continuous infusion. Extended infusions also possess the logistical advantage of less infusion time and therefore greater IV access. This is of particular benefit in patients who require multiple vasoactive and nutritional infusions.

Despite having sound PK/PD rationale, the clinical benefit of extended or continuous infusion strategies has yet to be documented in randomized clinical trials.¹⁸ Most available trials have important methodologic limitations. Although extended infusions increase T > MIC compared to standard infusions, the benefit is of greatest importance for bacterial isolates with elevated MICs because standard doses already provide optimal T > MIC when MIC is low. The benefit of extended infusions is also a function of the patient’s renal function. Nicasio and associates recently found 3-hour infusions of cefepime increased T > MIC compared to standard 0.5-hour infusions but the effect was limited to patients with preserved renal function (creatinine clearance [CrCl] 50-120 mL/minute).¹⁹ This effect modification is due to the prolonged half-life of cefepime in renal dysfunction, leading to higher trough concentrations and increased T > MIC. In light of these considerations, it is likely that the benefit of extended infusion strategies is greatest in patients with preserved renal function who are infected with high MIC pathogens, such as P. aeruginosa and Acinetobacter baumannii.

Aminoglycosides

Aminoglycosides are broad-spectrum gram-negative agents that have been in clinical use since the 1960s. These agents quickly developed a reputation for having poor effectiveness and a high rate of nephrotoxicity compared to β-lactam agents. However, much of the initially dismal results observed with these agents are likely related to an inadequate knowledge of their PD profile. At the time, PD data available from β-lactam studies demonstrated T > MIC to be the important factor predicting efficacy.⁶ As a result, early dosing strategies used small (1-2 mg/kg) doses given every 8 to 12 hours and little attention was paid to peak concentrations. The importance of achieving an adequate peak:MIC ratio was first described in patients by Moore and colleagues, who found that the likelihood of having a positive clinical response was greater than 90% when peak concentrations were 8 to 10 times the infecting organism’s MIC.²⁰ A later study found that time to defervescence and normalization of leukocytosis was greater than 90% when peak:MIC ratio was 10 or greater.²¹ These data suggest that achieving high peak aminoglycoside concentrations is fundamental to successful treatment. In recognition of this, clinicians began to monitor peak aminoglycoside levels and adjust dosing regimens to ensure optimal peak:MIC ratios.

Aminoglycosides also exhibit a prolonged PAE. The duration of PAE in neutropenic animal models varies from 1 to 8 hours and is a function of the peak:MIC ratio.²² Higher ratios produce longer PAE. In addition, data suggest that PAE may be enhanced in patients with an intact immune system.⁴ Based on the combination of concentration-dependent activity and a prolonged PAE the efficacy of these agents could be maximized by giving large doses less frequently. This strategy is known as extended interval dosing (EID). Because aminoglycosides have short half-lives, the drugs are completely cleared from serum near the end of a 24-hour dosing interval in patients with normal renal function. Although the absence of drug may be concerning for the regrowth of bacteria, this is prevented by the PAE. In addition, a drug-free period near the end of the dosing interval minimizes the phenomenon known as adaptive resistance. Primarily described in P. aeruginosa infection, adaptive resistance refers to the diminished rate of bacterial killing after initial exposure to aminoglycosides.²³ This effect is caused by up-regulation of membrane-bound efflux pumps, which decrease the amount of drug that reaches the site of action inside the cell.²³ When the bacteria are free from drug exposure for a sufficient amount of time the adaptive resistance is lost and the bacteria will become fully sensitive again. Thus, in addition to achieving high peak:MIC ratios, EID may also allow for the reversion of adaptive resistance and greater bactericidal effect.

A wide variety of doses have been utilized in EID strategies. However, the most common are 5 to 7 mg/kg for gentamicin and tobramycin and 15 to 20 mg/kg for amikacin.²⁴ These doses were chosen based directly on PK/PD relationships. EID assumes that patients have a Vd that is within the normal range (0.25-0.3 L/kg). When given to patients who meet this assumption, the doses will produce peak concentrations that range from 16 to 24 mg/L and will achieve target peak:MIC ratios for isolates with an MIC up to 2 mg/L.²⁵ EID is also designed to achieve a drug-free period of at least 4 hours at the end of the dosing interval.²⁵ Because aminoglycosides are cleared renally, dosing frequency is based on renal function assessment using estimated CrCl. To achieve an adequate drug-free interval, doses are given every 24 hours for patients with CrCl greater than 60 mL/minute, every 36 hours with CrCl 40 to 59 mL/minute, and every 48 hours with CrCl less than 40 mL/minute.²⁵ If aminoglycosides are used in renal dysfunction it is important that they still be dosed on weight owing to their peak:MIC dependent activity. EID of aminoglycosides has not been adequately studied in some patient populations (i.e., cystic fibrosis, thermal injury, pregnancy). The lack of validation data leads to the exclusion of these patients from EID nomograms, with the alternative being to use traditional dosing. However, based on our knowledge of the optimal PD parameter and the increased clearance seen in these populations, traditional dosing strategies may result in higher failure rates.

The benefit of EID has been studied in many small clinical trials and the results summarized in multiple meta-analyses. The conclusion from these studies is that EID produces similar efficacy to traditional dosing that is guided by close monitoring of peak concentrations.²⁶ However, most trials employed combination therapy with a β-lactam agent with activity against the infecting pathogen, potentially masking the effect of aminoglycoside dosing strategy.

As mentioned earlier, the use of aminoglycosides is limited by their propensity to induce nephrotoxicity. Nephrotoxicity is the result of accumulation in the epithelial cells of the proximal renal tubule. Of great importance is the fact that the rate of accumulation is saturable at relatively low concentrations in the tubule lumen.²⁷ This means that toxicity is not concentration dependent but rather time dependent. The implication is that high peak concentrations are just as safe as low peak concentrations. Once saturated, the rate-limiting step of tissue accumulation becomes the duration of exposure. Because EID produces a drug-free period near the end of the dosing interval, it reduces the amount of time drug can accumulate, potentially reducing toxicity. In vivo studies have confirmed that EID reduces renal accumulation.²⁸ It has been shown that a threshold of accumulation is needed before nephrotoxicity is produced and that this threshold is typically reached after 5 to 7 days of therapy.²⁹ Importantly, using EID prolongs the time to toxicity but the risk is not abolished. Once the duration of therapy exceeds 1 week, toxicity increases substantially regardless of dosing strategy. Duration of therapy was found to be a significant risk factor for toxicity in a cohort of elderly patients receiving once-daily aminoglycoside therapy.³⁰ The incidence of nephrotoxicity was only 3.9% in the 51 patients who received aminoglycoside therapy for less than 7 days compared to 30% in the 37 patients who received 8 to 14 days of therapy, and 50% of 8 patients receiving more than 14 days.

The aminoglycosides serve as a good example of how understanding PD principles can optimize the use of antibiotics. Concentration-dependent activity, prolonged PAE, adaptive resistance, and saturable renal accumulation characterize these agents. The use of EID takes best advantage of these characteristics. Regardless of dosing strategy, using the shortest duration of therapy possible is essential to minimizing the risk of toxicity.

Vancomycin

Methicillin-resistant Staphylococcus aureus (MRSA) remains one of the most important pathogens causing infection in critically ill patients.³¹ Vancomycin has been the drug of choice for treating this pathogen for nearly 50 years. It inhibits cell wall formation in gram-positive bacteria in a similar fashion to the action of β-lactams. However, vancomycin binds a different receptor and produces a slower bactericidal effect. This slow bactericidal activity likely explains the slower symptom resolution and higher failure rates with vancomycin compared to β-lactams in the treatment of MRSA infections.³² The current breakpoint for vancomycin susceptibility against Staphylococcus species is an MIC of 2 mg/L.³³ In recent years, studies have identified MIC to be an important indicator of response to vancomycin therapy, which serves as a good example of how MIC can modify the ability of dosing regimens to achieve PD targets.³⁴

It was unclear for many years which PD parameter correlated best with vancomycin activity. Because vancomycin, like the β-lactams, inhibits cell wall formation, one might presume T > MIC to be the best parameter. This assumption is supported by in vitro models showing that bacterial killing rate is concentration independent once above the MIC.³⁵ Other models show total drug exposure, as measured by the 24-hour AUC, to be more important for clinical response. In a study of patients with lower respiratory tract infection, Moise-Broder and coworkers found the AUC:MIC ratio to predict clinical response better than T > MIC.³⁶ They found a sevenfold increased probability of clinical cure and a decreased time to bacterial eradication when the AUC:MIC ratio was at least 400. No correlation with outcome was found for T > MIC. The discrepancy between vancomycin PD targets identified with in vitro models and human data underscores the importance of understanding the role of protein binding and tissue penetration. This is especially important for critically ill patients who can have altered tissue permeability and serum protein concentrations. Despite these limitations, total AUC:MIC ratio seems to be the best predictor of vancomycin activity and provides a parameter that can be easily monitored at the bedside.

Vancomycin dosing guidelines published in 2009 state that an AUC:MIC ratio of 400 or greater is the most appropriate PD target and that vancomycin trough concentrations should be monitored as a surrogate for AUC.³⁷ The guidelines recommend targeting steady-state trough concentrations of 15 to 20 mg/L for infections difficult to treat such as endocarditis, osteomyelitis, bacteremia, meningitis, and pneumonia. These troughs will achieve an AUC:MIC ratio of 400 or greater for pathogens with an MIC less than 1 mg/L. It is important to note that the success of this trough target is dependent on pathogen MIC. Mathematical simulations show that trough concentrations of 15 to 20 mg/L are unable to achieve target AUC:MIC ratios when the pathogen MIC is greater than 1 mg/L.³⁸ These simulations are supported by a recent meta-analysis that found a 64% relative increase in mortality risk when comparing high MIC (>1.5 mg/L) isolates to low MIC (<1.5 mg/L) isolates.³⁴ Although most MRSA isolates still have an MIC of 1 mg/L or less, many institutions have documented gradual increases in the number of isolates with MIC greater than 1 mg/L over the past decade.³⁹

MRSA isolates with a high MIC represent a currently unsolved therapeutic dilemma. An intuitive solution would be to increase target trough concentration in hopes of achieving target AUC:MIC. Steady-state troughs of 25 to 30 mg/L would reliably achieve AUC:MIC ratios greater than 400 against an MIC of 2 mg/L. This strategy would likely be unfeasible, however, as recent data have linked high troughs with increased risk of nephrotoxicity. One observational study showed the risk to increase when the initial trough concentration was greater than 20.⁴⁰ This finding is in agreement with data from a recent randomized clinical trial comparing vancomycin to linezolid for treatment of pneumonia.⁴¹ The rate of nephrotoxicity was increased in patients who receive vancomycin compared to linezolid (18.2% vs. 8.4%, respectively). In addition, a dose response was observed in the vancomycin arm: toxicity was observed in 37% of patients with initial trough greater than 20 mg/L, 22% when initial trough was 15 to 20 mg/L, and 18% when initial trough was less than 15 mg/L. Although these data use trough concentration to assess the dose:response relationship, trough is closely correlated with peak concentration and total AUC. Consequently, it is unclear which parameter is most closely associated with toxicity. An observational study showed continuous IV (CIV) infusions of vancomycin to have a slower rate of onset of nephrotoxicity compared to intermittent IV (IIV) infusion despite having similar cumulative doses in the two groups.⁴² This study suggests that toxicity may be related to high peak concentrations, although more data are needed to verify these findings. The only randomized clinical trial to date of this strategy found no difference in safety or efficacy of continuous versus intermittent IV vancomycin.⁴³ Consequently, until more data are available, targeting troughs above 15 to 20 mg/L or the use of high-dose CIV infusions cannot be recommended.

Another option for treating high MIC isolates is to use alternative agents with activity against MRSA (i.e., linezolid, daptomycin, telavancin, and ceftibiprole). However, to date no agent has definitively been shown to provide improved outcome compared to vancomycin in the general treatment of MRSA. Additionally, few data are available that compare agents specifically in patients with high MIC isolates, and cross-resistance between vancomycin and alternative agents has been noted.⁴⁴

Renal Disease

Acute kidney injury (AKI) is a common occurrence in the ICU. Using a consensus definition, rates of AKI range from 10% to 30% in the general ICU population, and 40% to 60% in patients with severe sepsis and septic shock In addition, approximately 5% will require some form of hemodialysis.⁷⁵ This frequency is an important concern for drug dosing because renal elimination is one of the two primary routes of drug clearance. Therefore, it is important for ICU practitioners to understand the basic approach to renal drug dosing.

Hepatic Disease

The liver serves as the primary site for drug metabolism, and therefore, drug dosing is an important consideration in any patient with hepatic disease. Hepatic drug clearance (CL_H) is an extremely complex process, dependent on hepatic blood flow (Q_H) and the hepatic extraction ratio (E_H). The hepatic extraction ratio depends on Q_H, intrinsic clearance of unbound drug (CL_int), and the fraction of unbound drug in blood (f_u).⁹⁴ The following equations can be used to estimate CL_H:

Most data regarding changes in drug clearance are in patients with cirrhosis and therefore do not necessarily apply to acute changes in liver function. Few data are available in patients with acute hepatic dysfunction, making assessments and recommendations in this patient population difficult. Drugs can be categorized as either high or low extraction ratio drugs. Elimination of high extraction ratio drugs is limited by hepatic blood flow and is less sensitive to changes in drug protein binding or enzyme activity (i.e., CL_int). After absorption from the GI tract the first stop for all drugs is the liver. High extraction ratio drugs undergo presystemic metabolism commonly referred to as the hepatic first-pass effect. This results in significantly decreased bioavailability and serum drug concentrations. In patients with decreased hepatic blood flow the first-pass effect is decreased, leading to increased serum concentrations and potentially more adverse effects. This effect is most pronounced in drugs that normally have low bioavailability after oral administration.

Low extraction ratio drugs are more sensitive to changes in drug protein binding and enzyme activity (i.e., CL_int) and are affected to a lesser degree by changes in blood flow. Plasma protein binding of drugs is decreased in hepatic disease due to a number of reasons including decreased protein production (albumin, AAG) and accumulation of endogenous compounds, which inhibit protein binding. As mentioned previously, this decrease in protein binding can increase free drug exposure for certain drugs, increasing the risk of adverse effects. Intrinsic hepatic clearance is the ability of the liver to clear unbound drug from the blood. It is highly dependent on the activity of metabolic enzymes and hepatic transporters. These processes may be altered in chronic liver disease, resulting in decreased drug metabolism. The two phases of hepatic metabolism are phase 1 (i.e., hydrolysis, oxidation, reduction) and phase 2 (i.e., acetylation, glucuronidation, sulfation). The cytochrome P-450 family of enzymes is responsible for approximately 75% of drug metabolism and is classified as phase 1 reactions.⁹⁵ Phase 1 metabolism is dependent on molecular oxygen and is thought to be more sensitive to changes that result in decreased oxygen delivery such as to shunting, sinusoidal capillarization, and reduced liver perfusion.^94,96 Although data demonstrate that enzyme activity is decreased with increasing disease severity, the decreases are variable and nonuniform across the different CYP450 isoenzymes. Although phase 2 metabolism was historically thought to be spared in patients with liver disease, recent data suggest that it is impaired in patients with advanced cirrhosis as well.⁹⁴

Obese Patients

Approximately 30% of adults in the United States are considered obese.¹⁰³ Available data suggest upward of 25% of all patients admitted to ICUs can be categorized as obese, with 6% to 7% of patients being morbidly obese.^104,105 These alterations in body weight present potential pharmacokinetic challenges with many drugs that have not been adequately studied in this population.

Elderly Patients

Current estimates from the administration on aging predict that by 2050 approximately 20% of the U.S. population will be older than 65.¹⁴¹ As a result elderly patients will make up a larger percentage of ICU admissions. These patients frequently have multiple chronic diseases and are at increased risk for polypharmacy. Unfortunately, prior to 1990 drug companies were not required to study drugs in elderly patients. This leads to a lack of dosing recommendations that are specific to the elderly patient population.

As individuals age a number of physiologic changes occur that lead to significant pharmacokinetic alterations. Drug absorption may be decreased as a result of changes in gastric pH, gastric emptying, splanchnic blood flow, and GI motility. Half-life and Vd may be increased for lipophilic drugs as a result of increases in body fat and decreases in lean body mass. Hydrophilic drugs will have increased serum concentrations because of decreases in total body water. The free fraction of highly protein bound drugs is increased as a result of decreases in serum protein production. Decreases in hepatic blood flow and hepatic mass may result in decreased hepatic first-pass effect and potentially decreased phase 1 metabolism. Age-related decreases in renal blood flow and GFR may result in impaired renal drug elimination.¹⁴² Unfortunately, these changes vary among patients, making drug dosing especially challenging.

In an effort to minimize polypharmacy and adverse drug effects several criteria have been developed to screen medication therapy in elderly patients. The most commonly cited are the Beers’ criteria, originally developed in 1991 and updated in 2012.¹⁴³ The most recent version includes 53 medications or medication classes divided into 3 categories. A newer set of recommendations that are gaining popularity are the STOPP (Screening Tool of Older Persons’ potentially inappropriate Prescriptions) criteria. They consist of 64 medications or medication classes divided into 10 categories. Both criteria have been validated and at least one should be used in the evaluation of the appropriateness of medications in elderly patients. In addition to the use of screening criteria drug therapy should be started at a low dose and carefully titrated until the lowest effective dose is achieved.

Pregnancy

Pregnancy is a dynamic state with physiologic changes occurring throughout gestation. These changes include alterations in cardiovascular, pulmonary, GI, renal, and hepatic function that may result in clinically significant changes in drug PK.¹⁴⁴ Pregnant patients are frequently excluded from PK trials, limiting data that describe PK/PD and fetal adverse effect profiles for many drugs commonly used in critically ill pregnant patients. An in-depth discussion of all drug classes in pregnancy is beyond the scope of this chapter. There are several good review articles in the literature for specific drugs or disease states that should be reviewed prior to using the agents in pregnancy.^145,146

Burn Injury

Two phases of burn injury have significant effects on PK and PD. The first 48 hours following injury are characterized by hypovolemia, edema, hypoalbuminemia, and decreases in GFR. The second phase occurs beyond 48 hours and is a hyperdynamic state. During this hyperdynamic phase patients will have increased renal and hepatic blood flow, altered serum protein production, and insensible drug losses through exudate leakage resulting in altered binding, distribution, and clearance.¹⁵⁴

The pharmacokinetic changes seen with burn injury vary from patient to patient, making drug dosing recommendations difficult. A 2008 review article discusses the available pharmacokinetic data.¹⁵⁴ As with other disease states, therapeutic drug monitoring should be used if available to determine drug doses. Because significant changes in serum proteins are common, the use of levels that detect free drug concentrations are preferred. If free levels are not available, clinicians must be aware that a total level in the therapeutic range does not necessarily reflect an appropriate drug dose. In these situations physical and laboratory assessment to evaluate therapeutic efficacy and adverse effects is warranted. If TDM is not available and the agent is a wide therapeutic index drug, then using maximal drug dosing is acceptable to ensure therapeutic effect.

Hypothermia

The process of cooling patients to mild hypothermia (32-34° C) has been studied for a number of different conditions including traumatic brain injury, spinal cord injury, stroke, cardiac surgery, and cardiac arrest.¹⁵⁵ It is most frequently used after cardiac arrest and is currently a recommended treatment in comatose adult patients following out-of-hospital ventricular fibrillation cardiac arrest. In addition, the guidelines from the American Heart Association suggest it may be beneficial for other cardiac arrest patients including in-patients and those with nonshockable rhythms.¹⁵⁶ With the increasing prevalence of hypothermia for cardiac arrest and the potential for use in other indications it is important to understand the impact hypothermia has on drug PK.

Hypothermia results in multiple physiologic changes that may impact the kinetics and dynamics of certain agents. Available literature report varied effects of hypothermia on drug absorption, distribution, drug target affinity, and time to onset.¹⁵⁷ However, hypothermia has been repeatedly shown to decrease drug clearance. This is especially true for drugs that undergo hepatic metabolism via the CYP450 system. Midazolam is one of the most studied drugs in hypothermia because of its frequent use as a sedative and metabolism by CYP3A4 and CYP3A5. One study in traumatic brain-injured patients cooled to less than 35° C demonstrated a fivefold increase in midazolam serum concentrations and a 100-fold decrease in clearance compared to a group of normothermic patients.¹⁵⁸ Data from healthy volunteers predicted an 11% decrease in midazolam clearance for every 1° C decrease in temperature below 36.5° C.¹⁵⁹ This is an important consideration, as it may result in a prolonged duration of pharmacologic effect, even after rewarming. Similar results have been reported for other drugs metabolized by the CYP450 family of enzymes.¹⁶⁰

Although hypothermia has been shown to alter the clearance of drugs metabolized by the CYP450 family of enzymes, there are fewer data on the impact of hypothermia on toxicity. Pending further research it is important for ICU practitioners to recognize drugs that are metabolized by the liver and to monitor drug levels when possible and other markers of drug efficacy (i.e., sedation scores).

1. Shargel, L, Yu, A. Applied Biopharmaceutics and Pharmacokinetics, 4th ed. New York: McGraw-Hill; 1999.

2. Kimura, T, Higaki, K. Gastrointestinal transit and drug absorption. Biol Pharm Bull. 2002; 25:149–164.

3. Boucher, HW, Talbot, GH, Bradley, JS, et al. Bad bugs, no drugs: No ESKAPE! An update from the Infectious Diseases Society of America. Clin Infect Dis. 2009; 48:1–12.

4. Craig, WA. Pharmacokinetic/pharmacodynamic parameters: Rationale for antibacterial dosing of mice and men. Clin Infect Dis. 1998; 26:1–10.

5. Drusano, GL. Antimicrobial pharmacodynamics: Critical interactions of “bug and drug. ”. Nat Rev Microbiol. 2004; 2:289–300.

6. Eagle, H, Fleischman, R, Musselman, AD. Effect of schedule of administration on the therapeutic efficacy of penicillin; importance of the aggregate time penicillin remains at effectively bactericidal levels. Am J Med. 1950; 9:280–299.

7. Lipman, J, Wallis, SC, Rickard, C. Low plasma cefepime levels in critically ill septic patients: Pharmacokinetic modeling indicates improved troughs with revised dosing. Antimicrob Agents Chemother. 1999; 43:2559–2561.

8. Taccone, FS, Laterre, PF, Dugernier, T, et al. Insufficient beta-lactam concentrations in the early phase of severe sepsis and septic shock. Crit Care. 2010; 14:R126.

9. Vogelman, B, Gudmundsson, S, Leggett, J, et al. Correlation of antimicrobial pharmacokinetic parameters with therapeutic efficacy in an animal model. J Infect Dis. 1988; 158:831–847.

10. Bhat, SV, Peleg, AY, Lodise, TP, Jr., et al. Failure of current cefepime breakpoints to predict clinical outcomes of bacteremia caused by gram-negative organisms. Antimicrob Agents Chemother. 2007; 51:4390–4395.

11. Tam, VH, McKinnon, PS, Akins, RL, et al. Pharmacodynamics of cefepime in patients with gram-negative infections. J Antimicrob Chemother. 2002; 50:425–428.

12. Tam, VH, Gamez, EA, Weston, JS, et al. Outcomes of bacteremia due to Pseudomonas aeruginosa with reduced susceptibility to piperacillin-tazobactam: Implications on the appropriateness of the resistance breakpoint. Clin Infect Dis. 2008; 46:862–867.

13. Dandekar, PK, Maglio, D, Sutherland, CA, et al. Pharmacokinetics of meropenem 0. 5 and 2 g every 8 hours as a 3-hour infusion. Pharmacotherapy. 2003; 23:988–991.

14. Kim, A, Sutherland, CA, Kuti, JL, Nicolau, DP. Optimal dosing of piperacillin-tazobactam for the treatment of Pseudomonas aeruginosa infections: Prolonged or continuous infusion? Pharmacotherapy. 2007; 27:1490–1497.

15. Lipsitch, M, Levin, BR. The population dynamics of antimicrobial chemotherapy. Antimicrob Agents Chemother. 1997; 41:363–373.

16. Mouton, JW, den Hollander, JG. Killing of Pseudomonas aeruginosa during continuous and intermittent infusion of ceftazidime in an in vitro pharmacokinetic model. Antimicrob Agents Chemother. 1994; 38:931–936.

17. Boselli, E, Breilh, D, Rimmele, T, et al. Alveolar concentrations of piperacillin/tazobactam administered in continuous infusion to patients with ventilator-associated pneumonia. Crit Care Med. 2008; 36:1500–1506.

18. Tamma, PD, Putcha, N, Suh, YD, et al. Does prolonged beta-lactam infusion improve clinical outcomes compared to intermittent infusions? A meta-analysis and systematic review of randomized, controlled trials. BMC Infect Dis. 2011; 11:181.

19. Nicasio, AM, Ariano, RE, Zelenitsky, SA, et al. Population pharmacokinetics of high-dose, prolonged-infusion cefepime in adult critically ill patients with ventilator-associated pneumonia. Antimicrob Agents Chemother. 2009; 53:1476–1481.

20. Moore, RD, Lietman, PS, Smith, CR. Clinical response to aminoglycoside therapy: Importance of the ratio of peak concentration to minimal inhibitory concentration. J Infect Dis. 1987; 155:93–99.

21. Kashuba, AD, Nafziger, AN, Drusano, GL, Bertino, JS, Jr. Optimizing aminoglycoside therapy for nosocomial pneumonia caused by gram-negative bacteria. Antimicrob Agents Chemother. 1999; 43:623–629.

22. Vogelman, B, Gudmundsson, S, Turnidge, J, et al. In vivo postantibiotic effect in a thigh infection in neutropenic mice. J Infect Dis. 1988; 157:287–298.

23. Skiada, A, Markogiannakis, A, Plachouras, D, Daikos, GL. Adaptive resistance to cationic compounds in Pseudomonas aeruginosa. Int J Antimicrob Agents. 2011; 37:187–193.

24. Chuck, SK, Raber, SR, Rodvold, KA, Areff, D. National survey of extended-interval aminoglycoside dosing. Clin Infect Dis. 2000; 30:433–439.

25. Nicolau, DP, Freeman, CD, Belliveau, PP, et al. Experience with a once-daily aminoglycoside program administered to 2,184 adult patients. Antimicrob Agents Chemother. 1995; 39:650–655.

26. Hatala, R, Dinh, T, Cook, DJ. Once-daily aminoglycoside dosing in immunocompetent adults: A meta-analysis. Ann Intern Med. 1996; 124:717–725.

27. Giuliano, RA, Verpooten, GA, Verbist, L, et al. In vivo uptake kinetics of aminoglycosides in the kidney cortex of rats. J Pharmacol Exp Ther. 1986; 236:470–475.

28. De Broe, ME, Verbist, L, Verpooten, GA. Influence of dosage schedule on renal cortical accumulation of amikacin and tobramycin in man. J Antimicrob Chemother. 1991; 27(Suppl C):41–47.

29. Drusano, GL, Ambrose, PG, Bhavnani, SM, et al. Back to the future: Using aminoglycosides again and how to dose them optimally. Clin Infect Dis. 2007; 45:753–760.

30. Paterson, DL, Robson, JM, Wagener, MM. Risk factors for toxicity in elderly patients given aminoglycosides once daily. J Gen Intern Med. 1998; 13:735–739.

31. Vincent, JL, Rello, J, Marshall, J, et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA. 2009; 302:2323–2329.

32. Kim, SH, Kim, KH, Kim, HB, et al. Outcome of vancomycin treatment in patients with methicillin-susceptible Staphylococcus aureus bacteremia. Antimicrob Agents Chemother. 2008; 52:192–197.

33. Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing, Sixteenth International Supplement. Standard M100-MS16. Wayne, PA: Clinical and Laboratory Standards Institute; 2006.

34. van Hal, SJ, Lodise, TP, Paterson, DL. The clinical significance of vancomycin minimum inhibitory concentration in Staphylococcus aureus infections: A systematic review and meta-analysis. Clin Infect Dis. 2012; 54:755–771.

35. Larsson, AJ, Walker, KJ, Raddatz, JK, Rotschafer, JC. The concentration-independent effect of monoexponential and biexponential decay in vancomycin concentrations on the killing of Staphylococcus aureus under aerobic and anaerobic conditions. J Antimicrob Chemother. 1996; 38:589–597.

36. Moise-Broder, PA, Forrest, A, Birmingham, MC, Schentag, JJ. Pharmacodynamics of vancomycin and other antimicrobials in patients with Staphylococcus aureus lower respiratory tract infections. Clin Pharmacokinet. 2004; 43:925–942.

37. Rybak, M, Lomaestro, B, Rotschafer, JC, 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, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2009; 66:82–98.

38. Mohr, JF, Murray, BE. Point: Vancomycin is not obsolete for the treatment of infection caused by methicillin-resistant Staphylococcus aureus. Clin Infect Dis. 2007; 44:1536–1542.

39. Steinkraus, G, White, R, Friedrich, L. Vancomycin MIC creep in non-vancomycin-intermediate Staphylococcus aureus (VISA), vancomycin-susceptible clinical methicillin-resistant S. aureus (MRSA) blood isolates from 2001-2005. J Antimicrob Chemother. 2007; 60:788–794.

40. Lodise, TP, Patel, N, Lomaestro, BM, et al. Relationship between initial vancomycin concentration-time profile and nephrotoxicity among hospitalized patients. Clin Infect Dis. 2009; 49:507–514.

41. Wunderink, RG, Niederman, MS, Kollef, MH, et al. Linezolid in methicillin-resistant Staphylococcus aureus nosocomial pneumonia: A randomized, controlled study. Clin Infect Dis. 2012; 54:621–629.

42. Ingram, PR, Lye, DC, Fisher, DA, et al. Nephrotoxicity of continuous versus intermittent infusion of vancomycin in outpatient parenteral antimicrobial therapy. Int J Antimicrob Agents. 2009; 34:570–574.

43. Wysocki, M, Delatour, F, Faurisson, F, et al. Continuous versus intermittent infusion of vancomycin in severe Staphylococcal infections: Prospective multicenter randomized study. Antimicrob Agents Chemother. 2001; 45:2460–2467.

44. Keel, RA, Sutherland, CA, Aslanzadeh, J, et al. Correlation between vancomycin and daptomycin MIC values for methicillin-susceptible and methicillin-resistant Staphylococcus aureus by 3 testing methodologies. Diagn Microbiol Infect Dis. 2010; 68:326–329.

45. Kohl, BA, Deutschman, CS. The inflammatory response to surgery and trauma. Curr Opin Crit Care. 2006; 12:325–332.

46. Di Giantomasso, D, May, CN, Bellomo, R. Vital organ blood flow during hyperdynamic sepsis. Chest. 2003; 124:1053–1059.

47. Udy, AA, Roberts, JA, Boots, RJ, et al. Augmented renal clearance: Implications for antibacterial dosing in the critically ill. Clin Pharmacokinet. 2010; 49:1–16.

48. Patanwala, AE, Norris, CJ, Nix, DE, et al. Vancomycin dosing for pneumonia in critically ill trauma patients. J Trauma. 2009; 67:802–804.

49. Rivers, E, Nguyen, B, Havstad, S, et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001; 345:1368–1377.

50. Brandstrup, B, Tonnesen, H, Beier-Holgersen, R, et al. Effects of intravenous fluid restriction on postoperative complications: Comparison of two perioperative fluid regimens: A randomized assessor-blinded multicenter trial. Ann Surg. 2003; 238:641–648.

51. Wiedemann, HP, Wheeler, AP, Bernard, GR, et al. Comparison of two fluid-management strategies in acute lung injury. N Engl J Med. 2006; 354:2564–2575.

52. Burton, ME, Shaw, LM, Schentag, JJ, Evans, WE. Applied Pharmacokinetics and Pharmacodynamics, 4th ed. Philadelphia: Lippincott Williams & Wilkins; 2006.

53. Dasta, JF, Armstrong, DK. Variability in aminoglycoside pharmacokinetics in critically ill surgical patients. Crit Care Med. 1988; 16:327–330.

54. Rea, RS, Capitano, B, Bies, R, et al. Suboptimal aminoglycoside dosing in critically ill patients. Ther Drug Monit. 2008; 30:674–681.

55. Tillement, JP, Lhoste, F, Giudicelli, JF. Diseases and drug protein binding. Clin Pharmacokinet. 1978; 3:144–154.

56. Israili, ZH, Dayton, PG. Human alpha-1-glycoprotein and its interactions with drugs. Drug Metab Rev. 2001; 33:161–235.

57. Benet, LZ, Hoener, BA. Changes in plasma protein binding have little clinical relevance. Clin Pharmacol Ther. 2002; 71:115–121.

58. de Winter, BC, van Gelder, T, Sombogaard, F, et al. Pharmacokinetic role of protein binding of mycophenolic acid and its glucuronide metabolite in renal transplant recipients. J Pharmacokinet Pharmacodynamics. 2009; 36:541–564.

59. Ulldemolins, M, Roberts, JA, Rello, J, et al. The effects of hypoalbuminaemia on optimizing antibacterial dosing in critically ill patients. Clin Pharmacokinet. 2011; 50:99–110.

60. Mutlu, GM, Mutlu, EA, Factor, P. GI complications in patients receiving mechanical ventilation. Chest. 2001; 119:1222–1241.

61. Ceppa, EP, Fuh, KC, Bulkley, GB. Mesenteric hemodynamic response to circulatory shock. Curr Opin Crit Care. 2003; 9:127–132.

62. Lautt, WW. Mechanism and role of intrinsic regulation of hepatic arterial blood flow: Hepatic arterial buffer response. Am J Physiol. 1985; 249:G549–G556.

63. Nguyen, NQ, Ng, MP, Chapman, M, et al. The impact of admission diagnosis on gastric emptying in critically ill patients. Crit Care. 2007; 11:R16.

64. Ritz, MA, Fraser, R, Edwards, N, et al. Delayed gastric emptying in ventilated critically ill patients: Measurement by 13 C-octanoic acid breath test. Crit Care Med. 2001; 29:1744–1749.

65. Heyland, DK, Tougas, G, King, D, Cook, DJ. Impaired gastric emptying in mechanically ventilated, critically ill patients. Intensive Care Med. 1996; 22:1339–1344.

66. Buijk, SL, Gyssens, IC, Mouton, JW, et al. Pharmacokinetics of sequential intravenous and enteral fluconazole in critically ill surgical patients with invasive mycoses and compromised gastrointestinal function. Intensive Care Med. 2001; 27:115–121.

67. de Marie, S, VandenBergh, MF, Buijk, SL, et al. Bioavailability of ciprofloxacin after multiple enteral and intravenous doses in ICU patients with severe gram-negative intra-abdominal infections. Intensive Care Med. 1998; 24:343–346.

68. Kanji, S, McKinnon, PS, Barletta, JF, et al. Bioavailability of gatifloxacin by gastric tube administration with and without concomitant enteral feeding in critically ill patients. Crit Care Med. 2003; 31:1347–1352.

69. Dorffler-Melly, J, de Jonge, E, Pont, AC, et al. Bioavailability of subcutaneous low-molecular-weight heparin to patients on vasopressors. Lancet. 2002; 359:849–850.

70. Jochberger, S, Mayr, V, Luckner, G, et al. Antifactor Xa activity in critically ill patients receiving antithrombotic prophylaxis with standard dosages of certoparin: A prospective, clinical study. Crit Care. 2005; 9:R541–548.

71. Bara, L, Planes, A, Samama, MM. Occurrence of thrombosis and haemorrhage, relationship with anti-Xa, anti-IIa activities, and D-dimer plasma levels in patients receiving a low molecular weight heparin, enoxaparin or tinzaparin, to prevent deep vein thrombosis after hip surgery. Br J Haematol. 1999; 104:230–240.

72. Levine, MN, Planes, A, Hirsh, J, et al. The relationship between anti-factor Xa level and clinical outcome in patients receiving enoxaparine low molecular weight heparin to prevent deep vein thrombosis after hip replacement. Thromb Haemost. 1989; 62:940–944.

73. Cheng, SS, Nordenholz, K, Matero, D, et al. Standard subcutaneous dosing of unfractionated heparin for venous thromboembolism prophylaxis in surgical ICU patients leads to subtherapeutic factor Xa inhibition. Intensive Care Med. 2012; 38:642–648.

74. Robinson, S, Zincuk, A, Strom, T, et al. Enoxaparin, effective dosage for intensive care patients: Double-blinded, randomised clinical trial. Crit Care. 2010; 14:R41.

75. Hoste, EA, Schurgers, M. Epidemiology of acute kidney injury: How big is the problem? Crit Care Med. 2008; 36:S146–S151.

76. Dowling, TC. Quantification of renal function. In Dipiro J, Talbert R, Yee G, et al, eds. : Pharmacotherapy: A Pathophysiologic Approach, 8th ed, New York: McGraw-Hill, 2011.

77. Cherry, RA, Eachempati, SR, Hydo, L, Barie, PS. Accuracy of short-duration creatinine clearance determinations in predicting 24-hour creatinine clearance in critically ill and injured patients. J Trauma. 2002; 53:267–271.

78. Herrera-Gutierrez, ME, Seller-Perez, G, Banderas-Bravo, E, et al. Replacement of 24-hour creatinine clearance by 2-hour creatinine clearance in intensive care unit patients: A single-center study. Intensive Care Med. 2007; 33:1900–1906.

79. Robert, S, Zarowitz, BJ, Peterson, EL, Dumler, F. Predictability of creatinine clearance estimates in critically ill patients. Crit Care Med. 1993; 21:1487–1495.

80. Cockcroft, DW, Gault, MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976; 16:31–41.

81. Levey, AS, Coresh, J, Greene, T, et al. Expressing the Modification of Diet in Renal Disease Study equation for estimating glomerular filtration rate with standardized serum creatinine values. Clin Chem. 2007; 53:766–772.

82. Nyman, HA, Dowling, TC, Hudson, JQ, et al. Comparative evaluation of the Cockcroft-Gault equation and the Modification of Diet in Renal Disease (MDRD) study equation for drug dosing: An opinion of the Nephrology Practice and Research Network of the American College of Clinical Pharmacy. Pharmacotherapy. 2011; 31:1130–1144.

83. National Kidney Disease Education Program (NKDEP), Chronic Kidney Disease and Drug Dosing: Information for Providers. National Institute of Diabetes and Digestive and Kidney Diseases, Washington, DC, 2010. http://www.nkdep.nih.gov/professionals/drug-dosing-information.htm

84. Stevens, LA, Coresh, J, Feldman, HI, et al. Evaluation of the modification of diet in renal disease study equation in a large diverse population. J Am Soc Nephrol. 2007; 18:2749–2757.

85. Cirillo, M, Anastasio, P, De Santo, NG. Relationship of gender, age, and body mass index to errors in predicted kidney function. Nephrol Dial Transplant. 2005; 20:1791–1798.

86. Verhave, JC, Fesler, P, Ribstein, J, et al. Estimation of renal function in subjects with normal serum creatinine levels: Influence of age and body mass index. Am J Kidney Dis. 2005; 46:233–241.

87. Pai, MP, Park, EJ, Dong, T, et al. The influence of body size descriptors on the estimation of kidney function in normal weight, overweight, obese, and morbidly obese adults. Ann Pharmacother. 2012; 46:317–328.

88. Joy, MS, Matzke, GR, Armstrong, DK, et al. A primer on continuous renal replacement therapy for critically ill patients. Ann Pharmacother. 1998; 32:362–375.

89. Awdishu, L, Bouchard, J. How to optimize drug delivery in renal replacement therapy. Semin Dial. 2011; 24:176–182.

90. Heintz, BH, Matzke, GR, Dager, WE. Antimicrobial dosing concepts and recommendations for critically ill adult patients receiving continuous renal replacement therapy or intermittent hemodialysis. Pharmacotherapy. 2009; 29:562–577.

91. Trotman, RL, Williamson, JC, Shoemaker, DM, Salzer, WL. Antibiotic dosing in critically ill adult patients receiving continuous renal replacement therapy. Clin Infect Dis. 2005; 41:1159–1166.

92. Uchino, S, Fealy, N, Baldwin, I, et al. Continuous is not continuous: The incidence and impact of circuit “down-time” on uraemic control during continuous veno-venous haemofiltration. Intensive Care Med. 2003; 29:575–578.

93. Mehta, RL, McDonald, B, Gabbai, FB, et al. A randomized clinical trial of continuous versus intermittent dialysis for acute renal failure. Kidney Int. 2001; 60:1154–1163.

94. Verbeeck, RK. Pharmacokinetics and dosage adjustment in patients with hepatic dysfunction. Eur J Clin Pharmacol. 2008; 64:1147–1161.

95. Guengerich, FP. Cytochrome P450 and chemical toxicology. Chem Res Toxicol. 2008; 21:70–83.

96. Morgan, DJ, McLean, AJ. Therapeutic implications of impaired hepatic oxygen diffusion in chronic liver disease. Hepatology. 1991; 14:1280–1282.

97. Pugh, RN, Murray-Lyon, IM, Dawson, JL, et al. Transection of the oesophagus for bleeding oesophageal varices. Br J Surg. 1973; 60:646–649.

98. Food and Drug Administration. Guidance for industry: Pharmacokinetics in patients with impaired hepatic function: Study design, data analysis, and impact on dosing and labeling. Rockville, MD: Food and Drug Administration; 2003.

99. Sokol, SI, Cheng, A, Frishman, WH, Kaza, CS. Cardiovascular drug therapy in patients with hepatic diseases and patients with congestive heart failure. J Clin Pharmacol. 2000; 40:11–30.

100. Klotz, U. Antiarrhythmics: Elimination and dosage considerations in hepatic impairment. Clin Pharmacokinet. 2007; 46:985–996.

101. Davis, M. Cholestasis and endogenous opioids: Liver disease and exogenous opioid pharmacokinetics. Clin Pharmacokinet. 2007; 46:825–850.

102. McCabe, SM, Ma, Q, Slish, JC, et al. Antiretroviral therapy: Pharmacokinetic considerations in patients with renal or hepatic impairment. Clin Pharmacokinet. 2008; 47:153–172.

103. Ogden, CL, Yanovski, SZ, Carroll, MD, Flegal, KM. The epidemiology of obesity. Gastroenterology. 2007; 132:2087–2102.

104. Martino, JL, Stapleton, RD, Wang, M, et al. Extreme obesity and outcomes in critically ill patients. Chest. 2011; 140:1198–1206.

105. Pieracci, FM, Barie, PS, Pomp, A. Critical care of the bariatric patient. Crit Care Med. 2006; 34:1796–1804.

106. Han, PY, Duffull, SB, Kirkpatrick, CM, Green, B. Dosing in obesity: A simple solution to a big problem. Clin Pharmacol Ther. 2007; 82:505–508.

107. Hanley, MJ, Abernethy, DR, Greenblatt, DJ. Effect of obesity on the pharmacokinetics of drugs in humans. Clin Pharmacokinet. 2010; 49:71–87.

108. Devine, BJ. Case number 25: Gentamicin therapy. Drug Intell Clin Pharm. 1974; 8:650–655.

109. James, WP. Research on Obesity. London: Her Majesty’s Stationery Office; 1976.

110. Mosteller, RD. Simplified calculation of body-surface area. N Engl J Med. 1987; 317:1098.

111. Pai, MP, Paloucek, FP. The origin of the “ideal” body weight equations. Ann Pharmacother. 2000; 34:1066–1069.

112. Zovirax IV injection, acyclovir sodium IV injections [package insert]. Research Triangle Park, NC: GlaxoSmithKline, 2003.

113. Refludan [package insert]. Montville, NJ: Berlex, 2004.

114. Argatroban IV [package insert]. Research Triangle Park, NC: GlaxoSmithKline, 2009.

115. Angiomax [package insert]. Parsippany, NJ: The Medicines Company, 2010.

116. Alteplase [package insert]. South San Francisco, CA: Genetech, Inc., 2011.

117. Abernethy, DR, Greenblatt, DJ. Phenytoin disposition in obesity. Determination of loading dose. Arch Neurol. 1985; 42:468–471.

118. Gould, MK, Garcia, DA, Wren, SM, et al. Prevention of VTE in nonorthopedic surgical patients: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed. American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012; 141:e227S–277S.

119. Greenblatt, DJ, Abernethy, DR, Locniskar, A, et al. Effect of age, gender, and obesity on midazolam kinetics. Anesthesiology. 1984; 61:27–35.

120. Lemmens, HJ, Brodsky, JB. The dose of succinylcholine in morbid obesity. Anesth Analg. 2006; 102:438–442.

121. Nutescu, EA, Spinler, SA, Wittkowsky, A, Dager, WE. Low-molecular-weight heparins in renal impairment and obesity: Available evidence and clinical practice recommendations across medical and surgical settings. Ann Pharmacother. 2009; 43:1064–1083.

122. Pai, MP, Bearden, DT. Antimicrobial dosing considerations in obese adult patients. Pharmacotherapy. 2007; 27:1081–1091.

123. Patel, JP, Roberts, LN, Arya, R. Anticoagulating obese patients in the modern era. Br J Haematol. 2011; 155:137–149.

124. Servin, F, Farinotti, R, Haberer, JP, Desmonts, JM. Propofol infusion for maintenance of anesthesia in morbidly obese patients receiving nitrous oxide. A clinical and pharmacokinetic study. Anesthesiology. 1993; 78:657–665.

125. Precedex Dosing Guidelines. Available at http://www.precedex.com/wp-content/uploads/2011/06/dosing_card.pdf. [Accessed April 5, 2012].

126. Wurtz, R, Itokazu, G, Rodvold, K. Antimicrobial dosing in obese patients. Clin Infect Dis. 1997; 25:112–118.

127. Hernandez, JO, Norstrom, J, Wysock, G. Acyclovir-induced renal failure in an obese patient. Am J Health Syst Pharm. 2009; 66:1288–1291.

128. Garonzik, SM, Li, J, Thamlikitkul, V, et al. Population pharmacokinetics of colistin methanesulfonate and formed colistin in critically ill patients from a multicenter study provide dosing suggestions for various categories of patients. Antimicrob Agents Chemother. 2011; 55:3284–3294.

129. Pai, MP, Norenberg, JP, Anderson, T, et al. Influence of morbid obesity on the single-dose pharmacokinetics of daptomycin. Antimicrob Agents Chemother. 2007; 51:2741–2747.

130. Cheymol, G. Effects of obesity on pharmacokinetics implications for drug therapy. Clin Pharmacokinet. 2000; 39:215–231.

131. Cortinez, LI, Anderson, BJ, Penna, A, et al. Influence of obesity on propofol pharmacokinetics: Derivation of a pharmacokinetic model. Br J Anaesth. 2010; 105:448–456.

132. Corbett, SM, Montoya, ID, Moore, FA. Propofol-related infusion syndrome in intensive care patients. Pharmacotherapy. 2008; 28:250–258.

133. Raschke, RA, Reilly, BM, Guidry, JR, et al. The weight-based heparin dosing nomogram compared with a “standard care” nomogram. A randomized controlled trial. Ann Intern Med. 1993; 119:874–881.

134. Barletta, JF, DeYoung, JL, McAllen, K, et al. Limitations of a standardized weight-based nomogram for heparin dosing in patients with morbid obesity. Surgery for obesity and related diseases. Off J Am Soc Bariatr Surg. 2008; 4:748–753.

135. Yee, WP, Norton, LL. Optimal weight base for a weight-based heparin dosing protocol. Am J Health Syst Pharm. 1998; 55:159–162.

136. Spinler, SA, Inverso, SM, Cohen, M, et al. Safety and efficacy of unfractionated heparin versus enoxaparin in patients who are obese and patients with severe renal impairment: Analysis from the ESSENCE and TIMI 11B studies. Am Heart J. 2003; 146:33–41.

137. Barba, R, Marco, J, Martin-Alvarez, H, et al. The influence of extreme body weight on clinical outcome of patients with venous thromboembolism: Findings from a prospective registry (RIETE). J Thromb Haemost. 2005; 3:856–862.

138. Myzienski, AE, Lutz, MF, Smythe, MA. Unfractionated heparin dosing for venous thromboembolism in morbidly obese patients: Case report and review of the literature. Pharmacotherapy. 2010; 30:324.

139. Wilson, SJ, Wilbur, K, Burton, E, Anderson, DR. Effect of patient weight on the anticoagulant response to adjusted therapeutic dosage of low-molecular-weight heparin for the treatment of venous thromboembolism. Haemostasis. 2001; 31:42–48.

140. Medico, CJ, Walsh, P. Pharmacotherapy in the critically ill obese patient. Crit Care Clin. 2010; 26:679–688.

141. Administration on Aging. Aging into the 21st century. Available at http://www.aoa.gov/AoARoot/Aging_Statistics/future_growth/aging21/health.aspx. [Accessed 3/30/2012].

142. Klotz, U. Pharmacokinetics and drug metabolism in the elderly. Drug Metab Rev. 2009; 41:67–76.

143. American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American Geriatrics Society Updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2012; 60(4):616–631.

144. Hill, CC, Pickinpaugh, J. Physiologic changes in pregnancy. Surg Clin North Am. 2008; 88:391–401.

145. Joglar, JA, Page, RL. Treatment of cardiac arrhythmias during pregnancy: Safety considerations. Drug Saf. 1999; 20:85–94.

146. Ko, R, Mazur, JE, Pastis, NJ, et al. Common problems in critically ill obstetric patients, with an emphasis on pharmacotherapy. Am J Med Sci. 2008; 335:65–70.

147. Anderson, GD. Pregnancy-induced changes in pharmacokinetics: A mechanistic-based approach. Clin Pharmacokinet. 2005; 44:989–1008.

148. Jentink, J, Loane, MA, Dolk, H, et al. Valproic acid monotherapy in pregnancy and major congenital malformations. N Engl J Med. 2010; 362:2185–2193.

149. ACOG Committee Opinion No. 514. Emergent therapy for acute-onset, severe hypertension with preeclampsia or eclampsia. Obstet Gynecol. 2011; 118:1465–1468.

150. ACOG Committee Opinion No. 494. Sulfonamides, nitrofurantoin, and risk of birth defects. Obstet Gynecol. 2011; 117:1484–1485.

151. Bates, SM, Greer, IA, Middeldorp, S, et al. VTE, thrombophilia, antithrombotic therapy, and pregnancy: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed. American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012; 141:e691S–736S.

152. Crider, KS, Cleves, MA, Reefhuis, J, et al. Antibacterial medication use during pregnancy and risk of birth defects: National Birth Defects Prevention Study. Arch Pediatr Adolesc Med. 2009; 163:978–985.

153. Briggs, GG, Freeman, RK, Yaffe, SJ. Drugs in Pregnancy and Lactation, 9th ed. Philadelphia: Lippincott Williams & Wilkins; 2011.

154. Blanchet, B, Jullien, V, Vinsonneau, C, Tod, M. Influence of burns on pharmacokinetics and pharmacodynamics of drugs used in the care of burn patients. Clin Pharmacokinet. 2008; 47:635–654.

155. Marion, D, Bullock, MR. Current and future role of therapeutic hypothermia. J Neurotrauma. 2009; 26:455–467.

156. Morrison, LJ, Deakin, CD, Morley, PT, et al. Part 8: Advanced life support: 2010 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science with Treatment Recommendations. Circulation. 2010; 122:S345–S421.

157. van den Broek, MP, Groenendaal, F, Egberts, AC, Rademaker, CM. Effects of hypothermia on pharmacokinetics and pharmacodynamics: A systematic review of preclinical and clinical studies. Clin Pharmacokinet. 2010; 49:277–294.

158. Fukuoka, N, Aibiki, M, Tsukamoto, T, et al. Biphasic concentration change during continuous midazolam administration in brain-injured patients undergoing therapeutic moderate hypothermia. Resuscitation. 2004; 60:225–230.

159. Hostler, D, Zhou, J, Tortorici, MA, et al. Mild hypothermia alters midazolam pharmacokinetics in normal healthy volunteers. Drug metabolism and disposition: The biological fate of chemicals. Drug Metab Dispos. 2010; 38:781–788.

160. Tortorici, MA, Kochanek, PM, Poloyac, SM. Effects of hypothermia on drug disposition, metabolism, and response: A focus of hypothermia-mediated alterations on the cytochrome P450 enzyme system. Crit Care Med. 2007; 35:2196–2204.

161. Kalow, W, Gunn, DR. The relation between dose of succinylcholine and duration of apnea in man. J Pharmacol Exp Ther. 1957; 120:203–214.

162. Meyer, UA. Pharmacogenetics—Five decades of therapeutic lessons from genetic diversity. Nat Rev Genet. 2004; 5:669–676.

163. Empey, PE. Genetic predisposition to adverse drug reactions in the intensive care unit. Crit Care Med. 2010; 38:S106–S116.

164. Levine, GN, Bates, ER, Blankenship, JC, et al. 2011 ACCF/AHA/SCAI Guideline for Percutaneous Coronary Intervention. A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines and the Society for Cardiovascular Angiography and Interventions. J Am Coll Cardiol. 2011; 58:e44–122.

165. Holbrook, A, Schulman, S, Witt, DM, et al. Evidence-based management of anticoagulant therapy: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed. American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012; 141:e152S–184S.

166. Spector, R, Park, GD, Johnson, GF, Vesell, ES. Therapeutic drug monitoring. Clin Pharmacol Ther. 1988; 43:345–353.