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The SPR+II overlay system is a pressure relieving support system intended to reduce the potential for development of pressure ulcers on at risk patients or to be used in the treatment of existing pressure ulcers.

The SPR+II System consists of an electromechanical inflation pump control unit which is connected to an overlay through a hose assembly connected to the inflation pump.

This is a premarket notification [510(k)] summary for the SPR+II System, a low air loss system designed to prevent and treat pressure ulcers. It primarily establishes substantial equivalence to a predicate device, the CLA 1500 System, rather than presenting a performance study with acceptance criteria and a detailed statistical analysis against those criteria. Therefore, most of the information requested cannot be extracted directly from the provided text.

Here is an attempt to address the request based on the available information:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in the typical sense of a target performance metric (e.g., accuracy, sensitivity, specificity) for a diagnostic or AI-driven device. Instead, it focuses on demonstrating substantial equivalence to a predicate device by comparing technological characteristics and nonclinical performance data.

The "acceptance criteria" here are implicitly that the SPR+II System performs similarly to or better than the CLA 1500 System in the listed characteristics, especially regarding safety and intended use.

Table of Acceptance Criteria and Reported Device Performance (based on Substantial Equivalence):

Study Details (Based on the provided document)

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

   • The document describes a submission for substantial equivalence based on a comparison of technological characteristics and nonclinical performance data between the SPR+II System and the predicate device (CLA 1500). It does not describe a clinical "test set" in the context of an algorithm or diagnostic device. The "performance data" referred to are related to the device's physical and functional properties, not data derived from patient testing or a specific dataset for algorithm evaluation.
   • Therefore, information regarding sample size, country of origin, or retrospective/prospective nature of a test set is not applicable here.

2. 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):

   • As this is a submission for a medical device (a low air loss system) and not an AI or diagnostic algorithm that requires "ground truth" derived from expert interpretation, this information is not applicable. The "ground truth" here is the established function and performance of the predicate device against which the new device is compared.

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

   • This is not applicable as there is no "test set" in the context of expert adjudication for an algorithm.

4. 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:

   • This is not applicable. The device is an electromechanical low air loss system, not an AI or diagnostic tool that would be used in an MRMC study to compare human reader performance.

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

   • This is not applicable. The device is a physical medical support system, not an algorithm.

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

   • For this type of device, "ground truth" refers to established engineering specifications, functional requirements, and safety standards, as well as the documented performance of the predicate device (CLA 1500). The "truth" is that the device meets these specifications and performs equivalently to a legally marketed predicate.

7. The sample size for the training set:

   • This is not applicable as the device is not an AI or machine learning algorithm requiring a "training set."

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

   • This is not applicable as the device is not an AI or machine learning algorithm.

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