Hemorrhage, Shock, Wounds and Injuries
Conditions
Brief summary
The purpose of this study is to evaluate the effects of TXA on the immune system, its pharmacokinetics, as well as safety and efficacy in severely injured trauma patients.
Detailed description
Trauma is the leading cause of death in persons younger than 40 years. Hemorrhage is the etiology in 30% of these deaths, and remains the leading cause of potentially preventable mortality (66-80%) on the battlefield. Death secondary to hemorrhagic shock occurs from both surgical bleeding and coagulopathy. Due to the knowledge of increased fibrinolysis promoting a hypocoagulable state in severe trauma, trials have been performed to determine if antifibrinolytics such as tranexamic acid (TXA) could reduce morbidity and mortality by reducing death from hemorrhage. TXA is an antifibrinolytic that inhibits both plasminogen activation and plasmin activity, thus preventing clot break-down rather than promoting new clot formation. Despite the extensive use of TXA in many surgical populations and an increasing use in severe trauma patients, TXA does not have an FDA approved indication for patients with traumatic injuries. The effect of TXA on immune function has not been thoroughly examined, especially in patients with severe traumatic injury. The study of the effects of TXA use on endothelial activation and injury is also important due to the inter-relationship between coagulation and endothelial function. Endothelial injury secondary to local hypoperfusion causes acute traumatic coagulopathy with fibrinolysis. Therefore a thorough and comprehensive evaluation of the effects of TXA on immune, coagulation, and endothelial parameters is important to allow for a better understanding of the mechanisms of action of this agent. This is a randomized placebo controlled trial to obtain mechanism of action data, pharmacokinetic information, and efficacy and safety data for the use of TXA in severely injured trauma patients. Participants will be randomized into 1 of 3 treatment arms (1:1:1): TXA 2 gram IV bolus, TXA 4 gram IV bolus, or placebo. The study period is from time of enrollment to hospital discharge or transfer. The study intervention will occur only once upon enrollment in the trial. Participants will receive study drug within two hours from their initial injury. Blood samples will be drawn at multiple time points for immune parameters, Pharmacodynamics, and repository samples. Immune parameter samples will be drawn at at approximately 0, 6, 24 and 72 hours after study drug/placebo administration. Pharmacokinetic and pharmacodynamic samples will be drawn according to two schedules. Even number sampling times, blood will be drawn at the approximate time points: 0, 20 min, 1 hr, 2 hr, 4 hr, 6 hr, 8 hr, and 12 hr. A patient sampled on odd number sampling times will have samples drawn at the approximate time points: 0, 10 min, 40 min, 1.5 hr, 3 hr, 6 hr, 10 hr and 24 hr. Repository samples will be drawn at approximate time points: 0, 1, 6, 24, and 72 hours.
Interventions
DRUGTranexamic Acid
Tranexamic acid is a man-made form of an amino acid (protein) called lysine. Tranexamic acid prevents enzymes in the body from breaking down blood clots.
OTHERPlacebo
Matching Volume Normal Saline Placebo given IV over 10 minutes within 2 hours of initial injury
Sponsors
United States Department of Defense
Washington University School of Medicine
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
TRIPLE (Subject, Caregiver, Investigator)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Patients with traumatic injury that are ordered to receive at least 1 blood product and/or 2. Patients admitted to the Emergency Department with a traumatic injury and require immediate transfer to the operating room to control the bleeding 3. Able to receive the study drug within 2 hours from estimated time of injury \*\*Please note that in circumstances where the patient initially met inclusion/
Exclusion criteria
(i.e. received blood products in the ED before a full evaluation of their injuries is complete) but is later found to only have a soft tissue involved injury or does not have a traumatic bleeding source), the Investigator may determine that the patient should not be randomized into the trial and the patient should be considered a screen failure
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in HLA-DR Expression on Monocytes 72 Hours After Drug or Placebo Administration in Patient Groups (0g TXA (Placebo); 2g TXA; 4g TXA). | Samples Drawn through 72 hours after study initiation | Blood was drawn from patients at baseline (0 h, just before placebo or drug administration) and at 72 hours post placebo or drug administration. Leukocytes in these blood samples were stained with fluroescent antibodies specific for CD45, CD14, and HLA-DR, analyzed by flow cytometry, and the median fluorescen intensity (MFI) of HLA-DR signal was recorded for monocytes (CD45+CD14+). The fold change in HLA-DR expression from prior to placebo/drug administration to 72 h after placebo/drug administration (0 h : 72 h) was calculated as HLA-DR MFI72hours ÷ HLA-DR CD14 MFI0hours. Non-paramteric one-way ANOVA (Kruskal-Wallis test) was performed between each treatment group at the given time pont, and the p-value reported. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Differences in Leukocyte Function Parameters Between the Three Study Groups | Samples Drawn through 72 hours after study initiation | To evaluate the effects of TXA on immune function parameters we will, in a RCT, analyze samples from 150 patients (50 in each study group), at multiple time points. Parameters are: a. Flow cytometric analyses on leukocytes measured from time 0 to 72 hours. |
| Total Transfusion Volume CL | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Total Transfusion Volume CL equals clearance (CL) affected by the covariate of Total Transfusion Volume (TxTot). This value is unitless per NONMEM reporting. |
| Determine the Incidence of Thromboembolic Events (DVT, MI, PE, Stroke) in All Three Study Groups. | Hospital Discharge (average 10 days) | The number of events per group for the incidence of thromboembolic events (DVT, MI, PE, Stroke) in all three study groups. |
| Determine the Incidence of Seizures at 24 Hours in All Three Study Groups. | 24 hours following TXA | The incidence of seizures at 24 hours in all three study groups. Number of participants with seizures are reported |
| Determine the Incidence of All Adverse Events in All Three Study Groups | Hospital Discharge (average 10 days) | All adverse events were totaled for each of the three study groups based on the number of incidents. |
| Platelet Count CL | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Platelet Count CL equals clearance (CL) affected by the covariate of Platelet Count (PLTint). This value is unitless per NONMEM reporting. |
| Differences in Cytokine Profiles Between the Three Study Groups | Samples Drawn through 72 hours after study initiation | To evaluate the effects of TXA on immune function parameters we will, in a RCT, analyze samples from 150 patients (50 in each study group), at multiple time points. Parameters are: a. Cytokines measured from time 0 to 72 hours. |
| Creatinine Count CL | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Creatinine Count CL equals clearance (CL) affected by the covariate of Creatinine levels (SCRint). This value is unitless per NONMEM reporting. |
| V2- Peripheral Volume (L/70kg) | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) V2 equals Peripheral Volume in L/70kg. |
| Q- Intercompartmental Clearance (L/70kg) | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Q equals intercompartmental clearance in L/70kg. |
| V1- Central Volume (L/70kg) | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) V1 equals central volume in L/70kg. |
| CL- Clearance of TXA (mL/(Min*70kg)) | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) CL equals clearance of TXA in mL/(min\*70kg). |
| Near Infrared Spectroscopy CL | 24 hours | Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Near Infrared Spectroscopy CL equals clearance (CL) affected by the covariate of Near Infrared Spectroscopy (NIRSint). This value is unitless per NONMEM reporting. |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Tranexamic Acid 2 Gram One time dose IV TXA 2 Grams given over 10 minutes within 2 hours of initial injury
Tranexamic Acid: Tranexamic acid is a man-made form of an amino acid (protein) called lysine. Tranexamic acid prevents enzymes in the body from breaking down blood clots. | 49 |
| Tranexamic Acid 4 Gram One time dose IV TXA 4 Grams given over 10 minutes within 2 hours of initial injury
Tranexamic Acid: Tranexamic acid is a man-made form of an amino acid (protein) called lysine. Tranexamic acid prevents enzymes in the body from breaking down blood clots. | 50 |
| Placebo Matching Volume Normal Saline Placebo given IV over 10 minutes within 2 hours of initial injury
Placebo: Matching Volume Normal Saline Placebo given IV over 10 minutes within 2 hours of initial injury | 50 |
| Total | 149 |
Baseline characteristics
| Characteristic | Tranexamic Acid 2 Gram | Tranexamic Acid 4 Gram | Placebo | Total |
|---|---|---|---|---|
| Age, Categorical <=18 years | 1 Participants | 1 Participants | 0 Participants | 2 Participants |
| Age, Categorical >=65 years | 1 Participants | 3 Participants | 1 Participants | 5 Participants |
| Age, Categorical Between 18 and 65 years | 47 Participants | 46 Participants | 49 Participants | 142 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants | 0 Participants | 1 Participants | 1 Participants |
| Race (NIH/OMB) Black or African American | 42 Participants | 43 Participants | 44 Participants | 129 Participants |
| Race (NIH/OMB) More than one race | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants | 1 Participants | 0 Participants | 1 Participants |
| Race (NIH/OMB) White | 7 Participants | 6 Participants | 5 Participants | 18 Participants |
| Region of Enrollment United States | 49 participants | 50 participants | 50 participants | 149 participants |
| Sex: Female, Male Female | 5 Participants | 8 Participants | 5 Participants | 18 Participants |
| Sex: Female, Male Male | 44 Participants | 42 Participants | 45 Participants | 131 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk |
|---|---|---|---|
| deaths Total, all-cause mortality | 5 / 49 | 4 / 50 | 9 / 50 |
| other Total, other adverse events | 25 / 49 | 39 / 50 | 26 / 50 |
| serious Total, serious adverse events | 14 / 49 | 18 / 50 | 13 / 50 |
Outcome results
Primary
Change in HLA-DR Expression on Monocytes 72 Hours After Drug or Placebo Administration in Patient Groups (0g TXA (Placebo); 2g TXA; 4g TXA).
Blood was drawn from patients at baseline (0 h, just before placebo or drug administration) and at 72 hours post placebo or drug administration. Leukocytes in these blood samples were stained with fluroescent antibodies specific for CD45, CD14, and HLA-DR, analyzed by flow cytometry, and the median fluorescen intensity (MFI) of HLA-DR signal was recorded for monocytes (CD45+CD14+). The fold change in HLA-DR expression from prior to placebo/drug administration to 72 h after placebo/drug administration (0 h : 72 h) was calculated as HLA-DR MFI72hours ÷ HLA-DR CD14 MFI0hours. Non-paramteric one-way ANOVA (Kruskal-Wallis test) was performed between each treatment group at the given time pont, and the p-value reported.
Time frame: Samples Drawn through 72 hours after study initiation
Population: Change in HLA-DR Expression on Monocytes 72 hours after administration. Leukocytes stained with antibodies and analyzed by flow cytometry. The median fluorescen intensity of HLA-DR signal was measured for monocytes at 0 and 72 hours. Non-paramteric one-way ANOVA was performed and the p-value reported.
| Arm | Measure | Value (MEDIAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | Change in HLA-DR Expression on Monocytes 72 Hours After Drug or Placebo Administration in Patient Groups (0g TXA (Placebo); 2g TXA; 4g TXA). | 0.503 fold change |
| Tranexamic Acid 4 Gram | Change in HLA-DR Expression on Monocytes 72 Hours After Drug or Placebo Administration in Patient Groups (0g TXA (Placebo); 2g TXA; 4g TXA). | 0.509 fold change |
| Placebo | Change in HLA-DR Expression on Monocytes 72 Hours After Drug or Placebo Administration in Patient Groups (0g TXA (Placebo); 2g TXA; 4g TXA). | 0.532 fold change |
Secondary
CL- Clearance of TXA (mL/(Min*70kg))
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) CL equals clearance of TXA in mL/(min\*70kg).
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | CL- Clearance of TXA (mL/(Min*70kg)) | 109 mL/(min*70kg) |
Secondary
Creatinine Count CL
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Creatinine Count CL equals clearance (CL) affected by the covariate of Creatinine levels (SCRint). This value is unitless per NONMEM reporting.
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | Creatinine Count CL | -0.084 unitless |
Secondary
Determine the Incidence of All Adverse Events in All Three Study Groups
All adverse events were totaled for each of the three study groups based on the number of incidents.
Time frame: Hospital Discharge (average 10 days)
Population: The number of incidents were totaled for the three study groups.
| Arm | Measure | Value (NUMBER) |
|---|---|---|
| Tranexamic Acid 2 Gram | Determine the Incidence of All Adverse Events in All Three Study Groups | 168 events |
| Tranexamic Acid 4 Gram | Determine the Incidence of All Adverse Events in All Three Study Groups | 264 events |
| Placebo | Determine the Incidence of All Adverse Events in All Three Study Groups | 138 events |
Secondary
Determine the Incidence of Seizures at 24 Hours in All Three Study Groups.
The incidence of seizures at 24 hours in all three study groups. Number of participants with seizures are reported
Time frame: 24 hours following TXA
Population: The incidence of seizures at 24 hours in all three study groups. This was done by totaling the number of participants with reported seizures.
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Tranexamic Acid 2 Gram | Determine the Incidence of Seizures at 24 Hours in All Three Study Groups. | 0 Participants |
| Tranexamic Acid 4 Gram | Determine the Incidence of Seizures at 24 Hours in All Three Study Groups. | 1 Participants |
| Placebo | Determine the Incidence of Seizures at 24 Hours in All Three Study Groups. | 0 Participants |
Secondary
Determine the Incidence of Thromboembolic Events (DVT, MI, PE, Stroke) in All Three Study Groups.
The number of events per group for the incidence of thromboembolic events (DVT, MI, PE, Stroke) in all three study groups.
Time frame: Hospital Discharge (average 10 days)
Population: The incidence of thromboembolic events (DVT, MI, PE, Stroke) in all three study groups are given based on events per group.
| Arm | Measure | Value (NUMBER) |
|---|---|---|
| Tranexamic Acid 2 Gram | Determine the Incidence of Thromboembolic Events (DVT, MI, PE, Stroke) in All Three Study Groups. | 13 events |
| Tranexamic Acid 4 Gram | Determine the Incidence of Thromboembolic Events (DVT, MI, PE, Stroke) in All Three Study Groups. | 16 events |
| Placebo | Determine the Incidence of Thromboembolic Events (DVT, MI, PE, Stroke) in All Three Study Groups. | 6 events |
Secondary
Differences in Cytokine Profiles Between the Three Study Groups
To evaluate the effects of TXA on immune function parameters we will, in a RCT, analyze samples from 150 patients (50 in each study group), at multiple time points. Parameters are: a. Cytokines measured from time 0 to 72 hours.
Time frame: Samples Drawn through 72 hours after study initiation
Population: Cytokine Levels at 0 and 72 hours after drug or placebo administration in patient groups. Blood was drawn, serum isolated, and frozen. Frozen sera were thawed and the listed cytokines measured uisng a multiplexed platform. Non-paramteric one-way ANOVA was performed between each treatment group, and the p- value reported.
| Arm | Measure | Group | Value (MEDIAN) |
|---|---|---|---|
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-23 hour 72 | 589.73 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IFNgamma hour 0 | 23.46 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-5 hour 0 | 9.3 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-5 hour 72 | 8.68 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-6 hour 0 | 54.48 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IFNgamma hour 72 | 17.89 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-6 hour 72 | 73.97 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-7 hour 0 | 18.53 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | ITAC hour 0 | 34.24 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-7 hour 72 | 18.47 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-10 hour 0 | 115.98 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-8 hour 72 | 26.9 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-1alpha hour 0 | 32.57 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-10 hour 72 | 31.76 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-1alpha hour 72 | 28.57 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-beta hour 0 | 44.91 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-beta hour 72 | 36.78 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-3a hour 0 | 22.95 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | TNFa hour 0 | 19.16 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | TNFa hour 72 | 19.38 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | ITAC hour 72 | 25.67 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-3a hour 72 | 38.49 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-12p70 hour 72 | 9.67 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-12p70 hour 0 | 9.5 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-13 hour 0 | 11.8 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | GM-CSF hour 0 | 67.79 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-13 hour 72 | 11.11 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL -17A hour 0 | 21.51 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-4 hour 72 | 49.99 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-17A hour 72 | 20.06 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | GM-CSF hour 72 | 69.22 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-1beta hour 0 | 4.17 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-1beta hour 72 | 4.15 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-2 hour 0 | 4.17 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-2 hour 72 | 4.26 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | Factalkine hour 0 | 223.61 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-21 hour 0 | 6.28 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-21 hour 72 | 6.44 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-8 hour 0 | 15.25 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-4 hour 0 | 69.45 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | Factalkine hour 72 | 174.91 pg/mL |
| Tranexamic Acid 2 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-23 hour 0 | 724.45 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-23 hour 0 | 428.26 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-23 hour 72 | 351.47 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-1beta hour 72 | 3.44 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-12p70 hour 0 | 8.64 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-5 hour 0 | 9.48 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IFNgamma hour 0 | 17.59 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | ITAC hour 72 | 21.69 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-5 hour 72 | 8.05 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-beta hour 0 | 37.66 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | GM-CSF hour 72 | 52.88 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-6 hour 0 | 39.7 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-12p70 hour 72 | 9.45 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-21 hour 72 | 6.95 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-6 hour 72 | 67.95 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IFNgamma hour 72 | 14.79 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-2 hour 0 | 4.29 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-7 hour 0 | 15.33 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-13 hour 0 | 11.11 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-4 hour 72 | 40.5 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-7 hour 72 | 16.24 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | Factalkine hour 72 | 124.23 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-10 hour 0 | 84.39 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-13 hour 72 | 10.27 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-8 hour 72 | 23.05 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | ITAC hour 0 | 32.75 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | GM-CSF hour 0 | 67.58 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-1alpha hour 0 | 30.98 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-2 hour 72 | 3.49 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL -17A hour 0 | 15.05 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-1alpha hour 72 | 27.24 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-10 hour 72 | 42.39 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-8 hour 0 | 13.59 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-1beta hour 0 | 3.75 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-4 hour 0 | 58.24 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-beta hour 72 | 29.02 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-17A hour 72 | 16.67 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | IL-21 hour 0 | 6.13 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | TNFa hour 0 | 16.4 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-3a hour 0 | 21.94 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | Factalkine hour 0 | 146.23 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | TNFa hour 72 | 20.09 pg/mL |
| Tranexamic Acid 4 Gram | Differences in Cytokine Profiles Between the Three Study Groups | MIP-3a hour 72 | 27.61 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | TNFa hour 72 | 16.16 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | MIP-3a hour 72 | 31.54 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-1beta hour 0 | 3.9 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | ITAC hour 0 | 29.34 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | ITAC hour 72 | 21.58 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | GM-CSF hour 0 | 64.69 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | GM-CSF hour 72 | 61.41 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | Factalkine hour 0 | 141.8 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | Factalkine hour 72 | 100.51 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IFNgamma hour 0 | 17.47 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IFNgamma hour 72 | 12.98 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-10 hour 0 | 105.07 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-10 hour 72 | 32.38 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | MIP-3a hour 0 | 22.95 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-12p70 hour 0 | 8.78 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-12p70 hour 72 | 7.58 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-13 hour 0 | 9.08 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-13 hour 72 | 10.28 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL -17A hour 0 | 18.73 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-17A hour 72 | 14 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-1beta hour 72 | 3.11 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-2 hour 0 | 4.01 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-2 hour 72 | 4.12 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-21 hour 0 | 7.02 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-21 hour 72 | 5.51 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-4 hour 0 | 58.16 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-4 hour 72 | 35.53 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-23 hour 0 | 406.46 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-23 hour 72 | 399.74 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-5 hour 0 | 9.06 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-5 hour 72 | 8.32 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-6 hour 0 | 63.56 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-6 hour 72 | 41.9 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-7 hour 0 | 16.52 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-7 hour 72 | 16.8 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-8 hour 0 | 13.78 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | IL-8 hour 72 | 17.64 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | MIP-1alpha hour 0 | 27.85 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | MIP-1alpha hour 72 | 25.47 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | MIP-beta hour 0 | 35.44 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | MIP-beta hour 72 | 28.15 pg/mL |
| Placebo | Differences in Cytokine Profiles Between the Three Study Groups | TNFa hour 0 | 16.4 pg/mL |
Secondary
Differences in Leukocyte Function Parameters Between the Three Study Groups
To evaluate the effects of TXA on immune function parameters we will, in a RCT, analyze samples from 150 patients (50 in each study group), at multiple time points. Parameters are: a. Flow cytometric analyses on leukocytes measured from time 0 to 72 hours.
Time frame: Samples Drawn through 72 hours after study initiation
Population: Change in CD11b and CD16 Expression on neutrophils 72 hours after. Leukocytes stained with antibodies specific and analyzed by flow cytometry. The median fluorescen intensity of CD11b or CD16 signal was measured on neutrophils. The fold change was measured, MFI72hours/MFI0hours. Non-paramteric one-way ANOVA was performed and the p-value reported.
| Arm | Measure | Group | Value (MEDIAN) |
|---|---|---|---|
| Tranexamic Acid 2 Gram | Differences in Leukocyte Function Parameters Between the Three Study Groups | CD 11b+ | 0.875 Fold Change |
| Tranexamic Acid 2 Gram | Differences in Leukocyte Function Parameters Between the Three Study Groups | CD 16+ | 0.917 Fold Change |
| Tranexamic Acid 4 Gram | Differences in Leukocyte Function Parameters Between the Three Study Groups | CD 16+ | 0.870 Fold Change |
| Tranexamic Acid 4 Gram | Differences in Leukocyte Function Parameters Between the Three Study Groups | CD 11b+ | 0.967 Fold Change |
| Placebo | Differences in Leukocyte Function Parameters Between the Three Study Groups | CD 11b+ | 0.844 Fold Change |
| Placebo | Differences in Leukocyte Function Parameters Between the Three Study Groups | CD 16+ | 0.817 Fold Change |
Secondary
Near Infrared Spectroscopy CL
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Near Infrared Spectroscopy CL equals clearance (CL) affected by the covariate of Near Infrared Spectroscopy (NIRSint). This value is unitless per NONMEM reporting.
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | Near Infrared Spectroscopy CL | -0.27 unitless |
Secondary
Platelet Count CL
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Platelet Count CL equals clearance (CL) affected by the covariate of Platelet Count (PLTint). This value is unitless per NONMEM reporting.
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | Platelet Count CL | 0.45 unitless |
Secondary
Q- Intercompartmental Clearance (L/70kg)
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Q equals intercompartmental clearance in L/70kg.
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | Q- Intercompartmental Clearance (L/70kg) | 174 L/70kg |
Secondary
Total Transfusion Volume CL
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) Total Transfusion Volume CL equals clearance (CL) affected by the covariate of Total Transfusion Volume (TxTot). This value is unitless per NONMEM reporting.
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | Total Transfusion Volume CL | 0.03 unitless |
Secondary
V1- Central Volume (L/70kg)
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) V1 equals central volume in L/70kg.
Time frame: 24 hours
Population: Of the 99 participants analyzed, 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | V1- Central Volume (L/70kg) | 1160 L/70kg |
Secondary
V2- Peripheral Volume (L/70kg)
Pharmacokinetic data was analyzed with NONMEM, using both the first-order and conditional non-Laplacian (with centering) estimation techniques. We considered two- and three-compartment models, parameterized in terms of both compartment volumes and clearances (distribution and elimination). We compared a basic model (in which pharmacokinetic parameters were independent of weight) to a model in which the pharmacokinetic parameters were assumed to be proportional to weight. The optimal model was selected on the basis of the objective function logarithm of the likelihood of the results) using standard criteria (NONMEM guide). Equations from optimal model: CL=109\*((WT/70)\*\*0.75) \* (SCRint\^-0.084) \* ((NIRSInt)/96)\^ -0.27 ) \* ((PLTint)/130)\^0.45) V1=1,160\*(WT/70) \* (TxTot)\^0.03) Q=174\*((WT/70)\*\*0.75) V2=1080 \*(WT/70) V2 equals Peripheral Volume in L/70kg.
Time frame: 24 hours
Population: Of the 99 participants analyzed 49 received the 2 gram dose and 50 received the 4 gram dose.
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Tranexamic Acid 2 Gram | V2- Peripheral Volume (L/70kg) | 1080 L/70kg |