Articles: sepsis.
-
The incidence of sepsis-induced coagulopathy (SIC) is high, leading to increased mortality rates and prolonged hospitalization and intensive care unit (ICU) stays. Early identification of SIC patients at risk of in-hospital mortality can improve patient prognosis. The objective of this study is to develop and validate machine learning (ML) models to dynamically predict in-hospital mortality risk in SIC patients. ⋯ Anion gap and age emerged as the most significant features for predicting the mortality risk in SIC. In this study, an ML model was constructed that exhibited excellent performance in predicting in-hospital mortality risk in SIC patients. Specifically, the stacking ensemble model demonstrated superior predictive ability.
-
Elevated central venous pressure (CVP) is deemed as a sign of right ventricular (RV) dysfunction. We aimed to characterize the echocardiographic features of RV in septic patients with elevated CVP, and quantify associations between RV function parameters and 30-day mortality. ⋯ Echocardiographic findings demonstrated a high prevalence of RV-related abnormalities (RV enlargement, RV systolic dysfunction and PVR increase) in septic patients with elevated CVP. Among those echocardiographic parameters, TAPSE and PVR were independently associated with 30-day mortality in these patients.
-
The prognostic evaluation of the septic patient has recently been enriched by some predictive indices such as albumin concentration, lactate/albumin ratio (LAR) and C-reactive protein/albumin ratio (CAR). The performance of these indices has been evaluated in septic patients in intensive care, but until now their performance in infected patients in the Emergency Department (ED) has not been evaluated. ⋯ All three indices had a good discriminatory ability for the risk of short-term death in patients with infection, indicating their promising use in the ED as well as in the ICU. Further studies are needed to confirm the better performance of albumin compared to LAR and CAR.
-
Multicenter Study Observational Study
Long-term risk of death in patients with infection attended by prehospital emergency services.
To develop and validate a risk model for 1-year mortality based on variables available from early prehospital emergency attendance of patients with infection. ⋯ The model showed excellent ability to predict 1-year mortality based on epidemiological, analytical, and clinical variables, identifying patients at high risk of death soon after their first contact with the health care system.