Articles: sepsis.
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J Clin Monit Comput · Apr 2024
Early prediction of mortality at sepsis diagnosis time in critically ill patients by using interpretable machine learning.
This study applied machine learning for the early prediction of 30-day mortality at sepsis diagnosis time in critically ill patients. Retrospective study using data collected from the Medical Information Mart for Intensive Care IV database. The data of the patient cohort was divided on the basis of the year of hospitalization, into training (2008-2013), validation (2014-2016), and testing (2017-2019) datasets. 24,377 patients with the sepsis diagnosis time < 24 h after intensive care unit (ICU) admission were included. ⋯ The calibration plot for the model revealed a slope of 1.03 (95% CI 0.94-1.12) and intercept of 0.14 (95% CI 0.04-0.25). The SHAP revealed the top three most significant features, namely age, increased red blood cell distribution width, and respiratory rate. Our study demonstrated the feasibility of using the interpretable machine learning model to predict mortality at sepsis diagnosis time.
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Critical care medicine · Apr 2024
Antibiotics, Sedatives, and Catecholamines Further Compromise Sepsis-Induced Immune Suppression in Peripheral Blood Mononuclear Cells.
We hypothesized that the immunosuppressive effects associated with antibiotics, sedatives, and catecholamines amplify sepsis-associated immune suppression through mitochondrial dysfunction, and there is a cumulative effect when used in combination. We thus sought to determine the impact of the exemplar drugs ciprofloxacin, propofol, and norepinephrine, used alone and in combination, at clinically relevant concentrations, on the ex vivo functionality of peripheral blood mononuclear cells (PBMCs) drawn from healthy, infected, and septic individuals. ⋯ Drugs commonly used in critical care lead to significant immune dysfunction ex vivo and enhance sepsis-associated immunosuppression. Further studies are required to identify underlying mechanisms and potential impact on patient outcomes.
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Pulmonary emboli (PE) is a life threatening condition that discovered in many patients only "post mortem". Sub massive and massive PE that led to hemodynamic collapse characterized by right ventricular (RV) dysfunction, leading to a higher risk of death. ⋯ Clinical parameters and hematological parameters could predict death of patients admitted with acute PE. RV diameter, measured by the non-ECG gated CTPA, had an additive predictive value for patients who admitted to the ICU.
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Serum and radiological parameters used to predict prognosis in COVID patients are not feasible in the Emergency Department. Due to its damaging effect on multiple organs and lungs, scores used to assess multiorgan damage and pneumonia such as Pandemic Medical Early Warning Score (PMEWS), National Early Warning Score 2 (NEWS2), WHO score, quick Sequential Organ Failure Assessment (qSOFA), and DS-CRB 65 can be used to triage patients in the Emergency Department. They can be used to predict patients with the highest risk of seven-day mortality and need for intensive respiratory or vasopressor support (IRVS). ⋯ PMEWS may be used for triaging patients presenting to the Emergency Department with COVID-19 and accurately predicts the need for IRVS and seven day mortality.
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Objective: The role of immune cells in sepsis remains unclear, and there is some controversy. Here, we aim to systematically assess whether distinct immune cell phenotypes impact the susceptibility to sepsis. Methods: In this study, we harnessed publicly available summary-level data from genome-wide association studies (GWASs). ⋯ Following FDR correction, only one immunophenotype was confirmed to be negatively correlated with the 28-day mortality: CD39 on CD39+ CD8br (OR, 0.820; 95% CI, 0.737~0.912; P < 0.001, PFDR = 0.184). Conclusion: This study, for the first time, has uncovered indicative evidence of a causal relationship between circulating immune cell phenotypes and varying degrees of sepsis through genetic means. These findings underscore the significance of immune cells in the pathogenesis of sepsis.