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HemoSphere Advanced Monitor with HemoSphere Swan-Ganz Module
The HemoSphere Advanced Monitor when used with the HemoSphere Swan-Ganz Module and Edwards Swan-Ganz Catheters is indicated for use in adult and pediatric critical care patients requiring of cardiac output [continuous (CO) and intermittent (iCO)] and derived hemodynamic parameters. It may also be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards Swan-Ganz catheter indications for use statement for information on target patient population specific to the catheter being used.
Refer to the Intended Use statement below for a complete list of measured and derived parameters available for each patient population.
HemoSphere Advanced Monitor with HemoSphere Oximetry Cable
The HemoSphere Advanced Monitor when used with the HemoSphere Oximetry cathetry catheters is indicated for use in adult and pediativ critical care patients requiring of venous oxygen saturation (Sv02 and ScvO2) and derived hemodynamic parameters in a hospital environment. Refer to the Edwards oximeter indications for use statement for information on target patient population specific to the catheter being used.
Refer to the Intended Use statement for a complete list of measured and derived parameters available for each patient population.
HemoSphere Advanced Monitor with HemoSphere Pressure Cable
The HemoSphere Advanced Monitor when used with the HemoSphere Pressure Cable is indicated for use in critical care patients in which the balance between cardiac function, fluid status, vascular resistance and pressure needs continuous assessment. It may be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards FloTrac, Acumen IQ and TruWave DPT sensor indications for use statement for information on target patient population specific to the sensor being used.
The Edwards Lifesciences Acumen Hypotension Prediction Index feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events (defined as mean arterial pressure 3 kg.
When used with Small Sensors, the FORE-SIGHT ELITE tissue oximeter module is indicated for cerebral use on pediatric subjects

HemoSphere Advanced Monitoring Platform consists of the HemoSphere Advanced Monitor that provides a means to interact with and visualize hemodynamic and volumetric data on a screen and five (5) optional external modules: the HemoSphere Swan-Ganz Module (K163381 Cleared, April 14, 2017), the HemoSphere Oximetry Cable (K163381 Cleared, April 14, 2017), HemoSphere Pressure Cable (K180881 Cleared, November 16, 2018), HemoSphere Tissue Oximetry Module (K190205 August 29, 2019), FORE-SIGHT ELITE Tissue Oximeter Module (K180003, May 10, 2018), and the subject HemoSphere ClearSight Module.
The subject HemoSphere ClearSight module is a non-invasive subsystem module intended to continuously and noninvasively measure blood pressure and associated hemodynamic parameters. HemoSphere ClearSight module is intended to provide ClearSight functionality (Non-Invasive) previously cleared in EV1000 Clinical Platform NI (K160552 June 1, 2017) to the HemoSphere Advanced Monitoring Platform. It provides power, communications, air and an interface to connect with currently cleared and commercially available Edwards Lifesciences ClearSight System (K160552 June 1, 2016) which includes ClearSight finger cuffs (K160552 June 1, 2016 and K190130 June 21, 2019), Pressure Controller/Wrist Unit (K160552 June 1, 2016), Heart Reference Sensor (K182245 Nov 30, 2018), and the HemoSphere Advanced Monitor (K190205 August 29, 2019).

The provided text is a 510(k) Summary for the "HemoSphere Advanced Monitoring Platform" and its associated modules, specifically focusing on the addition of the "HemoSphere ClearSight Module" and platform modifications. This document describes the device's technical characteristics, regulatory classification, and performance data to demonstrate substantial equivalence to predicate devices.

However, the document does not contain the specific acceptance criteria for the device performance study or the detailed results of a comparative effectiveness study (like MRMC) showing how human readers improve with AI vs. without AI assistance. The provided text primarily focuses on technical verification and validation, electrical safety, electromagnetic compatibility, and software verification to demonstrate that the modified device functions as intended and safely. It refers to "predetermined design and performance specifications" but does not explicitly list these specifications or the raw performance data against them.

Based on the provided information, I can extract and infer the following:

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

The document states: "Completion of all verification and validation activities demonstrated that the subject devices meet their predetermined design and performance specifications." However, it does not explicitly list these predetermined specifications or quantifiable performance metrics (e.g., accuracy, precision, bias) for the device's measurements in a table format.

The performance data mentioned includes:

• Usability Study: "The usability study demonstrated that the intended users can perform primary operating functions and critical tasks of the system without any usability issues that may lead to patient or user harm."
• System Verification (Non-Clinical Performance): "Measured and derived parameters were tested using a bench simulation. Additionally, individual modules were tested at a system level to verify the safety of these modules. They were also integrated as a system and verified for their safety and effectiveness. All tests passed."
• Electrical Safety and Electromagnetic Compatibility (EMC): "The system complies with the IEC 60601-1, IEC 60601-1-2, IEC 60601-1-6, IEC 60601-1-8, IEC 62304, IEC 62366-1, IEC 60601-2-34, IEC 60601-2-57, IEC 60601-2-49 and IEC 80601-2-49. All tests passed."
• Wireless Coexistence Testing: "Bench and simulated environment testing were performed on the entire HemoSphere Advanced Monitoring Platform, including all sub-system modules and interfacing analog inputs and outputs. All tests passed."
• Software Verification: "Software verification was performed per FDA's Guidance for Industry and FDA Staff, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices'. Software on each of the individual modules was tested at a sub-system level to ensure the safety of the device. All tests passed."

Therefore, a table of specific quantifiable acceptance criteria and reported numerical performance values cannot be constructed from the provided text. The acceptance criteria appear to be qualitative (e.g., "without any usability issues," "All tests passed," "meets their predetermined design and performance specifications") or compliance with standards.

2. Sample size used for the test set and the data provenance:

• Sample Size: The document does not specify a sample size for any clinical or test data set. All tests described are bench simulations or technical verifications rather than clinical trials with patient data.
• Data Provenance: Not applicable as no patient data test sets are described for performance evaluation. The "bench simulation" implies laboratory testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. The tests described are technical and bench-based, not involving expert interpretation of patient data to establish ground truth for performance evaluation of AI/algorithm outputs.

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

• Not applicable. No expert review or adjudication process for a test set is mentioned.

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, an MRMC comparative effectiveness study was not done. The document describes a "Programmable Diagnostic Computer" that measures hemodynamic parameters. It does not refer to an AI component that assists human readers (e.g., radiologists interpreting images) or that would necessitate an MRMC study. The "Hypotension Prediction Index (HPI)" is described as "additional quantitative information regarding the patient's physiological condition for reference only and no therapeutic decisions should be made based solely on the Hypotension Prediction Index (HPI) parameter," indicating it is not a primary diagnostic tool requiring human-in-the-loop performance evaluation in this context.

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

• The document implies that the device and its algorithms were tested in a standalone fashion through "System Verification (Non-Clinical Performance)" using "bench simulation." The statement "Measured and derived parameters were tested using a bench simulation... All tests passed" indicates algorithm-only performance testing against simulated inputs. However, no specific metrics of this standalone performance (e.g., accuracy against a gold standard) are provided, only that it "passed."

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

• For the "System Verification (Non-Clinical Performance)," the ground truth would have been established by the simulated inputs used in the bench testing. These would be controlled and known values of physiological parameters. For the "Electrical Safety and EMC" and "Wireless Coexistence Testing," the ground truth is compliance with established regulatory and technical standards (e.g., IEC 60601 series).

8. The sample size for the training set:

• The document describes a device that measures and derives physiological parameters. It mentions "Algorithm update" for continuous cardiac output and tissue oximetry, but it does not mention any machine learning or AI models that would require training data. The term "algorithm" here likely refers to deterministic computational methods rather than learned models. Therefore, there is no mention of a training set sample size.

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

• As the document does not mention the use of machine learning or AI models with training sets, this question is not applicable. The algorithms described appear to be based on pre-programmed physiological models and equations, not learned from data.

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