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Sepsis-Induced Coagulopathy and Japanese Association for Acute Medicine DIC in Coagulopathic Patients with Decreased Antithrombin and Treated by Antithrombin.

ABSTRACT: Disseminated intravascular coagulation (DIC) in patients with sepsis represents a critical condition. Thus, a simple and rapid diagnosis is required. The purpose of this study was to compare the performances of a recently developed Sepsis-Induced Coagulopathy (SIC) with the Japanese Association for Acute Medicine (JAAM) DIC. Four hundred nine patients with sepsis having coagulopathy and antithrombin activity of less than 70% and treated with antithrombin were retrospectively analyzed, and the SIC and JAAM-DIC criteria on days 1 (before treatment), 2, 4, and 7 were compared. The prevalence of JAAM-DIC on day 1 was significantly higher than that of SIC (91.4% vs 81.8%, P = .003), but there were no differences on days 2, 4, and 7. The mortality rates in the SIC and JAAM-DIC groups were both 23.3%. The specificity to 28-day mortality on day 1 was higher in the SIC group (15.8% vs 9.2%, P = .013). There were no differences in sensitivity on days 1, 2, 4, and 7. Mortality was significantly different between SIC-positive and SIC-negative groups on days 2, 4, and 7 ( P < .01, respectively), while significant differences were seen between JAAM-DIC-positive and JAAM-DIC-negative groups only on days 4 and 7 ( P < .05, .01, respectively). In summary, the SIC characteristics were similar to the JAAM-DIC group, and the classifications were comparable in terms of mortality prediction. The SIC scoring system is simple, easy to use, and adaptable to the new sepsis definitions and offers an important approach to evaluating patients in emergency and critical care settings.

SUBMITTER: Iba T

PROVIDER: S-EPMC6714750 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Sepsis-Induced Coagulopathy and Japanese Association for Acute Medicine DIC in Coagulopathic Patients with Decreased Antithrombin and Treated by Antithrombin.

Iba Toshiaki T Arakawa Makoto M Levy Jerrold H JH Yamakawa Kazuma K Koami Hiroyuki H Hifumi Toru T Sato Koichi K

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis 20180425 7

Disseminated intravascular coagulation (DIC) in patients with sepsis represents a critical condition. Thus, a simple and rapid diagnosis is required. The purpose of this study was to compare the performances of a recently developed Sepsis-Induced Coagulopathy (SIC) with the Japanese Association for Acute Medicine (JAAM) DIC. Four hundred nine patients with sepsis having coagulopathy and antithrombin activity of less than 70% and treated with antithrombin were retrospectively analyzed, and the SI ...[more]

PMID: 29695178

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Project description:INTRODUCTION: Current criteria for early diagnosis of coagulopathy in sepsis are limited. We postulated that coagulopathy is already complicated with sepsis in the initial phase, and severe coagulopathy or disseminated intravascular coagulation (DIC) becomes overt after progressive consumption of platelet and coagulation factors. To determine early diagnostic markers for severe coagulopathy, we evaluated plasma biomarkers for association with subsequent development of overt DIC in patients with sepsis. METHODS: A single-center, prospective observational study was conducted in an adult ICU at a university hospital. Plasma samples were obtained from patients with sepsis at ICU admission. Fourteen biomarkers including global markers (platelet count, prothrombin time, activated partial thromboplastin time, fibrinogen and fibrin degradation product (FDP)); markers of thrombin generation (thrombin-antithrombin complex (TAT) and soluble fibrin); markers of anticoagulants (protein C (PC) and antithrombin); markers of fibrinolysis (plasminogen, ?2-plasmin inhibitor (PI), plasmin-?2-PI complex, and plasminogen activator inhibitor (PAI)-1); and a marker of endothelial activation (soluble E-selectin) were assayed. Patients who had overt DIC at baseline were excluded, and the remaining patients were followed for development of overt DIC in 5 days, and for mortality in 28 days. RESULTS: A total of 77 patients were enrolled, and 37 developed overt DIC within the following 5 days. Most patients demonstrated hemostatic abnormalities at baseline with 98.7% TAT, 97.4% FDP and 88.3% PC. Most hemostatic biomarkers at baseline were significantly associated with subsequent development of overt DIC. Notably, TAT, PAI-1 and PC discriminated well between patients with and without developing overt DIC (area under the receiver operating characteristic curve (AUROC), 0.77 (95% confidence interval, 0.64 to 0.86); 0.87 (0.78 to 0.92); 0.85 (0.76 to 0.91), respectively), and using the three together, significantly improved the AUROC up to 0.95 (vs. TAT, PAI-1, and PC). Among the significant diagnostic markers for overt DIC, TAT and PAI-1 were also good predictors of 28-day mortality (AUROC, 0.77 and 0.81, respectively). CONCLUSIONS: Severe coagulation and fibrinolytic abnormalities on ICU admission were associated with subsequent development of overt DIC. A single measurement of TAT, PAI-1, and PC activity could identify patients with ongoing severe coagulopathy, early in the course of sepsis.

Project description:Background: Sepsis-induced coagulopathy (SIC) denotes an increased mortality rate and poorer prognosis in septic patients. Objectives: Our study aimed to develop and validate machine-learning models to dynamically predict the risk of SIC in critically ill patients with sepsis. Methods: Machine-learning models were developed and validated based on two public databases named Medical Information Mart for Intensive Care (MIMIC)-IV and the eICU Collaborative Research Database (eICU-CRD). Dynamic prediction of SIC involved an evaluation of the risk of SIC each day after the diagnosis of sepsis using 15 predictive models. The best model was selected based on its accuracy and area under the receiver operating characteristic curve (AUC), followed by fine-grained hyperparameter adjustment using the Bayesian Optimization Algorithm. A compact model was developed, based on 15 features selected according to their importance and clinical availability. These two models were compared with Logistic Regression and SIC scores in terms of SIC prediction. Results: Of 11,362 patients in MIMIC-IV included in the final cohort, a total of 6,744 (59%) patients developed SIC during sepsis. The model named Categorical Boosting (CatBoost) had the greatest AUC in our study (0.869; 95% CI: 0.850-0.886). Coagulation profile and renal function indicators were the most important features for predicting SIC. A compact model was developed with an AUC of 0.854 (95% CI: 0.832-0.872), while the AUCs of Logistic Regression and SIC scores were 0.746 (95% CI: 0.735-0.755) and 0.709 (95% CI: 0.687-0.733), respectively. A cohort of 35,252 septic patients in eICU-CRD was analyzed. The AUCs of the full and the compact models in the external validation were 0.842 (95% CI: 0.837-0.846) and 0.803 (95% CI: 0.798-0.809), respectively, which were still larger than those of Logistic Regression (0.660; 95% CI: 0.653-0.667) and SIC scores (0.752; 95% CI: 0.747-0.757). Prediction results were illustrated by SHapley Additive exPlanations (SHAP) values, which made our models clinically interpretable. Conclusions: We developed two models which were able to dynamically predict the risk of SIC in septic patients better than conventional Logistic Regression and SIC scores.

Dataset Information

Sepsis-Induced Coagulopathy and Japanese Association for Acute Medicine DIC in Coagulopathic Patients with Decreased Antithrombin and Treated by Antithrombin.

Publications

Sepsis-Induced Coagulopathy and Japanese Association for Acute Medicine DIC in Coagulopathic Patients with Decreased Antithrombin and Treated by Antithrombin.

Similar Datasets

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