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The Pitch-Patch is a single use device intended to be used for reinforcement of the rotator cuff following or during repair by suture or suture anchors, where weakness exists in the soft tissue.

The Pitch-Patch is not intended to replace normal body structure or provide the full mechanical strength to support the rotator cuff. Sutures, used to repair the tear, and sutures or bone anchors, used to attach the tissue to the bone, provide mechanical strength for the repair.

The Pitch-Patch is a permanent implantable device for reinforcement of rotator cuff tears. It is constructed from a warp knitted fabric with integral eyelets. It is reinforced around its perimeter and around each eyelet to increase the security of suture attachment. The Pitch-Patch is available in two sizes, to cover different tear sizes without trimming (30 x 20 mm and 35 x 25 mm). It should not be cut to size. The device is supplied sterile.

The Pitch-Patch is made from Polyethylene Terephthalate (PET) also referred as polyester. This a nonabsorbable material that has a long history of use in the orthopedic market.

The provided text describes the 510(k) clearance for the Pitch-Patch Tissue Reinforcement Device. This device is a surgical mesh intended to reinforce the rotator cuff during or after repair.

The information provided focuses on the performance testing conducted to demonstrate the device's substantial equivalence to predicate devices, rather than establishing acceptance criteria and proving the device meets them in the context of an AI/software device. The document describes a medical device, not an AI/software device. Therefore, many of the requested points related to AI/software performance criteria (e.g., sample size for test/training set, expert ground truth, MRMC study, standalone algorithm performance) are not applicable or extractable from this document.

However, I can extract information related to the performance studies done for this physical medical device.

Here's an analysis based on the document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" in the typical sense for an AI/software device (e.g., minimum sensitivity, specificity). Instead, it lists the types of performance tests conducted and concludes that the results demonstrate the device's mechanical properties are appropriate and that differences from predicates do not affect safety and efficacy.

2. Sample size used for the test set and the data provenance:

• Test Set Sample Size: For the clinical study, the sample size was 50 patients.
• Data Provenance: The document states it was a "prospective cohort study," implying prospective data collection. The country of origin is not explicitly stated for the patients, but the submitter (Xiros Ltd) is based in the United Kingdom.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• This question is not applicable as this is a physical medical device. "Ground truth" in the context of diagnostic AI is not relevant here. The clinical outcomes (Constant-Murley score, SSV, re-ruptures, revisions) are direct patient data.

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

• Not applicable for a physical medical device and clinical outcome study of this nature. Clinical outcomes were measured directly.

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 as this is a physical medical device, not an AI diagnostic tool.

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

• Not applicable as this is a physical medical device, not an AI algorithm.

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

• The "ground truth" equivalent for the clinical performance was patient outcomes data, specifically:
  • Constant-Murley score (a standardized functional outcome measure for the shoulder).
  • Subjective Shoulder Value (SSV).
  • Incidence of complete re-ruptures (diagnosed clinically).
  • Incidence and reasons for revision surgery.

8. The sample size for the training set:

• Not applicable as this is a physical medical device; there is no "training set" in the AI sense.

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

• Not applicable as this is a physical medical device; there is no "training set" in the AI sense.

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