ArticleThe Journal of surgical research2015
Thrombelastographic pattern recognition in renal disease and trauma.
Article in The Journal of surgical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 19 citations in OpenAlex.
- Artificial intelligence and machine learning for hemorrhagic trauma care.Military Medical Research · 2023Review
- The use of thromboelastography to assess post-operative changes in coagulation and predict graft function in renal transplantation.American journal of surgery · 2020Article
- Technology Advancements in Blood Coagulation Measurements for Point-of-Care Diagnostic Testing.Frontiers in bioengineering and biotechnology · 2019Review
- Microfluidics contrasted to thrombelastography: perplexities in defining hypercoagulability.The Journal of surgical research · 2018Article
- The hypercoagulability paradox of chronic kidney disease: The role of fibrinogen.American journal of surgery · 2017Article
- Evaluation of hypercoagulability state in perinatal arterial ischemic stroke with rotation thromboelastometry.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2016Article
- Clinical assessment of trauma-induced coagulopathy and its contribution to postinjury mortality: A TACTIC proposal.The journal of trauma and acute care surgery · 2015Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThrombelastography (TEG) is a viscoelastic hemostatic assay. We have observed that end-stage renal disease (ESRD) and trauma-induced coagulopathy (TIC) produce distinctive TEG tracings. We hypothesized that rigorously definable TEG patterns could discriminate between healthy controls and patients with ESRD and TIC.
methodsTEG was performed on blood from ESRD patients (n = 54) and blood from trauma patients requiring a massive blood transfusion (n = 16). Plots of independent TEG parameters were analyzed for patterns coupled to disease state, compared with controls. Decision trees for taxonomic classification were then built using the "R-Project" statistical software.
resultsMinimally overlapping clusters of TEG results were observed for the three patient groups when coordinate pairs of maximum amplitude (MA) and TEG-activated clotting time (ACT) were plotted on orthogonal axes. Based on these groupings, a taxonomical classification tree was constructed using MA and TEG ACT. Branch points were set at an ACT of 103 s, and these branches subdivided for MA at 60.8 mm for the high ACT branch and 72.6 mm for the low ACT branch, providing a correct classification rate of 93.4%.
conclusionsESRD and TIC demonstrate distinct TEG patterns. The coagulopathy of ESRD is typified by a prolonged enzymatic phase of clot formation, with normal-to-elevated final clot strength. Conversely, TIC is typified by prolonged clot formation and weakened clot strength. Our taxonomic categorization constitutes a rigorous system for the algorithmic interpretation of TEG based on cluster analysis. This will form the basis for clinical decision support software for viscoelastic hemostatic assays.
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Registered trials
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