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Ann Thorac Surg 2002;74:1589-1595
© 2002 The Society of Thoracic Surgeons

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Original article: cardiovascular

Rapid disappearance of protamine in adults undergoing cardiac operation with cardiopulmonary bypass

^a Department of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
^b Department of Cardiothoracic Surgery, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA

Accepted for publication July 11, 2002.

* Address reprint requests to Dr Butterworth, Department of Anesthesiology, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157-1009, USA.
e-mail: jbutter{at}wfubmc.edu

	Abstract

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BACKGROUND: Despite long use of protamine in cardiac operations, neither protamine concentrations nor pharmacokinetics have been reported in patients.

METHODS: Twenty-eight patients (age, 26 to 80 years) undergoing various cardiac surgical procedures gave their consent to receive 250 mg of protamine sulfate administered intravenously by an infusion pump during 5 minutes. Protamine was administered at the usual intraoperative time after separation from cardiopulmonary bypass for reversal of heparin. Timed arterial blood samples were obtained after protamine infusion. Blood plasma was subjected to solid-phase extraction and high-performance liquid chromatography. Total (free + heparin-bound) protamine concentration versus time data were subjected to pharmacokinetic modeling.

RESULTS: Twenty-six patients completed the study. Total plasma protamine concentrations declined rapidly. Model-independent pharmacokinetic analysis revealed median (range) values as follows: volume of distribution, 5.4 L (0.82 to 34 L); clearance, 1.4 L/min (0.61 to 3.8 L/min); and half-life, 4.5 min (1.9 to 18 min). Schwarz-Bayesian criterion identified a two-compartment exponential model with adjustment for weight in the central compartment volume of distribution as performing better than other compartmental or Michaelis-Menten models.

CONCLUSIONS: Protamine has a very short (approximately 5 minutes) half-life after a single 250-mg dose in adult patients. This short half-life could underlie recurrent anticoagulation after initial apparent reversal of heparin.

	Introduction

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Protamine has been used for decades to delay the absorption of insulin and to reverse heparin-induced anticoagulation. However, pharmacokinetic variables have not been reported for protamine in any of the common circumstances in which it is prescribed. Indeed, blood concentrations of protamine have only recently been measured in volunteers, but never in patients [1].

After heparin, rapid administration of protamine may cause marked systemic arterial hypotension or pulmonary hypertension [2]. Adverse drug reactions after protamine are common and typically are underreported [3]. Incomplete or nonpersistent reversal of heparin can lead to hemorrhage, transfusion of blood products, and a wide variety of complications. On the other hand, excess concentrations of protamine have been linked to a long list of adverse effects in vitro, including inhibition of platelet glycoprotein Ib-von Willebrand factor, increased P-selectin expression, block of the calcium release channel (ryanodine receptor type-1), and negative inotropic effects [4–6]. With these myriad drug-related adverse events in mind, we undertook these studies to obtain a more complete understanding of protamine pharmacokinetics. Our hope is that pharmacokinetically guided protamine dosing will increase the likelihood of successful heparin reversal and will reduce the possibility of exposing patients to excessively high blood protamine concentrations.

We recently reported protamine concentrations and pharmacokinetics in normal volunteers who had not received heparin [1], finding model-independent protamine half-lifes of less than 10 minutes. Our volunteer data prompted us to hypothesize that the rapid (<10 minutes of infusion) protamine dosing technique used commonly during cardiac operations would fail to sustain protamine concentrations for more than 20 minutes. Rapid protamine elimination could lead to recurrent anticoagulation if heparinized blood remaining in the pump oxygenator were later infused for volume replacement. To test our hypothesis, we used our recently described assay to measure total (free + heparin-bound) protamine blood concentrations in adult patients undergoing cardiac operation. We used the total protamine blood concentration data to define the pharmacokinetic variables describing protamine elimination from arterial plasma.

	Material and methods

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Our study protocol was reviewed and approved by our institutional review board. Each subject gave his or her written informed consent to participate in our study. Twenty-eight consenting patients undergoing cardiac operation were studied. Exclusion criteria included previous protamine allergy, vasectomy, or pregnancy; however, no subjects were encountered with any of these findings.

All patients had radial artery catheters inserted percutaneously, which were used to obtain blood samples. Patients were anticoagulated with beef lung heparin, 300 U/kg (the administered dose ranged from 20,000 to 30,000 U) for cardiopulmonary bypass (CPB), with a target activated coagulation time of more than 400 seconds.

After separation from CPB and stable hemodynamic measurements had been obtained (<10% variation between two mean arterial pressures), patients received 250 mg of protamine (Fujisawa USA, Inc., Deerfield, IL) during 5 minutes using a syringe pump (model AS40A; Baxter Healthcare Systems, Deerfield, IL). Protamine was infused through a dedicated intravenous catheter in the right or left internal jugular vein. Prior sham experiments in which the same dose of protamine was delivered (by our infusion pump and tubing) during 1, 3, 5, 8, or 10 minutes into a beaker showed less than 5% variation in total protamine recovery, confirming good pump performance and, at most, limited binding of protamine to the infusion tubing. Blood samples were obtained at baseline and at 5, 7, 10, 13, and in a few instances at 20 and 25 minutes. Sample collection began 15 seconds before the defined sample time and was completed by 10 to 15 seconds after the defined sample time. These samples were collected in vacuum tubes containing ethylenediamine tetraacetic acid and protease inhibitors. All collected samples were immediately cooled to 5°C in a container of ice water slush. Arterial blood was separated from cellular elements by centrifugation. Protease inhibitors (Boehringer Mannheim, Indianapolis, IN) were added to all blood samples. Plasma samples were frozen pending analysis in batches. Pilot experiments confirmed that measured protamine remained constant with freezing and thawing and analysis after storage as long as 105 days.

High-performance liquid chromatography
Our methodology has been described previously in detail, so we will only summarize it here [1]. Protamine was dissociated from heparin using 2 N NaOH. Pilot experiments confirmed that heparin bound free protamine in a dose-dependent manner. In the presence of heparin at 4.5 U/mL, free protamine could not be detected until the total concentration exceeded 40 mg/L. In the presence of heparin at 10 U/mL, free protamine could not be detected until the total protamine concentration exceeded 70 mg/L. These data indicate the need to dissociate protamine from heparin to accurately monitor total protamine concentrations. A series of pilot experiments in which varying chemical treatments (including 2 mol/L NaOH, 5 mol/L NH₄OH, 100 mmol/L NH₄OH, 1 mol/L NaCl, 1 mol/L NH₄Cl, and 1 mol/L NH₄Cl + (NH₄)₂SO₄) with spiked plasma samples containing up to 20 U/mL heparin and up to 31.25 mg/L protamine confirmed that 2 mol/L NaOH gave consistently good (>90%) recovery of bound protamine and did not shorten the useful life of the column (as did some other choices). Interestingly, NaCl was nearly as good as NaOH (70% to 90% recovery), but acid treatments were not useful. Plasma samples were centrifuged, then applied to the column.

Total (free + heparin-bound) protamine was extracted from plasma using solid-phase extraction with Varian Bond Elut C18/0H cartridges (Harbor City, CA). A "phase-switching" technique was used. After the column was washed with a mixture of methanol and 20 mmol/L Na₂HPO₄ (70:30 ratio at pH 9.0), protamine was eluted with 1% HClO₄ perchloric acid in acetonitrile. Eluates were evaporated, then reconstituted in acetonitrile before being applied to Zorbax 300SB-C8, 4.6 x 250 mm, 5 µm, 300 columns (Chadds Ford, PA). The high-performance liquid chromatography system consisted of a GPM-2 pump and a variable wavelength detector manufactured by Dionex (Sunnyvale, CA) and a Rheodyne (Cotati, CA) injector. Protamine was monitored at 200 nm. All chemicals were purchased from commercial sources and all were reagent or high-performance liquid chromatography grade. Standard curves were created daily during each analysis run using a lowest value of 1 mg/L.

Statistical methods
Pharmacokinetic variables were determined noncompartmentally using area under the curve methodology. Area under the concentration curve and the concentration-time over time curves were determined using the log-linear trapezoidal rule. Initial infusion segments of the area under the concentration and concentration-time over time curves were estimated using the linear trapezoidal rule [7]. The final area under the concentration curve (AUC) segments (at infinite time) were estimated, assuming the terminal decay to be log-linear, as with conc_final equal to the last recorded concentration and ß equal to the log linear slope. ß was estimated from the terminal portion of the concentration-time curve. The final concentration-time over time curve (AUMC) was likewise calculated using where t_final was the time of the final concentration sample [8].

Concentration versus time data were also fit to conventional compartmental models using the nonlinear mixed effects regression techniques of the NONMEM software package (NONMEM Project Group, University of California, San Francisco, CA) to estimate pharmacokinetic variables (Appendix). We fit both fixed and random model factors by minimizing the maximum likelihood objective function.

All analyses were performed using NONMEM (version V, 1.1) and SAS (version 8.0, SAS Institute, Cary, NC) with less than 0.05 considered significant. Demographic variables were compared between male and female patients using Student’s t test, Wilcoxon rank-sum test, or exact Pearson ², as appropriate. Efficiency of pharmacokinetic models was compared using Schwarz-Bayesian criterion and performance error [9] estimates.

We predicted that we would need at least 20 subjects to determine the form of a two-compartment exponential model. This was an estimate based on our earlier study in volunteers [1] and on our previous experiments in studying pharmacokinetics in patients undergoing cardiac operation [10, 11]. Note that since we were unsure as to the ultimate form that our pharmacokinetic model would take (our volunteer data suggested that a Michaelis-Menten model might be better than an exponential one), our sample size estimate involved more guesswork than a conventional power analysis for a clinical trial.

	Results

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Of 28 patients who consented to participate in our study, 1 patient was excluded when she was placed on extracorporeal membrane oxygenation after CPB and never received protamine. A second patient was excluded from the study owing to a protocol violation. The demographic characteristics and operative procedures of the remaining 26 patients are described in Table 1. These patients were anesthetized with intravenous opioids (22 patients received fentanyl [median dose, 1.5 mg; range, 0.5 to 3.0 mg], 4 patients received sufentanil [median dose, 0.425 mg; range, 0.25 to 0.55 mg]), and midazolam (median dose, 10 mg; range, 2 to 20 mg). Paralysis was achieved using pancuronium in every case. Twenty-one of 26 patients received isoflurane before and after CPB; all patients received isoflurane during CPB. Eighteen of 26 patients received prophylactic -aminocaproic acid. None of these patients received aprotinin.

View larger version (27K): [in this window] [in a new window]   Fig 1. Concentrations of protamine in arterial plasma after administration of 250 mg to 26 patients undergoing cardiac operation with cardiopulmonary bypass. Note the rapid rate of decline in arterial plasma protamine concentrations. Male patients are denoted by black lines and female patients by gray lines.

View larger version (24K): [in this window] [in a new window]   Fig 2. Comparison between the actual data collected and those predicted using our best pharmacokinetic model. The concentration data were predicted assuming that 250 mg of protamine was given during more than 5 minutes to an 80-kg patient. The simulation was carried out for 45 minutes to reflect typical times spent in the operating room after protamine administration. Note that the model predicts that protamine concentrations approach 0 only a short time after its administration.

	Comment

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In a previous study of protamine pharmacokinetics in volunteers, we identified significant differences between men and women, and in that study we obtained poor fits between our data and a variety of exponential models. These previous results in volunteers differ from our results in the present study in several ways. Table 3 compares model-independent and compartmental-model pharmacokinetic variables for the volunteers in our previous study [1] and the patients in our present study. Data from our previous study were adjusted to account for the larger protamine dose used in the present study (250 mg) as compared with the earlier study (0.5 mg/kg). Note that the patients in the current study had a shorter half-life and smaller volume of distribution than did the volunteers in the previous study. We found that in adult patients undergoing cardiac operation with CPB, male patients have a significantly larger volume of distribution than female patients, a sex difference that we did not observe in our previous study. We speculate that these differences between the two studies may be the result of differing ages of the study participants, the presence of cardiovascular disease and other comorbid conditions in our patients but not in the volunteers, effects of arterial sampling in the patients versus venous sampling in the volunteers, or possibly interaction between heparin and protamine. We gave a considerably larger dose of protamine to the patients than to the volunteers. Binding of protamine to heparin likely occurs rapidly and with high affinity and may serve to reduce the ability of protamine to migrate from blood to extracellular fluid, an action that would likely reduce estimates of central compartment volume of distribution. Lingering effects of CPB are also possible. Cardiopulmonary bypass alters elimination kinetics of many drugs, generally by increasing volume of distribution, decreasing elimination rates, or both [11, 13–16]. Finally, there was a greater range of estimates of volume of distribution in the female volunteers than in the female patients.

Surprisingly little is known about heparin pharmacokinetics during and after CPB. It has long been assumed that heparin remains within the bloodstream; however, there is evidence that heparin is taken up by reticuloendothelial and vascular smooth muscle cells, and it redistributes into extracellular fluid (for review see Shore-Lesserson and Gravlee [17]). These sites may create reservoirs of free heparin that can leak back into the bloodstream after protamine has cleared.

As previously noted, the rapid decline in protamine concentrations observed both in the present and previous studies suggests that conventional single-dose regimens might not be the optimal means to maintain reversal of heparin anticoagulation. Our data suggest that in situations in which patients undergo recurring exposure to small amounts of heparin (eg, with transfusion of heparinized blood from the CPB pump-oxygenator or from cell-salvage devices), a maintenance infusion of protamine might serve to ensure that sufficient protamine will be present to prevent reheparinization. Obviously this conjecture awaits experimental confirmation. Rapid protamine elimination also offers an explanation for why small, additional 25-mg to 50-mg protamine doses given to patients usually cause no apparent adverse effects despite the numerous adverse laboratory findings linked to excess protamine concentrations [18, 19].

Our study has several notable limitations. We conducted the study after a single protamine injection, which because of its rapid elimination provided us with only a limited number of concentration measurements with which to create our pharmacokinetic model. In some cases, the plasma protamine concentrations had declined to undetectable values within 20 minutes. Pharmacokinetic events limited to a short time frame can be heavily influenced by intravascular mixing and early tissue distribution processes. All these factors may have limited our ability to identify the best pharmacokinetic model. Future studies could use a maintenance infusion of protamine, allowing us to obtain additional blood samples with measurable protamine concentrations.

Our study was conducted without reference to bleeding or any other efficacy outcome. Thus, we can only speculate about optimal protamine infusion technique for heparin reversal in patients. Our study was conducted in patients undergoing various types of cardiac surgical procedures, and it is possible that patients without cardiac disease may respond differently. Moreover, all our patients were managed with CPB, and patients receiving protamine in other circumstances (eg, vascular surgical procedures or off-pump coronary artery bypass grafting) likely will have differing pharmacokinetic characteristics.

We conclude that protamine has a remarkably short half-life in plasma after single-dose administration for reversal of heparin anticoagulation. Use of our pharmacokinetic model could permit the identification of an optimal protamine dosing technique to produce both a rapid reversal of heparin and a minimal incidence of heparin "rebound" or other adverse events.

	Acknowledgments

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Funded by the Department of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, NC.

	Appendix

 
Pharmacokinetic compartmental models can be described in several ways. The assumption of pharmacokinetic models is that a drug administered intravenously will rapidly distribute within a central compartmental volume (of volume of distribution), shown here as V₁. The drug can leave V₁ either permanently (metabolism, excretion, and so forth) or transiently by diffusion into one or more peripheral compartments. The drug leaks back from the peripheral compartment (V₂) to the central compartment, a process defined by the rate constant k₂₁. These processes can be represented schematically as follows:
The various rate constants (subscripts indicate the compartment of origin and the compartment of destination) are shown.

These processes also can be described mathematically as a series of volumes and clearances, as for a two-compartment model, using V₁, V₂, Cl₁, Cl₂, where Cl₁ and Cl₂ represent clearances from the central or the peripheral compartments, respectively:

Operationally, V₁, k₁₀, k₂₁, and k₁₂ are estimated mathematically using concentration versus time data. Model rate constants, k₁₀, k₁₂, k₂₁, and the central compartment volume of distribution, V₁, were estimated directly by the NONMEM program. In addition to the standard exponential models, one-compartment and two-compartment nonlinear Michaelis-Menten elimination models with and without a parallel compartmental (ie, constant clearance) elimination and a compartmental model with irreversible binding were tested [1].

The standard one-compartment and two-compartment models were fit using NONMEM’s Advan 1 and Advan 3 subroutines. The Michaelis-Menten elimination models were fit to the data using NONMEM’s Advan 10 subroutine. And finally, the two-compartment with irreversible binding models were fit using Advan 6 with user-supplied differential equations as described in this appendix.

The Schwarz-Bayesian criterion (SBC) was used to determine which model best fit the data when good standard errors of the model parameters were obtained. Models with poor parameter estimates (ie, 95% confidence limits that include 0) were not considered for best fit. Models were fit to the data with and without parameter adjustments for sex, weight, and body mass index. Graphs showing model fits were used to confirm whether these choices improved model performance.

	References

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 

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