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The CINCH™ Knotless Fixation Implant System is intended for the fixation of soft tissue to bone during rotator cuff repair.

The CINCHT™ Knotless Fixation Implant includes single-use, sterile Anchor (3.5mm in diameter), which is preloaded onto a disposable anchor inserters. The CINCH™ Knotless Fixation Implant System is comprised of nondegradable suture anchors each pre-loaded onto an inserter.

The provided text describes a 510(k) submission for a medical device, the CINCHT™ Knotless Fixation Implant System. This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving performance against specific acceptance criteria through a clinical study or AI performance metrics.

Therefore, many of the requested categories for AI/clinical study performance data are not applicable to this document. The submission focuses on bench testing and comparison to existing devices.

Here's a breakdown of what can be extracted and what is N/A:

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

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 for Test Set: Not specified. The document refers to "bench testing" but does not give specific numbers of tests or implants used.
• Data Provenance: Not specified, but generally, bench testing for a 510(k) submission would be conducted by the manufacturer (C2M Medical, Inc. in San Antonio, Texas, USA) or a contracted lab. This is a retrospective analysis of the device's characteristics against its design.

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 a medical device 510(k) submission based on bench testing, "ground truth" is established by engineering and materials science principles and validated through empirical measurements (bench testing), not by expert consensus in the way AI models define it.

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

• Not Applicable. Adjudication methods are typically used in clinical trials or for establishing ground truth for AI models with human interpretation. This document describes bench 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

• Not Applicable. This is a medical device (surgical implant), not an AI-powered diagnostic or assistive tool.

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

• Not Applicable. This is a medical device (surgical implant), not an AI algorithm.

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

• Bench Testing Results / Engineering Specifications: The "ground truth" for this device's performance is its ability to meet engineering specifications and function as intended during bench tests. This is a physical or mechanical "ground truth."

8. The sample size for the training set

• Not Applicable. This is a physical medical device, not an AI model requiring a training set.

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

• Not Applicable. As above, no AI model, no training set, no ground truth to establish for a training set.

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