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OptiPillows EPAP Mask is intended for use during sleep to alleviate snoring. It is intended for the adult population with snoring only.

OptiPillows EPAP mask is a nasal dilator device for alleviation of snoring. The EPAP mask is a reusable device. The EPAP mask has nasal pillows that fit against the nostrils similar to the ones used in several nasal pillow CPAP masks. The EPAP mask has a one-way valve attached to it that allows air to flow freely without resistance during inspiration. The mask is held in place with adjustable head straps connected to the sides of the mask. During expiration, the air is redirected through a narrow opening, on the side of the expiratory opening creates resistance to airflow, thus increasing the back pressure in the nose, mouth, and upper airways. The increase in back pressure during expiration prevents the collapse of the upper airways, alleviating airway obstruction. The level of back pressure can be adjusted to the patient comfort by turning a rotating sleeve/collar to open or close the expiratory opening on the side of the valve. The adjustable expiratory resistance improves the comfort and safety for the user and facilitates adaptation to the EPAP mask.

The EPAP mask is a small device and is used like a CPAP mask, but does not require using a power supply, a CPAP machine or tubing that restricts movement of the patient during sleep.

The provided text is a 510(k) summary for the OptiPillows EPAP Mask, which is a nasal dilator device intended for use during sleep to alleviate snoring. However, the document does not contain specific acceptance criteria tables or a detailed study plan that measures performance against predefined quantitative metrics suitable for a typical AI/ML medical device submission.

Instead, this submission is for a physical medical device (a nasal dilator) and focuses on demonstrating substantial equivalence to a predicate device (InVent Snoring Device) based on intended use, principle of operation, material biocompatibility, and general safety. The "clinical study" described is more of a user feedback and usability assessment rather than a traditional clinical trial with a defined test set, ground truth experts, and statistical performance metrics.

Therefore, many of the requested details about acceptance criteria, test set specifics, expert qualifications, and comparison with AI/ML-based studies cannot be extracted directly from this document.

However, I will extract what information is available and indicate when information is not present in the document.

Description of Device and Purpose of Study

The OptiPillows EPAP Mask is a reusable nasal dilator device intended for use during sleep to alleviate snoring in adults. It works by creating positive pressure during expiration through a resistance valve, preventing the collapse of upper airways. The "study" described is primarily a user feedback and usability assessment to support the device's safety and effectiveness claim through substantial equivalence.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not provide a formal table of quantitative acceptance criteria with corresponding performance metrics like those typically seen for AI/ML device submissions (e.g., sensitivity, specificity, AUC). The "acceptance" here primarily relies on qualitative user feedback, observed usability, and demonstration of comparable mechanism of action to a predicate device.

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

• Sample Size (Clinical Questionnaire/User Feedback):
  • Group 1 (Existing Users): 39 questionnaires provided, 29 responded (21 men, 8 women).
  • Group 2 (New Users): 18 patients, 13 responded and completed questionnaires (4 females, 9 males).
  • Total Responded: 29 + 13 = 42 patients.
• Data Provenance: The document does not explicitly state the country of origin. Given the "Phoenix, Arizona" address for the submitter, it is implied the users were likely from the US.
• Retrospective or Prospective:
  • Group 1: Retrospective (patients already using the mask for >6 months).
  • Group 2: Prospective (new patients trying the mask, followed for 30-60 days).

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

Not Applicable (N/A) in the context of an AI/ML device.
This submission is for a physical mechanical device. The "ground truth" for snoring alleviation and usability was primarily based on self-reported user feedback and bed-partner observations, documented via questionnaires. There were no "experts" in the sense of radiologists adjudicating images or clinicians diagnosing conditions for a test set. The Epworth Sleepiness Scale (ESS) is a self-administered questionnaire.

4. Adjudication Method for the Test Set

N/A in the context of an AI/ML device.
There was no adjudication process involving multiple expert readers or diagnosticians as would be seen for image-based AI/ML devices. The "clinical study" was a collection of user feedback.

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

No MRMC study was done.
This is an application for a physical device, not an AI/ML diagnostic or assistive tool. Therefore, there was no comparison of human reader performance with or without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance)

N/A.
This applies to AI/ML algorithms. The device is a physical mask used by a human. Its performance is inherent in its physical function and user experience.

7. Type of Ground Truth Used

The "ground truth" for the effectiveness of the device in alleviating snoring and improving sleep quality was established through:

• Self-reported user feedback: From the clinical questionnaire regarding usability, benefits, and overall experience.
• Bed-partner observations: Users reported that their bed partners noticed improvement in snoring.
• Epworth Sleepiness Scale (ESS) scores: Self-administered questionnaire to assess daytime sleepiness before and after using the mask in new users (Group 2) and after use in existing users (Group 1). This is an outcomes-based measure for symptoms.

8. Sample Size for the Training Set

N/A.
This is a physical device, not an AI/ML algorithm that requires a training set.

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

N/A.
As there is no AI/ML algorithm, there is no training set or ground truth establishment for a training set.

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The F&P Pilairo Nasal Pillows Mask is intended to be used by individuals who have been diagnosed by a physician as requiring CPAP or Bi-Level Ventilator treatment. The F&P Pilairo Nasal Pillows Mask is intended for single-patient adult use in the home and multiplepatient adult use in the hospital or other clinical setting where proper disinfection of the device can occur between patient uses.

The Pilairo™ is a CPAP nasal pillows mask which has an external connector attached to a frame and face seal that encloses the nasal airway entrance, held in place by a single head strap. The external connector allows connection to a CPAP device. The device conveys pressurised air to the nares. The air may also be humidified and/or oxygen enriched. An oxygen pressure port accessory is available to be used with the device for oxygen therapy and/or gas monitoring.

The provided text is a 510(k) summary for a medical device, the Pilairo™ Nasal Pillows Mask. It details the device's description, intended use, and comparison to predicate devices, focusing on demonstrating substantial equivalence for regulatory approval.

However, the document does not contain the kind of information typically found in a study demonstrating performance based on acceptance criteria for AI/ML-based medical devices. Specifically, it does not include:

• Quantitative acceptance criteria for device performance (e.g., sensitivity, specificity, accuracy thresholds).
• Study design details like sample size for test sets, data provenance, ground truth establishment methods (expert consensus, pathology, etc.).
• Information about human expert involvement (number of experts, qualifications, adjudication methods).
• Details on AI/ML specific studies such as MRMC studies, standalone AI performance, or training set specifics.

The document describes non-clinical tests that were performed to compare the Pilairo™ Nasal Pillows Mask to predicate devices for performance and biocompatibility, stating that these tests demonstrate "substantial equivalence." However, it does not provide the specific results or the acceptance criteria used for these non-clinical tests in a format that would allow for the table requested. The "performance" mentioned refers to engineering performance of the mask (e.g., sealing, pressure delivery), not AI/ML model performance.

Therefore, many of the requested fields cannot be filled from the provided text as they pertain to a different type of device evaluation (AI/ML performance studies) than what is described for this medical mask.

Based on the provided text, here's what can be inferred and what cannot be provided:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states "Copies of test reports are included in Appendix B," but Appendix B is not provided in the input text. Thus, the specific numerical results of these non-clinical tests and the precise quantitative acceptance criteria are not available.

Information Not Found in the Provided Text:

• Any form of AI/ML or algorithm performance metrics (e.g., accuracy, sensitivity, specificity, AUC).
• Quantitative thresholds for these metrics.

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

• Sample Size for Test Set: Not specified. The document mentions "non-clinical tests" but does not detail the sample sizes (e.g., number of masks tested, number of simulated breathing cycles, or simulated patients). This is expected for a physical device rather than an algorithm.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not applicable in the context of AI/ML studies. For this physical device, testing would likely be performed in a lab setting, presumably by Fisher & Paykel Healthcare in New Zealand, as indicated by their address. The nature of testing would be prospective (performing tests on new masks).

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

• Number of Experts: Not specified. This type of human expert ground truth establishment is not typically performed for the evaluation of physical medical masks (like a CPAP mask), as their performance (e.g., seal, pressure delivery) is evaluated through engineering tests and clinical use validation rather than via human expert "reading" of data.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. As there are no human "readers" or interpretations that would require adjudication for this physical device. Performance is measured through engineering parameters.

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

• MRMC Study: No. This type of study is relevant for AI/ML diagnostic or assistive devices where human readers interpret medical images or data. It is not applicable to a CPAP nasal mask.

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

• Standalone Performance: Not applicable. This device is a physical medical mask, not an algorithm.

7. The Type of Ground Truth Used

• Type of Ground Truth: For a physical medical device like a CPAP mask, "ground truth" typically refers to:
  • Engineering Specifications/Standards: Performance is validated against established industry standards or internal engineering specifications for parameters like pressure drop, dead space, leak rates, and material properties.
  • Comparison to Predicate Device: The primary method stated is comparison to the "Fisher & Paykel Healthcare Opus HC482 Direct Nasal Mask for performance" and "Zest™ Nasal Mask for biocompatibility" to demonstrate substantial equivalence. These predicate devices are the "ground truth" standard.
  • Biocompatibility Testing: Adherence to material safety standards.
  • Clinical Use Performance: Implicitly, the mask must function effectively without causing harm during use in patients requiring CPAP/Bi-Level therapy.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a physical product, not an AI/ML algorithm that requires training data.

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

• Ground Truth Establishment for Training Set: Not applicable. As there is no AI/ML algorithm, there is no "training set." The "ground truth" for the device's design and manufacture would be based on human engineering and medical knowledge, design specifications, and successful performance of predicate devices.

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The 3B Flex-Lite™ channels airflow noninvasively to a patient from a positive airway pressure (PAP) device such as a continuous positive airway pressure (CPAP) or a bilevel system. The 3B Flex-Lite™ is:

• to be used by adult patients (>66lb / 30 kg); (1)
• to be used for single-patient reuse in the home environment and multipatient (2) reuse in the hospital/institutional environment.
• (3) to be used in the following environments: home, hospital, and sub-acute institutions.
• intended for prescription use. (4)

The 3B Flex-Lite™ is a mask interface, of the nasal pillow variety, that directs airflow from a positive pressure device to the patient's nose. The mask is held in place with adjustable headgear that straps the mask to the face.

The 3B Flex-Lite™ is safe when used under the conditions and purposes intended as indicated in the labeling provided with the product.

The 3B Flex-Lite™ is a prescription device supplied non-sterile.

The provided document describes the 3B Flex-Lite Nasal Mask, a device intended to channel airflow noninvasively to a patient from a positive airway pressure (PAP) device. The document focuses on demonstrating substantial equivalence to predicate devices rather than establishing novel performance criteria. Therefore, the information provided does not directly outline "acceptance criteria" as distinct performance thresholds that the device must meet for a specific clinical task. Instead, the "acceptance criteria" are implicitly met by demonstrating substantial equivalence to legally marketed predicate devices through comparable technological characteristics and performance.

Here's an analysis based on the provided text, focusing on how the device meets the implicit acceptance criteria of substantial equivalence:

1. Table of Acceptance Criteria and Reported Device Performance

As explicit acceptance criteria with numerical targets are not stated, this table will frame the "acceptance criteria" as comparability to predicate devices for key performance and safety characteristics.

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

The document refers to "Performance bench testing of both the 3B Flex-Lite™ and the Nasal Aire II were conducted" and explicitly mentions a "Piper Medical" test report dated March 23, 2011, annexed at Appendix A. However, the specific sample size for these bench tests (e.g., number of units tested) and the country of origin of the data are not detailed in the provided text. The testing appears to be retrospective in the sense that it evaluates the manufactured device against established performance benchmarks and comparisons to existing devices, rather than a prospective clinical trial with human subjects.

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

This information is not provided in the document. The "ground truth" for the bench tests would typically be defined by engineering specifications, regulatory standards, and the performance characteristics of the predicate devices. The individuals conducting and reporting the tests (e.g., Piper Medical) would be engineers or technicians with expertise in medical device testing, but their specific qualifications or the number involved are not stated.

4. Adjudication Method for the Test Set

This information is not provided. Given that the tests are bench tests, an adjudication method in the clinical sense (e.g., 2+1 physician consensus) is not directly applicable. The "adjudication" would be based on comparison of test results to predefined criteria or to the predicate device's measured performance.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not applicable to this device. The 3B Flex-Lite™ Nasal Mask is a physical medical device (mask interface), not an AI-powered diagnostic or assistive technology for human readers. Therefore, there is no discussion of human reader improvement with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

A standalone performance study of an algorithm is not applicable to this device, as it is a physical device, not an algorithm or AI system. The performance tests ("Non-clinical Tests") evaluated the physical mask's characteristics.

7. The Type of Ground Truth Used

The ground truth used for evaluating the 3B Flex-Lite™ appears to be based on:

• Engineering specifications and regulatory standards for medical devices (implicitly, concerning safety, materials, and performance parameters like dead space, CO2 rebreathing, flow vs. leak pressure).
• Performance characteristics of legally marketed predicate devices (InnoMed Nasal-Aire II and Resmed Swift FX) as established through their own testing and marketing. The goal was to demonstrate that the new device is "substantially equivalent" in terms of performance to these predicates.

8. The Sample Size for the Training Set

This is not applicable. The 3B Flex-Lite™ Nasal Mask is a physical medical device, not a machine learning model, and therefore does not have a "training set" in the context of AI.

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

This is not applicable for the same reasons as #8.

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