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DBX® Strip is indicated as a bone void filler for treatment of surgically created osseous voids or gaps that are not intrinsic to the stability of the bony structure. It can be used in the pelvis, extremities, and the posterolateral spine for posterolateral fusion. DBX® Strip, when used for posterolateral spine fusion, may be used with autograft.

DBX® Strip is for single patient use only.

DBX® Strip is a flat, malleable device composed of human demineralized bone matrix (DBM), sodium hyaluronate (NaHy), sodium phosphate dibasic buffer and gelatin (procine origin). DBX® Strip is for single patient use only and is available in five sizes.

The provided text describes a 510(k) submission for the DBX® Strip, a bone void filler. The submission focuses on demonstrating substantial equivalence to a previously cleared device (K042829) rather than presenting a de novo study with explicit acceptance criteria and performance data. Therefore, many of the requested criteria cannot be directly extracted from this document.

Here's an analysis based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance & 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 & 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

This information is not applicable as the device is a bone void filler, not an AI/imaging device. The submission is not for a software-as-a-medical-device (SaMD) or an AI-powered diagnostic tool. The "acceptance criteria" discussed are related to demonstrating substantial equivalence for a medical device, primarily through biocompatibility and osteoinductivity potential, rather than performance metrics like sensitivity, specificity, accuracy, or reader improvement, which are typical for AI studies.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

This information is not applicable in the context of an AI/imaging study's "test set" because the submission is for a medical device (bone void filler). The "studies" mentioned are laboratory tests (biocompatibility, sterility, osteoinductivity, viral clearance) and a reference to prior clinical use of the materials. No specific "test set" of patient data in the AI sense is described.

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):

This information is not applicable for the same reason as above. There is no "ground truth" to be established by clinical experts in the context of an AI study.

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

This information is not applicable as there is no "test set" requiring adjudication by multiple experts.

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

The "ground truth" for this device's safety and effectiveness is established through:

• Biocompatibility testing: Compliance with ISO 10993 standards.
• Sterility testing: Compliance with USP <71>.
• Osteoinductivity potential: Demonstrated in an athymic mouse model.
• Viral clearance: Laboratory testing with model viruses.
• Previous clinical use: The materials used in the device have a "long history of safe and effective clinical use."

These are primarily laboratory and regulatory compliance-based "ground truths" for the device's properties, not clinical "ground truths" for diagnostic accuracy.

8. The sample size for the training set:

This information is not applicable. There is no "training set" as this is not an AI/machine learning device.

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

This information is not applicable. Since there is no training set, there is no ground truth established for it.

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