The CLEWICU System is a software platform that uses AI machine learning models to predict the likelihood of future hemodynamic instability in adult patients in various hospital critical care units. It integrates patient data from electronic health records and monitoring devices to help clinicians assess a patient's risk of clinical deterioration or stability, providing valuable physiological insights as an aid to clinical judgment.
CLEWICU provides the clinician with physiological insight into a patient’s likelihood of future hemodynamic instability. CLEWICU is intended for use in hospital critical care settings for patients 18 years and over, providing additional information on predicted risk for clinical deterioration and identifying low risk patients. Predictions are for reference only and not for sole therapeutic decisions.
The system consists of the ClewICUServer backend software running machine learning models on patient data imported from electronic health records and monitoring devices via HL7 connection, and the ClewICUnitor web-based interface displaying model outputs. It calculates indices representing likelihood of hemodynamic instability and low risk status for patients in critical care.
Validation studies using retrospective cohorts from independent datasets (UMass eICU and MIMIC-III) demonstrated model sensitivity and specificity meet predefined clinical acceptance criteria, confirming performance after retraining with reduced input features. Software validation followed IEC 62304 standards.
No predicate devices specified
Submission
9/28/2023
FDA Approval
1/13/2024
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