ArticlePloS one2018
A local and global sensitivity analysis of a mathematical model of coagulation and platelet deposition under flow.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 85 citations in OpenAlex.
- Mathematical modeling of flow-mediated thrombin generation after treatment of postoperative bleeding in cardiac surgery with cardiopulmonary bypass.Journal of thrombosis and haemostasis : JTH · 2026Article
- Mechanisms of thrombin inhibition by protein S and the TFPIα-fVshort-protein S complex.Biophysical journal · 2026Article
- Determination of Patient-Specific Blood Coagulation Kinetic Parameters via Neural Networks: Toward Thrombosis Prediction in Personalized Medicine.Annals of biomedical engineering · 2025Article
- Rankings of tuberculosis antibiotic treatment regimens are sensitive to spatial scale, detection limit, and initial host bacterial burden.Journal of theoretical biology · 2025Article
- A new look at TFPI inhibition of factor X activation.PLoS computational biology · 2024Article
- Mathematical modeling identifies clotting factor combinations that modify thrombin generation in normal and factor VIII-, IX-, or XI-deficient blood.Research and practice in thrombosis and haemostasis · 2024Article
- Studying the Effects of Oral Contraceptives on Coagulation Using a Mathematical Modeling Approach.Mathematical modeling for women's health : Collaborative Workshop for Women in Mathematical Biolog. Collaborative Workshop for Women in Mathematical Biology (2022) · 2024Article
- Unravelling the impact of SARS-CoV-2 on hemostatic and complement systems: a systems immunology perspective.Frontiers in immunology · 2024Article
- A model of fluid-structure and biochemical interactions for applications to subclinical leaflet thrombosis.International journal for numerical methods in biomedical engineering · 2023Article
- Inhibition of platelet-surface-bound proteins during coagulation under flow I: TFPI.Biophysical journal · 2023Article
- Inhibition of platelet-surface-bound proteins during coagulation under flow II: Antithrombin and heparin.Biophysical journal · 2023Article
- Article
- Critical evaluation of kinetic schemes for coagulation.PloS one · 2023Article
- Analysis of Hepatic Lipid Metabolism Model: Simulation and Non-Stationary Global Sensitivity Analysis.Nutrients · 2022Article
- Modelling the performance of an integrated fixed-film activated sludge (IFAS) system: a systematic approach to automated calibration.Scientific reports · 2022Article
- Understanding virtual patients efficiently and rigorously by combining machine learning with dynamical modelling.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke.Frontiers in cardiovascular medicine · 2022Review
- Exploring the sensitivity in jellyfish locomotion under variations in scale, frequency, and duty cycle.Journal of mathematical biology · 2021Article
- Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model.Journal of theoretical biology · 2021Article
- Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
The hemostatic response involves blood coagulation and platelet aggregation to stop blood loss from an injured blood vessel. The complexity of these processes make it difficult to intuit the overall hemostatic response without quantitative methods. Mathematical models aim to address this challenge but are often accompanied by numerous parameters choices and thus need to be analyzed for sensitivity to such choices. Here we use local and global sensitivity analyses to study a model of coagulation and platelet deposition under flow. To relate with clinical assays, we measured the sensitivity of three specific thrombin metrics: lag time, maximum relative rate of generation, and final concentration after 20 minutes. In addition, we varied parameters of three different classes: plasma protein levels, kinetic rate constants, and platelet characteristics. In terms of an overall ranking of the model's sensitivities, we found that the local and global methods provided similar information. Our local analysis, in agreement with previous findings, shows that varying parameters within 50-150% of baseline values, in a one-at-a-time (OAT) fashion, always leads to significant thrombin generation in 20 minutes. Our global analysis gave a different and novel result highlighting groups of parameters, still varying within the normal 50-150%, that produced little or no thrombin in 20 minutes. Variations in either plasma levels or platelet characteristics, using either OAT or simultaneous variations, always led to strong thrombin production and overall, relatively low output variance. Simultaneous variation in kinetics rate constants or in a subset of all three parameter classes led to the highest overall output variance, incorporating instances with little to no thrombin production. The global analysis revealed multiple parameter interactions in the lag time and final concentration leading to relatively high variance; high variance was also observed in the thrombin generation rate, but parameters attributed to that variance acted independently and additively.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.