Early prediction of septic shock in hospitalized patients

2010 ◽  
Vol 5 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Steven W. Thiel ◽  
Jamie M. Rosini ◽  
William Shannon ◽  
Joshua A. Doherty ◽  
Scott T. Micek ◽  
...  
Keyword(s):  
Septic Shock ◽  
Hospitalized Patients ◽  
Early Prediction

scholarly journals Dissemination of extreme levels of extracellular vesicles: tissue factor activity in patients with severe COVID-19

2021 ◽  
Vol 5 (3) ◽  
pp. 628-634
Author(s):  
Christophe Guervilly ◽  
Amandine Bonifay ◽  
Stephane Burtey ◽  
Florence Sabatier ◽  
Raphaël Cauchois ◽  
...  
Keyword(s):  
Septic Shock ◽  
Tissue Factor ◽  
Extracellular Vesicles ◽  
Severe Disease ◽  
Plasminogen Activator Inhibitor ◽  
Hospitalized Patients ◽  
Plasminogen Activator Inhibitor 1 ◽  
Thrombotic Risk ◽  
Public Health Challenges ◽  
Inflammatory State

Abstract Coronavirus disease 2019 (COVID-19) has become one of the biggest public health challenges of this century. Severe forms of the disease are associated with a thrombo-inflammatory state that can turn into thrombosis. Because tissue factor (TF) conveyed by extracellular vesicles (EVs) has been implicated in thrombosis, we quantified the EV-TF activity in a cohort of hospitalized patients with COVID-19 (n = 111) and evaluated its link with inflammation, disease severity, and thrombotic events. Patients with severe disease were compared with those who had moderate disease and with patients who had septic shock not related to COVID-19 (n = 218). The EV-TF activity was notably increased in patients with severe COVID-19 compared with that observed in patients with moderate COVID-19 (median, 231 [25th to 75th percentile, 39-761] vs median, 25 [25th to 75th percentile, 12-59] fM; P < .0001); EV-TF was correlated with leukocytes, D-dimer, and inflammation parameters. High EV-TF values were associated with an increased thrombotic risk in multivariable models. Compared with patients who had septic shock, those with COVID-19 were characterized by a distinct coagulopathy profile with significantly higher EV-TF and EV-fibrinolytic activities that were not counterbalanced by an increase in plasminogen activator inhibitor-1 (PAI-1). Thus, this article is the first to describe the dissemination of extreme levels of EV-TF in patients with severe COVID-19, which supports the international recommendations of systematic preventive anticoagulation in hospitalized patients and potential intensification of anticoagulation in patients with severe disease.

Sepsis-3 Septic Shock Criteria and Associated Mortality Among Infected Hospitalized Patients Assessed by a Rapid Response Team

CHEST Journal ◽  
2018 ◽  
Vol 154 (2) ◽  
pp. 309-316 ◽  
Author(s):  
Shannon M. Fernando ◽  
Peter M. Reardon ◽  
Bram Rochwerg ◽  
Nathan I. Shapiro ◽  
Donald M. Yealy ◽  
...  
Keyword(s):  
Septic Shock ◽  
Rapid Response Team ◽  
Hospitalized Patients ◽  
Rapid Response ◽  
Response Team

scholarly journals Temporal Belief Memory: Imputing Missing Data during RNN Training

2018 ◽  
Author(s):  
Yeo Jin Kim ◽  
Min Chi
Keyword(s):  
Septic Shock ◽  
Missing Data ◽  
Real Time ◽  
Short Term Memory ◽  
Early Prediction ◽  
Short Term ◽  
Time Intervals ◽  
Domain Experts ◽  
Long Short Term Memory ◽  
Temporal Sequences

We propose a bio-inspired approach named Temporal Belief Memory (TBM) for handling missing data with recurrent neural networks (RNNs). When modeling irregularly observed temporal sequences, conventional RNNs generally ignore the real-time intervals between consecutive observations. TBM is a missing value imputation method that considers the time continuity and captures latent missing patterns based on irregular real time intervals of the inputs. We evaluate our TBM approach with real-world electronic health records (EHRs) consisting of 52,919 visits and 4,224,567 events on a task of early prediction of septic shock. We compare TBM against multiple baselines including both domain experts' rules and the state-of-the-art missing data handling approach using both RNN and long-short term memory. The experimental results show that TBM outperforms all the competitive baseline approaches for the septic shock early prediction task. 

Recent Temporal Pattern Mining for Septic Shock Early Prediction

2018 ◽  
Author(s):  
Farzaneh Khoshnevisan ◽  
Julie Ivy ◽  
Muge Capan ◽  
Ryan Arnold ◽  
Jeanne Huddleston ◽  
...  
Keyword(s):  
Septic Shock ◽  
Temporal Pattern ◽  
Pattern Mining ◽  
Early Prediction ◽  
Temporal Pattern Mining

Cardiovascular response to dopamine and early prediction of outcome in septic shock: A prospective multiple-center study*

2005 ◽  
Vol 33 (10) ◽  
pp. 2172-2177 ◽  
Author(s):  
Bruno Levy ◽  
Benjamin Dusang ◽  
Djillali Annane ◽  
Sebastien Gibot ◽  
Pierre-Edouard Bollaert
Keyword(s):  
Septic Shock ◽  
Cardiovascular Response ◽  
Early Prediction ◽  
Prediction Of Outcome ◽  
Center Study

scholarly journals CLINICAL COURSE AND OUTCOME OF COVID-19 ACUTE RESPIRATORY DISTRESS SYNDROME: DATA FROM A NATIONAL REPOSITORY

2020 ◽  
Author(s):  
Ali A. El-Solh ◽  
Umberto G. Meduri ◽  
Yolanda Lawson ◽  
Michael Carter ◽  
Kari A. Mergenhagen
Keyword(s):  
Septic Shock ◽  
Renal Failure ◽  
Acute Renal Failure ◽  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome ◽  
Hospitalized Patients ◽  
Historical Cohort ◽  
Risk Of Death

ABSTRACTBackgroundMortality attributable to coronavirus disease-19 (COVID-19) 2 infection occurs mainly through the development of viral pneumonia-induced acute respiratory distress syndrome (ARDS).Research QuestionThe objective of the study is to delineate the clinical profile, predictors of disease progression, and 30-day mortality from ARDS using the Veterans Affairs Corporate Data Warehouse.Study Design and MethodsAnalysis of a historical cohort of 7,816 hospitalized patients with confirmed COVID-19 infection between January 1, 2020, and August 1, 2020. Main outcomes were progression to ARDS and 30-day mortality from ARDS, respectively.ResultsThe cohort was comprised predominantly of men (94.5%) with a median age of 69 years (interquartile range [IQR] 60-74 years). 2,184 (28%) were admitted to the intensive care unit and 643 (29.4%) were diagnosed with ARDS. The median Charlson Index was 3 (IQR 1-5). Independent predictors of progression to ARDS were body mass index (BMI)≥ 40 kg/m2, diabetes, lymphocyte counts<700×109/L, LDH>450 U/L, ferritin >862 ng/ml, C-reactive protein >11 mg/dL, and D-dimer >1.5 ug/ml. In contrast, the use of an anticoagulant lowered the risk of developing ARDS (OR 0.66 [95% CI 0.49-0.89]. Crude 30-day mortality rate from ARDS was 41% (95% CI 38%-45%). Risk of death from ARDS was significantly higher in those who developed acute renal failure and septic shock. Use of an anticoagulant was associated with two-fold reduction in mortality. Survival benefit was observed in patients who received corticosteroids and/or remdesivir but there was no advantage of combination therapy over either agent alone.ConclusionsAmong those hospitalized for COVID-19, nearly one in ten progressed to ARDS. Septic shock, and acute renal failure are the leading causes of death in these patients. Treatment with either remdesivir and corticosteroids reduced the risk of mortality from ARDS. All hospitalized patients with COVID-19 should be placed at a minimum on prophylactic doses of anticoagulation.

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