Is Coagulopathy an Appropriate Therapeutic Target During Critical Illness Such as Trauma or Sepsis?

Moore, Hunter B.; Winfield, Robert D.; Aibiki, Mayuki; Neal, Matthew D.

doi:10.1097/shk.0000000000000854

Cited by 23 publications

(19 citation statements)

References 101 publications

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“…Specific to traumatic injury, trauma‐induced coagulopathy (TIC) appears to stem from various factors including shock, hemodilution, hypothermia, inflammation, and acidemia . In addition, there are unique, trauma‐derived mechanisms that result in an endogenous coagulopathy, making TIC a separate disease entity from DIC . Nevertheless, in some patients after severe injury, the pathophysiology of TIC largely resembles DIC, including decreased fibrinogen levels and antithrombin III, in addition to increased prothrombin time and thrombin–antithrombin III complexes.…”

Section: Systemic Role Of Vwf In Coagulopathy and Inflammation Followmentioning

confidence: 99%

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Von Willebrand factor as a thrombotic and inflammatory mediator in critical illness

et al. 2020

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The endothelial exocytosis of high‐molecular‐weight multimeric von Willebrand factor (vWF) may occur in critical illness states, including trauma and sepsis, leading to the sustained elevation and altered composition of plasma vWF. These critical illnesses involve the common process of sympathoadrenal activation and loss of the endothelial glycocalyx. As a prothrombotic and proinflammatory molecule that interacts with the endothelium, the alterations exhibited by vWF in critical illness have been implicated in the development and damaging effects of downstream pathologies, such as disseminated intravascular coagulation and systemic inflammatory response syndrome. Given the role of vWF in these pathologies, there has been a recent push to further understand how the molecule may be involved in the pathophysiology of related diseases, such as trauma‐induced coagulopathy and acute renal injury, which are also known to develop secondarily to critical illness states. Elucidation of the role of vWF across the broader spectrum of generalized pathologies may provide a basis for the development of novel preventative and restorative measures, while also bolstering the scaffold of more widely used treatments, such as the administration of plasma‐containing blood products.

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Section: Systemic Role Of Vwf In Coagulopathy and Inflammation Followmentioning

confidence: 99%

“…In traumatic injury, coagulation factors are lost or consumed due to hemorrhage and its attendant effects . The tenets of hemostatic resuscitation in the care of trauma patients appropriately emphasize replacement of these lost coagulation factors with plasma products.…”

Section: Effect Of Vwf On Clinical Management With Blood Productsmentioning

confidence: 99%

Von Willebrand factor as a thrombotic and inflammatory mediator in critical illness

et al. 2020

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“…8 We retrospectively investigated the correlation between the presepsin value trend and prognosis, and investigated coagulation abnormalities in sepsis. In patients with multiple organ dysfunction, coagulopathy is known to be common in sepsis and associated with a worse prognosis.…”

Section: Introductionmentioning

confidence: 99%

“…In patients with multiple organ dysfunction, coagulopathy is known to be common in sepsis and associated with a worse prognosis. 8 We retrospectively investigated the correlation between the presepsin value trend and prognosis, and investigated coagulation abnormalities in sepsis.…”

Section: Introductionmentioning

confidence: 99%

An evaluation of clinical inflammatory and coagulation markers in patients with sepsis: a pilot study

Fujii

Fujino

Eguchi

2019

Acute Medicine & Surgery

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Aim Presepsin values could assist early diagnosis and prognosis of sepsis. In sepsis, prognosis is determined according to multiple organ dysfunction, where coagulopathy is common and associated with prognosis. This study aimed to determine the correlation between presepsin value trend and prognosis, and investigate coagulation abnormality in sepsis. Methods We retrospectively examined 18 intensive care unit patients diagnosed with sepsis whose presepsin values at admission were ≥500 ng/mL. If presepsin values had decreased ≥50% on hospital day 6, compared to admission values, the patient was allocated into a decreased presepsin group. Results Presepsin values in non‐survivors with sepsis were significantly higher than in survivors on day 6 (P = 0.022). No significant differences in procalcitonin or C‐reactive protein were identified between survivors and non‐survivors, and platelet counts were significantly lower in non‐survivors on days 0, 3, and 6 (P = 0.001, P < 0.001, and P = 0.001, respectively). The 90‐day mortality rate in a decreased presepsin group significantly improved, even when presepsin values were high on admission (P = 0.012). Platelet counts were significantly lower on all hospital days in the non‐decreased presepsin group. Conclusion Fifty percent decrease in presepsin levels could be a useful prognostic predictor of sepsis. Larger studies are required to confirm our findings.

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“…Our results revealed that complication of coagulopathy and coagulation profile during admission, including platelet counts, PT, APTT, and INR, were associated with increased in-hospital death among patients developed postoperative sepsis. The occurrence of coagulopathy was commonly complicated with sepsis, which was strongly related to organ dysfunction and poor outcomes (24,25). The activation of monocytes and endothelial cells is evident in the early phase of sepsis and results in massive exposure of tissue factor, thereby contributing to the over activation of coagulation and subsequent thrombin generation (26).…”

Section: Discussionmentioning

confidence: 99%

A machine learning-based prediction of hospital mortality in patients with postoperative sepsis

Yao

Jin²,

Wang

et al. 2020

Preprint

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Background: The incidence of postoperative sepsis is continually increased, while few studies have specifically focused on the risk factors and clinical outcomes associated with the development of sepsis after surgical procedures. The present study aimed to develop a mathematical model for predicting the in-hospital mortality among patients with postoperative sepsis.Methods: Surgical patients in Medical Information Mart for Intensive Care (MIMIC-III) database who simultaneously fulfilled Sepsis 3.0 as well as Agency for Healthcare Research and Quality (AHRQ) criteria during ICU admission were incorporated. We employed both extreme gradient boosting (XGBoost) and stepwise logistic regression model to predict in-hospital mortality among included patients with postoperative sepsis. Consequently, model performance was assessed from the angles of discrimination and calibration.Results: We included 3713 patients who fulfilled our inclusion criteria, in which 397 (10.7%) patients died during hospitalization, while 3316 (89.3%) of them survived through discharge. Fluid-electrolyte disturbance, coagulopathy, renal replacement therapy (RRT), urine output, and cardiovascular surgery were important features related to the in-hospital mortality. The XGBoost model had a better performance in both discriminatory ability (c-statistics, 0.835 [95% CI, 0.786 to 0.877] vs. c-statistics, 0.737 [95% CI, 0.688 to 0.786]) and goodness of fit (visualized by calibration curve) compared to the stepwise logistic regression model. Conclusion: XGBoost model appears to be a better performance in predicting hospital mortality among postoperative septic patients compared to the conventional stepwise logistic regression model. Machine learning-based algorithm might have significant application in the development of early warning system for septic patients following major operations.

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Is Coagulopathy an Appropriate Therapeutic Target During Critical Illness Such as Trauma or Sepsis?

Cited by 23 publications

References 101 publications

Von Willebrand factor as a thrombotic and inflammatory mediator in critical illness

Von Willebrand factor as a thrombotic and inflammatory mediator in critical illness

An evaluation of clinical inflammatory and coagulation markers in patients with sepsis: a pilot study

A machine learning-based prediction of hospital mortality in patients with postoperative sepsis

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