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The Cogent HMS is intended for patients for whom the monitoring of CCO and calculated hemodynamic parameters is indicated for diagnostic and prognostic evaluation by a clinician. The Cogent HMS is intended for use with ICU Medical pulmonary artery catheters and central venous oximetry catheters and with ICU Medical Cogent sensors. The Cogent HMS is intended to measure and calculate venous oxygen saturation in patients. PulseCO functionality is limited to adult patients.

The Cogent HMS is designed to compute and display cardiac and oximetry parameters relevant to patient care in the hospital acute care areas including Intensive Care Units and the Operating Room. Monitoring parameters include cardiac output and blood oxygen saturation levels, as well as other derived hemodynamic parameters. Measurements are obtained through the compatible ICU Medical pulmonary artery and central venous oximetry catheters, and ICU Medical CardioFlo™ sensors.

Input data for derived parameters may be keyed in by a clinician or may be obtained from a bedside monitor.

The Cogent HMS provides the following functions:

• monitors patient cardiac output continuously (CCO) using continuous thermodilution -(TdCO), and intermittently, using bolus thermodilution (Bolus CO);
• monitors continuous cardiac output (CCO) using pulse power analysis on an arterial pressure waveform;
• monitors venous oxygen saturation (SvO2) by measuring the reflectance spectrum of the blood; and
• provides a general-purpose interface to the analog input/output channels of other monitoring devices.

The Cogent HMS consists of:

• a base unit (patient interface module or PIM);
• a dedicated touch-screen display unit (user interface module or UIM) which allows for patient monitoring remotely (up to 50 feet); and
• associated cables

The PIM and UIM modules communicate with each other in docked, tethered (wired) or wireless mode.

The provided text describes a 510(k) premarket notification for the ICU Medical Cogent™ Hemodynamic Monitoring System (HMS). However, the document focuses on demonstrating substantial equivalence to a predicate device (K152006) primarily due to updates to the operating system (Windows 7 to Windows 10), software (version 1.1.8 to 1.4.0), and minor hardware changes. The submission primarily relies on non-clinical testing and verification, rather than a clinical study with detailed acceptance criteria and performance metrics for a novel algorithm.

Based on the provided text, the device is an updated version of an already cleared hemodynamic monitoring system. Therefore, the "acceptance criteria" discussed are largely related to ensuring the updated device performs equivalently to its predicate and meets relevant safety and performance standards. No specific "acceptance criteria" in terms of clinical performance metrics of an AI algorithm are explicitly stated, as the device is not presented as an AI-powered diagnostic algorithm with a performance threshold to meet.

Here's a breakdown of the information based on your request, as much as can be extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

As the submission is for an updated version of an existing device, the "acceptance criteria" largely revolve around demonstrating equivalent performance to the predicate device and compliance with relevant standards. The document doesn't provide a table of precise quantitative acceptance criteria for clinical performance (e.g., sensitivity, specificity for a diagnostic algorithm) and corresponding reported performance of a novel AI component. Instead, it states that "the measurement performance of the subject device is equivalent to that of the predicate device."

2. Sample Size Used for the Test Set and Data Provenance

The document explicitly states: "No new human factors, animal, and/or clinical studies were conducted as was determined not required to demonstrate device safety and effectiveness for the subject device."

Therefore, there is no "test set" in the context of clinical data with a sample size or provenance for this specific 510(k) submission. The testing performed was primarily non-clinical (bench testing, software V&V).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

Since no new clinical studies were conducted for this submission, there is no mention of experts establishing ground truth for a test set.

4. Adjudication Method for the Test Set

Not applicable, as no new clinical test set was used.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. The device is a hemodynamic monitoring system, not an AI-assisted diagnostic imaging or interpretation tool. The submission focuses on software and hardware updates to an existing monitoring device, not the evaluation of an AI algorithm's impact on human reader performance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The "Cogent System Software Validation" and various algorithm validations (PulseCO, Bolus CO, SO2, CCO) were performed, which could be considered standalone performance evaluations of the specific algorithms within the device. However, these are validations of established medical algorithms for physiological measurements, not novel AI algorithms in the common sense. The text implies these were bench validations, not clinical standalone performance studies.

7. The Type of Ground Truth Used

For the algorithm validations (e.g., PulseCO, Bolus CO, SO2, CCO), the ground truth was established through "in vitro validation" using flow simulators or electronically generated data. This suggests a controlled laboratory environment where the "true" physiological values could be precisely set or simulated.

8. The Sample Size for the Training Set

Not applicable. The document discusses updates to an existing device and its algorithms, not the training of a new AI algorithm that would require a distinct training set. The algorithms mentioned (e.g., thermodilution, pulse power analysis) are based on established physiological principles and are not typically "trained" in the machine learning sense with large datasets.

9. How the Ground Truth for the Training Set was Established

Not applicable, as there is no mention of a training set for a novel AI algorithm.

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The Cogent™ Hemodynamic Monitoring System (HMS) is intended for patients for whom the monitoring of continuous cardiac output and calculated hemodynamic parameters is indicated for diagnostic and prognostic evaluation by a clinician. Suitability for use on a patient is up to the physician's judgment and the diameter to be used. The target population includes patients for whom hemodynamic monitoring will improve clinical care. The target populations are identical to those for the predicate devices and include: Critical Care Patients, Trauma Patients, Cardiac Surgery Patients. The Cogent™ HMS is intended for use with ICU Medical pulmonary artery catheters and central venous oximetry catheters, and with ICU Medical Cogent™ sensors. The Cogent™ HMS is intended to measure and calculate venous oxygen saturation in patients. PulseCO functionality is limited to adult patients. The intended environment for use is the hospital including Critical Care Units (such as Medical, Surgical, and Coronary), Trauma and Accident Emergency Units, Post Anesthesia Care Units, Operating Rooms, and Cardiac Catheterization labs. The Cogent™ HMS is intended to be used by trained and qualified individuals in medical and surgical intensive care units, operating rooms, trauma and accident emergency units, coronary and intensive care units and cardiac catheterization laboratories. The CogentTM HMS is restricted to one patient at a time.

The Cogent™ HMS system is designed to compute and display cardiac and oximetry parameters relevant to patient care in the hospital acute care areas including Intensive Care Units and the Operating Room. Parameters include cardiac output and blood oxygen saturation levels, as well as other derived hemodynamic parameters. Measurements are obtained through ICU Medical pulmonary artery and central venous oximetry catheters, and ICU Medical CardioFloTM sensors. Input data for derived parameters may be keyed in by a clinician or may be obtained from a bedside monitor. The Cogent™ HMS provides the following functions: monitors patient cardiac output continuously, using continuous thermodilution, and intermittently, using bolus thermodilution; monitors cardiac output continuously using Pulse Power analysis on an arterial pressure waveform; monitors venous oxygen saturation by measuring the reflectance spectrum of the blood; and provides a general-purpose interface to the analog input/output channels of other monitoring devices. The Cogent" HMS consists of a base unit (patient interface module, PIM), a dedicated touch-screen display unit (user interface module, UIM) which allows for patient monitoring remotely (up to 50 feet), and the associated cables. The modules communicate with each other in docked, tethered (wired) or wireless mode. A physically separate optical module (OpMod) connects with an oximetry catheter. The Cogent™ HMS is designed for compatibility with PA catheters via connection to existing patient cables, i.e. unchanged cables as supplied with the primary predicate Q2 Plus. For the purpose of PulseCO™ data acquisition, the Cogent™ HMS is designed for compatibility with the CardioFloTM sensor and the new CardioFloTM reusable cable. In order to calculate blood oxygen saturation, the Cogent™ HMS is designed for compatibility with the existing optical module, its existing integrated cable and its associated compatible PA and oximetry catheters.

Here's an analysis of the provided text regarding the acceptance criteria and the study that proves the device meets those criteria:

The document primarily focuses on demonstrating substantial equivalence to predicate devices rather than defining specific acceptance criteria for a novel device performance. However, based on the content, we can infer some "acceptance criteria" through the comparison to predicate devices.

1. A table of acceptance criteria and the reported device performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Bench Tests (CCO, TdCO, SO2 algorithms): The sample size or specific dataset characteristics for the simulated physiological data are not explicitly provided. It simply states "bench simulation."
• Bench Test (PulseCO algorithm): The sample size or specific dataset characteristics are not explicitly provided. It states "the same simulated physiological data set as was used for the secondary predicate device."
• Animal Study: The sample size was 5 pigs. The provenance is not specified (e.g., country of origin, prospective/retrospective), but it describes an intervention-based study, suggesting it was prospective in design within the animal model.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• For the bench tests, the ground truth was established by the simulated physiological data set. There is no mention of human experts establishing ground truth for these tests.
• For the animal study, the ground truth was established by "accepted reference devices." The number, qualifications, or adjudication method of human experts in establishing this "ground truth" or comparing to reference devices is not specified.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• None explicitly mentioned. The ground truth for bench tests was simulated data, and for the animal study, it was "accepted reference devices." There's no indication of human expert adjudication.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• No MRMC study was done. The device (Cogent™ Hemodynamic Monitoring System) is a diagnostic computer for physiological parameters, not an imaging AI device where human readers interact directly with AI output. The document explicitly states: "No clinical performance testing was required to demonstrate device safety and effectiveness."

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Yes, standalone performance was assessed. The bench studies and the animal study evaluated the algorithms and hardware of the Cogent™ HMS independently against simulated data or accepted reference devices. The system is designed to compute and display parameters, not to provide an initial AI interpretation for a human to then review or modify.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Bench Studies: Simulated physiological data.
• Animal Study: Measurements from "accepted reference devices" following pharmacological and ventilator interventions.

8. The sample size for the training set

• Since this is a 510(k) submission for a device primarily relying on established algorithms (continuous thermodilution, bolus thermodilution, oximetry, and PulseCO, which is also from a predicate), and not explicitly an AI/machine learning model that undergoes a distinct "training" phase with a large dataset, the concept of a "training set sample size" as typically understood for deep learning is not applicable or mentioned. The algorithms are described as being "measurement algorithms" or "analysis" algorithms, implying deterministic or well-defined computational processes rather than adaptive learning from a large training dataset.

9. How the ground truth for the training set was established

• As noted above, a distinct "training set" with ground truth in the context of machine learning is not applicable to the description of this device. The algorithms are based on established physiological measurement principles. For the PulseCO algorithm, it is stated to be "the PulseCO algorithm which is used in the secondary predicate device," suggesting its design and validation are tied to previous work on that predicate, not a new training process described here.

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