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The Insuflow® DewHeart™ is a Blower/Mister Gas conditioner device for use in cardiovascular surgical procedures intended to heat, humidify and filter a CO2 gas stream for introduction into the surgical cavity to improve visibility and reduce the risk of air embolism.

The Insuflow DewHeart™ device is a single use blower/mister device that attaches to the outlet port of the Insuflow controller with regulated CO2 source and is designed to warm and humidify the CO2 gas stream prior to introduction into the cardiovascular cavity. The Insuflow DewHeart™ device consists of a disposable filter heater/humidifier tubing set and a control module that houses the control and safety circuits for the system. Regulated CO2 gas flows into the Insuflow® DewHeart™ device, through the in-line filter, continues along the tube to enter the Insuflow® DewHeart™ device cassette that contains the heating element and humidification media, through a nozzle/wand for directional. localization of a CO2 gas stream entry into the patient's surgical cavity

The provided text is a 510(k) summary for the Insuflow® DewHeart™ device, which is a blower/mister gas conditioner. It states that the device is technically the same as a previously cleared device (Insuflow®, K063546) and substantially equivalent to other predicate devices.

Here's an analysis of the requested information based only on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics. It generally states that "Extensive performance testing has been conducted to assure that the Insuflow DewHeart™ performs in accordance with its specifications and applicable standards." However, specific numerical acceptance criteria or performance results are not detailed in this summary.

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

The document does not specify any sample size for a test set. It refers to "Extensive performance testing" but does not provide details on the experimental setup or the data used. Therefore, the data provenance (country of origin, retrospective/prospective) cannot be determined from this text.

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

The document does not describe any study involving human experts to establish ground truth or evaluate the device's performance. The "performance testing" mentioned appears to refer to engineering or laboratory testing against specifications, not clinical or expert-reviewed data.

4. Adjudication Method for the Test Set

As no human expert review or ground truth establishment is described, there is no mention of an adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No MRMC study is mentioned. The document primarily focuses on demonstrating substantial equivalence to predicate devices based on technical characteristics and intended use, rather than comparing performance with human readers with and without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was Done

The device described is a physical medical device (blower/mister gas conditioner), not an AI algorithm. Therefore, the concept of "standalone (algorithm only)" performance is not applicable in this context. The performance testing refers to the device's physical functions like heating, humidifying, and filtering.

7. The Type of Ground Truth Used

The document discusses "performance testing" against "specifications and applicable standards." This implies the ground truth for evaluating the device's functionality would be engineering specifications and established standards for heating, humidifying, and filtering CO2 gas, rather than expert consensus, pathology, or outcomes data.

8. The Sample Size for the Training Set

As this is a physical medical device and not an AI/machine learning algorithm, the concept of a "training set" is not relevant.

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

Not applicable, as there is no training set for an AI algorithm.

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