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eCART is a software product that provides automated risk stratification and early warning for impending patient deterioration, signified as the composite outcome of death or ICU transfer. It is intended to be used on hospitalized ward patients 18 years of age or older by trained medical professionals. As a clinical decision support device, eCART's risk score and trend analysis is intended to aid clinical teams in identifying which patients are most likely to clinically deteriorate. eCART provides additional information and does not replace the standard of care or clinical judgment. eCART scoring is initiated by the documentation of any vital sign on an adult ward patient. The device calculates risk only from validated EHR data, such as vitals that have been confirmed by a registered nurse (RN); unvalidated data streaming from monitors/devices will not be used until confirmed by a healthcare professional. The product predictions are for reference only and no therapeutic decisions should be made based solely on the eCART scores.

The AgileMD eCARTv5 Clinical Deterioration Suite ("eCART") is a cloud-based software device that is integrated into the electronic health record ("EHR") in order to anticipate clinical deterioration in adult ward patients, which is signified as either of the following two predicted outcomes: (1) death or (2) ICU transfer. The tool synthesizes routine vital signs, laboratory data, and patient demographics into a single value that can be used to flag patients at-risk of the composite outcome of clinical deterioration for additional evaluation and monitoring. eCARTv5 requires the healthcare system within which it will be used, to provide an EHR connection and data interfaces through which the patient data necessary to run the software will be transmitted. The primary functions of the system are imparted by the Gradient Boosted Machine ("GBM") learning algorithm that takes input directly from the EHR, in real time, to provide an assessment of patients and displays its outputs in an intuitive user interface which drives providers to follow standardized clinical workflows (established by their institutions) for elevated-risk patients. eCARTv5's end users include med-surg nursing staff, physicians and other providers caring for these patients. The eCARTv5 composite score is determined from the model output (predicted probability of deterioration) scaled from 0-100, based on the specificity (true negative rate). The observed rate of deterioration at each eCART score threshold, displayed as the odds of deterioration in the next 24 hours, is presented to the user along with the scaled score. Default thresholds are set to an eCART of 93 and 97, respectively, for moderate and high risk categorization.

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. CLEWICU is considered to provide additional information regarding the patient's predicted future risk for clinical deterioration, as well as identifying patients at low risk for deterioration. The product predictions are for reference only and no therapeutic decisions should be made based solely on the CLEWICU predictions.

The CLEWICU System is a stand-alone analytical software product that includes the ClewICUServer and the ClewICUnitor. It uses models derived from machine learning to calculate the likelihood of occurrence of certain clinically significant events for patients in hospital critical care settings including: - Intensive Care Unit (ICU) . - . Emergency Department's (ED) Critical Care or Resuscitation area - Post-Anesthesia Care Unit (PACU) . - . Step-Down Unit - Post-Surgical Recovery Unit . - . Other Specialized Care Units (e.g., Cardiac Care Unit (CCU), Neurocritical Care Unit (NCU), High-dependency Care Unit (HDU) ClewICUServer and ClewICUnitor are software-only devices that are run on a user-provided server or cloud-infrastructure. The ClewICUServer is a backend software platform that imports patient data from various sources including Electronic Health Record (EHR) data and patient monitoring devices through an HL7 data connection. The data are then used by models operating within the ClewICUServer to compute and store the CLEWHI index (likelihood of hemodynamic instability requiring vasopressor / inotrope support), and CLEWLR (indication that the patient is at "low risk" for deterioration). The ClewICUnitor is the web-based user interface displaying CLEWHI, and CLEWLR associated notifications and related measures, as well as presenting the overall unit status.

The SignalHF System is intended for use by qualified healthcare professionals (HCP) managing patients over 18 years old who are receiving physiological monitoring for Heart Failure surveillance and implanted with a compatible Cardiac Implantable Electronic Devices (CIED) (i.e., compatible pacemakers, ICDs, and CRTs). The SignalHF System provides additive information to use in conjunction with standard clinical evaluation. The SignalHF HF Score is intended to calculate the risk of HF for a patient in the next 30 days. This System is intended for adjunctive use with other physiological vital signs and patient symptoms and is not intended to independently direct therapy.

SignalHF is a software as medical device (SaMD) that uses a proprietary and validated algorithm, the SignalHF HF Score, to calculate the risk of a future worsening condition related to Heart Failure (HF). The algorithm computes this HF score using data obtained from (i) a diverse set of physiologic measures generated in the patient's remotely accessible pre-existing cardiac implant (activity, atrial burden, heart rate variability, heart rate, heart rate at rest, thoracic impedance (for fluid retention), and premature ventricular contractions per hour), and (ii) his/her available Personal Health Records (demographics). SignalHF provides information regarding the patient's health status (like a patient's stable HF condition) and also provides alerts based on the SignalHF HF evaluation. Based on an alert and a recovery threshold on the SignalHF score established during the learning phase of the algorithm and fixed for all patients, our monitoring system is expected to raise an alert 30 days (on median) before a predicted HF hospitalization event. SignalHF does not provide a real-time alert. Rather, it is designed to detect chronic worsening of HF status. SignalHF is designed to provide a score linked to the probability of a future decompensated heart failure event specific to each patient. Using this adjunctive information, healthcare professionals can make adjustments for the patient based on their clinical judgement and expertise. The score and score-based alerts provided through SignalHF can be displayed on any compatible HF monitoring platform, including the Implicity platform. The healthcare professional (HCP) can utilize the SignalHF HF score as adjunct information when monitoring CIED patients with remote monitoring capabilities. The HCP's decision is not based solely on the device data which serves as adjunct information, but rather on the full clinical and medical picture and record of the patient.

The Global Hypoperfusion Index (GHI) algorithm provides the clinician with physiological insight into a patient's likelihood of future hemodynamic instability. The GHI algorithm provides the risk of a global hypoperfusion event (defined as SvO2 ≤ 60% for at least 1 minute) occurring in the next 10-15 minutes. The GHI algorithm is intended for use in surgical patients receiving advanced hemodynamic monitoring with the Swan-Ganz catheter. The GHI algorithm is considered to provide additional information regarding the patient's predicted future risk for clinical deterioration, as well as identifying patients at low risk for deterioration. The product predictions are for reference only and no therapeutic decisions should be made based solely on the GHI algorithm predictions.

The Global Hypoperfusion Index (GHI) parameter provides the clinician with physiological insight into a patient's likelihood of a global hypoperfusion event on average 10-15 minutes before mixed venous oxygen saturation (SvO2) reaches 60%. The GHI feature is intended for use in surgical or nonsurgical patients. The product predictions are adjunctive for reference only and no therapeutic decisions should be made based solely on the GHI parameter.

CLEWICU provides the clinician with physiological insight into a patient's likelihood of future hemodynamic instability. CLEWICU is intended for use with intensive care unit (ICU) patients 18 years and over. CLEWICU is considered to provide additional information regarding the patient's predicted future risk for clinical deterioration, as well as identifying patients at low risk for deterioration. The product predictions are for reference only and no therapeutic decisions should be made based solely on the CLEWICU predictions.

The CLEWICU System is a stand-alone analytical software product that includes the ClewICUServer and the ClewICUnitor. It uses models derived from machine learning to calculate the likelihood of occurrence of certain clinically significant events for patients in the intensive care unit (ICU). ClewICUServer and ClewICUnitor are software-only devices that are installed on user-provided hardware. The ClewICUServer is a backend software platform that imports patient data from various sources including Electronic Health Record (EHR) data and medical device data. The data are then used by models operating within the ClewICUServer to compute and store the CLEWHI index (likelihood of hemodynamic instability requiring vasopressor / inotrope support), and CLEWLR (indication that the patient is at "low risk" for deterioration). The ClewICUnitor is the web-based user interface displaying CLEWHI, and CLEWLR associated notifications and related measures, as well as presenting the overall unit status.