Pressly, Michelle
(2020)
Dynamic Modeling of Coagulation Advances the Bloody Fight to Improve Patient Outcomes.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Treating hospitalized patients with coagulation problems can prove complex. In trauma or obstetrics, complex coagulation events present a unique challenge to clinicians. These challenges are amplified by interpatient variability, dynamic changes, transfusion decisions, and source of the event. When the coagulation process is abnormal (insufficient or excessive), the risk of hemorrhage or venous thromboembolism increases. Dynamic modeling has the potential as a tool for identifying a patient's coagulation state. Thereby, dynamic modeling provides a method for the improvement in clinical response. Multiple published models capture the coagulation cascade in varying levels of complexity. However, one significant void demonstrated in the literature is the lack of direct application of a coagulation model to clinically available data to improve medical protocols.
To address this void, simplified coagulation models are proposed to capture blood coagulation data from the Thromboelastogram, or TEG, to subtype coagulopathy. The combination of dynamic and statistical models with the initial minutes of data provides actionable data to clinicians much sooner than the TEG, which usually takes over an hour. Providing outputs to clinicians sooner in trauma and obstetrics settings can be the difference between a good and a bad outcome. Focusing on the obstetric population, other efforts of this work aim to determine the physiological dynamics that could drive venous thromboembolism with a mechanistic model assessing coagulation challenges faced during and after birth. In parallel, to broadly understand risk factors that could lead to adverse coagulation events, statistical models of a large obstetric database are constructed in order to analyze both insufficient and excessive clotting challenges faced by obstetric patients. Developed models and methods have expedited understanding and treatment decisions around patient coagulation.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
28 September 2020 |
| Date Type: |
Publication |
| Defense Date: |
14 July 2020 |
| Approval Date: |
28 September 2020 |
| Submission Date: |
27 July 2020 |
| Access Restriction: |
1 year -- Restrict access to University of Pittsburgh for a period of 1 year. |
| Number of Pages: |
188 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Chemical Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Blood, Dynamic Modeling, Statistics, Trauma, Obstetrics |
| Date Deposited: |
28 Sep 2020 18:51 |
| Last Modified: |
28 Sep 2021 05:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/39467 |
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