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510(k) Data Aggregation
(116 days)
The Tigon Medical All-Suture Anchors are intended for the reattachment of soft tissue to bone for the following indications:
• Elbow: Biceps Tendon Reattachment. Ulnar or Radial Collateral Liqament Reconstruction
• Shoulder: Rotator Cuff Repair, Bankart Repair, SLAP Lesion Repair, Biceps Tenodesis, Acromio-Clavicular Separation Repair, Deltoid Repair, Capsular Shift or Capsulolabral Repair
• Hand/Wrist: Scaphulolunate Ligament Reconstruction, Carnal Ligament Reconstruction, Repair/ Reconstruction of Collateral Ligaments, Repair of Flexor and Extensor Tendons at the PIP, DIP and MCP Joints for all Digits, Digital Tendon Repair
• Foot/Ankle: Lateral Stabilization, Medial Stabilization, Achilles Tendon Repair, Metatarsal Ligament Repair, Hallux Valgus Reconstruction, Digital Tendon Transfers, Mid-foot Reconstruction
• Knee: Medial Collateral Ligament Repair, Lateral Collateral Ligament Repair, Patellar Tendon Repair, Posterior Oblique Ligament Repair, Iliotibial Band Tenodesis
• Hip: Capsular Repair, Acetabular Labral Repair, Gluteal Tendon Repair
The Tigon Medical All-Suture Anchors are soft-tissue fixation devices provided sterile, preloaded on an inserter. The anchor consists of different load configurations consisting of one or more working sutures. The inserters can be reprocessed after use and are made from stainless steel.
This document is a 510(k) premarket notification for a medical device (Tigon Medical All-Suture Anchors). It does not include information about AI/ML device performance or clinical studies with human readers. Therefore, I cannot extract the requested information regarding acceptance criteria, study details, sample sizes for test/training sets, or expert qualifications for ground truth establishment.
The document discusses the substantial equivalence of the device to legally marketed predicate devices based on mechanical testing, specifically according to ASTM F543. The acceptance criteria and "performance" in this context relate to the physical and mechanical properties of the anchor itself, not the performance of an AI/ML algorithm.
Here's the information that can be extracted or inferred from the provided text, related to the device's assessment:
1. Table of Acceptance Criteria and Reported Device Performance:
Acceptance Criteria | Reported Device Performance |
---|---|
Mechanical properties (as per ASTM F543) such as insertion strength and fixation strength | "Mechanical test data demonstrates that the Tigon Medical All-Suture Anchors are substantially equivalent to the predicate device identified." Specific numerical values or tables of criteria and performance are not provided. |
2. Sample size used for the test set and the data provenance:
Not applicable for an AI/ML study. The "test set" here refers to the samples of the medical device used for mechanical testing. The specific sample size for the mechanical testing is not explicitly stated in this document. Data provenance would refer to the origin of the mechanical test results.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable as this is not an AI/ML study involving human interpretation of medical images or data. Ground truth in this context would be established by the mechanical testing protocols and measurements.
4. Adjudication method for the test set:
Not applicable as this is not an AI/ML study requiring expert adjudication of results. Mechanical testing results are typically evaluated against pre-defined engineering specifications.
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, an MRMC comparative effectiveness study was not done. This document pertains to the clearance of a physical medical device (all-suture anchors), not an AI/ML-powered diagnostic or assistive tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
No, standalone algorithm performance was not done. This document is not about an algorithm.
7. The type of ground truth used:
The "ground truth" for the device's performance is established through mechanical testing (per ASTM F543) comparing the device's physical properties (e.g., insertion strength, fixation strength) to those of predicate devices.
8. The sample size for the training set:
Not applicable, as this is not an AI/ML study.
9. How the ground truth for the training set was established:
Not applicable, as this is not an AI/ML study.
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(37 days)
The Smith & Nephew SUTUREFIX Curved Suture Anchors are intended for the secure fixation of soft tissue to bone for the following indications:
Hip
• Acetabular labrum repair/reconstruction
Shoulder
- · Capsular stabilization
- Bankart repair
- Anterior shoulder instability
- SLAP lesion repairs
- Capsular shift or capsulolabral reconstructions
- Rotator cuff tear repairs
- Bicepts tenodesis
The Smith & Nephew SUTUREFIX Curved suture anchor system consists of an all suture based implant, hole preparation, and curved insertion accessory instruments. The implant will be offered in multiple suture configurations including single and double loaded suture options. The instruments will include sterile flexible drills and reusable curved drill guides and obturators.
This document is a 510(k) premarket notification for a medical device, specifically the Smith & Nephew SUTUREFIX Curved Suture Anchor. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed study of the device's performance against specific acceptance criteria.
Therefore, much of the requested information regarding acceptance criteria, study design, sample sizes, expert involvement, and ground truth establishment is not present in this type of regulatory submission. The document states that performance data exists, but does not provide the specifics of those studies.
Here's a breakdown of the available information based on your request:
1. A table of acceptance criteria and the reported device performance
Performance Metric | Acceptance Criteria | Reported Device Performance |
---|---|---|
Bacterial Endotoxin | Acceptable limits per ANSI/AAMI ST72:2011 | Met acceptable endotoxin limits |
Insertion Strength | Performance specifications (not detailed) | Met performance specifications |
Pull-out Strength | Performance specifications (not detailed) | Met performance specifications |
Note: The specific numerical acceptance criteria and reported values for insertion and pull-out strength are not provided in this summary.
2. Sample sized used for the test set and the data provenance
Not provided in this document. The document mentions "Performance data demonstrates," but does not specify the sample sizes or the provenance (e.g., country of origin, retrospective/prospective nature) of the data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable/Not provided. This is a physical device, and the "ground truth" would relate to its physical and mechanical properties, not an assessment by human experts in the way an AI or diagnostic device would require.
4. Adjudication method for the test set
Not applicable/Not provided. See point 3.
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
Not applicable. This is a surgical implant, not an AI or diagnostic device that involves human readers/interpreters.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a surgical implant, not an algorithm.
7. The type of ground truth used
For the physical performance tests (insertion strength, pull-out strength, bacterial endotoxin), the "ground truth" would be established by objective laboratory measurements following validated test methods.
8. The sample size for the training set
Not applicable. This is a medical device, not an AI model that requires a training set.
9. How the ground truth for the training set was established
Not applicable. See point 8.
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