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The BiPAP AutoSV Advanced is intended to provide non-invasive ventilatory support to treat adult patients with OSA and Respiratory Insufficiency caused by central and/or mixed apneas and periodic breathing.

The Respironics BiPAP AutoSV Advanced is a microprocessor controlled blower based Bi-level positive pressure system that delivers two positive pressure levels (IPAP/EPAP). The dual pressure levels provide a more natural means of delivering pressure support therapy to the patient resulting in improved patient comfort. A flow sensor and redundant pressure sensors in the patient airway feed data on measured flow and pressure into a microprocessor controller, which in turn regulates the blower assembly. A user interface displays clinical data and enables the operator to set and adjust certain clinical parameters.

The BiPAP AutoSV Advanced pressure control contains various which are used to configure positive pressure therapies. With these controls, the device delivers minimum pressure support determined by the PSmin control. The device may automatically provide additional pressure support with inspiratory pressures between PSmin and PSmax to normalize patient ventilation during sleep disordered breathing events. Note: When PSmin = PSmax, this is equivalent to traditional bi-level therapy.

The BiPAP AutoSV Advanced is fitted with alarms to alert the user to changes that will affect the treatment. Some of the alarms are pre-set (fixed), others are user adjustable.

The BiPAP AutoSV Advanced Ventilatory Support System is intended for use with a patient circuit that is used to connect the device to the patient interface device (mask). A typical patient circuit consists of a six-foot disposable or reusable smooth lumen 22mm tubing and a method of venting exhaled gases.

The provided text does not contain detailed information about specific acceptance criteria and a study proving the device meets them in the format requested. The document is a 510(k) summary for the BiPAP AutoSV Advanced, focusing on its substantial equivalence to predicate devices and general performance modifications.

However, based on the text, I can extract the following relevant information:

Key Takeaways from the Text:

• Clinical Validation: The manufacturer performed "clinical validation to ensure the efficacy of the algorithm was not affected" due to modifications to the AutoSV algorithm.
• Bench Data: Other device modifications were validated using "bench data" including waveform performance, triggering data, and overall event detection and control data.
• Equivalence Claim: The testing "confirmed that the BiPAP AutoSV Advanced performs equivalently to the device predicate BiPAP AutoSV (K063540). All tests were verified to meet the required acceptance criteria."

Given the limited information, I cannot accurately fill out many of the requested fields. Here's a structured response based on what is available and what cannot be determined:

1. Table of Acceptance Criteria and Reported Device Performance:

The document broadly states that "All tests were verified to meet the required acceptance criteria" and that the device "performs equivalently to the device predicate BiPAP AutoSV (K063540)." However, it does not provide a specific table of these criteria or quantitative reported performance values for each criterion.

2. Sample Size and Data Provenance:

• Sample Size for Test Set: Not specified. The document mentions "clinical validation" but does not give the number of patients or cases.
• Data Provenance: Not specified. It's unclear if the validation data was prospective or retrospective, or its country of origin.

3. Number of Experts and Qualifications for Ground Truth:

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method:

• Adjudication Method: Not specified.

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

• MRMC Study Done?: No information provided. The document focuses on performance equivalence to a predicate device, not on human reader improvement with AI assistance.

6. Standalone Performance Study:

• Standalone Study Done?: Likely yes, as implied by "bench data" and "clinical validation to ensure the efficacy of the algorithm was not affected." However, specific metrics for standalone performance (e.g., sensitivity, specificity for event detection) are not provided. The comparison is made against a predicate device.

7. Type of Ground Truth Used:

• Type of Ground Truth: Not specified explicitly. For clinical validation of a ventilator algorithm, it would typically involve physiological measurements and potentially expert interpretation of physiological signals (e.g., polysomnography data for sleep disordered breathing events). For bench testing, it would be against known physical models or simulated conditions.

8. Sample Size for Training Set:

• Sample Size: Not specified. The document mentions modifications to an existing algorithm ("AutoSV algorithm") but does not detail a training set for a de novo algorithm development.

9. How Ground Truth for Training Set was Established:

• How Ground Truth Established: Not specified. As it's an update to an existing algorithm, it's possible that historical data and expert-defined criteria from the predicate device's development were used, but this is conjecture.

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The BiPAP AutoSV is intended to provide non-invasive ventilatory support to treat adult patients with OSA and Respiratory Insufficiency caused by central and/or mixed apneas and periodic breathing.

The Respironics BIPAP AutoSV is a microprocessor controlled blower based Bi-level positive pressure system that delivers two positive pressure levels (IPAP/EPAP). The dual pressure levels provide a more natural means of delivering pressure support therapy to the patient resulting in improved patient comfort. A flow sensor and redundant pressure sensors in the patient airway feed data on measured flow and pressure into a microprocessor controller, which in turn regulates the blower assembly. A user interface displays clinical data and enables the operator to set and adjust certain clinical parameters.

The BiPAP AutoSV pressure control that contains various which are used to configure positive pressure therapies. With these controls, the device delivers minimum pressure support determined by the EPAP and IPAP Min controls. The device may automatically provide additional pressure support with inspiratory pressures between IPAP Min and IPAP Max to normalize patient ventilation during sleep disordered breathing events. Note: When EPAP

The provided text describes a 510(k) premarket notification for a modified device, the Respironics BiPAP AutoSV. The submission claims substantial equivalence to previously cleared predicate devices. The "study" mentioned refers to design verification tests performed on the device to ensure it meets required acceptance criteria. However, the document does not contain detailed information about a clinical study with a detailed methodology, acceptance criteria, and specific performance results in the format you requested for "proving" the device meets acceptance criteria.

Based on the provided text, here's what can be extracted and what is missing:

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

Missing Information:

• Specific quantitative acceptance criteria (e.g., "pressure accuracy must be within +/- X cmH2O").
• Specific quantitative performance results from the design verification tests (e.g., "pressure accuracy was Y cmH2O").

2. Sample size used for the test set and the data provenance:

• Sample Size: Not specified. The document mentions "design verification tests" but does not detail the number of devices or scenarios tested.
• Data Provenance: Not specified. It's internal testing conducted by Respironics.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. The "ground truth" for design verification tests is typically established through engineering specifications and regulatory standards, not expert consensus on patient data.

4. Adjudication method for the test set:

• Not applicable. This typically refers to clinical study data 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:

• No. This type of study is not mentioned in the document. The device is a ventilator, not an AI-assisted diagnostic tool.

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

• The document implies that the device (which contains a microprocessor controller) underwent standalone testing as part of the design verification process. The "algorithm" here would be the control logic of the ventilator. However, specific details about protocol for standalone algorithm performance are not provided.

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

• For design verification tests, the "ground truth" would be the engineering specifications and regulatory standards that the device is required to meet.

8. The sample size for the training set:

• Not applicable in the context of this document. This refers to AI/ML model training, which is not the focus of this submission. The device is microprocessor-controlled but not described as using machine learning that would require a "training set" in the common sense of the term for AI products.

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

• Not applicable (see point 8).

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