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The CanGaroo Envelope is intended to securely hold a cardiac implantable neurostimulator to create a stable environment when implanted in the cardiac implantable electronic devices that may be used with the CanGaroo Envelope include pacemaker pulse generators, defibrillators, or other cardiac implantable neurostimulator devices that may be used with the CanGaroo Envelope include vagus nerve stimulators, spinal cord neuromodulators, deep brain stimulators and sacral nerve stimulators.

The CanGaroo Envelope is intended to securely hold a cardiac implantable electronic device or an implantable neurostimulator to create a stable environment when implanted in the cardiac implantable electronic devices that may be used with the CanGaroo Envelope include pacemaker pulse generators, defibrillators, or other cardiac implantable electronic devices. The implantable neurostimulator devices that may be used with the CanGaroo Envelope include vagus nerve stimulators, spinal cord neuromodulators, deep brain stimulators and sacral nerve stimulators.

The CanGaroo Envelope is constructed from two to four perforated, multilaminate sheets (4-ply) of decellularized, non-crosslinked, lyophilized ECM (extracellular matrix) derived from porcine small intestinal submucosa. The 3 mm perforations are spaced evenly at 10 mm apart to allow exit of any exudate. The ECM is assembled into pouch form using violet 5-0 polydioxanone suture (PDS). The device design is identical to the device cleared under K182255.

The provided text describes a 510(k) submission for the CanGaroo Envelope, which is a surgical mesh envelope intended to securely hold cardiac implantable electronic devices or implantable neurostimulators. This submission (K192616) is a Special 510(k) application based on a change in the labeled shelf life of the device, rather than a new device or significant modification to its design or indications for use.

Therefore, the document does not contain information typically found in a clinical study report for an AI/ML device, such as:

• Acceptance criteria related to AI performance (e.g., sensitivity, specificity, AUC)
• A test set of medical images or patient data
• Information on expert readers, ground truth establishment, or adjudication methods
• Details of a multi-reader, multi-case (MRMC) study or standalone algorithm performance
• Training set details for an AI model

Instead, the "testing" mentioned in this document refers to non-clinical testing (specifically, shelf-life testing and seam strength testing of aged products) to support the extended shelf life.

Based on the provided text, it is not possible to fill out the requested table or answer the questions related to AI device performance evaluation. The device described is a physical medical device (surgical mesh), not an AI/ML software device.

However, if we were to interpret the "device" as a product undergoing a 510(k) pathway, and map the available information to the request (even if it doesn't perfectly fit), here's what could be inferred, focusing on the concept of 'acceptance criteria' for the shelf-life change:

Simulated "Acceptance Criteria" for Shelf Life Extension (based on inference):

Given the context of a Special 510(k) for shelf-life extension, the "acceptance criteria" and "study" would relate to the physical properties of the device over its proposed new shelf life.

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: Not explicitly stated, but for shelf-life testing of physical products, samples from specific manufacturing lots would have been used for real-time aging studies. This would typically be a pre-defined statistical sample size based on relevant standards (e.g., ISO, ASTM) and risk assessment.
• Data Provenance: The testing was "real-time aged product," implying the device was stored for the full 30-month period under specified conditions, then tested. This is prospective testing for the shelf-life study itself. The country of origin of the data/testing is not specified but would typically be performed at the manufacturer's facility or a contract testing lab.

3. Number of Experts Used and Qualifications:

• Not Applicable. This is a physical product shelf-life test, not an AI/ML diagnostic performance study involving human readers or expert consensus on medical images. The "experts" would be analytical chemists or material scientists performing laboratory tests.

4. Adjudication Method for the Test Set:

• Not Applicable. This is a laboratory test with objective, measurable outcomes (e.g., force measured for seam strength). There is no "adjudication" in the sense of reconciling subjective expert opinions.

5. MRMC Comparative Effectiveness Study:

• Not Applicable. This is a physical medical device, not an AI/ML software.

6. Standalone Algorithm Performance:

• Not Applicable. This is a physical medical device, not an AI/ML algorithm.

7. Type of Ground Truth Used:

• For shelf-life testing, the "ground truth" is the measured physical properties of the aged device (e.g., measured seam strength, visual inspection for degradation, etc.) compared against pre-defined specifications. This is an objective, laboratory-derived "truth."

8. Sample Size for the Training Set:

• Not Applicable. This device does not involve a "training set" in the context of AI/ML.

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

• Not Applicable.

In summary, the provided document is a 510(k) clearance letter and summary for a physical medical device, focusing on a shelf-life extension. It does not provide the information requested about AI/ML device performance or associated clinical studies.

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