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The Rapid Thermal Exchange System is designed to noninvasively lower or raise a patient's temperature and/or maintain a desired patient temperature. This is accomplished with local application of negative pressure and heating/cooling to a distal appendage.

The Rapid Thermal Exchange (RTX) System consists of three main parts. The 1) Field Controller unit is the vacuum source; it also regulates and pumps the temperaturecontrolled water through the 2) Attachment Hoses that are connected to 3) the Thermal Exchange Chamber (identified in earlier submissions as the Palmo Thermoregulating Accessory).

The patient inserts his/her hand through the arm seal of the Thermal Exchange Chamber. The palm is placed on the temperature-controlled thermal exchange surface. A light vacuum is created by connecting the Thermal Exchange Chamber to the Field Controller Unit's vacuum pump via the inline vacuum control valve. The physician can monitor the adequacy of the vacuum and seal from the dial on the mechanical vacuum gauge mounted to the top of the Thermal Exchange Chamber. A light vacuum (25 inches of water, 47mmHg) is applied to increase the amount of blood available in the appendage.

This combination of light vacuum and a thermal exchange surface provides a rapid and noninvasive mechanism for changing the temperature of the blood flowing through the appendage. This, in turn, changes the temperature of the body core.

The arm seal of the Thermal Exchange Chamber is available in three different sizes (small, medium & large) to accommodate the range of possible hand and wrist sizes of athletes. A variation of the Chamber can be applied to the foot in a similar manner.

The provided text describes a medical device, the Rapid Thermal Exchange (RTX) System, and its substantial equivalence to a predicate device, the Palmo Thermoregulating Accessory. However, it does not contain information about acceptance criteria or a study proving the device meets specific performance criteria in the format typically used for AI/ML device evaluations (e.g., accuracy, sensitivity, specificity, F1 score).

Instead, the submission focuses on:

• Device Description: How the RTX System works, its components, and its similarities to the predicate.
• Indications for Use: What the device is intended for.
• Testing in Support of Substantial Equivalence: This section mentions "bench testing" to support operating characteristics and compliance with IEC 60601-1. It also refers to "human studies reported in a predicate submission" that demonstrated the effectiveness of the predicate's underlying mechanism.
• Substantial Equivalence Conclusion: The core argument is that the RTX System is substantially equivalent to the predicate because it has the same intended use, uses identical technology and operating parameters, and incorporates the exact same components.

Given this, I cannot fill out the requested table for acceptance criteria and reported device performance, nor can I provide information on sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth for test sets, training set size, or how ground truth was established for the training set. These elements are standard for evaluating AI/ML models but are not present in this 510(k) submission for a non-AI medical device.

Here's a breakdown of what can be extracted from the text, framed within your request, but with the caveat that it does not align with AI/ML evaluation metrics:

1. Table of Acceptance Criteria and 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)

• The summary mentions "bench testing" for operating characteristics but provides no details on sample sizes or data provenance.
• It also refers to "human studies reported in a predicate submission" for effectiveness, but these were for the predicate device, not the RTX System itself. No details about these predicate studies' sample size or provenance are given in this document.

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)

• This information is not provided as the submission focuses on functional equivalence to a predicate, not clinical performance evaluation against a defined ground truth set by experts.

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

• Not applicable/Not provided.

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. This device is a thermal regulation system, not an AI-powered diagnostic tool involving human readers.

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

• Not applicable. This is a physical medical device, not an algorithm.

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

• For the "effectiveness" claim, the ground truth for the predicate device's human studies would likely have been measured changes in body core temperature or maintenance of desired temperature in human subjects (outcomes data). The RTX System relies on the predicate's demonstration of this.
• For safety and operating characteristics, the ground truth would be physical measurements against engineering specifications and regulatory standards (e.g., precise temperature control, vacuum pressure, electrical safety tests per IEC 60601-1).

8. The sample size for the training set

• Not applicable. This is not an AI/ML device with a "training set."

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

• Not applicable.

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