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The Mini MaxLock Extreme® Plating System is intended to stabilize and aid in the repair of fractures, fusions, and osteotomies for small bones and bone fragments.

The submission is a modification to the Mini MaxLock Extreme® Plating System to add additional plate styles. No modifications were made to the existing plates or screws

The provided text describes a 510(k) submission for a medical device (Mini MaxLock Extreme® Plating System), which is a premarket notification to demonstrate that the device is at least as safe and effective as a legally marketed predicate device.

For this type of device (bone fixation appliances), the FDA review primarily focuses on establishing substantial equivalence to a predicate device, rather than defining specific acceptance criteria for a new, standalone performance study in the way one might for a diagnostic AI algorithm. The 510(k) summary explicitly states:

"Calculations and finite element analysis comparing the strength of the subject and predicate devices were performed and the results support substantial equivalence. Due to similarities in indications, design, and materials, no other testing was required. No new issues of safety and effectiveness have been raised."

This means that a direct "acceptance criteria" and "device performance" in terms of clinical outcomes or diagnostic accuracy were not established or tested in this submission. Instead, the acceptance criteria were implicitly met by demonstrating mechanical equivalence to an already approved device.

Therefore, many of the requested points regarding acceptance criteria, study details, and ground truth establishment are not applicable to this specific 510(k) submission.

Here's an breakdown of the requested information based on the provided text:

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)

• Not Applicable. No human or animal test set data was used. The study relied on computational analysis (calculations and Finite Element Analysis).

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. No expert-established ground truth was required for this type of substantial equivalence demonstration. The "ground truth" was derived from engineering principles and comparison to the predicate device's established properties.

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

• Not Applicable. No human adjudication was involved as no patient data or expert review was part of this submission.

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 hardware device (bone plating system), not an AI diagnostic tool. MRMC studies are irrelevant here.

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

• Not Applicable. This is a hardware device.

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

• Not Applicable / Engineering Equivalent. The "ground truth" for showing substantial equivalence was the known mechanical properties and performance of the predicate device, as assessed through engineering calculations and finite element analysis.

8. The sample size for the training set

• Not Applicable. No machine learning or AI models were involved; therefore, no training set was used.

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

• Not Applicable. No training set was used.

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The Mini MaxLock Extreme® Plating System is intended to stabilize and aid in the repair of fractures, fusions, and osteotomies for small bones and bone fragments.

The submission is a modification to the Mini MaxLock Extreme® Plating System to add Mini MTP Plates. This submission also includes the ISO plate that was previously cleared through internal documentation. No modifications were made to the existing plates or screws. The OrthoHelix Mini MTP Plates are designed for 18 MTP joint fusions.

This document describes a 510(k) submission for a medical device called the Mini MaxLock Extreme® Plating System. The submission is for a modification to an existing system, specifically the addition of Mini MTP Plates for MTP joint fusions.

However, the provided text does not contain information about acceptance criteria or a study that proves the device meets those criteria in the way typically expected for a diagnostic AI/ML device.

Instead, this 510(k) summary focuses on demonstrating substantial equivalence to existing, legally marketed predicate devices. For mechanical devices like bone plates, this usually involves showing that the new device has similar:

• Indications for use
• Design
• Materials
• Performance (often through mechanical testing and/or finite element analysis)

Therefore, the requested information elements related to AI/ML device performance (like accuracy metrics, sample sizes for test/training sets, expert adjudication, MRMC studies, standalone performance, and ground truth establishment) are not applicable or available in this specific regulatory filing.

Based on the provided text, here’s an analysis of what is available:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance
Not applicable. This is a mechanical device, not an AI/ML diagnostic. The "test set" would refer to mechanical test samples, 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. This is a mechanical device.

4. Adjudication method for the test set
Not applicable. This is a mechanical device.

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 mechanical device, not an AI/ML system assisting human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a mechanical device.

7. The type of ground truth used
Not applicable in the context of diagnostic performance. For a mechanical device, "ground truth" would relate to material properties, mechanical limits, and biomechanical performance data, which are typically established through engineering standards, material science, and physical testing.

8. The sample size for the training set
Not applicable. This is a mechanical device. There is no "training set" in the context of machine learning.

9. How the ground truth for the training set was established
Not applicable. There is no "training set" or "ground truth establishment" in the AI/ML sense for this mechanical device.

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The Mini MaxLock Extreme® Plating System is intended to stabilize and aid in the repair of fractures, fusions, and osteotomies for small bones and bone fragments.

The Mini MaxLock Extreme® Plating System consists of various size plates and screws used to stabilize and aid in the fusion or repair of fractured small bones and bone fragments. The plates are offered in different lengths and sizes. The screws are offered in different diameters and lengths. All implantable components are manufactured from implant grade titanium alloy.

The provided text describes the "Mini MaxLock Extreme® Plating System," a medical device, and its 510(k) submission to the FDA. The submission focuses on demonstrating substantial equivalence to existing devices through mechanical testing. This type of regulatory submission for a physical implantable device (bone fixation system) does not involve AI or machine learning. Therefore, most of the requested information regarding AI study design (like ground truth, expert consensus, MRMC studies, training/test sets, etc.) is not applicable.

However, I can extract the relevant information regarding the device's acceptance criteria and the type of study used to prove it.

Here's the information based on the provided text:

Device: Mini MaxLock Extreme® Plating System

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance:

• Not Applicable: This is a physical device, not an AI/ML product. The "test set" in this context refers to the samples used in mechanical testing. The text does not specify the exact number of plates and screws tested, but it refers to "various size plates and screws." The provenance is internal testing by OrthoHelix Surgical Designs, Inc.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not Applicable: There is no "ground truth" in the AI/ML sense for a mechanical device. The "ground truth" for mechanical properties would be established by validated engineering standards and testing protocols. No human experts are mentioned as establishing a ground truth for mechanical performance, as it's a quantitative measurement.

4. Adjudication method for the test set:

• Not Applicable: As there are no human interpretations or classifications involved, no adjudication method like 2+1 or 3+1 is relevant. Mechanical tests are typically governed by standardized protocols.

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: This is a physical medical device (bone fixation system), not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study is not relevant.

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

• Not Applicable: This is a physical implantable device, not an algorithm.

7. The type of ground truth used:

• Mechanical Engineering Standards and Measurements: For the mechanical testing, the "ground truth" would be the direct measurements of bending and torsional strength, compared against established engineering standards and the performance of predicate devices.

8. The sample size for the training set:

• Not Applicable: There is no "training set" in the context of an AI/ML model for this physical device.

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

• Not Applicable: There is no "training set" or corresponding "ground truth" in the AI/ML sense for this physical device.

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