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510(k) Data Aggregation
(131 days)
The Suspension™ Acromioclavicular (AC) Repair System can be used for adult patients. The AC Repair System is indicated for securing suture to bone for acromioclavicular separations and coracoclavicular displacement.
The Suspension" Acromioclavicular (AC) Repair System is an internal fixation system consisting of a non-absorbable suture anchor, pre-threaded suture and other attachment accessories that eliminate the need for tying a knot in the suture. The metallic suture anchor and metallic accessories are fabricated from 316L stainless steel. The suture is a USP size 5, co-braided, white/blue polypropylene, non-absorbable suture.
The provided text describes a 510(k) summary for the "Suspension™ Acromioclavicular (AC) Repair System." This document is a premarket notification to the FDA for medical devices, asserting substantial equivalence to existing legally marketed devices. It focuses on demonstrating that the new device is as safe and effective as its predicates.
The information provided does not describe a study involving acceptance criteria for device performance based on statistical metrics like accuracy, sensitivity, or specificity, nor does it involve human readers, ground truth established by experts, or MRMC comparative effectiveness studies.
Instead, the "Performance" section outlines non-clinical testing for mechanical properties to demonstrate substantial equivalence. Therefore, many of the requested categories are not applicable to this type of regulatory submission.
Here's the breakdown of the information that is available or can be inferred:
1. A table of acceptance criteria and the reported device performance
The document states: "The device has been subjected to non-clinical testing including Driving Torque, Pull-Out Strength, Lock Screw Torque, Anchor Torque, and Suture Testing." It also mentions: "The axial pull test data was compared and analyzed."
However, specific numerical acceptance criteria (e.g., "Pull-Out Strength > X N") and the reported numerical performance data for these tests are not provided in the summary. The summary concludes that the device "perform[s] in a manner equivalent to the predicate devices," implying that the performance met unstated acceptance criteria derived from the predicate devices.
Acceptance Criteria (Inferred from Test Types) | Reported Device Performance (General Statement) |
---|---|
Driving Torque (must meet certain limits) | Performed in a manner equivalent to predicate devices. |
Pull-Out Strength (must meet certain limits) | Axial pull test data was compared and analyzed; performed in a manner equivalent to predicate devices. |
Lock Screw Torque (must meet certain limits) | Performed in a manner equivalent to predicate devices. |
Anchor Torque (must meet certain limits) | Performed in a manner equivalent to predicate devices. |
Suture Testing (must meet certain standards) | Performed in a manner equivalent to predicate devices. |
2. Sample size used for the test set and the data provenance
The document does not specify the sample sizes for the "non-clinical testing" (Driving Torque, Pull-Out Strength, etc.). The data provenance is not explicitly mentioned but implies laboratory testing of the device itself. This is not patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. No ground truth based on expert medical opinion was established for these mechanical performance tests.
4. Adjudication method for the test set
Not applicable. No human adjudication was involved for these mechanical performance tests.
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 510(k) summary for a physical medical device (AC Repair System), not an AI diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a 510(k) summary for a physical medical device, not an algorithm.
7. The type of ground truth used
For the non-clinical tests, the "ground truth" would be the direct measurement of the physical properties (e.g., force, torque) of the device components, compared against established engineering and material science standards, and performance characteristics of predicate devices. There is no expert consensus, pathology, or outcomes data used as ground truth for these specific tests.
8. The sample size for the training set
Not applicable. This is not a machine learning model.
9. How the ground truth for the training set was established
Not applicable. This is not a machine learning model.
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