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Anesthesia / Respiratory Filters
For use with ventilators, anesthesia machines and open flow systems where filtration of inspired and / or expired gases is desired.
Model – HEPA filter 3000/04 – Single patient use for exhalation limb of circuit on NPB 700 series ventilators
Models – HEPA filters - 6500/01, 6888/01, 8222/01, 8444/01 Model – Non-HEPA filters - 4000/01 Single patient use up to 24 hours. Patient tidal volumes > 150 ml, when applicable.

The Air Safety HEPA and Non-HEPA filters are available in multiple sizes and shapes, and incorporate standard 15 / 22 mm connectors with or without a gas sampling luer port. Some models adapt to fit ventilator exhalation limb only. The depth (HEPA filtration) filter uses a pleated paper fiber for filtration. Filters are tested for rating performance according to EN 13328 Salt for Breathing System filtration performance. The "HEPA" performance was also tested in accordance to DOE-3025-99, DOE-3020-97 and ASTM D2986 - DOP. The electrostatic (non-HEPA filtration) filters are tested by Nelson Laboratories for BFE and VFE.

This document describes the safety and effectiveness of Air Safety HEPA and Non-HEPA Filters. However, it does not fit the typical format of a study designed to prove a device meets acceptance criteria, especially in the context of an AI/ML powered device. This is a 510(k) premarket notification for traditional medical devices (filters), and therefore, many of the requested categories are not applicable.

Here's an attempt to answer the questions based on the provided text, with clear indications where the information is not available or not relevant to this type of device submission.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present "acceptance criteria" in a pass/fail format with direct device performance comparison in a single table, as might be found in a study for an AI/ML device. Instead, it lists technical characteristics and performance standards that the device meets.

However, based on the General Technical Characteristics table, we can infer performance criteria and compare them to the device's reported performance:

Summary of "Study" to Prove Device Meets Criteria:

The document details the device characteristics and states that the devices were tested to specific performance standards. This is not a "study" in the clinical trial sense but rather a series of engineering and laboratory performance tests.

• Testing Methodologies:
  • Filtration Performance: Tested according to EN 13328 Salt for Breathing System filtration performance.
  • HEPA Performance (Specific models): Tested in accordance with DOE-3025-99, DOE-3020-97, and ASTM D2986 - DOP.
  • Electrostatic (non-HEPA) Filtration (BFE and VFE): Tested by Nelson Laboratories.
• Conclusion: The submission concludes that "The data within the submission demonstrates that the proposed devices when compared to the legally marketed predicate devices are safe and effective and substantially equivalent." This implies that the performance characteristics met or exceeded those of the predicate devices and applicable standards.

Information Not Applicable / Not Provided for this Device Type:

The following requested information is primarily relevant for AI/ML-powered diagnostic or predictive devices, or those requiring clinical studies with human assessors. The provided document concerns a physical filter, for which these criteria are generally not applicable or not detailed in this type of 510(k) submission.

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

• Not Applicable / Not provided in this context. For physical filters, testing typically involves laboratory samples of the filters themselves, not patient data in the sense of AI/ML. The number of filter units tested for each specific performance claim (e.g., BFE, VFE, resistance) is not specified. Data provenance like "country of origin" for test data is not a typical requirement for device performance testing in this manner.

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):

• Not Applicable. "Ground truth" established by experts (like radiologists for an image analysis AI) is not relevant for a breathing circuit filter. Performance is measured objectively through standardized laboratory tests (e.g., particle counts, pressure measurements).

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

• Not Applicable. Adjudication methods are used to resolve discrepancies in expert opinions, typically for establishing ground truth in clinical datasets. This is not relevant for the objective performance testing of a physical filter.

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 filter, not an AI/ML-powered diagnostic tool that assists human readers.

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

• Not Applicable. This is a physical filter, not an algorithm.

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

• Not Applicable. The "ground truth" for a filter's performance is derived from standardized physical and biological challenge tests (e.g., aerosolized particles, bacterial/viral suspensions) and measurements, not clinical expert consensus or pathology.

8. The sample size for the training set:

• Not Applicable. This is a physical medical device, not an AI/ML algorithm that requires a training set.

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

• Not Applicable. As there is no training set for an AI/ML algorithm, this question is not relevant.

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