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BioBlanket™ Surgical Mesh is indicated for use in general surgical procedures for the reinforcement and repair of soft tissue where weakness exists including, but not limited to defects of the thoracic wall, muscle flap reinforcement, rectal and vaginal prolapse, reconstruction of the pelvic floor, hernias, suture line reinforcement and reconstructive procedures. The device is also intended for reinforcement of the soft tissues which are repaired by suture or suture anchors, limited to the supraspinatus, during rotator cuff repair surgery. The device is intended for one time use.

BioBlanket™ Surgical Mesh is comprised of a single layer porous, cross-linked collagen patch that is supplied sterile and for one-time use.

The provided document is a 510(k) summary for the Kensey Nash Corporation's BioBlanket™ Surgical Mesh. This type of submission is for medical devices and focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed performance data derived from clinical studies with specified acceptance criteria in the same way an AI/ML device would.

Therefore, the information requested in the prompt, which is typically relevant for AI/ML device performance studies, is not explicitly available within this 510(k) summary. These include:

• Acceptance criteria and reported device performance table: The document states the device "passed the requirements of all tests" but does not define specific acceptance ranges or thresholds.
• Sample size and data provenance for test set: Not applicable for a device of this nature as there's no "test set" in the context of AI/ML evaluation. Pre-clinical or clinical studies for surgical meshes would involve animal or human subjects, but this detail is not provided.
• Number of experts and qualifications for ground truth: Not applicable.
• Adjudication method for test set: Not applicable.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not applicable.
• Standalone algorithm performance: Not applicable.
• Type of ground truth used: For surgical meshes, "ground truth" would typically come from histological analysis, biomechanical testing outcomes, or clinical outcomes, but this is not specified.
• Sample size for training set: Not applicable.
• How ground truth for training set was established: Not applicable.

Instead, the document states:

"BioBlanket™ Surgical Mesh has been subjected to biocompatibility, integrity, in-vitro and in-vivo performance tests. The device passed the requirements of all tests."

This indicates that various types of non-clinical (and possibly some clinical) tests were performed, and the device met the internal requirements of those tests. However, the specific acceptance criteria and detailed results are not part of the 510(k) summary provided. Substantial equivalence is primarily based on similarity in intended use, technological characteristics, performance, and material to previously cleared devices.

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BioBlanket™ Surgical Mesh is indicated for use in general surgical procedures for the reinforcement and repair of soft tissue where weakness exists including, but not limited to defects of the thoracic wall, muscle flap reinforcement, rectal and vaginal prolapse, reconstruction of the pelvice floor, hernias, suture line reinforcement and reconstructive procedures. The device is also intended for reinforcement of the soft tissues which are repaired by suture or suture anchors, limited to the supraspinatus, during rotator cuff repair surgery. The device is intended for one time use.

DioBlanket™ Surgical Mesh is comprised of a single layer porous, cross-linked collagen patch that is supplied sterile and for one-time use.

The provided text describes a submission for a 510(k) premarket notification for the BioBlanket™ Surgical Mesh. This type of submission is for medical devices that are substantially equivalent to legally marketed predicate devices, and as such, it focuses on demonstrating equivalence rather than establishing novel performance criteria through clinical trials designed to prove efficacy or specific performance metrics against acceptance criteria.

Therefore, the document does not contain the following information:

• A table of acceptance criteria and reported device performance.
• Sample size used for a test set or its provenance.
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method for a test set.
• Information about a multi-reader multi-case (MRMC) comparative effectiveness study or effect size.
• Details on a standalone (algorithm only) performance study.
• The type of ground truth used for a test set (expert consensus, pathology, outcomes data).
• Sample size for a training set.
• How ground truth for a training set was established.

Instead, the document states:

Performance Data:
"BioBlanket™ Surgical Mesh was subjected to biocompatibility, integrity, in-vitro and invivo performance tests. The device passed the requirements of all tests."

This statement indicates that the device underwent a set of pre-defined tests (biocompatibility, integrity, in-vitro, and in-vivo) and met their respective requirements. However, the specific acceptance criteria for these tests and the detailed results are not provided in this summary. The focus is on demonstrating that the device is "substantially equivalent in terms of intended use, technological characteristics, performance and material" to previously cleared predicate devices.

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BioBlanket™ Surgical Mesh is indicated for use in general surgical procedures for reinforcement of soft tissue where weakness exists and for the repair of ruptured or damaged soft tissues. The device is supplied sterile and is intended for one time use.

BioBlanket™ is comprised of a single layer porous, cross-linked collagen patch that is supplied sterile in the form of a pad. This pad will be available in 2 different sizes, 5 cm x 5 cm and 5 cm x 10 cm, both with a 1.0 mm ± 0.25 mm thickness.

The provided text describes a 510(k) submission for the BioBlanket™ Surgical Mesh. However, it does not contain specific acceptance criteria, detailed study designs, or performance data beyond a general statement that the device passed required tests.

Therefore, I cannot populate the table or answer most of your questions based on the provided input. The document is primarily focused on seeking clearance for the device by demonstrating substantial equivalence to a predicate device, rather than presenting detailed performance study results against specific criteria.

Here's what can be inferred and what cannot:

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

2. Sample size 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.
• Data provenance: Not specified (e.g., country of origin, retrospective/prospective).

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 as this document does not describe a study involving expert-established ground truth for a test set in the way one would for diagnostic or AI-driven devices. The "performance data" mentioned refers to engineering and biocompatibility tests, not clinical studies with human review.

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

• Not applicable.

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

• No MRMC study was mentioned. This device is a surgical mesh, not an AI-driven diagnostic tool that would typically involve human readers.

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

• Not applicable. This is not an algorithm-based device.

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

• For the "biocompatibility, integrity and performance tests," the ground truth would likely be established by pre-defined engineering standards, material specifications, and biological response criteria, rather than expert consensus on clinical images or pathology.

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device that would require a training set.

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

• Not applicable.

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