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The Spetzler Snap-On/Slide-On Scalp Retractor Clamps are accessories that are intended to be used to assist in the retraction of the scalp during all supratentorial and infratentorial skull operations.

The Spetzler Snap-On/Slide-On Scalp Retractor Clamps are surqical accessories that affix to the appropriately sized surgical bars surrounding the patient's head during neurosurgical procedures. The clamps interact with elastic scalp retraction hooks to assist with the self-retaining retraction of the scalp during neurosurgical procedures. The clamps are offered in two versions (Snap-On and Slide-On) and each version is offered in two sizes (0.5" and 20mm) to accommodate most commonly used surgical accessory bars.

This document describes the Spetzler Snap-On/Slide-On Scalp Retractor Clamps and their intended use. The information provided is primarily for regulatory submission (510(k) summary) rather than a detailed study report. Therefore, much of the requested information regarding acceptance criteria and a specific study proving device performance in a clinical or statistical sense (e.g., sample sizes, expert ground truth, MRMC studies) is not present. The document focuses on demonstrating substantial equivalence to predicate devices through non-clinical performance testing.

Here's an attempt to answer the questions based only on the provided text, highlighting what is available and what is not:

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

The document does not explicitly state quantitative acceptance criteria or detailed reported device performance in a numerical table format for characteristics like strength, durability, or exact fit. Instead, it refers to a qualitative assessment of "functional characteristics."

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 for Test Set: Not specified. The document globally refers to "non-clinical tests" without detailing the number of units tested, the number of surgical bars it was tested with, or the number of different hooks used.
• Data Provenance: Not specified. It's implied the testing was conducted by Cardinal Health, likely in the US (their address is in Illinois, USA). The document does not specify if the testing involved human subjects or patient data. Given the nature of a scalp retractor clamp, "non-clinical tests" would typically refer to bench or mechanical testing.
• Retrospective or Prospective: N/A, as this refers to non-clinical bench testing, not a clinical study.

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)

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The document only mentions "Performance testing demonstrated..." without detailing who conducted or evaluated this performance.

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

• Adjudication Method: Not specified.

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, an MRMC study was not done. This device is a mechanical surgical accessory, not an AI-powered diagnostic or assistive tool for "human readers." Therefore, this question is not applicable.

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

• Standalone Performance: Not applicable. This is a mechanical device, not an algorithm. The "standalone" performance would be its functional performance as described in the non-clinical tests.

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

For this mechanical device, "ground truth" would refer to its designed specifications and functional requirements.

• Type of Ground Truth: The "non-clinical tests" assessed "design performance and conformance to design specifications." This implies the ground truth was the device's design specifications and functional requirements itself, as evaluated through engineering and mechanical testing. The comparison point ("substantially equivalent") was against predicate devices.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This is a mechanical device, not a machine learning model, so there is no "training set."

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

• How Ground Truth for Training Set was Established: Not applicable, as there is no training set.

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