Prognostic value of sepsis-induced coagulation abnormalities: an early assessment in the emergency department

Innocenti, Francesca; Gori, Anna Maria; Giusti, Betti; Tozzi, Camilla; Donnini, Chiara; Meo, Federico De; Giacomelli, Irene; Ralli, Maria; Sereni, Alice; Sticchi, Elena; Zari, M.; Caldi, Francesca; Tassinari, Irene; Zanobetti, Maurizio; Marcucci, Rossella; Pini, Riccardo

doi:10.1007/s11739-018-1990-z

Cited by 19 publications

(9 citation statements)

References 19 publications

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“…Lyons et al reported that the increased severity of coagulopathy can lead to increased mortality [16]. Besides, hemostasis-related parameter has also been reported as a predictor of sepsis-related mortality [17][18][19]. In this study, we found that the INR value in death group was signi cantly higher than in survival group and it was an independent factor for 90-day death identi ed by multivariate analysis.…”

Section: Discussionsupporting

confidence: 54%

A novel nomogram to predict 90-day mortality of patients with sepsis

Zeng¹,

He²,

Zhang³

et al. 2021

Preprint

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Background Sepsis is a prevalent disease among intensive care units and continues to be a frequent cause of death. This study aimed to establish a nomogram for mortality prediction in patients with sepsis. Methods We carried out a retrospective, single-center study based on 231 patients with sepsis and data was collected from May 2018 to October 2020. Patients were randomly split into training and validation cohorts. In the training cohort, multivariate logistic regression analysis and a stepwise algorithm were performed to identify risk factors, which were presented with a predictive nomogram. The receiver operating characteristic (ROC), calibration plots and decision curve analysis (DCA) were used to estimate the performance of the nomogram in both the training and validation cohorts. Results A total of 231 patients with sepsis were enrolled in the study, and the 90-day mortality was 31.6%. There were 161 and 70 cases in training and validation cohorts respectively. Statistical analyses showed that Age, international normalized ratio (INR), lactate (Lac), and thrombomodulin (TM) were the risk factors for 90-day mortality. The area under the curve was 0.810 (95% CI, 0.739 to 0.881) in training cohort and 0.813(95% CI, 0.708 to 0.917) in the validation cohort. Calibration curve showed good performance of this nomogram. Decision curve analysis demonstrated that the nomogram was clinical utility. Conclusion This nomogram offering a probability of mortality for a given patient can benefit outcome improvement and clinicians in making clinical decision.

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Section: Discussionsupporting

confidence: 54%

A novel nomogram to predict 90-day mortality of patients with sepsis

Zeng¹,

He²,

Zhang³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…This method has been developed to a relatively mature stage, and the sensitivity and specificity can be maintained at a high level. 28 The screening process is relatively simple and fast, and can be synchronized with the DD measurement process. 29 Therefore, TAT is a relatively simple and reasonable indicator for coagulation system.…”

Section: Discussionmentioning

confidence: 99%

The Risk Factors of VTE and Survival Prognosis of Patients With Malignant Cancer: Implication for Nursing and Treatment

Hu²,

Chen

et al. 2020

Clin Appl Thromb Hemost

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Venous thromboembolism (VTE) is very common in patients with malignant cancer. We aimed to conduct a retrospective analysis on the risk factors of VTE and its survival prognosis of patients with malignant cancer, to provide evidence into the management of VTE. Patients with malignant cancer treated in our hospital were selected. The characteristic of patients and related lab detection results including activated partial thromboplastin time (APTT), plasma prothrombin time (PT) and thrombin coagulation time (TT), fibrinogen (FIB), thrombin AT-Ⅲ complex (TAT) and D-dimer (D-D) were collected and analyzed. And logistic regression analyses were performed to identify the potential risk factors. And ROC curves were established to evaluate their predictive ability of VTE for patients with malignant cancers. A total of 286 patients were included, of which 63 patients had VTE, the incidence of VTE in patients with malignant cancers was 22.03%. There were significant differences on the D-D, TAT level between VTE and no VTE patients (all P < 0.05). The survival condition of VTE patients was significantly worse than that of no VTE patients(P = 0.017). D-D (RR7.895, 3.228∼19.286) and TAT (6.122, 2.244∼16.695) were risk factors of VTE for patients with cancers (all P < 0.05). The area under the curve (AUC) of D-D, TAT and combined use was 0.764, 0.698, 0.794 respectively, and the cutoff value for D-D, TAT was 1.835mg/L and 4.58μg/L respectively. For cancer patients with D-D >1.835 mg/L and TAT >4.58 μg/L, early interventions are needed for the prophylaxis of VTE.

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“…Coagulopathy is frequently observed in sepsis [ 15 ], and it contributes to multiple organ dysfunction syndrome [ 16 ]. More severe coagulopathy has been linked to higher risk of mortality among patients with sepsis [ 17 ], and clinical parameters reflecting hemostasis can predict sepsis-related mortality [ 18 – 20 ]. Our results are consistent with this literature.…”

Section: Discussionmentioning

confidence: 99%

Prediction of 90‐Day Mortality among Sepsis Patients Based on a Nomogram Integrating Diverse Clinical Indices

Zeng

He²,

Zhang

et al. 2021

BioMed Research International

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Background. Sepsis is prevalent among intensive care units and is a frequent cause of death. Several studies have identified individual risk factors or potential predictors of sepsis-associated mortality, without defining an integrated predictive model. The present work was aimed at defining a nomogram for reliably predicting mortality. Methods. We carried out a retrospective, single-center study based on 231 patients with sepsis who were admitted to our intensive care unit between May 2018 and October 2020. Patients were randomly split into training and validation cohorts. In the training cohort, multivariate logistic regression and a stepwise algorithm were performed to identify risk factors, which were then integrated into a predictive nomogram. Nomogram performance was assessed against the training and validation cohorts based on the area under receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis. Results. Among the 161 patients in the training cohort and 70 patients in the validation cohort, 90-day mortality was 31.6%. Older age and higher values for the international normalized ratio, lactate level, and thrombomodulin level were associated with greater risk of 90-day mortality. The nomogram showed an AUC of 0.810 (95% CI 0.739 to 0.881) in the training cohort and 0.813 (95% CI 0.708 to 0.917) in the validation cohort. The nomogram also performed well based on the calibration curve and decision curve analysis. Conclusion. This nomogram may help identify sepsis patients at elevated risk of 90-day mortality, which may help clinicians allocate resources appropriately to improve patient outcomes.

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Prognostic value of sepsis-induced coagulation abnormalities: an early assessment in the emergency department

Cited by 19 publications

References 19 publications

A novel nomogram to predict 90-day mortality of patients with sepsis

A novel nomogram to predict 90-day mortality of patients with sepsis

The Risk Factors of VTE and Survival Prognosis of Patients With Malignant Cancer: Implication for Nursing and Treatment

Prediction of 90‐Day Mortality among Sepsis Patients Based on a Nomogram Integrating Diverse Clinical Indices

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