Predicting the risk of invasive fungal infections in ICU sepsis population: the AMI risk assessment tool.

Background: Invasive fungal infections (IFI) represent a significant contributor to mortality among sepsis patients in the Intensive Care Unit (ICU). Early diagnosis of IFI is challenging, and currently, there are no predictive tools for identifying sepsis patients who may develop IFI. Our study aims to develop a predictive scoring system to assess the risk of IFI in patients with sepsis admitted to the ICU.

Optimal fluid resuscitation targets in septic patients with acutely decompensated heart failure.

Background: To determine the optimal fluid resuscitation volume in septic patients with acutely decompensated heart failure (ADHF).

Methods: Septic patients with ADHF were identified from a tertiary urban medical center. The generalized additive models were used to explore the association between fluid resuscitation volume and endpoints, and the initial 3 h fluid resuscitation volume was divided into four groups according to this model: < 10 mL/kg group, ≥ 10 to ≤ 15 mL/kg group, > 15 to ≤ 20 mL/kg group, and > 20 mL/kg group.

Combining host immune response biomarkers and clinical scores for early prediction of sepsis in infection patients.

Background: The performance of host immune responses biomarkers and clinical scores was compared to identify infection patient populations at risk of progression to sepsis, ICU admission and mortality.

Methods: Immune response biomarkers were measured and NEWS, SIRS, and MEWS. Logistic and Cox regression models were employed to evaluate the strength of association.