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510(k) Data Aggregation
(65 days)
ANTERIOR LUMBAR BUTTRESS SYSTEM
The Anterior Lumbar Buttress System is intended for anterior intravertebral body screw fixation/attachment to the L1-S1 spine over one vertebral body extending onto the adjacent intervertebral space. Due to variations in the anatomy, the plate is designed for applications caudal to the bifurcation of the great vessels. Specifically, the device is intended for stabilization and buttressing of bone graft over one motion segment following anterior structural reconstruction for degenerative disc disease (DDD). DDD is defined as follows: back pain of a discogenic origin with degeneration of the disc confirmed by history and radiographic studies.
The Anterior Lumbar Buttress System includes titanium allov screws, buttress plates, and a washer. The screws will be offered in 5.5 and 6.5mm diameters and in six lengths, 18, 20, 22, 24, 25, and 26mm, for each diameter. The plates will be available in three sizes: 15 x 19, 15 x 20, and 15 x 21mm. The washer will be offered in a 15mm size to be compatible with the plates. The product is supplied "NON-STERILE" and must be sterilized prior to use. The Anterior Lumbar Buttress System also utilizes some instruments to assist in placement of the devices. These instruments include a plate inserter, hex driver, and an awl. The instruments will be fabricated from stainless steel, aluminum, and Radel. The product is supplied "NON-STERILE" and must be sterilized prior to use.
The provided 510(k) summary for the "Anterior Lumbar Buttress System" does not include information about acceptance criteria or a study proving the device meets acceptance criteria using a test set, ground truth experts, or training sets in the way that an AI/ML device submission would. This document pertains to a traditional medical device (an implantable spinal system) and its submission focuses on demonstrating substantial equivalence to predicate devices based on design, materials, and mechanical strength, rather than performance metrics related to diagnostic accuracy from image analysis.
Here's an analysis based on the information provided, highlighting the absence of AI/ML-specific study components:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not specify quantitative acceptance criteria or device performance in terms of diagnostic accuracy metrics (e.g., sensitivity, specificity, AUC) that would be relevant for an AI/ML device. Instead, the "acceptance criteria" are implied by the demonstration of substantial equivalence to predicate devices, particularly regarding mechanical strength.
Acceptance Criteria (Implied) | Reported Device Performance |
---|---|
Mechanical Strength equivalent to predicate devices | "See test results" (Referenced in Table 1, but specific results or quantitative acceptance criteria are not provided in this summary document.) |
2. Sample Size Used for the Test Set and Data Provenance
No information is provided about a "test set" in the context of diagnostic performance (e.g., a set of images or clinical cases). The "test results" mentioned pertain to mechanical strength testing, for which sample sizes and data provenance are not detailed in this summary.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This information is not applicable and not provided. The device is a physical implant, not a diagnostic tool requiring expert interpretation of data to establish ground truth for performance evaluation.
4. Adjudication Method for the Test Set
This information is not applicable and not provided.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, Effect Size of Human Readers with AI vs. Without AI Assistance
This information is not applicable and not provided. This is not an AI/ML device.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable and not provided.
7. The Type of Ground Truth Used
For mechanical strength testing, the "ground truth" would be established by validated engineering test methods and objective measurements of material properties and structural integrity. However, specific details are not provided in this summary.
8. The Sample Size for the Training Set
This information is not applicable and not provided. This is not an AI/ML device; therefore, there is no "training set."
9. How the Ground Truth for the Training Set was Established
This information is not applicable and not provided.
Summary of Study Information Provided in the 510(k):
The 510(k) submission for the Anterior Lumbar Buttress System relies on demonstrating substantial equivalence to existing predicate devices (DePuy AcroMed's BowTi Anterior Buttress Staple System and Synthes' Synthes Titanium Locking Plate System).
The primary "study" referenced for performance is:
- Mechanical Strength Testing: The document states "See test results" under the "Mechanical Strength" feature in Table 1 (Summary of Design Comparison). This indicates that biomechanical testing was performed to compare the new device's strength to that of the predicate devices. However, the summary does not provide the actual test results, the methodology, the sample size, or the specific quantitative acceptance criteria for this mechanical strength testing. It only states that the new device's mechanical strength is "Similar" to the predicate devices, leading to a "Yes" for substantial equivalence on this feature.
Key Absence of AI/ML-Specific Information:
The provided text explicitly states:
"A financial certification and/or disclosure statement is not needed for this submission as no clinical studies have been undertaken in regards to the products under consideration." (Page 2)
This statement confirms that no human clinical trials were conducted. The evaluation is based on engineering principles and comparison to existing devices. Thus, the concepts of test sets, ground truth experts, training sets, clinical performance metrics, or reader studies, which are crucial for AI/ML device evaluations, are not relevant to this traditional device submission.
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