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The Respironics BiPAP Synchrony 2 is intended to provide non-invasive ventilation for pediatric patients 7 years or older (> 40 lbs) or adult patients (> 66 lbs) with respiratory insufficiency or obstructive sleep apnea, in the hospital or home.

The Respironics BiPAP Synchrony 2 device is unchanged from K063533. The only change is to include a Respironics pediatric mask as a second option for use by its pediatric users. This mask is the same mask design as is used by the cleared Respironics Reusable Contour Deluxe Nask (K991648). The mask consists of a silicon cushion, polycarbonate faceplate with an elbow that contains the exhalation feature. The anthropometric profile of the Respironics Pediatric Mask matches that of the Resmed Kidsta previously cleared in K063533.

This document describes a 510(k) premarket notification for the BiPAP Synchrony 2 Ventilatory Support System with the addition of a Respironics pediatric mask. The core device itself (BiPAP Synchrony 2) is unchanged from a previously cleared predicate device (K063533). The submission specifically addresses the compatibility of the new pediatric mask.

Here's an analysis of the acceptance criteria and supporting study information:

1. Table of Acceptance Criteria and Reported Device Performance

The general acceptance criteria and performance are reported qualitatively in the document. No specific numerical thresholds are provided, as the study focused on compatibility and function rather than a new "performance metric."

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

• Sample Size: Not explicitly stated in the provided text. The document refers to "mask compatibility testing" but does not detail the number of masks, devices, or test subjects used in this testing.
• Data Provenance: Not explicitly stated, however, the testing was performed by Respironics, Inc. and is part of a submission to the FDA in the United States. It's likely a controlled, in-house laboratory study. It would be considered prospective for the specific purpose of this submission (testing the new mask's compatibility).

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The testing was conducted by the manufacturer, Respironics, likely by their engineering and R&D teams.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/specified. The testing described appears to be objective, functional performance testing (e.g., pressure, waveform analysis, discrete function activation) rather than subjective expert assessment. There is no indication of multiple readers or an adjudication process for these technical tests.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, an MRMC comparative effectiveness study was not done. This submission focuses on the compatibility of a new mask with an existing device, involving technical performance testing, not the clinical effectiveness or human-in-the-loop performance with or without AI.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: No, a standalone performance study in the context of an algorithm or AI was not done. This device is a ventilatory support system, not an AI/algorithm-based diagnostic or therapeutic device.

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth for this testing was based on pre-defined engineering specifications and performance requirements for the ventilatory support system. The "acceptance criteria" for the mask compatibility testing (pressure, waveform, triggering, cycling, alarm functionality) refer to these established technical standards for proper device function.

8. Sample Size for the Training Set

• Sample Size: Not applicable. This submission concerns a physical medical device and mask, not an AI or machine learning algorithm that would require a 'training set.'

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

• Ground Truth Establishment: Not applicable, as there is no training set for an AI/ML model.

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