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The Trilliant Sniper Staple System is indicated for fixation of fractures and osteotomies of the hand, foot, and bones appropriate for the size of the device.

The Sniper Staple System consists of different-sized staples composed of Nitinol (Nickel-Titanium alloy) intended for fixation of fractures and osteotomies of the hand, foot, and bones appropriate for the size of the device. The system will be offered non-sterile in a tray for sterilization at the user's facility prior to use.

Here's an analysis of the provided text regarding acceptance criteria and the supporting study, structured as requested. It's important to note that this document describes a medical device (bone staple), not an AI/algorithm-based device. Therefore, many of the requested fields pertinent to AI (like human reader improvement with AI assistance, training set details, or ground truth for AI) will not be applicable.

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

For a medical device like the Sniper Staple System, acceptance criteria are typically demonstrated through performance testing against established consensus standards.

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: The document does not specify the exact number of staples or test specimens used for each non-clinical test (elastic static bending, pull-out, transformation temperature, corrosion resistance). It only states that "The following tests were performed."
• Data Provenance: Not applicable as these are non-clinical (laboratory/bench) tests on manufactured device samples, not patient data.

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. For non-clinical performance testing of a physical medical device, "ground truth" is established by adherence to recognized engineering and material science standards (ASTM in this case), and the results are quantified through laboratory measurements. Expert opinions in the context of clinical interpretation are not relevant here.

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

Not applicable. Adjudication methods are typically relevant for clinical studies or image interpretation tasks where there's variability in human assessment. These are objective engineering tests.

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 bone staple device, not an AI/imaging diagnostic tool.

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

Not applicable. This is a physical bone staple device, not an algorithm. The "standalone" performance here refers to the device's material and mechanical properties as tested against standards.

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

The "ground truth" for the non-clinical tests is defined by the objective pass/fail criteria and quantitative measurements specified within the referenced ASTM (American Society for Testing and Materials) standards. These standards prescribe specific methodologies, acceptable ranges, and performance benchmarks for metallic bone staples and Nitinol materials.

8. The sample size for the training set

Not applicable. This refers to a physical medical device, not a machine learning model.

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

Not applicable. This refers to a physical medical device, not a machine learning model.

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The Trilliant Surgical Sniper Staple System is indicated for fixation of fractures and osteotomies of the hand, foot, and bones appropriate for the size of the device.

The Sniper Staple is a mechanical osteosynthesis device allowing for fixation and compression of the bone fragments in order to encourage early bone healing. The staple is fabricated from a nickel-titanium alloy (Nitinol) and possesses super-elastic properties at room temperature. The staple offering is composed of staples consisting of a 1.5 mm x 1.2 mm diameter "U" shaped wire. The "U" shaped staple is available in 8 mm x 8 mm and 10 mm x 10 mm sizes.

This document is a 510(k) premarket notification for a medical device called the "Sniper Staple System." It is a submission to the FDA to demonstrate substantial equivalence to legally marketed predicate devices, not a study proving the device meets specific acceptance criteria in the context of an AI/algorithm-based device.

Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, ground truth establishment, expert involvement, and AI/MRMC studies is not applicable to this type of document.

However, I can extract the relevant information from the document in the context of a traditional medical device (a surgical staple).

Here's the information that can be extracted:

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

For a traditional medical device like a surgical staple, "acceptance criteria" are typically defined by recognized standards and mechanical testing rather than a numerical performance metric like sensitivity/specificity for an AI. The document describes several non-clinical tests performed.

2. Sample sized 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 mechanical testing, sample sizes are typically determined by the specific ASTM standards referenced (e.g., F564, F2082, F2129).
• Data Provenance: Not applicable. These are laboratory-based mechanical and biological (pyrogenicity) tests performed on the device itself, not data from human subjects or clinical records.

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 as typically understood for AI/diagnostic algorithms is not relevant here. The "truth" is established by the physical properties and performance of the device as measured by standardized engineering and biological tests.

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

• Not applicable. This concept pertains to human review of medical data for ground truth establishment, which is not relevant for this device's testing.

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 is a traditional surgical staple, not an AI or diagnostic imaging device.

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

• No. This is a physical medical device, not an algorithm.

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

• For mechanical tests: Engineering standards (ASTM F564, F2082, F2129) define acceptable performance.
• For biocompatibility/safety test: Biological standards (e.g., maximum endotoxin level for pyrogenicity).

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device.

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

• Not applicable. This is not an AI/machine learning device.

Summary from the document for the Sniper Staple System:
The device's substantial equivalence to predicate devices is based on non-clinical testing, including:

• Four-point Bending (ASTM F564)
• Pull-out Testing (ASTM F564)
• Bend and Free Recovery Testing (ASTM F2082)
• Corrosion testing (ASTM F2129)
• Pyrogenicity testing (Limulus amebocyte lysate (LAL) assay)

The document states, "The results of these evaluations indicate that the Sniper Staple is equivalent to predicate devices," and for pyrogenicity, "The testing demonstrated that the subject device meets the recommended maximum endotoxin level of 20 EU per device." No clinical studies were performed. The conclusion for equivalence is based on similarities in principles of operation, technology, materials, and indications for use.

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