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Designed for use in the operating room, recovery room, anesthetic room, intensive care, medical and surgical floors, patient transport and emergency department; the Inditherm Patient Warming System provides safe and controlled warming to assist patients to maintain normal body temperature. In addition to providing warming and control, the mattress also provides pressure relief to help prevent pressure sores.

The Inditherm Patient Warming System consists of a precision temperature control unit that controls and monitors the temperature of a mattress or blanket composed of a carbon polymer material. A pressure relief pad is integrated into the mattress, underneath the flexible warming surface.

The provided document is a 510(k) summary for the Inditherm Patient Warming System. It details the device's characteristics, intended use, and its substantial equivalence determination by the FDA. However, it does not contain information about acceptance criteria or a specific study proving the device meets those criteria in the way typically associated with AI/ML device performance evaluations.

Here's an analysis based on the information provided, highlighting why most of the requested fields cannot be answered:

1. Table of Acceptance Criteria and Reported Device Performance:

Reasons for limited information:

• This is a traditional medical device (patient warming system), not an AI/ML device. Therefore, the concept of "device performance" in terms of clinical metrics like sensitivity, specificity, accuracy, or AUC, as applied to AI algorithms, is not relevant here.
• The performance standards listed (BS EN 60601-1, BS EN 60601-2-35, MDD) are general safety and performance standards for medical electrical equipment and specific heated blankets/mattresses, not performance metrics like accuracy for a diagnostic algorithm.
• The primary "performance" discussed for this type of device in a 510(k) context is its substantial equivalence to predicate devices, focusing on technological characteristics and intended use.

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

Not applicable. This device is a hardware/software system for patient warming, not a diagnostic or prognostic algorithm that uses a "test set" of data for performance evaluation in the AI/ML sense. The document states: "The Inditherm Patient Warming System has been in clinical use since Clinical Data: 1999 in Europe. No additional clinical testing was required." This implies a reliance on pre-existing clinical use and compliance with technical standards rather than a formal clinical study with a specific test set.

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

Not applicable. See point 2. The device does not produce an output that requires expert adjudication for ground truth.

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

Not applicable. See point 2 and 3.

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 is not an AI-assisted diagnostic device.

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

Not applicable. This is not an AI algorithm. It's a patient warming system.

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

Not applicable. The ground truth concept for this device would relate to its ability to maintain a target temperature, safety, and effectiveness in preventing hypothermia (as indicated by its intended use). Compliance with technical standards and prior clinical use serve as the "proof" rather than a specific ground truth for an AI prediction.

8. The sample size for the training set:

Not applicable. This device is not an AI/ML system that requires a "training set."

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

Not applicable. See point 8.

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