Hemostasis, Hematoma Expansion, and Outcomes after Intracerebral Hemorrhage
Authors: Lindholm Paul F , Kwaan Hau C. , Naidech Andrew M 
Published: November 2019

Background: Intracerebral hemorrhage (ICH) is a serious complication of stroke with significant morbidity and mortality. Intracerebral bleeding and hematoma expansion (HE) cause displacement and damage to brain tissue leading to disability and death. An important approach to improve patient outcomes from ICH is to prevent HE. Our ability to improve patient outcomes depends on our ability to recognize HE and the associated hemostatic mechanisms. This study is designed to evaluate biomarkers of platelet function, coagulation and fibrinolysis and relate these biomarkers to statistically powerful estimates of HE and patient outcomes.

Study Design and Methods: Patients with acute ICH within the first 12 hours of the onset of symptoms will be studied to identify hemostasis biomarkers which may predict hematoma expansion.

Major inclusion criteria: Spontaneous ICH within 12 hours of symptom onset; age at least 21 years; consent from the patient or a representative.

Exclusion criteria: hereditary hemostasis disorders, history of malignancy, vascular malformation suspected or on imaging, sepsis, comorbid condition that is likely to be disabling or fatal, hemoglobin less than 7.5 g/dL, pregnancy.

Statistical methods: We will test the hypothesis that each hemostasis biomarker predicts HE by using Mann-Whitney U (for non-parametric) or ANOVA (for normally distributed results). We will set P<0.01 given the multiple biomarkers to be assessed. The 80% power using a Mann-Whitney U to test the hypothesis that the distributions of HE are 3 mL different would require 147 patients (calculations made with PASS v.12, NCSS Inc., Kaysville, UT). Machine learning techniques will be applied to hemostasis biomarkers to predict the modified Rankin score (mRS), T Scores of HRQoL, and T Scores of NIH Toolbox outcomes. Precision-recall and receiver operating characteristic (ROC) curves will be constructed, and area under the curve will be compared.

Biomarker selection or companion diagnostics: This study will measure platelet activity, coagulation activation and fibrinolysis in patients with acute onset (less than 12 hours) intracerebral hemorrhage ICH to determine hemostatic mechanisms of hematoma expansion. Global activity of platelets, coagulation factors and fibrinolysis activity are measured by thromboelastogram (TEG) and rotational thromboelastometry (ROTEM) assays. Platelet activity is also measured with Platelet Function assay, PFA-100, Platelet Aspirin Assay and the Platelet P2Y12 Assay. Coagulation activation is measured by Tissue Factor antigen and activity and Thrombin Generation Assay. Fibrinolysis is assayed by Plasmin/antiplasmin (PAP) complex, Fibrinogen, D-Dimer and PAI-1 antigen and activity.

Study treatment, endpoints: The hemostatic parameters and hematoma expansion are compared to patient outcomes measured by the mRS and health related quality of life (HRQoL) and objective outcomes measures from the NIH toolbox to determine the relationship to patient outcomes. The mRS is a standard outcome measure for patients with ICH. The NIH developed and validated HRQoL measures Patient-Reported Outcomes Measurement Information System (PROMIS), Quality of Life in Neurological Disorders (Neuro-QoL), and objective function NIH Toolbox are the most sensitive and provide statistically powerful estimates of patient outcomes in survivors of ICH.

Future Directions: This study is designed to identify hemostatic factor abnormalities and mechanisms of ICH hematoma expansion treatable with targeted therapies (e.g., desmopressin to counteract aspirin effect or fibrinolysis inhibitors). Machine learning algorithms will be employed for predicting patient outcomes after ICH and may illuminate when HE is most impactful and determine specific therapies which improve patient outcomes.

This study is funded by a National Institutes of Health (NIH)/ The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) grant ID: SP0049593; R01 NS110779.

Disclosures

Naidech: NIH: Other: NS110779-Grant.