Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host immune response to an infection. Sepsis is often associated with significant hemostatic disorders that may lead to extensive intravascular thrombosis, disseminated intravascular coagulation (DIC), multi-organ dysfunction syndrome (MODS), and increased mortality. Sepsis-induced coagulopathy (SIC) is currently recognized as an early distinct phase of hemostatic derangement caused by sepsis, and a prodrome of overt DIC. SIC is characterized by endovascular clotting activation, hypercoagulability, and consumption of clotting factors and platelets. DIC, traditionally considered the final stage of this process, is now recognized as a part of a continuum of pathophysiological dysregulation with a distinct clinical significance. Despite being extensively studied in the adult population, SIC remains poorly defined in neonates. The distinct characteristics of neonatal hemostasis, coupled with immunological immaturity, pose significant challenges to the direct application of adult diagnostic approaches of SIC in this population. This review focuses on the pathophysiological mechanisms of SIC and the unique characteristics of neonatal hemostasis, summarizes current knowledge regarding the underlying mechanisms of neonatal SIC, and explores the developmental interplay between inflammation and hemostasis. By integrating current evidence, the review aims to establish a conceptual framework that will guide future experimental and clinical studies directed toward improving the management and outcomes of neonates who develop coagulopathy during sepsis.

Sepsis-induced disseminated intravascular coagulation (DIC) is characterized by impaired fibrinolysis, partly due to neutrophil elastase-mediated plasminogen degradation. We aimed to evaluate whether plasminogen supplementation could restore fibrinolytic capacity in patients with sepsis-induced coagulopathy and in a murine model of septic DIC. 60 patients with sepsis-induced coagulopathy were randomized to receive 12mL/kg of placebo (NaCl 0.9%) or OctaplasLG®, a pathogen-inactivated pooled human plasma containing 2µM plasminogen. Pre- and post-infusion levels of functional plasminogen, plasmin generation, and fibrinolysis markers (plasmin-antiplasmin complexes, plasminogen activator inhibitor-1, and tissue-type plasminogen activator) were measured. In parallel, in a sepsis-induced DIC model, transgenic TMpro/pro mice received either purified plasminogen or placebo. Functional plasminogen levels and plasmin generation were assessed via enzymatic assays. In patients, baseline plasminogen and plasmin generation were significantly lower than in healthy controls. OctaplasLG® significantly increased functional plasminogen (+ 46nM [-96; 118] vs. -84 [-180; 27] nM, p < 0.05) and improved plasmin generation (0.12 [-0.25; 1.27] vs. -0.36 [-1.58; 0.12] fmol, p < 0.05). No changes were observed in plasmin-antiplasmin, plasminogen activator inhibitor-1, or tissue-type plasminogen activator levels. A non-significant trend toward reduced mortality was noted in patients receiving OctaplasLG® (42.3% vs. 60.0%). Septic DIC-mice also exhibited reduced functional plasminogen (100 [66-126] vs. 295 [268-343] nM) and impaired plasmin generation (1.8 [1.4-2.1] vs. 3.0 [2.8-3.3] fmol, p < 0.05), which were restored after plasminogen supplementation (plasminogen: 346 [287; 360] nM; plasmin generation: 4.1 [3.7; 5.5] fmol). Plasminogen supplementation restores fibrinolytic capacity, supporting its therapeutic potential in sepsis-induced DIC.

Sepsis-induced coagulopathy (SIC) is known to be linked with an increased mortality of sepsis. We designed this study to investigate whether there is heterogeneity in the clinical manifestations of SIC between cases with international normalized ratio (INR) as the dominant factor and those with platelet (PLT) as the dominant factor. In this survey, 1421 SIC patients admitted to Peking Union Medical College Hospital were enrolled. External verification was conducted using data from 4732 SIC patients in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. According to the difference of INR and PLT, SIC was divided into four subtypes: SIC-severe (PLT < 100 and INR > 1.4), SIC-INR (PLT ≥ 100 and INR > 1.4), SIC-PLT (PLT < 100 and INR ≤ 1.4), and SIC-mild (100 ≤ PLT < 150 and 1.2 < INR ≤ 1.4). The incidence of SIC in sepsis patients was 48.70% (1421/2918). Compared with the SIC-INR group, the SIC-PLT group had shorter activated partial thromboplastin time, lower fibrinogen levels, lower lactate levels, and lower blood glucose levels (P < 0.05). Regarding liver function, compared to the SIC-INR group, the SIC-PLT group exhibited lower levels of total bilirubin, direct bilirubin, and alanine aminotransferase (P < 0.05). Concerning kidney function, the proportion of patients receiving continuous renal replacement therapy support in the SIC-PLT group was lower than that in the SIC-INR group (P < 0.05). There was no statistically significant difference in SOFA total score between the SIC-INR group and the SIC-PLT group after deducting the coagulation system score. In terms of outcomes, there were no statistically differences in costs and mortality between the SIC-INR and the SIC-PLT group, but the SIC-PLT group had shorter duration of mechanical ventilation and hospital stays after diagnosis of sepsis than the SIC-INR group (P < 0.05). Data from the MIMIC-IV database further corroborate there was heterogeneity between the SIC-INR group and the SIC-PLT group. The incidence rate of DVT in the SIC-PLT group was significantly lower than that in the SIC-INR group (P < 0.05). SIC with PLT change as the dominant factor and SIC with INR change as the dominant factor exhibited significant heterogeneity. Sepsis-induced coagulopathy (SIC), a condition that can lead to DIC, is associated with a significantly higher mortality rate. The diagnosis of SIC relies on the international normalized ratio (INR), which is a measure of blood clotting time, and platelet count (PLT), in conjunction with the sequential organ failure assessment (SOFA). Compared with SIC cases where INR changes are the dominant factor, those with PLT changes as the dominant factor exhibit milder liver and kidney impairment and require shorter durations of mechanical ventilation time and hospital stay after diagnosis. When studying SIC, it is important to note the heterogeneity of the aforementioned phenotypes.

Coagulopathy is a key driver of organ dysfunction during sepsis/septic shock, yet its relationship with microcirculatory autoregulation is not fully characterized. This study aimed to evaluate the association between sepsis-induced coagulopathy (SIC) and alterations in tissue oxygenation, oxygen extraction capacity and microvascular reactivity. Prospective observational study on 23 adult septic patients. Coagulation status was evaluated with standard laboratory parameters and thromboelastography (TEG). A SIC score ≥ 4 was used to identify the presence of coagulopathy. The peripheral (skeletal muscle) tissue oxygen saturation (StO2) was assessed using thenar near infrared spectroscopy (NIRS). By combining a vascular occlusion test, the desaturation rate during ischemia was assessed as an index of oxygen extraction capacity: this was measured separately for the first (StO2 downslope-1) and last part (StO2 downslope-2) of the desaturation curve, and the difference between the two was calculated (delta-downslope). The reoxygenation rate (StO2 upslope) and the area of the hyperemic phase were calculated to evaluate microvascular reactivity. In patients with SIC, the delta-downslope was higher (1.7 ± 2.5 versus -0.8 ± 3.2, p = 0.049) and the StO2 upslope was reduced (96 ± 74 versus 185 ± 91, p = 0.017), suggesting altered tissue oxygen extraction capacity and microvascular reactivity. Both parameters were able to discriminate the presence of SIC in the receiver operating characteristics curve analysis. Negative correlations were found between StO2 downslope-1 and TEG maximum amplitude (r = -0.470, p = 0.023), and Delta-Downslope and platelet count (r = -0.527, p = 0.01). SIC is associated with alterations in peripheral tissue oxygen extraction capacity and microvascular reactivity.

Sepsis-Induced coagulopathy (SIC) is not only a common complication in the development process of sepsis but also related to poor prognosis of sepsis. We aimed to establish a machine learning (ML) model to predict the 28-day mortality risk of patients with SIC. We collected data for model training from the Medical Information Mart for Intensive Care IV Database version 2.2 to establish the model. We extracted patient data from the First Affiliated Hospital of Wenzhou Medical University for the model's external validation. We used Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression analysis to identify predictive factors for a 28-day mortality risk. Then, we built prognostic prediction models for SIC patients using multiple ML classification models. We evaluated predictive performance using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA). We used Shapley Additive Explanations (SHAP) to interpret the models. We selected seventeen variables for model development, and the XGBoost model performed the best. The area under the curve (AUC) (95% CI) of the test set reached 0.840 (0.810-0.870), with an accuracy of 0.807, sensitivity of 0.836, and specificity of 0.798. The model also demonstrated excellent predictive performance in external validation, with an AUC (95% CI) of 0.864 (0.794-0.934). We constructed an XGBoost model and provided model interpretability using the SHAP. This model provides a basis for assessing the 28-day mortality risk of patients with SIC, aiding in clinical decision support and the formulation of personalized treatment strategies.

This study aimed to investigate the relationship between the timing of anticoagulation initiation and clinical outcomes in critically ill patients with sepsis-induced coagulopathy (SIC). We conducted a retrospective cohort study using the MIMIC-IV database. Adult patients diagnosed with SIC (ISTH-SIC score ≥ 4) and receiving anticoagulation therapy during their ICU stay were included. Anticoagulation therapy was defined as administration of unfractionated heparin, low-molecular-weight heparin, vitamin K antagonists, or direct oral anticoagulants, as captured in medication records; additionally, a heparin-only analysis was performed given its predominant use in this population. Patients were stratified into early (≤ 48hours post-ICU admission) or delayed (> 48hours) anticoagulation groups. Baseline characteristics were balanced using propensity score matching (PSM). Primary outcomes included 28-day, 60-day, and 90-day mortality. Cox proportional hazard models were applied to assess survival differences across subgroups. Among 12738 eligible patients, 10689 received early anticoagulation and 2049 received delayed treatment. After PSM (n=3986), delayed anticoagulation was associated with significantly lower 28-day mortality (15% vs 19%, P < 0.001), and similar reductions were observed at 60 and 90days. Kaplan-Meier survival curves showed significantly better survival in the delayed group (P < 0.001). Subgroup analyses revealed that the survival benefit was more pronounced in patients aged >65years, those without acute kidney injury (AKI), platelet count ≥ 100×109/L, Sequential Organ Failure Assessment score ≥ 6, and those treated with unfractionated heparin. Among critically ill patients with SIC, delayed initiation of anticoagulation was independently associated with improved short- and medium-term survival. These findings support a phenotype-guided, time-stratified approach to anticoagulation in sepsis and highlight the need for prospective trials to validate optimal timing strategies.

Cytosporone B ameliorates hypercoagulability in sepsis by agonizing the Nur77-thrombomodulin pathway.

Sphincterotomy during endoscopic biliary drainage in cholangitis with sepsis-induced coagulopathy increases bleeding without clinical benefits.

Multi-omics integration reveals molecular heterogeneity and constructs a machine learning survival model for sepsis-induced coagulopathy.

Anthrax toxins exacerbate sepsis-induced coagulopathy and endothelial dysfunction in a baboon model of anthrax.

To develop and evaluate a nomogram model for predicting prolonged ICU length of stay (LOS) in patients with sepsis-induced coagulopathy (SIC), identify associated risk factors, and facilitate early identification of high-risk patients, with the aim of optimizing clinical management strategies, improving patient outcomes, and enhancing ICU resource utilization. A total of 3728 patients meeting the diagnostic criteria of International Society for Thrombosis and Hemostasis (ISTH) criteriawere included fromthe Medical Information Mart for Intensive Care (MIMIC-IV) database. Based on the third quartile value of ICU LOS in the cohort, patients were categorized into a prolonged ICU LOS group (≥ 5days) and a non-prolonged ICU LOS group (< 5days). General demographic data, clinical characteristics, and laboratory test results within 24h of ICU admission were collected to identify independent risk factors for prolonged ICU LOS in SIC patients. Predictive variables were selected using LASSO-logistic regression combined with Shapley Additive Explanations (SHAP) for interpretability. A nomogram model was constructed and evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Among the 3728 enrolled patients, 832 had a prolonged ICU LOS (≥ 5days), while 2896 had a non-prolonged ICU LOS (< 5days). LASSO-logistic regression and SHAP analysis identified six predictive variables: SOFA score, heart rate, monocyte percentage, acute kidney injury (AKI), use of vasopressors, and use of mechanical ventilation. The nomogram demonstrated an area under the curve (AUC) of 0.737 (95% CI 0.716-0.758). Risk factors for prolonged LOS in patients with SIC included: increased SOFA score, elevated heart rate, higher monocyte percentage, occurrence of AKI, use of vasopressors, and use of mechanical ventilation. By integrating these readily available clinical indicators into an intuitive nomogram, we have developed a practical risk assessment tool for clinicians. This tool aids in the identification of SIC patients at risk for prolonged hospitalization. Furthermore, our analysis revealed that prolonged LOS was significantly associated with increased long-term mortality. The application of this predictive model may ultimately contribute to reducing ICU length of stay and improving patient prognosis.

Sepsis-induced coagulopathy (SIC) is commonly observed in patients with sepsis and is correlated with an elevated risk of mortality. The objective of this study is to analyse the association between the lactate-to-albumin ratio (LAR) and the occurrence of SIC, as well as all-cause mortality. From the MIMIC-IV3.1 database, patients with sepsis who fulfilled the inclusion criteria were selected. The relationship between LAR and SIC was assessed by constructing a multivariate logistic regression model and performing Restricted cubic spline (RCS) analysis. To evaluate the predictive ability of different biomarkers for SIC, we performed ROC curve analysis. Subgroup analysis verifies the robustness of the results. Additionally, Cox regression analysis was conducted to investigate the association between LAR and mortality. A total of 8,661 patients with sepsis were included in the final analysis, of whom 5,784 developed SIC. In the comprehensive logistic regression model, each additional unit of LAR increased the odds of SIC rather by 1.85 (OR, 2.85, 95% CI, 2.48-3.28; p < 0.001). The odds of SIC rather in the highest LAR group was significantly increased (T3 vs T1: OR, 3.57; 95% CI, 3.06-4.17; p < 0.001). The relationship between LAR levels and SIC incidence was found to be nonlinear and positive, as revealed by RCS analysis. ROC analysis indicated superior predictive performance of LAR (AUC = 0.71) compared to albumin (AUC = 0.61) or lactate (AUC = 0.69). Subgroup analysis indicates a stable relationship between LAR and SIC. Moreover, an increase in LAR was correlated with a heightened risk of mortality at both 28 days and 360 days (28-d HR, 1.15; 95% CI, 1.11-1.19; 360-d HR, 1.14; 95% CI, 1.11-1.18; all p < 0.001). Observational findings indicate that elevated early LAR levels may be associated with increased rates of SIC and all-cause mortality in patients with sepsis. However, further prospective studies are needed to validate these associations and assess their clinical utility.

Thrombosis, bleeding, and mortality in patients with sepsis-induced coagulopathy: Analysis of a prospective cohort.

OBJECTIVES:Sepsis-induced coagulopathy (SIC) is a common complication in patients with sepsis and septic shock. Early detection of SIC is crucial for timely intervention, as it can significantly impact patient outcomes. This study aims to evaluate the prevalence of SIC and its impact on the 28-day mortality rate in patients with sepsis and septic shock.METHODS:A single-center retrospective observational cohort study was conducted in Vietnam from January 2021 to August 2024. Adult patients diagnosed with sepsis or septic shock who were admitted to the intensive care unit within 24 h of initial presentation were included. Patients with do-not-resuscitate orders, coagulopathy, malignant blood disorders, incomplete data, or refusal of treatment were excluded. SIC scores were assessed, and 28-day mortality rates were recorded.RESULTS:A total of 340 patients were included, with 216 (63.5%) exhibiting SIC (SIC score ≥4). The mean age of patients was 69.01 ± 17.04 years, and the majority were male (61.5%). Septic shock accounted for 79.7% of the cases. SIC patients had significantly higher mortality rates at both 4 days (17.6% vs. 4.8%, P = 0.001) and 28 days (40.3% vs. 24.4%, P = 0.005). Nonsurvivors exhibited higher SIC (73.9% vs. 57.9%, P = 0.003) and had worse disease severity scores. Multivariate analysis confirmed that SIC score ≥4 was strongly associated with increased 28-day mortality (odds ratio 1.799, P = 0.033).CONCLUSIONS:The prevalence of SIC is high in patients with sepsis and septic shock, especially in our cohorts. SIC score ≥4 is also a strong and independent predictor for 28-day mortality.

Objective: The aim of this study was to identify the risk factors for sepsis-induced coagulopathy (SIC). Methods: A retrospective analysis was conducted on 170 sepsis patients, including 131 in the SIC group and 39 in the non-SIC group. Clinical characteristics, thromboelastography parameters, and microbiological data were collected and analyzed for each patient. The predictive value of these parameters in SIC patients was evaluated using receiver operating characteristic (ROC) curve analysis. Results: Univariate analysis showed significant differences between the two groups in terms of lymphocyte count, interleukin-10 (IL-10), interleukin-6 (IL-6), digestive system tumors, history of surgical treatment, magnesium ion concentration, and thromboelastography R value (P < .05). Multivariate logistic regression analysis indicated that IL-6 (β = 0.004, OR = 1.004, 95% CI: 1.002-1.007) was an independent risk factor for SIC (P < .05), while the absolute lymphocyte count (β = -0.504, OR = 0.604, 95% CI: 0.431-0.847) was an independent protective factor (P < .05). ROC curve analysis showed that the area under the curve (AUC) for predicting SIC by absolute lymphocyte count and IL-6 was 0.716 and 0.963 (P < .05). Conclusion: lymphocyte count and IL-6 have certain predictive value for whether sepsis patients develop SIC. It is particularly noteworthy that IL-6 is not only an independent risk factor (OR = 1.004), but also shows extremely high predictive efficacy (AUC = 0.963). In clinical practice, when IL-6 levels rise, the possibility of SIC should be vigilant, and its continuous increase may also indicate a poor prognosis for SIC patients.

Sepsis is characterized by life-threatening organ dysfunction caused by an uncontrolled immune response to infection. Neutrophils play a vital role in this process, which can lead to immunothrombosis and disseminated intravascular coagulation (DIC) via the formation of neutrophil extracellular traps (NETs). This study aimed to validate the impact of NETs biomarkers in evaluating their potential as diagnostic, prognostic, and therapeutic indicators in critical care for patients with sepsis. We conducted a case-control study with a 7-day follow-up to assess mortality in 138 sepsis patients, focusing specifically on the occurrence of DIC. Additionally, 80 healthy volunteers, matched by age and sex, served as controls. Our findings reveal a strong connection between histones in sepsis and both the initial inflammatory response and sepsis-related coagulopathy/DIC. Furthermore, we found that myeloperoxidase can effectively predict short-term mortality among sepsis patients, regardless of their DIC status. This study highlights a concerning simultaneous increase in myeloperoxidase and histones (thresholds of > 84.9 ng/ml and > 126.4 ng/ml, respectively), which may serve as vital indicators indicating the urgent need for NETs inhibitors in sepsis treatment. Applying this approach, we anticipate a significant reduction in thrombotic events and mortality, thereby enhancing patient care and outcomes in the management of critical sepsis.

Sepsis is now considered a dysregulated host response in which inflammation, coagulation, and endothelial injury converge to create a self-amplifying network of thromboinflammation. This definition reflects maladaptive immunothrombosis-a defense mechanism that becomes pathogenic when excessive, rather than an isolated inflammatory process. This review integrates recent mechanistic advances linking damage-associated molecular patterns (DAMPs), endothelial dysfunction, and intravascular coagulation. Endogenous alarmins, such as high-mobility group box 1, histones, and mitochondrial DNA, engage in pattern recognition (Toll-like receptors, receptor for advanced glycation end products) to propagate leukocyte activation, platelet aggregation, and endothelial disruption. The resulting loss of critical endothelial anticoagulant molecules (thrombomodulin, endothelial cell protein C receptor, antithrombin) and glycocalyx degradation convert the vascular endothelium into a procoagulant interface. Complement activation and protease-activated receptor signaling reinforce this loop, producing microvascular thrombosis, capillary leakage, and organ ischemia. Platelet-leukocyte aggregates and neutrophil extracellular traps (NETs) serve as intravascular scaffolds for fibrin deposition, thereby propagating disseminated intravascular coagulation (DIC). Targeted interventions, including recombinant thrombomodulin, antithrombin supplementation, neutralization of NETs and DAMPs, complement blockade, and endothelial-protective strategies, seek to restore vascular homeostasis. A multidomain biomarker approach integrating DAMPs, endothelial markers, and coagulation indices, combined with machine learning-based phenotyping, may enable precision stratification of sepsis endotypes. The convergence of DAMP signaling, immune activation, and coagulation underlies the pathophysiologic continuum from sepsis-induced coagulopathy to DIC. Therapeutically interrupting this axis represents the most promising avenue toward personalized, mechanism-driven treatment in sepsis.

To identify predictors of sepsis-induced coagulopathy (SIC) in children and to establish a prediction model. Clinical data were retrospectively collected from children with sepsis treated in the pediatric intensive care unit of Xinjiang Hospital of Beijing Children's Hospital between July 2021 and December 2023. Patients were classified into the SIC group (n=64) and the non-SIC group (n=61) according to whether SIC occurred. Multivariable logistic regression was employed to identify independent predictors of SIC. A prediction model was developed based on these factors. The predictive performance and clinical utility of the model were evaluated using the area under the receiver operating characteristic curve, calibration curve, and decision curve analysis. The multivariable logistic regression analysis showed that procalcitonin, Pediatric Sequential Organ Failure Assessment (pSOFA) score, and mean platelet volume were independent predictors of SIC in children with sepsis (P<0.05). The model developed from these three predictors yielded an area under the curve of 0.903 (95%CI: 0.852-0.953; P<0.001), with sensitivity and specificity of 0.922 and 0.738, respectively. The calibration curve analysis indicated good agreement between predicted and observed outcomes. The decision curve analysis showed favorable clinical benefit of the prediction model. Procalcitonin, pSOFA score, and mean platelet volume are predictors of SIC among children with sepsis; the prediction model based on these three predictors shows high performance and has good clinical applicability.

BackgroundThere are currently no suitable biomarkers for early diagnosis and prognostic evaluation of sepsis-induced coagulopathy (SIC), therefore, studying the diagnostic and prognostic value of antithrombin III (AT-III) activity in SIC may be useful for early identification and intervention of SIC.MethodsThis study is a single-center cohort study, prospectively enrolling patients with sepsis admitted to the ICU from March 2023 to March 2024. Based on whether the SIC score was greater than or equal to 4, the enrolled sepsis patients were divided into the SIC group and the non-SIC group. The SIC scoring system consists of three parameters: International normalized ratio (INR), platelet count, and Sequential Organ Failure Assessment (SOFA) score. The measurement of AT-III activity was completed within 12 h of the patient being admitted to the ICU. The receiver operating characteristic (ROC) curve analysis and area under the ROC curve (AUC) were used to evaluate the accuracy of different biomarkers in the diagnosis and prognostic assessment of SIC. The DeLong Test was employed to compare whether there was a significant difference between AUCs. Kaplan-Meier survival curve was plotted and Log-rank test was performed to compare the 28-day survival rates among different groups.ResultsThis study included a total of 366 patients with sepsis, among which 235 (64.2%) were in the SIC group and 131 (35.8%) were in the non-SIC group. The AT-III activity in the SIC group was significantly lower than that in the non-SIC group (P < 0.001). ROC curve analysis showed that the AUC for AT-III activity was 0.799 (P < 0.001), the AUC for platelets was 0.806 (P < 0.001), the AUC for Sequential Organ Failure Assessment (SOFA) score was 0.746 (P < 0.001), and the AUC for international normalized ratio (INR) was 0.765 (P < 0.001). The results of the DeLong Test showed that the AUC for AT-III activity in diagnosing SIC had no statistically significant difference compared with the AUCs of the traditional diagnostic indicators, including platelets, SOFA score, and INR (P > 0.05). The cut-off value of AT-III activity for diagnosing SIC is 59.7%, with a sensitivity of 79.91%, specificity of 69.77%, positive predictive value (PPV) of 82.59%, and negative predictive value (NPV) of 65.94%. There was no statistical difference in AT-III activity between the survival and non-survival groups of SIC patients (P > 0.05). The proportion of shock and the duration of vasopressor use were both lower in the high AT-III group (≥ 59.7%) than in the low AT-III group < 59.7%) (P < 0.05). Kaplan-Meier survival curves showed that there was no statistically significant difference in the 28-day survival probability between the high AT-III group and the low AT-III group (P = 0.350).ConclusionAT-III activity is a potentially helpful adjunctive biomarker for diagnosing SIC that performs similarly to the biomarkers and scores currently used to diagnose SIC.

Natural products in treatment and management of sepsis-induced coagulopathy: Pharmacological basis and mechanisms.