Thrombelastography detects possible coagulation disturbance in intracerebral hemorrhage patients with hematoma enlargement

Abstract

Background and Purpose

Intracerebral hemorrhage (ICH) has high morbidity and hematoma enlargement (HE) causes worse outcome. Thrombelastography (TEG^™) measures the dynamics of clot formation and dissolution, and might be useful for assessing bleeding risk. We used TEG^™ to detect changes in clotting in patients with and without HE after ICH.

Methods

This prospective study included 64 patients with spontaneous ICH admitted from 2009 to 2013. TEG^™ was performed within 6 hours of symptom onset and after 36 hours. Brain imaging was obtained at baseline and 36 ± 12 hours, and HE defined as total volume increase > 6cc or >33%. TEG^™ was also obtained from 57 controls.

Results

Compared to controls, ICH patients demonstrated faster and stronger clot formation; shorter R and delta (p<0.0001) at baseline; and higher MA and G (p < 0.0001) at 36 hours. 11 patients had HE. After controlling for potential confounders, baseline K and delta were longer in HE + compared to HE − patients, indicating that HE+ patients had slower clot formation (p<0.05). TEG^™ was not different between HE + and HE − patients at 36 hours.

Conclusions

TEG^™ may detect important coagulation changes in patients with ICH. Clotting may be faster and stronger in immediate response to ICH and a less robust response may be associated with HE. These findings deserve further investigation.

Introduction

Intracerebral hemorrhage (ICH) has high morbidity. Hematoma enlargement (HE) causes worse outcome and is a potentially modifiable factor in treatment of ICH¹. The causes of HE probably are multifactorial. Lipohyalinosis affecting the perforating arterioles may initiate bleeding in turn causing shearing damage to adjacent vessels^2,3. Elevated blood pressure may increase the risk of hematoma enlargement ⁴. Radiographic features such as spot sign or contrast extravasation have also been used to predict early ICH growth⁵. Coagulation status may be another important variable explaining HE. Coagulopathy associated with the use of warfarin and other anticoagulants is certainly a cause of HE ⁶, and treatments to correct such iatrogenic coagulation abnormalities are recommended in all guidelines, though still not proven to improve outcome ⁷

There is limited understanding of the coagulation status of non-anticoagulated patients with ICH, and how it may be related to HE and ICH outcome. Pro-coagulant drugs such as activated factor VII and Epsilon Amino Caproic acid reduce HE in non-anticoagulated ICH patients, but have not been shown to improve outcome⁸. These trials did not include detailed testing of the patients’ underlying coagulation status.

Recently, we undertook a series of prospective studies using Thrombelastography (TEG^™) to determine the coagulation status of stroke patients and to determine if TEG^™ can help identify their risk of bleeding. TEG^™ measures the dynamics of clot formation and dissolution, and therefore logically might be useful for assessing bleeding risk.

TEG^™ values (Figure 1) include speed of clot formation (minutes) measured by parameters R (time until clot firmness reaches amplitude of 2 mm), K (speed of clot strengthening to amplitude of 20 mm), and delta (time to reach maximum speed of initial clot formation) as well as clot strength measured by maximum amplitude (MA - mm) and G, derived from MA (dynes/cm²).

Figure 1.

Explanation of TEG values. SP-initial fibrin formation. R-reaction time to clot formation. Delta- (R-SP) Thrombin burst. K- speed of clot strengthening. Angle- rate of initial clot strengthening. MA-clot firmness. G -calculated from MA as per text. LY30-lysis as determined by clot strength measured 30 minutes after maximal amplitude of clot strength (MA) is reached.

TEG^™ has been available since 1948, but has not been used routinely in stroke patients. Our initial TEG^™ study confirmed an earlier study by Ettinger demonstrating that TEG^™ can identify a hypercoagulable state in 29–38% of patients with an ischemic stroke versus 12% of age-matched controls⁹. Acute ischemic stroke patients had shorter R, greater α-Angle and shorter K, indicating faster clotting¹⁰. However, TEG ^™ has not been reported in patients with ICH.

The objective of this study was to use TEG^™ to detect any changes in clotting characteristics in ICH patients compared to controls, and whether TEG^™ differed in patients with and without HE. We hypothesized that HE patients would have less robust clotting after ICH. Our hypothesis is that TEG^™ abnormalities might help us understand the components of any clotting abnormality leading to HE, provide a clue for future therapeutic interventions to prevent HE, and possibly serve as a clinically useful tool to predict patients that will develop HE.

Methods

This prospective study included consecutive patients at least 18 years of age with spontaneous ICH who could be consented and have blood drawn for TEG^™ analysis within 6 hours of symptom onset. Patients were excluded if bleeding was due to known coagulopathy (including use of anticoagulants), trauma or known vascular malformation, and if they had surgical clot evacuation (other than hemicraniectomy or ventriculostomy) or receipt of any hemostatic agents prior to the baseline TEG^™ draw. After the first 36 patients were enrolled, a second blood draw was obtained after 36 hours on subsequent patients if possible. This protocol change occurred based on observations as our study was ongoing that initial TEG^™ abnormalities in acute ischemic stroke patients normalized by 36 hours. Whole blood was collected into a citrated tube upon the patient’s arrival at the emergency department. The blood was held at room temperature and taken for processing within 2 hours of collection. The test was run on a computerized TEG coagulation analyzer (Haemonetics Corp, Model 5000, Braintree Mass, USA©). Personnel who performed the testing were all trained on the procedure.

R, K and Delta were available within 10 minutes of test initiation; Angle, MA and G within 20–30 minutes; and LY30 within 30 minutes. The TEG^™ machine was validated for quality assurance through daily quality control procedures using normal and abnormal controls for calibration verification and operational checks. Variability in run-to-run precision, day-to-day precision, and between site and manufacturer was <3%.

Data collected at baseline included age, race, sex, and past medical history of hypertension, diabetes, hyperlipidemia, coronary artery disease, smoking, and use of outpatient medications as per patient or family report. We also documented results of computed tomography (CT) scan without contrast, National Institutes of Health Stroke Scale (NIHSS), glucose, hemoglobin, hematocrit, platelets, prothrombin time (PT), international normalized ratio (INR) and partial thromboplastin time (PTT). Brain imaging was obtained at baseline and 36 ± 12 hours. The ABC/2 method was used for calculating hematoma volume, based on ellipsoid volume formula¹¹. HE was defined as total volume increase > 6cc or >33%, as used in prior studies¹².

TEG^™ values were also obtained from controls who were either healthy volunteers or patients seen in our out-patient clinic with non-vascular diagnoses.

Continuous variables with normal distributions were summarized by mean ± standard deviation, and variables with skewed distributions were summarized by median and interquartile range. Categorical variables were described with frequency and percentages. The differences between groups with respect to demographics, medical history, outpatient medications and baseline lab values were compared using t test (or Wilcoxon rank sum test) and Chi-square test (or Fisher exact test) as appropriate.

To compare baseline and 36 hour TEG^™ values between ICH patients and the control group, we conducted simultaneous comparisons of all components of TEG^™ values based on multivariate analysis (Hotelling-Lawley Trace test). If significant differences were observed, post-hoc analysis on each individual TEG^™ value was conducted using two sample t-test to compare the differences in baseline and 36 hour TEG^™ values between ICH patients and the control group. Multivariable regression models were performed to compare the differences between HE + and HE − groups while controlling for confounders. The identification of confounders was based on both a priori and empirical considerations. First, the important factors correlated with TEG^™ parameters (e.g., age, smoking status, and antithrombotic medications), judged by knowledge and literature were included in the analysis. Second, we identified the factors which were associated with both group status (HE + and HE −) and TEG^™ parameters at p-value <0.25 in univariate analysis. The covariates were considered to be confounders if the regression coefficient of group status varied by >20% when the covariate was added to (or deleted from) the final model. All statistical analyses were performed using SAS 9.3 (SAS Institute. Inc., Cary, NC) and a p-value <0.05 was considered as significant.

Our initial sample size estimate was 67 patients based on differences in TEG^™ observed between ischemic stroke patients and normal controls in our previous study¹⁰. This sample size would allow us to detect differences of 0.57 standard deviations for each of the TEG values with a power of 80%. Except for the study statistician, all investigators remained blind to the grouped data throughout the study.

This study was approved by the Committee for the Protection of Human Subjects of The University of Texas Health Science Center at Houston. Informed consent was obtained from each individual prior to participation in the study.

Results

Sixty seven patients with spontaneous ICH admitted through the Memorial Hermann Hospital-Texas Medical Center Emergency Department from 2009 to 2013 were included, but 3 patients were missing baseline TEG^™ data leaving a total of 64 for analysis. 36 hour TEG^™ values were obtained in the final 27 patients. We also obtained TEG^™ samples from 57 controls.

There was no significant difference between ICH patients and controls for age (59.0±12.7 vs 54.6±13.1) or sex (male n (%): 37 (57.8) vs 30 (52.6)).

The p-values for simultaneous comparisons of all components of baseline and 36 hour TEG^™ values between ICH patients and the control group based on multivariate analysis (Hotelling-Lawley Trace test) were both <0.0001. Compared to controls, ICH patients demonstrated faster clot formation within 6 hours of onset; shorter R and delta (p<0.0001), and steeper angle (p<0.05) at baseline. By 36 hours, ICH patients had higher MA and G (p < 0.0001) suggesting the development of stronger clot formation (Table 1).

Table 1.

Comparison of ICH patients and controls with respect to baseline TEG and 36 hour TEG values

Variables	mean±SD			p-values for comparing baseline TEGs in ICH patients and controls	p-values for comparing 36 hour TEGs in ICH patients and controls	§ p-values for comparing baseline and 36 hour TEGs in ICH patients
	Baseline TEG in ICH patients (N=64)	36 hours TEG in ICH patients (N=27)	Controls (N=57)
R	4.7±1.7	6.5±4.4	6.1±1.8	<0.0001	0.65	0.01
Delta	0.6±0.3	0.9±1.6	0.9±0.4	<0.0001	0.98	0.23
K	2.1±1.6 *	2.1±2.8	2.1±0.6	0.94	0.99	0.20
MA	64.5±14.1	70.7±4.8	64.4±5.8	0.98	<0.0001	0.02
Angle	64.4±10.8	66.4±12.3	61.3±5.8	<0.05†	<0.05‡	0.10
G	10.4±4.1	12.5±2.9	9.3±2.0	<0.05†	<0.0001	0.03

^*N=62;

^†p-value=0.049;

^‡p-value=0.047;

^§denote p-values obtained from paired t-test or Wilcoxon signed rank test where appropriate; other p-values are obtained by two sample t-test; the p-values for simultaneous comparisons of all components of baseline and 36 hour TEG^™ values between ICH patients and the control group based on multivariate analysis (Hotelling-Lawley Trace test) were both <0.0001.

Eleven of the ICH patients developed HE. Male sex and prior clopidogrel use were more frequent in the HE + group (p<0.05) compared to HE −, but otherwise there were no differences in important variables that might be associated with HE (Table 2). Multivariable regression in Table 3 adjusting for potential confounding effects revealed that HE + patients showed slower (longer K and delta and a trend towards longer R) clot formation compared to HE− patients. TEG^™ was not different between HE + and HE − patients at 36 hours, suggesting that any differences in clot formation among the ICH patients had disappeared by 36 hours. (Data not shown).

Table 2.

Comparison of hematoma enlargement status (Yes, No) groups with respect to demographics, outpatient medications, medical history, baseline lab values and interventions during hospitalization

Variables	Hematoma Enlargement		p-values
	Yes (N=11)	No (N=38)
Age, mean±SD	56.2±13.3	57.2±12.1	0.81
Male, n(%)	10 (90.9)	18 (47.4)	0.01
Race			0.79
African American	5 (45.5)	15 (41.7)
Caucasian	2 (18.2)	10 (27.8)
Hispanic	2 (18.2)	8 (22.2)
Other	2 (18.2)	3 (8.3)
Hypertension, n(%)	7 (63.6)	30 (79.0)	0.43
Hyperlipidemia, n(%)	1 (9.1)	2 (5.3)	0.54
Diabetes Mellitus, n(%)	4 (36.4)	11 (29.0)	0.72
Coronary artery disease, n(%)	3 (27.3)	3 (7.9)	0.12
Smoking, n(%)	3 (27.3)	7 (19.4) *	0.68
Aspirin, n(%)	3 (27.3)	5 (13.2)	0.36
Clopidogrel, n(%)	4 (36.4)	3 (7.9)	0.04
Warfarin, n(%)	0 (0)	1 (2.6)	1.0
Blood Products-Admission to 36 hr, n(%)			0.55
None	8 (72.7)	32 (84.2)
RBC	1 (9.1)	3 (7.9)
Platelets	2 (18.2)	3 (7.9)
Interventions			0.17
Hemi-craniectomy	2 (18.2)	1 (2.6)
Ventriculostomy	2 (18.2)	12 (31.6)
None	7 (63.6)	25 (65.8)
Glucose, median (Q1, Q3)	133.0 (99.0,	145.5 (116.0, 232.0)	0.67
Hemoglobin, mean±SD	13.9±1.6	13.0±2.1	0.18
Platelet count, mean±SD	201.2±65.0	224.3±60.8	0.28
PTT, mean±SD	31.0±8.2	28.6±3.7	0.37
INR, mean±SD	1.1±0.2	1.0±0.1	0.14
NIHSS Score, median (Q1, Q3)	17.0 (14.0, 19.0)	16.5 (13.0, 26.0)	0.96
Time of baseline blood draw since symptom onset (hrs), median (Q1, Q3)	2.2 (1.8, 3.3)	2.5 (1.6, 3.4) *	0.90
Baseline hematoma volume (cc), median (Q1, Q3)	16.0 (11.4, 76.4)	17.8 (11.4, 28.7)	0.84
Systolic blood pressure, mean±SD
At baseline	191±23	194±42	0.78
Average value during follow-up	137±8	139±8	0.43
Diastolic blood pressure, mean±SD
At baseline	106±18	106±25	0.97
Average value during follow-up	75±7	73±7	0.25

^*N=36, Q1=1^st quartile, Q3=3^rd quartile, RBC = red blood cells, PTT= partial thromboplastin time, INR = international normalized ratio, NIHSS = national institutes of health stroke scale.

Table 3.

Adjusted means and 95% confidence intervals (CI) for baseline TEG values by hematoma enlargement status (Yes vs No) groups after controlling for potential confounding effects

Baseline TEG values	Adjusted mean (95% CI)		p-values
	Hematoma Enlargement
	Yes (N=11)	No (N=38)
R	5.7 (4.5, 6.9)	4.4 (3.5, 5.4)	0.09
Delta	0.8 (0.6, 1.0)	0.5 (0.4, 0.7)	0.02
K	3.1 (2.0, 4.1)	1.6 (0.6, 2.6)*	0.04
MA	61.7 (52.0, 71.4)	61.6 (53.5, 69.7)	0.99
Angle	58.0 (50.6, 65.4)	62.0 (55.8, 68.1)	0.39
G	9.1 (6.5, 11.6)	10.3 (8.2, 12.5)	0.42

^*N=36. Adjusted means are calculated based on multivariable analysis after controlling for potential confounders: age, clopidogrel use, baseline international normalized ratio, and baseline platelet count.

Figure 2 shows a histogram representing the distribution of delta values at baseline between controls, all ICH patients, and the HE + and HE − subgroups.

Figure 2.

Distribution of Delta values at baseline for controls, all ICH patients, hemorrhage enlargement (HE) + and no hemorrhage enlargement (HE) − patients.

Discussion

This is the first study to evaluate coagulation status as reflected by TEG^™ in ICH patients. Our first major finding was that ICH patients overall have faster initial clot formation and therefore are hypercoagulable compared to controls, after adjusting for age and sex. We cannot say from our data if this finding reflects an adaptive hemostatic response to bleeding or is a more generalized acute phase homeostatic response. Our finding that TEG^™ remained abnormal at 36 hours reflecting stronger clot formation, and that patients with HE differed from those without, all suggest a specific response to bleeding.

Our second important finding is that this initial acceleration of clot formation was not seen in patients with HE, possibly indicating that heterogeneity in an adaptive response to ICH might play a role in whether parenchymal bleeding continues or stops. If this observation is confirmed in a larger cohort of patients, it would support pro-coagulation strategies in the first hours after ICH, particularly those focused on speeding the initial formation of the clot. Many other factors as already mentioned likely play a role in HE, and it is unlikely that TEG^™ as a baseline test would be sufficiently precise to identify the subset of patients who is at highest risk for developing HE. But further understanding of coagulation disturbances as reflected by TEG^™ might help guide the design of therapeutic interventions. One prior study in a mixed neuro-critical care cohort (including patients with ICH and traumatic brain injury) suggested that hypocoagulability by TEG^™ (longer R time, smaller angle and MA) was independently associated with higher mortality¹³. However, when the hypocoagulable state was defined according to conventional plasma based coagulation tests (international normalized ratio more than 1.3, platelet count less than 100,000, or activated partial thromboplastin time more than 35 sec) there was no correlation with worse prognosis. TEG^™ findings are also used to guide transfusion decisions and pro-hemostatic therapy in the perioperative period¹⁴. Given the application of TEG^™ data to guide specific interventions such as platelet transfusion, fibrinogen and recombinant factor VII administration in cardiac, liver transplant and trauma surgery ¹⁵ our preliminary findings support further investigation of a similar potential role for the TEG^™ in patients with ICH and HE.

In order to minimize the overall type I error when comparing various components of the TEG^™ values between ICH patients and the control group, we performed multivariate analysis (Hotelling-Lawley Trace test) to simultaneously test the mean differences in TEG^™ values as vector of outcomes. If a significance difference was observed, then we conducted post-hoc analysis on each TEG^™ value. Although all multivariate analyses were significant at the 0.05 level, we acknowledge that the p-value for a simultaneous comparison of all components of TEG^™ values between 36 hour TEG^™ and baseline values was marginally significant (p=0.09). However, we attribute this to the limited sample size in this study and hence caution the interpretation of these particular findings.

In our analysis, male sex and prior clopidogrel use were associated with HE. A higher prevalence of ICH but not HE has been reported in men, driven by an excess of deep hemorrhages^16,17. Antiplatelet drug use has been associated with increased risk of hematoma enlargement as well as increased mortality in patients presenting with ICH ^18,19, though data on this issue are conflicting. The same effect was not seen with aspirin use, however the low number of patients on aspirin could account for this finding.

Our study has some limitations besides the relatively small sample size of patients with HE, and the relatively small number of 36 hour samples. TEG^™ measurements can be operator- dependent and our analysis may be limited by the multiple operators who performed TEG^™ measurements. However, we minimized this with dedicated staff training on the procedure, use of the same equipment, and daily quality control. Our identification of the HE + group depends on the accuracy of our ICH volume measurement. The inter-rater reliability for the ABC/2 formula in previous studies has ranged from 0.63 to 0.99²⁰ and has been used for determining eligibility in ICH trials²¹. In our study, hematoma volume on the baseline and 36 hour scans was calculated independently using the ABC/2 method by 2 authors and our intra class correlation was excellent (0.795 for baseline volume, 0.971 for 36 hour hematoma volume). There was 100% agreement on the presence or absence of HE based on the definition used in this study.

Another limitation was the timing of tests. Except in two patients, our baseline testing occurred within 6 hours of symptom onset during the time that HE most frequently occurs^22,23, and there was no difference in time of TEG^™ blood draw between the HE + and HE − groups. However, TEG^™ values are dynamic and change within minutes or hours after ICH, and we might have found greater or less differences between groups if TEG^™ measurements were made at some other time point after ICH. Many of our patients were critically ill and 36 hour TEG^™ values may have been affected by the large number of medications and other variables inherent in critical care management. Some patients received blood products and underwent procedures (hemicraniectomy and ventriculostomy) which likely affected the 36 hour TEG^™ measurements, though again there were no differences between the groups in the occurrence of these events or in blood pressure at baseline or during the next 36 hours.

Summary

In conclusion, TEG^™ may detect important coagulation changes in patients with ICH; clotting may become faster and stronger in immediate response to ICH, and a less robust response may be associated with HE. These findings may have relevance to the cause and management of patients with HE and deserve further investigation.