# Pharmacokinetics of Curative Tranexamic Acid in Parturients Undergoing Cesarean Delivery

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Ethics Approval and Consent to Participate

#### 2.2. Patients and Data Collection

^{®}0.5 g/5 mL, Sanofi-Aventis, Compiègne, France) was administered blindly over 1 min in included patients. The intravenous injection was performed using a strict control of 1 min duration. T1 was defined the time-point of the end of injection. It was suggested that T1 corresponded to the plasma concentration peak of TXA. A rescue second dose of 0.5 g or 1 g was given if hemorrhage became severe (total blood loss >1500 mL). Blood loss volume (mL) was measured using the surgical or cell saver aspiration bag, the under-buttock delivery bag collecting vaginal blood flow during CS, and by weighing drapes and pads.

#### 2.3. Measurements and Data Handling

#### 2.4. Sample Analysis

^{−1}were added to a 50 µL-sample of plasma or diluted urine (1:10). This mixture was centrifuged (4500× g, 4 °C, 10 g). Water/formic acid at a concentration of 0.1% (180 μL) was mixed with 20 µL of the obtained supernatant.

#### 2.5. PK Modeling

_{i,j}, the plasma or urinary concentration in TA estimated for a patient i (i = …) at time j (j = …) as follows:

_{i}represents the vector of an individual PK parameter for subject i, g represents the residual error model, and ε

_{i,j}represents the residual error. As we worked on parametric software, the normality of ε

_{i,j}was assumed. The random variation in the population PK parameters was described by between-subject variability (BSV) for every fixed-effect assuming that parameters were log-normally distributed. The tested base models are displayed in Figure 1.

_{urine}”, and is calculated as follows:

#### 2.6. Noncompartmental Analysis

_{T1}). The integral method was computed using linear log trapezoidal parametrization.

_{T1}, TXA blood concentrations measured at T30 (C

_{T30}), AUC(T1-30), and MRT were computed between the different groups according to the bleeding status at T30.

_{T1}, TXA blood concentrations measured at T60 (C

_{T60}), and AUC(T1-60) were computed between the different groups according to the bleeding status at T60.

#### 2.7. Model Internal Evaluation

#### 2.8. Simulations to Derive Optimal Dosing

## 3. Results

#### 3.1. Recruitment

#### 3.2. Exploratory Analysis

#### 3.3. Base Model

#### 3.4. Covariate Model

^{2}= 0.41, p-value = 1.87 × 10

^{−4}).

^{2}= 0.65, p-value = 1.09 × 10

^{−10}); estimated Glomerular Filtration Rate (eGFR) determined using the CKD-EPI formula calculated based on BWbef (r

^{2}= 0.61, p-value = 3.47 × 10

^{−9})).

^{−16}) and log(BWbef/70) as a covariate for V1 (p-value = 1.04 × 10

^{−4}).

^{−6}).

#### 3.5. Simulations

#### 3.6. Noncompartmental Analysis

_{T1}, C

_{T30}, AUC (T1-T30), and MRT between the groups defined according to their bleeding status at T30. Our results also failed to point out any significant differences for C

_{T1}, C

_{T60}, MRT, and AUC (T1-T60) between the groups defined according to their bleeding status at T60.

_{T1}). Concerning the results for patients recruited in the TXA0.5g group, C

_{T1}, AUC (T1-T30), and AUC (T1-T60) were found to be quite similar regarding the status of bleeding of the patients. Concerning the MRT, C

_{T30}, and C

_{T60}values, no tendency was noticed for both groups (TXA0.5g and TXA1g).

## 4. Discussion

^{−1}, normalized based on a body weight of 70 kg. Both results are consistent with the findings of Li et al. [20] and with our preliminary results, suggesting an estimated populational clearance and central distribution volume of 10.3 L/h and 11.5 L, respectively [11]. One of the parameters that varied significantly in comparison with the preliminary model estimations was the fraction of urinary elimination. It was estimated at around 50% in this study versus 25% in the previous study. This variability may be associated with a covariate that has not been investigated yet; it will be interesting to study the variability of the purine regarding the pharmacodynamics to investigate whether there may be any balance between the renal elimination and the TXA efficacy. Indeed, the mechanism of action of TXA consists of inhibiting fibrinolysis by preventing the plasminogen and t-PA from binding to fibrin. An assumption of the non-urinary elimination of TXA could be the trapping of TXA between plasmin and fibrin according to the mechanism of action of TXA that would influence either the efficacy of TXA or the fraction of TXA excreted in the urine. The second assumption that could explain the non-urinary elimination of TXA is the elimination of TXA through the uterine hemorrhagic blood flow. Unpublished results revealed that a part of the TXA is eliminated through the hemorrhagic blood flow; however, imprecisions concerning the collection of that blood made it difficult to determine the real concentration of TXA in the hemorrhagic blood and led us to exclude those blood uterine concentrations from the PK analysis. In fact, the collecting process was considered too imprecise to measure the exact volume of uterine blood and, thus, the excreted amount of TXA. The precision of the uterine blood collection was considered as less important than the management of the hemorrhagic CS in our study.

^{2}= 0.65). This is the first study suggesting a correlation between the BSV on CL and the estimated renal clearance according to the Cockroft–Gault formula.

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A

Parameters | Formula |
---|---|

ABW, adjusted body weight, kg | $\mathrm{ABW}=\text{}\mathrm{IW}\text{}+0.4\times \left(\mathrm{BW}-\mathrm{IW}\right)\text{}$ |

BMI, body mass index, kg/m^{2} | $\mathrm{BMI}=\frac{\mathrm{BW}}{\mathrm{Height}}$ |

LBW, lean body weight, kg | $\mathrm{LBW}=9270\times \text{}\mathrm{BW}/\left[8780+\left(244\ast \mathrm{BMI}\right)\text{}\right]$ |

IW, ideal weight, kg Devine et al., 1974, height in cm. | $45.4+0.89\times \left(\mathrm{Height}\text{}\left(\mathrm{cm}\right)-152.4\right)$ |

BSA, body surface area, m^{2}Dubois and Dubois [24], height in m. | $0.20247\times {\mathrm{Height}}^{0.725}\times {\mathrm{BW}}^{0.425}$ |

eClcr, estimated creatinine clearance, mL/min Cockroft–Gault formula [25] SCr for serum creatinine in mg/dL. | $\frac{0.85\times \left(140-\mathrm{Age}\right)\times \mathrm{BW}}{\mathrm{SCr}\times 72}$ |

eGFR, estimated glomerular filtration rate, mL/min/1.73 m^{2}, CKD-EPI formula [26]SCr for serum creatinine in mg/dL. | $\left[144\times {\left(\frac{\mathrm{SCr}}{0.7}\right)}^{-0.329}\times {0.993}^{\mathrm{Age}}\right]\times \frac{\mathrm{BSA}}{1.73}$ |

eGFR, estimated glomerular filtration rate, mL/min/1.73 m^{2}, MDRD formula [27]SCr for serum creatinine in mg/dL. | $\left[0.742\times 175\times {\mathrm{SCr}}^{-1.154}\times {\mathrm{Age}}^{-0.203}\right]\times \frac{\mathrm{BSA}}{1.73}$ |

## Appendix B

**Figure A1.**Individual weighted residuals (IWRES) plotted versus time (

**a**) and tranexamic acid (TXA) blood concentrations. (

**c**) Normalized prediction distribution errors (NPDE) plotted versus time (

**b**) and TXA blood concentrations (

**d**).

## Appendix C

Patient | Age | BW | BWbef | eClcr | Blood Loss at T0 | Inclusion Group | Time of Rescue Dose (Dose) | Additional Blood Loss at the Time of Second Dose | TXA Amount Measured in the Total Urine at T360 |
---|---|---|---|---|---|---|---|---|---|

Units | - | kg | kg | mL·min^{−1} | mL | - | Min | mL | mg |

01-1-049 | 33 | 73 | 60 | 151.6 | 1019 | TXA1g | 117 (1 g) | 802 | 1144 |

01-1-065 | 40 | 74 | 63 | 148.8 | 850 | TXA1g | 236 (1 g) and 300 (1 g) | 1620 | 1058 |

01-1-070 | 36 | 66 | 53 | 72.3 | 1200 | TXA1g | 87 (1 g) | 1175 | 1199 |

01-1-099 | 37 | 85 | 75 | 182.4 | 1308 | TXA1g | 36 (1 g) | 345 | 1206 |

01-1-108 | 42 | 78 | 65 | 125.3 | 1275 | TXA0.5g | 72 (0.5 g) | 695 | 1303 |

01-1-119 | 33 | 86 | 68 | 95.4 | 1020 | TXA1g | 50 (1 g) | 1870 | 344 |

01-1-134 | 31 | 70 | 50 | 91.9 | 1720 | TXA1g | 153 (1 g) | 2020 | 105 |

01-1-151 | 35 | 115 | 99 | 204.5 | 1900 | TXA1g | 35 (1 g) | 600 | 648 |

Patient | CL | V1 | V2 | Q | Purine |
---|---|---|---|---|---|

Units | L·min^{−1} | L | L | L·min^{−1} | - |

01-1-049 | 0.16 | 29.37 | 0.32 | 9.5 | 0.61 |

01-1-065 | 0.16 | 8.08 | 0.38 | 9.58 | 0.39 |

01-1-070 | 0.11 | 16.79 | 0.27 | 10.01 | 0.51 |

01-1-099 | 0.12 | 6.43 | 0.068 | 9.4 | 0.46 |

01-1-108 | 0.16 | 9.87 | 0.39 | 8.98 | 0.77 |

01-1-119 | 0.086 | 14.62 | 0.46 | 9.64 | 0.31 |

01-1-134 | 0.11 | 8.21 | 0.38 | 9.64 | 0.36 |

01-1-151 | 0.19 | 25.34 | 0.31 | 9.61 | 0.53 |

## References

- Say, L.; Chou, D.; Gemmill, A.; Tunçalp, Ö.; Moller, A.B.; Daniels, J.; Gülmezoglu, A.M.; Temmerman, M.; Alkema, L. Global causes of maternal death: A WHO systematic analysis. Lancet Glob. Health
**2014**, 2, e323–e333. [Google Scholar] [CrossRef][Green Version] - Kassebaum, N.J.; Barber, R.M.; Bhutta, Z.A.; Dandona, L.; Gething, P.W.; Hay, S.I.; Kinfu, Y.; Larson, H.J.; Liang, X.; Lim, S.S.; et al. Global, regional, and national levels of maternal mortality, 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet
**2016**, 388, 1775–1812. [Google Scholar] [CrossRef][Green Version] - Borovac-Pinheiro, A.; Priyadarshani, P.; Burke, T.F. A review of postpartum haemorrhage in low-income countries and implications for strengthening health systems. Int. J. Gynecol. Obstet.
**2021**, 154, 393–399. [Google Scholar] [CrossRef] [PubMed] - Vogel, J.P.; Oladapo, O.T.; Dowswell, T.; Gülmezoglu, A.M. Updated WHO recommendation on intravenous tranexamic acid for the treatment of post-partum haemorrhage. Lancet Glob. Health
**2018**, 6, e18–e19. [Google Scholar] [CrossRef][Green Version] - Cai, J.; Ribkoff, J.; Olson, S.; Raghunathan, V.; Al-Samkari, H.; DeLoughery, T.G.; Shatzel, J.J. The many roles of tranexamic acid: An overview of the clinical indications for TXA in medical and surgical patients. Eur. J. Haematol.
**2020**, 104, 79–87. [Google Scholar] [CrossRef] - Ducloy-Bouthors, A.S.; Jude, B.; Duhamel, A.; Broisin, F.; Huissoud, C.; Keita-Meyer, H.; Mandelbrot, L.; Tillouche, N.; Fontaine, S.; Le Goueff, F.; et al. High-dose tranexamic acid reduces blood loss in postpartum haemorrhage. Crit Care
**2011**, 15, R117. [Google Scholar] [CrossRef][Green Version] - Shakur-Still, H.; Roberts, I.; Fawole, B.; Kuti, M.; Olayemi, O.O.; Bello, A.; Huque, S.; Ogunbode, O.; Kotila, T.; Aimakhu, C.; et al. Effect of tranexamic acid on coagulation and fibrinolysis in women with postpartum haemorrhage (WOMAN-ETAC): A single-centre, randomised, double-blind, placebo-controlled trial. Wellcome Open Res.
**2018**, 3, 100. [Google Scholar] [CrossRef] - Shakur, H.; Roberts, I.; Bautista, R.; Caballero, J.; Coats, T.; Dewan, Y.; El-Sayed, H.; Gogichaishvili, T.; Gupta, S.; Herrera, J.; et al. Effects of tranexamic acid on death, vascular occlusive events, and blood transfusion in trauma patients with significant haemorrhage (CRASH-2): A randomised, placebo-controlled trial. Lancet
**2010**, 376, 23–32. [Google Scholar] - Pilbrant, A.; Schannong, M.; Vessman, J. Pharmacokinetics and bioavailability of tranexamic acid. Eur. J. Clin. Pharm.
**1981**, 20, 65–72. [Google Scholar] [CrossRef] - Elkomy, M.H.; Sultan, P.; Drover, D.R.; Epshtein, E.; Galinkin, J.L.; Carvalho, B. Pharmacokinetics of Prophylactic Cefazolin in Parturients Undergoing Cesarean Delivery. Antimicrob. Agents Chemother.
**2014**, 58, 3504–3513. [Google Scholar] [CrossRef][Green Version] - Shakur-Still, H.; Roberts, I.; Fawole, B.; Kuti, M.; Olayemi, O.O.; Bello, A.; Huque, S.; Ogunbode, O.; Kotila, T.; Aimakhu, C. Hypothesis for a partially non urinary elimination of tranexamic acid in haemorrhagic caesarean section: Traces pilot pharmacokinetic study: Pharmacokinetics of tranexamic acid in obstetrics. Eur. J. Pharm. Sci.
**2020**, 153, 105486. [Google Scholar] - Ducloy-Bouthors, A.S.; Jeanpierre, E.; Saidi, I.; Baptiste, A.S.; Simon, E.; Lannoy, D.; Duhamel, A.; Allorge, D.; Susen, S.; Hennart , B. TRAnexamic acid in haemorrhagic CESarean section (TRACES) randomized placebo controlled dose-ranging pharmacobiological ancillary trial: Study protocol for a randomized controlled trial. Trials
**2018**, 19, 149. [Google Scholar] [CrossRef] [PubMed][Green Version] - Bouthors, A.S.; Hennart, B.; Jeanpierre, E.; Baptiste, A.S.; Saidi, I.; Simon, E.; Lannoy, D.; Duhamel, A.; Allorge, D.; Susen, S. Therapeutic and pharmaco-biological, dose-ranging multicentre trial to determine the optimal dose of TRAnexamic acid to reduce blood loss in haemorrhagic CESarean delivery (TRACES): Study protocol for a randomised, double-blind, placebo-controlled trial. Trials
**2018**, 19, 148. [Google Scholar] [CrossRef] [PubMed][Green Version] - Ghasemi, A.; Zahediasl, S. Normality Tests for Statistical Analysis: A Guide for Non-Statisticians. Int. J. Endocrinol. Metab.
**2012**, 10, 486–489. [Google Scholar] [CrossRef][Green Version] - Grassin-Delyle, S.; Semeraro, M.; Foissac, F.; Bouazza, N.; Shakur-Still, H.; Roberts, I.; Treluyer, J.M.; Urien, S. Tranexamic acid through intravenous, intramuscular and oral routes: An individual participant data meta-analysis of pharmacokinetic studies in healthy volunteers. Fundam. Clin. Pharmacol.
**2019**, 33, 670–678. [Google Scholar] [CrossRef] - Grassin-Delyle, S.; Tremey, B.; Abe, E.; Fischler, M.; Alvarez, J.C.; Devillier, P.; Urien, S. Population pharmacokinetics of tranexamic acid in adults undergoing cardiac surgery with cardiopulmonary bypass. Br. J. Anaesth.
**2013**, 111, 916–924. [Google Scholar] [CrossRef][Green Version] - Grassin-Delyle, S.; Theusinger, O.M.; Albrecht, R.; Mueller, S.; Spahn, D.R.; Urien, S.; Stein, P. Optimisation of the dosage of tranexamic acid in trauma patients with population pharmacokinetic analysis. Anaesthesia
**2018**, 73, 719–729. [Google Scholar] [CrossRef][Green Version] - Dowd, N.P.; Karski, J.M.; Cheng, D.C.; Carroll, J.A.; Lin, Y.; James, R.L.; Butterworth, J. Pharmacokinetics of tranexamic acid during cardiopulmonary bypass. Anesthesiology
**2002**, 97, 390–399. [Google Scholar] [CrossRef] - Grassin-Delyle, S.; Semeraro, M.; Lamy, E.; Urien, S.; Runge, I.; Foissac, F.; Bouazza, N.; Treluyer, J.M.; Arribas, M.; Roberts, I.; et al. Pharmacokinetics of tranexamic acid after intravenous, intramuscular, and oral routes: A prospective, randomised, crossover trial in healthy volunteers. Br. J. Anaesth.
**2022**, 128, 465–472. [Google Scholar] [CrossRef] - Li, S.; Ahmadzia, H.K.; Guo, D.; Dahmane, E.; Miszta, A.; Luban, N.L.; Berger, J.S.; James, A.H.; Wolberg, A.S.; van den Anker, J.N.; et al. Population pharmacokinetics and pharmacodynamics of Tranexamic acid in women undergoing caesarean delivery. Br. J. Clin. Pharm.
**2021**, 87, 3531–3541. [Google Scholar] [CrossRef] - Ahmed, S.B.; Bentley-Lewis, R.; Hollenberg, N.K.; Graves, S.W.; Seely, E.W. A comparison of prediction equations for estimating glomerular filtration rate in pregnancy. Hypertens Pregnancy
**2009**, 28, 243–255. [Google Scholar] [CrossRef] [PubMed][Green Version] - Gao, M.; Vilayur, E.; Ferreira, D.; Nanra, R.; Hawkins, J. Estimating the glomerular filtration rate in pregnancy: The evaluation of the Nanra and CKD-EPI serum creatinine-based equations. Obs. Med.
**2021**, 14, 31–34. [Google Scholar] [CrossRef] [PubMed] - Picetti, R.; Shakur-Still, H.; Medcalf, R.L.; Standing, J.F.; Roberts, I. What concentration of tranexamic acid is needed to inhibit fibrinolysis? A systematic review of pharmacodynamics studies. Blood Coagul Fibrinolysis
**2019**, 30, 1–10. [Google Scholar] [CrossRef][Green Version] - Dubois, D.; Dubois, E.F. A formula to estimate the approximate surface area if height and weight be known. Arch. Intern. Med.
**1989**, 5, 303–311. [Google Scholar] - Cockcroft, D.W.; Gault, M.H. Prediction of creatinine clearance from serum creatinine. Nephron
**1976**, 16, 31–41. [Google Scholar] [CrossRef] [PubMed] - Levey, A.S.; Stevens, L.A.; Schmid, C.H.; Zhang, Y.; Castro, A.F., III; Feldman, H.I.; Kusek, J.W.; Eggers, P.; Van Lente, F.; Greene, T.; et al. A New Equation to Estimate Glomerular Filtration Rate. Ann. Intern. Med.
**2009**, 150, 604–612. [Google Scholar] [CrossRef] - Levey, A.S.; Coresh, J.; Greene, T.; Marsh, J.; Stevens, L.A.; Kusek, J.W.; Van Lente, F. 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. [Google Scholar] [CrossRef][Green Version]

**Figure 1.**Hypothetical base models tested. The hypothetical tested parameters are represented in blue color.

**Figure 4.**Correlations between the conditional mean of individual pharmacokinetic parameters and covariates of the final covariate model. Individual parameters are displayed by blue dots and regression line is displayed by the red line.

**Figure 5.**Goodness-of-fit plots obtained from the final covariate model: (

**A**) The visual predictive check graph represents the observed plasma concentrations in tranexamic acid (TXA) plotted against time, based on 1000 Monte Carlo simulations. Prediction intervals for each percentile are estimated across all simulated data and represented as colored areas (pink for the 50th percentile, blue for the 10th and 90th percentiles). Observed data are displayed as blue dots. Predicted medians and empirical percentiles are displayed as green dotted lines and blue lines, respectively. (

**B**) Normalized prediction distribution errors (NPDE) plotted against time and tranexamic acid (TXA) plasma concentrations. Observations plotted against populational (

**C**) and individual (

**D**) predicted tranexamic acid (TXA) plasma concentrations. Observations plotted against populational (

**E**) and individual (

**F**) predicted tranexamic acid (TXA) urinary concentrations. The limits of the 90% confidence intervals are displayed as green dotted lines. Concerning the VPC graph, curves representing empirical percentiles overlaid the prediction intervals. Concerning the observations versus predictions graph, the ratio of observed/predicted concentrations was around the x = y line for both plasma and urinary values. The proportions of plasma and urinary ratios that fell outside the 90% prediction interval were 2.2% and 6.8%, respectively. The distribution of NPDE was quite well adjusted to the density of the standard Gaussian distribution. The Shapiro–Wilk test of normality was significant, but significance is often observed when analyzing a large number of observations (Fc = 0.98, p-value = 5.8 × 10

^{−5}for blood concentrations; Fc = 0.96, p-value = 4.84 × 10

^{−4}for urinary concentrations) [14].

**Figure 6.**Monte Carlo simulations with the base model for 1000 individuals. Legend: (

**a**) administration of a single dose of 1 g of tranexamic acid at T0; (

**b**) administration of a single dose of 0.5 g of tranexamic acid at T0.

**Figure 7.**Representation of the mean resident time of TXA (

**A**), the predicted maximal blood concentration of TXA (

**B**), the blood concentration of tranexamic acid measured 30 min after the TXA administration (

**C**), and the AUC estimated over the 30 min following the TXA administration (

**D**) according to the groups of bleeding status defined 30 min after the first TXA injection. Legend: AUC, area under the curve; TXA, tranexamic acid.

**Figure 8.**Representation of the mean resident time of TXA (

**A**), the predicted maximal blood concentration of TXA (

**B**), the blood concentration of tranexamic acid measured 60 min after the TXA administration (

**C**), and the AUC estimated over the 60 min following the TXA administration (

**D**) according to the groups of bleeding status defined 60 min after the first TXA injection. Legend: AUC, area under the curve; TXA, tranexamic acid.

Characteristics, Mean (SD ^{1}) | Group TXA0.5g ^{2} (n = 34) | Group TXA1g ^{2} (n = 45) | p-Value |
---|---|---|---|

Age (years) | 34 (5) | 33 (4) | 0.47 |

Height (cm) | 166 (8) | 164 (7) | 0.19 |

IW ^{3} (kg) | 58.3 (7.0) | 56.3 (6.3) | 0.19 |

BW 4 before pregnancy (kg) | 73.2 (21.1) | 72 (17) | 0.46 |

BW (kg) | 84.3 (18.6) | 83.0 (15.2) | 0.73 |

BMI ^{5} before pregnancy (kg/m^{2}) | 26.4 (7.0) | 26.6 (6.0) | 0.54 |

BMI (kg/m^{2}) | 30.4 (6.0) | 30.8 (5.1) | 0.68 |

ABW ^{6} before pregnancy (kg) correction factor = 0.4 ^{1} | 68.7 (10.0) | 67.0 (8.3) | 0.65 |

LBW ^{7} before pregnancy (kg) | 43.9 (7.4) | 43.0 (6.3) | 0.65 |

LBW (kg) | 47.8 (6.4) | 46.9 (5.4) | 0.58 |

BSA ^{8} before pregnancy (m^{2}) | 1.8 (0.2) | 1.8 (0.2) | 0.88 |

BSA (m^{2}) | 1.9 (0.2) | 1.9 (0.2) | 0.54 |

Serum creatinine concentration (mg/dL) | 6.5 (1.5) | 6.7 (1.6) | 0.25 |

eClcr ^{9} (Cockroft–Gault, mL/min) with BW before pregnancy | 150.5 (64.5) | 143.4 (53.2) | 0.47 |

eClcr (Cockroft–Gault, mL/min) | 172.3 (62.3) | 166.3 (56.1) | 0.42 |

eGFR ^{10} (CKD-EPI, mL/min/1.73 m^{2}) with BW before pregnancy | 122.5 (20.8) | 119.7 (17.2) | 0.44 |

eGFR (CKD-EPI, mL/min/1.73 m^{2}) | 130.3 (19.1) | 127.9 (16.4) | 0.42 |

eGFR (MDRD, mL/min/1.73 m^{2}) with BW before pregnancy | 117.1 (37.1) | 111.9 (35.5) | 0.42 |

eGFR (MDRD, mL/min/1.73 m^{2}) | 124.5 (37.5) | 119.5 (37.0) | 0.47 |

Bleeding volume at inclusion (mL) | 1091 (273) | 1163 (318) | 0.34 |

^{1}Standard deviation,

^{2}Tranexamic acid,

^{3}Ideal weight,

^{4}Body Weight,

^{5}Body Mass Index,

^{6}Adjusted Body Weight,

^{7}Lean Body Weight,

^{8}Body Surface Area,

^{9}estimated Creatinine Clearance,

^{10}estimated Glomerular Fraction Rate.

Nb ^{1} of Compartments | Elimination A ^{2} | Elimination A′ ^{3} | Elimination B ^{4} | −2LL ^{5} | BICc ^{6} | Condition Index |
---|---|---|---|---|---|---|

1 | First-order | - | - | 4283.98 | 4323.8 | 3 |

First-order | First-order | - | 4045.05 | 4101.69 | 12 | |

2 | Non-linear | - | - | 4229.73 | 4301.42 | 111 |

2 | Non-linear | - | First-order | NA ^{7} | NA | NA |

2 | Non-linear | - | Non-linear | NA | NA | NA |

2 | First-order | - | - | 4097.00 | 4158.44 | 6 |

2 | First-order | - | First-order | 4127.8 | 4199.49 | 33 |

2 | First-order | - | Non-linear | 4071.26 | 4153.57 | 84 |

2 | First-order | First-order | - | 3980.12 | 4051.81 | 81 |

3 | First-order | - | - | 3987.84 | 4080.78 | 14 |

^{1}Number,

^{2}urinary elimination from compartment 1,

^{3}non-urinary elimination from compartment 1,

^{4}non-urinary elimination from compartment 2,

^{5}maximized log-likelihood,

^{6}corrected Bayesian information criterion,

^{7}non-applicable (attributed to parameters that failed to be found by the algorithm).

Model | Parametrization | −2LL ^{1} | BICc ^{2} | κ ^{3} |
---|---|---|---|---|

(A): Base model | CL, V1, V2, Q, purine | 3774.45 | 3845.38 | 12.98 |

(B): (A)+ covariate effect | * $\mathrm{log}\left(\mathrm{CL}\right)=\mathrm{log}\left({\mathsf{\theta}}_{\mathrm{CL}}\right)+\mathsf{\beta}{{\mathrm{CL}}_{\text{}}}^{4}\times $
eClcr ^{5} + η_{CL} ^{6} | 3725.64 | 3800.94 | 41.21 |

$\mathrm{log}\left(\mathrm{V}1\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{1}\right)+\mathsf{\beta}{\mathrm{V}}_{1}\times $ BWbef ^{7} + η_{V1} | 3760.16 | 3835.46 | 948.88 | |

$\mathrm{log}\left(\mathrm{Q}\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{2}\right)+{\mathsf{\beta}}_{\mathrm{Q}}\times $ BWbef + ηV_{2} | 3758.82 | 3834.12 | 189.46 | |

$\mathrm{log}\left(\mathrm{V}1\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{1}\right)+\mathsf{\beta}{\mathrm{V}}_{1}\times $ log(BWbef/70) + η_{V1} | 3762.93 | 3838.23 | 30.82 | |

(C): (B) * + covariate effect | $\mathrm{log}\left(\mathrm{V}1\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{1}\right)+\mathsf{\beta}{\mathrm{V}}_{1}\times $ BW ^{8} + η_{V1} | 3710.77 | 3790.44 | 227.97 |

$\mathrm{log}\left(\mathrm{V}1\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{1}\right)+\mathsf{\beta}{\mathrm{V}}_{1}\times $ log(BW/70) + η_{V1} | 3712.91 | 3792.58 | 71.90 | |

$\mathrm{log}\left(\mathrm{V}1\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{1}\right)+\mathsf{\beta}{\mathrm{V}}_{1}\times $ BWbef + η_{V1} | 3714.07 | 3793.74 | 137.24 | |

** $\mathrm{log}\left(\mathrm{V}1\right)=\mathrm{log}\left(\mathsf{\theta}{\mathrm{V}}_{1}\right)+\mathsf{\beta}{\mathrm{V}}_{1}\times $ log(BWbef/70) + η_{V1} | 3711.10 | 3790.77 | 35.14 | |

(D): (C) ** + covariate effect | $\mathrm{log}\left(\mathrm{CL}\right)=\mathrm{log}\left({\mathsf{\theta}}_{\mathrm{CL}}\right)+{\mathsf{\beta}}_{\mathrm{CL}}\times $ Age + η_{CL} | 3705.86 | 3789.90 | 346.30 |

^{1}maximized log-likelihood,

^{2}corrected Bayesian information criterion,

^{3}condition index,

^{4}factor applied to the covariate,

^{5}creatinine clearance estimated according to the Cockroft-Gault equation,

^{6}between-subject variability,

^{7}Body Weight before pregnancy,

^{8}Body Weight, * the best model B according to BICc and κ, ** the best model C according to BICc and κ.

**Table 4.**Parameter estimates of the final model in parturient women undergoing hemorrhagic caesarean section.

Parametrization | Original Dataset | Bootstrap | |||
---|---|---|---|---|---|

Population Parameters | Covariate Effect | Estimated Values (RSE ^{1}, %) | Shrinkage (Conditional Distribution) % | Median | (Q1; Q3) ^{2} |

θ_{CL} (L/min)
| ${e}^{\left(\beta \mathrm{C}\mathrm{L}\times e\mathrm{C}\mathrm{l}cr\right)}$ | 0.077 (7.3) | 2.88 | 0.0785 | (0.0746; 0.0825) |

β_{CL} | 0.0039 (11.8) | NA ^{4} | 0.0038 | (0.0035; 0.0042) | |

θ_{V1} (L)
| $\beta \mathrm{V}1\times \frac{BW{}^{3}}{70}$ | 9.25 (12.0) | 0.857 | 9.76 | (7.78; 12.61) |

β_{V1} | - | 1.41 (25.8) | NA | 1.31 | (0.93; 1.68) |

θ_{Q} (L/min)
| - | 0.32 (15.3) | −3.74 | 0.30 | (0.24; 0.37) |

θ_{V2} (L)
| - | 9.49 (5.1) | 2.64 × 10^{−4} | 9.58 | (8.41; 10.36) |

θ_{purine} | - | 0.54 (7.0) | −1.37 | 0.55 | (0.53; 0.57) |

ω_{CL} (%)
| - | 20 (11.2) | - | 0.19 | (0.18; 0.21) |

ω_{V1} (%)
| - | 59 (14.1) | - | 0.48 | (0.32; 0.61) |

ω_{Q} (%)
| - | 67 (18.8) | - | 0.65 | (0.54; 0.74) |

ω_{V2} (%)
| - | 13 (31.9) | - | 0.20 | (0.14; 0.30) |

ω_{purine} (%)
| - | 46 (11.9) | - | 0.44 | (0.36; 0.52) |

a1 | NA | 0.44 (33.0) | NA | 0.38 | (0.10; 0.52) |

b1 | NA | 0.15 (6.8) | NA | 0.15 | (0.14; 0.16) |

b2 | NA | 0.52 (7.9) | NA | 0.52 | (0.49; 0.54) |

^{1}Residual standard error,

^{2}(first quartile;third quartile),

^{3}body weight before pregnancy,

^{4}non-applicable.

**Table 5.**Estimated mean concentrations after administration of a single dose of 1 g of tranexamic acid and a single dose of 0.5 g of tranexamic acid.

Mean (10th–90th Percentile) | 15 min after Administration | 30 min after Administration | 60 min after Administration | 120 min after Administration | 360 min after Administration |
---|---|---|---|---|---|

Single dose of 0.5 g of TXA | 55.1 (35.3;77.8) | 39.2 (28.7;51.6) | 27.5 (19.6;35.6) | 17.3 (10.7;23.9) | 4.6 (1.3;8.8) |

Single dose of 1 g of TXA | 27.1 (17.3;37.6) | 19.6 (13.9;25.6) | 13.8 (10.0;18.3) | 8.9 (5.5;12.4) | 2.4 (0.6;4.6) |

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## Share and Cite

**MDPI and ACS Style**

Gilliot, S.; Ducloy-Bouthors, A.-S.; Loingeville, F.; Hennart, B.; Allorge, D.; Lebuffe, G.; Odou, P. Pharmacokinetics of Curative Tranexamic Acid in Parturients Undergoing Cesarean Delivery. *Pharmaceutics* **2022**, *14*, 578.
https://doi.org/10.3390/pharmaceutics14030578

**AMA Style**

Gilliot S, Ducloy-Bouthors A-S, Loingeville F, Hennart B, Allorge D, Lebuffe G, Odou P. Pharmacokinetics of Curative Tranexamic Acid in Parturients Undergoing Cesarean Delivery. *Pharmaceutics*. 2022; 14(3):578.
https://doi.org/10.3390/pharmaceutics14030578

**Chicago/Turabian Style**

Gilliot, Sixtine, Anne-Sophie Ducloy-Bouthors, Florence Loingeville, Benjamin Hennart, Delphine Allorge, Gilles Lebuffe, and Pascal Odou. 2022. "Pharmacokinetics of Curative Tranexamic Acid in Parturients Undergoing Cesarean Delivery" *Pharmaceutics* 14, no. 3: 578.
https://doi.org/10.3390/pharmaceutics14030578