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The Mirage Swift is intended for Multiple Patient Reuse by adult patients (>30 Kg) prescribed continuous positive airway pressure or bilevel therapy for use in home, hospitals or clinics.

The Mirage Swift is designed for adult patients for the delivery of non-invasive ventilatory support using continuous positive airway pressure or bi-level therapy. It is intended for multiple patient re-use and is minimally obtrusive to the user providing a high level of comfort, ease-ofuse and seal.

The provided document is a 510(k) summary for the ResMed Mirage Swift Nasal Mask, seeking clearance for "Multiple Patient Reuse" after initially being cleared as a single patient reuse device.

Based on the provided text, there is no specific performance study with acceptance criteria and a detailed report of device performance as one might expect for a new AI/software device. This document is for a physical medical device (a CPAP mask) and focuses on demonstrating substantial equivalence to predicate devices for an expanded indication for use (multiple patient reuse), not for establishing performance metrics of a novel diagnostic or therapeutic algorithm.

Therefore, many of the requested points regarding acceptance criteria, sample sizes for test/training sets, expert adjudication, MRMC studies, or standalone algorithm performance are not applicable or discoverable from this particular 510(k) summary.

Here's an attempt to answer the questions based only on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or a direct performance report in the context of a new diagnostic/therapeutic device. Instead, the "acceptance criterion" is implicitly demonstrating substantial equivalence to predicate devices that are already cleared for multiple patient reuse. The reported "performance" is that this substantial equivalence has been met.

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

Not applicable. This is not a study assessing diagnostic performance against a test set. The "performance data" mentioned would likely pertain to cleaning, disinfection, and material compatibility relevant to multiple patient reuse, rather than a clinical outcome study with a "test set" of patients.

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)

Not applicable. "Ground truth" in the context of expert consensus for a diagnostic test is not relevant here. The "ground truth" for multiple patient reuse would be established through testing cleaning efficacy, material degradation after disinfection cycles, and biocompatibility, typically performed in a lab setting rather than by clinical experts establishing a diagnosis.

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

Not applicable. There is no "test set" in the context of expert adjudication for this type of submission.

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 document is about a physical CPAP mask, not an AI or software-assisted diagnostic device. Therefore, no MRMC study or AI improvement metrics are relevant or present.

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 concensus, pathology, outcomes data, etc)

The concept of "ground truth" as it applies to diagnostic algorithms is not relevant here. For the "Multiple Patient Reuse" claim, the "ground truth" would be objective evidence from laboratory testing demonstrating that the device can be effectively cleaned and disinfected according to a validated protocol without material degradation or compromising safety/performance, making it suitable for subsequent patient use. The document states that "Performance data and rationale are provided" to support this.

8. The sample size for the training set

Not applicable. This is a physical medical device, not an algorithm that requires a "training set."

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

Not applicable. As above, this is not an algorithm requiring a "training set" or "ground truth" in that context.

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