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The ComfortGel Blue Nasal Mask is intended to provide an interface for application of CPAP or bi-level therapy to patients. The mask is for single patient use in the home or multi-patient use in the hospital/institutional environment. The mask is to be used by patients (>66lbs/30kg) for whom CPAP or bi-level therapy has been prescribed.

The Respironics ComfortGel Blue Nasal Mask consists of a polycarbonate faceplate with a gel cushion encapsulated in a polyester seal for the face. The mask includes integrated exhalation features on the elbow. It is an accessory for use with CPAP and bi-level devices in the home (single patient use) and hospital/institution (multi-patient use).

The ComfortGel Blue Nasal mask covers the patient's nose only. It is strapped to the patient's face using headgear which connects to the mask via slots in the forehead bracket at the top, and via ball clip headgear attachments, which fit into sockets in the mask faceplate at the bottom. The mask is connected to the CPAP or bi-level flow generator via standard 22mm patient tubing. Positive pressure ventilation is then able to be applied to the lungs in a non-invasive way.

The provided text describes a 510(k) summary for the ComfortGel Blue Nasal Mask. This document focuses on demonstrating substantial equivalence to predicate devices for a medical device rather than presenting a performance study with acceptance criteria and results in the typical sense of an AI/ML device study.

Therefore, many of the requested categories for AI/ML performance studies are not applicable to the information contained within this 510(k) summary. I will answer the questions to the best of my ability based on the provided text, indicating where information is not available or not relevant for this type of submission.

Here's a breakdown based on your request:

1. A table of acceptance criteria and the reported device performance

The 510(k) summary does not explicitly list "acceptance criteria" and "reported device performance" in the context of a statistical study with metrics like sensitivity, specificity, accuracy, etc., as would be common for AI/ML devices. Instead, it compares the technical characteristics and performance of the subject device to predicate devices to demonstrate substantial equivalence. The "acceptance criteria" in this context would implicitly be that the subject device's performance characteristics (e.g., leak rates, pressure drop, dead space) are comparable to or within acceptable limits of the predicate devices and do not raise new safety or effectiveness concerns.

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

• Sample Size for Test Set: The document mentions "extensive performance testing" on "both untreated and treated samples" for characteristics like intentional leak, pressure drop, CO2 rebreathing, deadspace, swivel torque, and disinfection efficacy. However, it does not specify the number of masks or subjects included in these tests for the test set.
• Data Provenance: Not specified. As the manufacturer is Respironics, Inc. (Murrysville, PA, USA), it's highly likely the testing was conducted in the USA, but this is not explicitly stated. The nature of the testing implies prospective, in-house laboratory testing of the device prototypes.

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 is not applicable. For a physical medical device like a nasal mask, "ground truth" as it relates to expert consensus for image interpretation or diagnosis is not relevant. The "ground truth" here is established through objective physical measurements (e.g., pressure, flow rates, CO2 concentration) and microbiological testing standards for disinfection.

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

Not applicable. Adjudication methods like 2+1 or 3+1 are used for expert consensus in subjective assessments, typically with imaging data. The testing described for this device involves objective physical and microbiological measurements.

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 a physical medical device (CPAP mask), not an AI/ML diagnostic tool, so MRMC studies, human readers, and AI assistance are irrelevant to this submission.

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

Not applicable. There is no algorithm or AI component in this device.

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

The "ground truth" for this device's performance testing is based on:

• Objective physical measurements: Flow rates, pressure, CO2 concentration, dead space volume, torque.
• Established engineering and biomedical standards: Referenced standards for disinfection efficacy (AAM TIR No. 12-2004, AAMI TIR 30-2003, ANSI/AAMI/ISO 14937-2000, and FDA guidance).
• Comparison to predicate devices: The established performance characteristics of legally marketed predicate devices serve as benchmarks for safety and effectiveness.

8. The sample size for the training set

Not applicable. This device does not use a training set as it is not an AI/ML device.

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

Not applicable. As there is no training set, there is no ground truth to establish for it.

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