This study aims to prospectively validate the GRADY prediction models, which use machine learning algorithms to estimate the risk of gram-negative bacteremia and sepsis in intensive care unit (ICU) patients based on routinely collected vital signs and laboratory data. Sepsis, a life-threatening condition associated with high ICU mortality, requires early diagnosis and treatment-yet current diagnostic methods relying on blood cultures are time-consuming. Existing scoring systems such as SOFA, SIRS, and NEWS2 often lack sufficient sensitivity and specificity in early sepsis detection. Unlike traditional tools, the GRADY models seek to provide earlier and more accurate risk stratification. This study will compare the clinical performance of GRADY models against standard scoring systems and explore their integration as early warning tools to support rapid intervention and improve outcomes in critical care.
Patients aged 18 years or older
ICU stay of 48 hours or longer
Patients from whom blood cultures were obtained during routine monitoring
Signed informed consent form
Patients younger than 18 years
ICU stay shorter than 48 hours
Patients without blood cultures
Patients over the age of 18 who are suspected of having bacteremia while being treated in intensive care will be included in the study.
Cohort
Prospective
Not listed
Gram(-) negative bacteremia
Gram (-) bacteria growth in blood culture
SOFA
The Sequential Organ Failure Assessment (SOFA) score is a clinical tool that evaluates the extent of a patient's organ dysfunction based on six parameters - respiratory function (PaO₂/FiO₂), coagulation (platelet count), liver function (bilirubin level), cardiovascular status (mean arterial pressure or vasopressor use), central nervous system function (Glasgow Coma Scale), and renal function (creatinine level or urine output) - and it will be assessed at the time of patient admission.
SIRS
The Systemic Inflammatory Response Syndrome (SIRS) criteria are used to identify a generalized inflammatory state based on four parameters - body temperature, heart rate, respiratory rate or PaCO₂, and white blood cell count
NEWS-2
The National Early Warning Score 2 (NEWS-2) is a clinical scoring system used to assess the severity of a patient's acute illness based on six parameters - respiratory rate, oxygen saturation, systolic blood pressure, heart rate, level of consciousness or new confusion, and temperature
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