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FortiShield is intended for use as a temporary wound covering, and to provide a moist wound healing environment on cleanly debrided wounds after hemostasis has been established.

FortiShield is indicated for: partial thickness wounds, pressure sores, venous ulcers, diabetic ulcers, chronic vascular ulcers, surgical wounds (donor sites/grafts, post-laser surgery, podiatric, wound dehiscence), trauma wounds (abrasions, lacerations, partial thickness burns, and skin tears) and draining wounds.

FortiShield is a sterile, translucent biosynthetic wound matrix made from a knitted tri-filament nylon fabric that is mechanically bonded to a semi-permeable silicone membrane. Denatured porcine dermal collagen is bonded to the nylon/silicone bi-layer membrane to provide a dressing that is designed to adhere to the application site, provide a barrier to the external environment, and allow for excess exudate drainage.

FortiShield is not made with natural rubber latex. FortiShield is non-pyrogenic.

This is a 510(k) premarket notification for the FortiShield device, a biosynthetic wound matrix. The document asserts the device's substantial equivalence to predicate devices based on technological characteristics and performance data.

Here's an analysis of the provided information regarding acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly define formal "acceptance criteria" in a quantitative manner as one might expect for a diagnostic AI device (e.g., minimum sensitivity/specificity). Instead, the assessment focuses on demonstrating equivalence to predicate devices. The "acceptance criteria" are implicitly met by showing comparable performance against the predicate devices across several characteristics.

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

The document does not describe a "test set" in the context of a typical AI/software performance study with a specific number of cases. The "study" here is a series of non-clinical mechanical and biocompatibility tests on the device itself and direct comparison to predicate devices, not an evaluation of diagnostic performance on patient data.

• Sample Size for Mechanical Testing: Not explicitly stated, but these would be a number of FortiShield device samples and predicate device samples.
• Sample Size for Biocompatibility Testing: Not explicitly stated, but this refers to samples of the FortiShield device tested according to ISO 10993 protocols.
• Data Provenance: Not applicable in the sense of patient data. The data originates from laboratory testing of the physical devices.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

Not applicable. "Ground truth" in the context of this device is established through:
* Material characterization and manufacturing specifications.
* Standard ISO and FDA-recognized mechanical testing protocols.
* Standard ISO and FDA-recognized biocompatibility testing protocols.
* Comparison to the known characteristics of legally marketed predicate devices.

4. Adjudication Method for the Test Set:

Not applicable. There is no human adjudication process described here for establishing ground truth, as it's a conformity assessment against physical and material properties and a comparison to known predicate devices.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

Not applicable. This device is a wound dressing, not a diagnostic imaging AI algorithm. There is no human interpretation component where AI assistance would be evaluated.

6. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance):

Not applicable. This is not an AI algorithm. The performance evaluation is for the physical device itself.

7. Type of Ground Truth Used:

The "ground truth" for this device's performance is established based on:
* Material and Device Specifications: Characteristics like composition, structure, dimensions, and manufacturing standards.
* Validated Laboratory Testing: Results from mechanical tests (tensile elongation, fatigue, water vapor transmission rate) and biocompatibility tests (ISO 10993 endpoints like irritation, toxicity, cytotoxicity, etc.).
* Predicate Device Characteristics: The known, legally marketed properties and performance of the substantially equivalent predicate devices.

8. Sample Size for the Training Set:

Not applicable. This is not an AI device or a machine learning model, so there is no training set.

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

Not applicable, as there is no training set for this device.

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