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A patient interface accessory for use with CPAP and bi-level systems used in the treatment of adult OSA and / or ventilatory support. Single patient, multi-use. Environment of use – hospital, sub-acute institutions, sleep laboratories and home

The proposed nasal pillow patient interface incorporates a number of features, which are designed to maximize seal and comfort, and maintain the mask in the correct position throughout use.

• . Three (3) sizes of nasal pillows to assure a good fit
• Integral fixed leak port, identical to the predicate .
• . Headgear for attachment

This submission for the LifeSource CPAP nasal mask with pillows (K071773) is a 510(k) premarket notification. These types of submissions aim to demonstrate "substantial equivalence" to a legally marketed predicate device, rather than proving safety and efficacy through extensive clinical trials with specific acceptance criteria in the same way a PMA (Premarket Approval) submission would.

Therefore, the study conducted here is comparative testing to demonstrate that the new device performs similarly to the predicate device, not a study against a pre-defined acceptance criterion for a novel device.

Here's a breakdown of the requested information based on the provided document:

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

For a 510(k) submission, "acceptance criteria" are typically demonstrating equivalence to a predicate device's performance. The "reported device performance" is the new device exhibiting similar characteristics.

The study proving the device meets the acceptance criteria is described as "Comparative testing for safety and efficacy." This testing specifically investigated:

• Flow vs. Leak / Pressure: This likely involved measuring the flow characteristics and leak rates at various pressure settings to ensure performance similar to the predicate and within acceptable ranges for CPAP therapy.
• Dead space: Measurements were taken to confirm the dead space volumes (26 ml for interface, 2-4 ml for pillows) are identical to the predicate device.

The premise of a 510(k) clearance is that no significant differences that affect the safety or effectiveness exist between the proposed device and the predicate. The "comparative testing" implicitly demonstrated this by showing similar performance in key areas like flow characteristics, leak, and dead space, along with material biocompatibility.

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

The document does not specify the sample size used for the comparative testing (Flow vs. Leak / Pressure, Dead space). It also does not mention the country of origin of the data or whether the study was retrospective or prospective. Given the nature of bench testing for a medical device accessory, it's typically prospective bench testing conducted in a lab environment.

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 information is not applicable and not provided in the document. For a physical device like a CPAP mask, "ground truth" related to expert consensus is not typically established. The performance metrics (flow, leak, dead space) are measured objectively by engineering and testing personnel, not clinical experts establishing a ground truth.

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

This information is not applicable and not provided. Adjudication methods are typically used in clinical studies where subjective assessments (e.g., image interpretation, clinical outcomes) require consensus among multiple observers. The performance testing for this device (flow, leak, dead space) is objective measurement.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI/radiology devices where human interpretation is involved. This submission is for a physical medical device (CPAP mask) and does not involve AI or human readers for diagnostic interpretation.

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

No, a standalone algorithm performance evaluation was not done. This device is a physical product, not an algorithm or AI system.

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

For the "comparative testing" of the CPAP mask, the "ground truth" for parameters like dead space and flow/leak characteristics would be based on objective physical measurements using calibrated equipment and engineering standards. It is not based on expert consensus, pathology, or outcomes data in the clinical sense.

8. The sample size for the training set

This information is not applicable and not provided. "Training set" refers to data used to train machine learning models. This submission is for a physical medical device, not a machine learning or AI system.

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

This information is not applicable and not provided for the same reason as point 8.

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