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Intended to be worn by operating room personnel to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids and particulate material.

These disposable surgical masks are formed of three layers and are flat-fold disposable face masks comprised of two segments which form a comfortable mask covering the nose and mouth areas of the face. The outer mask surface is of non-woven polypropylene. The middle layer, between the non-woven outer and inner lavers, is made of "meltblown" air filtration media. This material is designed as a highly efficient bacterial filter with very low pressure drop, to facilitate breathing and minimize spectacle fogging. The facial layer is of non-woven polypropylene. The mask is designed to be resistant to penetration even when body fluids strike it with impact, while allowing cool, comfortable breathing.

Drawings of the Defend Surgical Mask appear in Attachment I. These are intended to be exemplary rather than exhaustive. The mask is formed of three layers and is a flat-fold disposable face mask comprised of pleated segments which open to form a comfortable mask covering the nose and mouth areas of the face. The sides are secured by binding tapes to which is attached the elastic band to secure the mask to the face. The top and bottom of the mask are fused to prevent fabric delamination.

The outer mask surface is of Spunbond non-woven polypropylene (20 g/m'). The middle layer, between the non-woven outer and inner layers, is made of meltblown air filtration media. The characteristics of this media are listed in Attachment VI, This material is designed as a highly efficient bacterial filter with very low pressure drop, to facilitate breathing and minimize spectacle fogging. The facial layer is of Thermobond non-woven polypropylene (15 g/m²). The characteristics of the two outer layers are also listed in Arachment VI. The mask is designed to be resistant to penetration even when body fluids strike it with impact, while allowing cool, comfortable breathing.

The mask has a light aluminum strip which bends readily to fit closely over the nose, diminishing fogging of spectacles. It also has a light foam strip fused to this edge to provide more effective coverage and user comfort. Two woven elastic ear loops complete the mask.

The products will be sold non-sterile, prepackaged, and are disposable, for single use only.

The provided text describes a 510(k) summary for the DEFEND™ Surgical Mask, focusing on its substantial equivalence to other legally marketed devices. It details the device's description and the tests performed to demonstrate this equivalence.

Here's an analysis based on your requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The submission states, "Performance Standard: None established under section 514." Therefore, explicit acceptance criteria in terms of specific threshold values are not provided within the document. Instead, the study aims to show "substantial equivalence" to predicate devices. The "reported device performance" is essentially that the device performed comparably to predicate devices in the listed tests.

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

The document does not specify the sample sizes used for each of the tests. It only states, "Test data supplied to show the equivalence of this device to Technol and others cited below included..."

The data provenance (country of origin, retrospective/prospective) is not mentioned. Given the nature of a 510(k) submission for a surgical mask, these tests are typically prospective laboratory tests conducted on samples of the device.

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

This type of information is not relevant or typically included in a 510(k) submission for a surgical mask. The "ground truth" for material performance tests is established by standardized testing methodologies, not expert consensus in the diagnostic sense. The tests themselves provide objective measurements.

4. Adjudication Method for the Test Set

Not applicable. As mentioned above, the assessment is based on objective laboratory tests against established standards or predicate device performance, not on expert adjudication of subjective interpretations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No, an MRMC comparative effectiveness study was not done. These types of studies are relevant for medical imaging or diagnostic devices where human interpretation plays a significant role. This submission pertains to a surgical mask, where performance is evaluated through physical and material tests.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. This device is a physical product (surgical mask), not an algorithm or software. Therefore, the concept of "standalone performance" in that context does not apply. The tests described are inherently "standalone" in the sense that they measure the device's intrinsic properties.

7. The Type of Ground Truth Used

For the performance tests listed (e.g., penetration, filtration efficiency, breathability), the "ground truth" is based on objective measurements derived from standardized laboratory testing protocols. These protocols aim to quantify specific physical and material properties of the surgical mask in a controlled environment. The comparison is then made against "predicate devices" (other surgical masks already on the market) which are presumed to be safe and effective.

8. The Sample Size for the Training Set

Not applicable. This device is a physical product and does not involve AI or machine learning algorithms that require a "training set."

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

Not applicable, as no training set was used.

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to act as physical barrier including fluidresistant properties, provide only very low impediment to breathing, avoid fogging of surgeons glasses, effective filtration of particles, droplets, not hinder speech. These are the same as those of the predicate devices These products also have the same intended yses as similar products currently cleared for marketing by the 510(k) process

These disposable surgical masks are formed of three layers and are flat-fold disposable face masks comprised of two arcuale segments which form a comfortable mask covering the nose and mouth areas of the face The outer mask surface is of non-woven polypropylene The middle layer, between the non-woven outer and inner layers, is made of "Web Dynamics" air filtration media. This material is designed as a highly efficient bacterial filter with very low pressure drop, to faciliate breathing and minimize spectacle fogging. The facial layer is of non-woven polypropylene. The mask is designed to be resistant to penetration even when body fluids strike it with impact, while allowing cool, comfortable breathing

The provided text describes a 510(k) premarket notification for a new surgical mask. The information focuses on establishing substantial equivalence to predicate devices rather than proving a device meets specific acceptance criteria through a study with predefined performance metrics. Therefore, many of the requested sections (e.g., sample sizes for test and training sets, expert qualifications, MRMC studies) are not applicable to this type of regulatory submission.

However, I can extract the 'acceptance criteria' implicitly from the tests performed to demonstrate substantial equivalence, and report the 'device performance' as stated in the submission.

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

Acceptance Criteria and Device Performance

Study Details (Based on the 510(k) submission type)

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

• Sample Size: Not specified in the document for the performance tests. Implied to be sufficient for the specific test protocols.
• Data Provenance: Not explicitly stated, but the tests were performed as part of a U.S. regulatory submission (Hauppauge, NY is mentioned as the submitter's location). The studies are inherently prospective, as they were conducted to support the 510(k) submission for this specific device.

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 is not applicable. The tests performed are laboratory-based and do not involve expert interpretation or clinical ground truth establishment in the way, for example, a medical imaging AI product would.

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

• This is not applicable. Adjudication methods are relevant for studies involving human interpretation or clinical endpoints, not for laboratory performance tests of a surgical mask.

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

• This is not applicable. MRMC studies are typically used for medical imaging or diagnostic devices where human readers interpret results, and the device assists or provides a diagnosis. This submission is for a physical barrier device (surgical mask).

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

• This is not applicable. There is no "algorithm" in the context of a surgical mask. The performance tests are for the physical properties of the mask itself.

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

• The "ground truth" for the performance tests is based on established laboratory standards and protocols for evaluating surgical masks (e.g., synthetic blood penetration, bacterial filtration efficiency). It's not clinical "ground truth" derived from patient data.

8. The sample size for the training set

• This is not applicable. There is no training set in the context of physical property testing for a surgical mask. This is not a machine learning or AI device.

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

• This is not applicable, as there is no training set.

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