Abstract
BackgroundSepsis remains the leading cause of mortality in-hospital in the intensive care unit (ICU). Continuous renal replacement therapy (CRRT) is recommended as an adjuvant therapy for hemodynamics management in patients with sepsis. The aim of this study was to develop an adaptive least absolute shrinkage and selection operator (LASSO) for the Cox regression model to predict the hospital mortality in patients with Sepsis-3.0 undergoing CRRT using Medical Information Martin Intensive Care (MIMIC)-III v1.4.MethodsPatients who met the Sepsis-3.0 definition were identified using the MIMIC-III v1.4. Among them, patients who received CRRT during ICU hospitalization were included in this study. According to the survival status, patients were split into death or survival group. Adaptive LASSO for the Cox regression model was constructed by STATA software. At last, nomogram and Kaplan-Meier curves were drawn to validate the model.ResultsA total of 181 patients who met Sepsis 3.0 criteria received CRRT were included in the study, in which, there were 31 deaths and 150 survivals during hospitalization, respectively. The overall in-hospital mortality was 17.1%. According to the results of multivariate Cox-LASSO regression analysis, use of vasopressor, international normalized ratio (INR) ≥1.5, and quick sequential organ failure assessment (qSOFA) score were associated with hospital mortality in patients with sepsis who underwent CRRT, but lactate level, mechanical ventilation (MV) support, PaO2/FiO2, platelet count, and indicators of acute kidney injury (AKI), such as blood urea nitrogen (BUN) and creatinine, were not independently associated with hospital mortality after adjusted by qSOFA. The risk nomogram and Kaplan-Meier curves verified that the use of vasopressor and INR ≥1.5 possess significant predictive value.ConclusionsUsing the Cox-LASSO regression model, use of vasopressor, INR ≥1.5, and qSOFA score are found to be associated with hospital mortality in patients with Sepsis-3.0 who received CRRT. This finding may assist clinicians in tailoring precise management and therapy for these patients who underwent CRRT.
Highlights
Sepsis is a major condition with high morbidity and mortality in intensive care unit (ICU) patients [1]
We excluded those with conditions who may be associated with hospital mortality, such as: [1] the length of ICU stay
The age, gender, ethnicity, first service type, blood infection, and the length of ICU stay showed no significant difference between survival and non-survival groups
Summary
Sepsis is a major condition with high morbidity and mortality in intensive care unit (ICU) patients [1]. Severe sepsis and septic shock are characterized by vasoplegia and alterations of microcirculation, resulting in aggressively hemodynamic alterations that render the patient hypotensive or with organ dysfunction [2,3,4,5]. Sepsis remains the leading cause of mortality in-hospital in the intensive care unit (ICU). Continuous renal replacement therapy (CRRT) is recommended as an adjuvant therapy for hemodynamics management in patients with sepsis. The aim of this study was to develop an adaptive least absolute shrinkage and selection operator (LASSO) for the Cox regression model to predict the hospital mortality in patients with Sepsis-3.0 undergoing CRRT using Medical Information Martin Intensive Care (MIMIC)-III v1.4
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