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The Mirage Full Face Mask (FFM) Series 2 is intended for multiple-patient use for adult patients prescribed continuous positive airway pressure (CPAP) and bi-level therapy in hospital, clinic, and home environments.

Mirage FFM Series 2 is a respiratory mask covering the nose and the mouth. It is a patient interface accessory for use with CPAP and bi-level devices.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Mirage Full Face Mask (FFM) Series 2:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not explicitly stated for each disinfection method. The text mentions "The semi-critical mask components can withstand 15 cycles of high-level disinfection." This implies that a sufficient number of components were tested through these cycles to validate the claim. However, the exact number of masks or components constituting the "test set" is not specified.
• Data Provenance: The study was conducted by ResMed Ltd, an Australian company. The context suggests this was an internal prospective validation study conducted to support the 510(k) submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Not Applicable. This device is a medical mask validated for its disinfection compatibility and material equivalence. The "ground truth" here relates to the physical integrity and continued functionality of the components after disinfection, not a diagnostic interpretation that would involve medical experts establishing a "ground truth" for a test set. The validation would have been performed by engineers, material scientists, or laboratory technicians.

4. Adjudication Method for the Test Set

• Not Applicable. As mentioned above, there is no "adjudication" in the sense of expert review for diagnostic accuracy. The assessment would have involved objective measurements or visual inspections following the disinfection cycles to determine if the components met predefined criteria for integrity and functionality.

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 (a mask), not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study is irrelevant.

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

• The ground truth used was physical validation of device components' integrity and functionality after undergoing specified disinfection cycles, and material composition comparison to the predicate device. This would likely involve:
  • Visual inspection for damage, degradation, or changes.
  • Functional testing of connections, flexibility, and overall fit after disinfection.
  • Material analysis to confirm equivalence or safety.

8. The Sample Size for the Training Set

• Not Applicable. This is a physical device, and the evaluation described is a validation study, not a machine learning study that would have a "training set."

9. How the Ground Truth for the Training Set Was Established

• Not Applicable. See point 8.

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The Mirage Full Face Mask (FFM) Series 2 is intended for multiple-patient use for adult patients prescribed continuous positive airway pressure (CPAP) and bi-level therapy in hospital, clinic, and home environments.

Mirage FFM Series 2 is a respiratory mask covering the nose and the mouth. It is a patient interface accessory for use with CPAP and bi-level devices.

The provided text describes the ResMed Mirage Full Face Mask (FFM) Series 2 and its substantial equivalence to a predicate device, focusing on disinfection methods. It does not contain information typically associated with acceptance criteria and studies proving performance for a diagnostic AI/ML device, such as sensitivity, specificity, or clinical outcome studies.

Therefore, many of the requested fields cannot be filled. The information available pertains to the device's technological characteristics and its validation for disinfection.

Here's an attempt to answer based on the provided text, highlighting where information is unavailable or not applicable to the format requested for AI/ML device studies:

Additional Information based on the text:

1. Sample size used for the test set and the data provenance: Not applicable. The "test set" here refers to the physical mask components undergoing disinfection cycles, not a dataset for an AI/ML model. No specific sample size (e.g., number of masks, components) is mentioned for the disinfection validation beyond "components can withstand 15 cycles." Data provenance is not relevant in this context.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for disinfection validation involves laboratory testing against established chemical and biological standards, not expert consensus interpreting data.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. Adjudication methods are for human interpretation differences in diagnostic tasks.
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: Not applicable. This is not an AI/ML diagnostic device; it's a medical mask.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For disinfection validation, the ground truth would be established through microbiology laboratory testing to confirm the effectiveness of disinfection agents against specified microorganisms and material integrity testing to ensure the components withstand the disinfection cycles without degradation.
7. The sample size for the training set: Not applicable. This is not an AI/ML device; there is no training set mentioned.
8. How the ground truth for the training set was established: Not applicable. There is no training set.

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The Mirage Full Face Mask (FFM) Series 2 is intended for multiple-patient use for adult patients prescribed continuous positive airway pressure (CPAP) and bi-level therapy in hospital, clinic, and home environments.

Mirage FFM Series 2 is a respiratory mask covering the nose and the mouth. It is a patient interface accessory for use with CPAP and bi-level devices.

The provided text describes the Mirage Full Face Mask Series 2 and its substantial equivalence to the predicate device, Mirage FFM. The primary focus of this submission is to validate the addition of a new sterilization method (Sterrad 100S System) for multi-patient use.

Here's an analysis based on the information provided, keeping in mind that this document is a 510(k) submission, which focuses on substantial equivalence rather than detailed performance studies like those for novel devices.

1. Table of Acceptance Criteria and Reported Device Performance

• 3.4% glutaraldehyde solution (e.g., Cidex Plus)
• 0.08% peroxyacetic acid and 1% hydrogen peroxide (e.g., Cidex PA).
  Semi-critical mask components withstand 15 cycles of high-level disinfection. (The predicate Mirage FFM was already validated for these methods, and the new device maintains this.) |
  | For Sterilization (Sterrad 100S System): | Validation performed: Mirage FFM Series 2 was validated for multiple-patient use with sterilization using the Sterrad 100S System made by ASP (K991999).
  Semi-critical mask components withstand 15 cycles of sterilization. |
  | Functional Integrity after Disinfection/Sterilization (15 cycles): | Implied successful performance as the device is deemed "substantially equivalent" and the sterilization method "does not affect safety and effectiveness." |
  | Material Compatibility after Disinfection/Sterilization: | Implied successful performance, as the materials in air-path are identical to the predicate, and new materials (headgear, port caps) are deemed compatible with the cleaning/sterilization processes. |
  | Headgear (non-critical item) does not require high-level disinfection/sterilization: | The headgear is classified as a non-critical item and thus does not require high-level disinfection/sterilization, as stated. |
  | Valve membrane and air tubing replacement requirement (post-disinfection/sterilization for multi-patient use): | The user instructions highlight that the valve membrane and air tubing cannot be disinfected/sterilized and must be replaced before reusing on another patient. |

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify a "test set" in the context of clinical performance or a specific patient cohort for the sterilization validation. The validation is focused on the device's ability to withstand disinfection/sterilization processes.

• Sample Size: Not explicitly stated for number of units tested or patient data. The statement "15 cycles" refers to the number of disinfection/sterilization cycles the components were subjected to.
• Data Provenance: Not applicable in the context of country of origin for clinical data, as this is a device reprocessing validation, not a clinical trial. The validation was conducted to support the 510(k) submission to the FDA.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

Not applicable. The ground truth for this submission relates to the efficacy of the disinfection/sterilization processes and the material integrity of the device components. This is typically established through laboratory testing and engineering analysis rather than expert clinical consensus on patient data.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of a human-reviewed "test set" requiring adjudication.

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 medical device for respiratory therapy, not an AI diagnostic tool.

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

The ground truth used for this submission is based on:

• Performance Standards for Disinfection/Sterilization: The ability of the device components to withstand 15 cycles of specified high-level disinfection methods and the Sterrad 100S System sterilization method, while maintaining functionality and material integrity.
• Material Compatibility: Confirmation that the materials used are compatible with the reprocessing methods and maintain their intended properties.
• Predicate Device Equivalence: The foundation of the submission is demonstrating substantial equivalence to the predicate "Mirage FFM," which means its performance and safety characteristics, including its reprocessing capabilities, are comparable.

8. The Sample Size for the Training Set

Not applicable. There is no "training set" in the context of machine learning for this device submission.

9. How the Ground Truth for the Training Set Was Established

Not applicable. As there is no training set, there is no ground truth for a training set to be established.

Summary of the Study Proving Acceptance Criteria:

The study proving the device meets the acceptance criteria is generally referred to as "Performance Data" within the submission. It involves validation studies related to the reprocessing of the device for multi-patient use.

• The Mirage FFM Series 2 was subjected to 15 cycles of:
  • High-level disinfection with 3.4% glutaraldehyde solution.
  • High-level disinfection with 0.08% peroxyacetic acid and 1% hydrogen peroxide.
  • Sterilization with the Sterrad 100S System made by ASP.
• A "conditioning cycle" for each reprocessing method included disassembly, cleaning, disinfection/sterilization, and re-assembly.
• The acceptance criterion was that the "semi-critical mask components can withstand 15 cycles" of these processes. While the specific metrics of "withstanding" (e.g., burst pressure, leakage, material degradation assessment) are not detailed in this summary, they would have been part of the underlying validation reports.
• The "performance data" effectively demonstrates that the device's semi-critical components retain their integrity and functionality after repeated reprocessing, thus supporting its suitability for multiple-patient use with these methods. The conclusion of substantial equivalence further implies that this reprocessing does not compromise the device's safety or effectiveness compared to the predicate.

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