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510(k) Data Aggregation
(71 days)
SPORTMESH OR ARTELON TISSUE REINFORCEMENT
SportMesh™ Artelon® Tissue Reinforcement is intended for use in general surgical procedures for reinforcement of soft tissue where weakness exists.
SportMesh™/ Artelon® Tissue Reinforcement is also intended for reinforcement of soft tissues that are repaired by suture or suture anchors, during tendon repair surgery including reinforcement of rotator cuff, patellar, Achilles, biceps, or quadriceps tendons.
SportMesh™ Artelon® Tissue Reinforcement is not intended to replace normal body structure or provide the full mechanical strength to support the rotator cuff, patellar, Achilles, biceps, or quadriceps tendons. Sutures, used to repair the tear, and sutures or bone anchors, used to attach the tissue to the bone, provide mechanical strength for the tendon repair. SportMesh™/ Artelon® Tissue Reinforcement reinforces soft tissue and provides a degradable scaffold that is incorporated into the patient's own tissue.
SportMesh™ / Artelon® Tissue Reinforcement is a knitted fabric made from Artelon® fibers. The construction permits the mesh to be cut into any desired shape or size without unraveling. The device is supplied sterile in sheet form in double laver peelable packaging.
The provided text describes a 510(k) premarket notification for a surgical mesh device, not an AI/ML medical device. Therefore, a direct application of the requested acceptance criteria for AI algorithms is not possible. The document focuses on demonstrating substantial equivalence to predicate devices through material composition, intended use, and performance data, rather than AI performance metrics.
However, I can extract the information relevant to the device's "performance" as presented and the study that "proves" it meets the criteria, reinterpreting the request for a non-AI medical device.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Analogous to Predicate Device Characteristics) | Reported Device Performance (SportMesh™/Artelon® Tissue Reinforcement) | Study/Method |
|---|---|---|
| Biocompatibility Safety (per ISO 10993 standards) | Demonstrated appropriate biocompatibility. | Biocompatibility safety studies conducted and successfully completed (ISO 10993 standards). Specific metrics not detailed but implied to meet standards. |
| Mechanical Properties (for soft tissue repair) | Provides appropriate mechanical properties for its use in soft tissue repair. (Supports reinforcement, but not full mechanical strength, relying on sutures/anchors for primary strength). | Mechanical testing conducted in accordance with "Guidance for the Preparation of a Premarket Notification Application for a Surgical Mesh; Guidance for Industry and/or for FDA Reviewers/Staff and/or Compliance." Specific metrics (e.g., tensile strength, elasticity) are not detailed but results are stated to be "appropriate." |
| Material Composition (identical to predicate) | Identical to predicate Artimplant's SportMesh™ (K052830) in material composition (Artelon® fibers). | Direct comparison of material specifications with predicate device. |
| Indications for Use (shared with predicate devices) | Each indication for use shared by one or more predicate devices. Intended for reinforcement of soft tissue where weakness exists, including specific tendon repairs (rotator cuff, patellar, Achilles, biceps, quadriceps). | Comparison of intended use statements with predicate devices. |
| Overall Equivalence (to predicate devices) | Substantially equivalent to legally marketed predicate devices and presents no new concerns of safety and effectiveness. | Conclusion based on a collection of tests (biocompatibility, mechanical) and comparison to predicate devices. |
2. Sample Size Used for the Test Set and Data Provenance
This information is not provided in the document. For a physical medical device like this, the "test set" would refer to the samples of the device itself undergoing testing. The document states "A collection of tests has been conducted," but does not specify the number of samples for biocompatibility or mechanical testing. Data provenance is also not specified beyond the general statement that tests were conducted.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
This concept is not applicable to this type of device submission. Ground truth for a physical medical device typically comes from objective measurements in a lab setting (e.g., mechanical testing, chemical analysis) or animal/human studies for biocompatibility, not expert consensus in the way it's used for AI models to interpret images or other data.
4. Adjudication Method for the Test Set
This concept is not applicable to this type of device submission. Adjudication methods like 2+1 or 3+1 are used in AI performance studies to resolve disagreements among human labelers for establishing ground truth, a process not described here for a surgical mesh.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, an MRMC comparative effectiveness study was not done. This type of study is relevant to AI systems where the AI's impact on human reader performance is being evaluated. This document pertains to a physical surgical mesh.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
No, a standalone study was not done. This term specifically refers to the performance of an AI algorithm without human involvement, which is not relevant to a surgical mesh.
7. The Type of Ground Truth Used
The "ground truth" for this device's performance would be derived from:
- Objective Laboratory Measurements: For mechanical properties (e.g., tensile strength, degradation rate – though not explicitly listed as specific metrics, implied by "appropriate mechanical properties").
- Standardized Biocompatibility Assays: According to ISO 10993 standards. This involves in vitro and in vivo tests to assess material interaction with biological systems.
- Material Characterization: Chemical composition and structural analysis to confirm it's "identical" to the predicate device.
8. The Sample Size for the Training Set
This concept is not applicable to this type of device submission. "Training set" refers to data used to train an AI model.
9. How the Ground Truth for the Training Set Was Established
This concept is not applicable to this type of device submission.
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