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The 2.4 mm LCP Distal Radius System is intended for fixation of complex intra- and extra-articular fractures and osteotomies of the distal radius and other small bones in adults, skeletally mature adolescents, and the following adolescent distal radius fractures: intra-articular fractures exiting the epiphysis, intra-articular fractures exiting the metaphysis, physeal crush injuries, and any injuries which cause growth arrest to the distal radius.

Device Description

The 2.4mm Variable Angle LCP Distal Radius Plates are used with a range of 2.4 mm variable angle locking screws, 2.4 mm cortex screws, and 2.7 mm cortex screws. The dorsal plate has a pre-contoured design to fit along the dorsal radial column of the distal radius. These new plates incorporated variable angle locking technology. There are 6 different plate types and they are available in 316L stainless steel and CP -4 titanium. The plates are offered in 5 basic shapes: 2-hole L-plate, a 3-hole L-plate, straight (radial column) plates, oblique plates and T-plates. The L-plates, T-plates, and oblique plates come in 3- and 5-hole lengths. The straight (radial column) plates come in 5- and 6- hole lengths. The 2-Hole L-plate, a 3-hole L-plate, and oblique plates are also offered in left and right-angled configurations

AI/ML Overview

This document describes a 510(k) premarket notification for a medical device, specifically a new plate system (K012694- 2.4mm Variable Angle LCP Dorsal Distal Radius System) and an expansion of indications for existing plate systems.

Based on the provided text, the submission focuses on demonstrating substantial equivalence to predicate devices through mechanical testing and does not involve AI/ML-driven performance acceptance criteria or studies as typically understood for software devices.

Therefore, most of the requested information regarding AI/ML-specific acceptance criteria, study design, expert involvement, and ground truth establishment is not applicable to this document. The study described is primarily a mechanical testing regimen.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria	Reported Device Performance
Substantial Equivalence: Features of subject components are substantially equivalent to predicate devices based on similarities in intended use and design.	"The features of the subject components are substantially equivalent to the predicate devices based on similarities in intended use and design."
Mechanical Strength: Mechanical testing demonstrates substantial equivalence of subject components to predicate devices in regards to mechanical strength.	"Mechanical testing demonstrates substantial equivalence of the subject components to the predicate devise in regards to mechanical strength."
Material Equivalence: Made from stainless steel and commercially pure titanium, with comparable mechanical & functional properties to predicate devices.	"The subject and predicate devices are made from stainless steel and commercially pure titanium. Functional and mechanical testing demonstrates the comparable mechanical & functional properties of the subject 2.4mm VA-LCP Dorsal Distal Radius System to the predicate devices."
Fatigue Strength: Assessment of the fatigue strength of the subject device, with finite element analysis determining the worst-case construct and dynamic loading testing confirming substantial equivalence to the predicate device construct.	"Testing conducted to support the substantial equivalence of the 2.4mm VA- LCP Dorsal Distal Radius System was aimed to assess the fatigue strength of the subject device. Finite Element Analysis was used to determine the worst case construct and dynamic loading testing was used to confirm that the subject device construct is substantially equivalent to the predicate device construct."

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

Sample Size: Not explicitly stated in terms of number of physical devices tested; however, the testing methodology involved "Finite Element Analysis" (FEA) to determine worst-case scenarios and "dynamic loading testing" to confirm equivalence. FEA is a computational method, and dynamic loading testing would involve physical specimens. The specific number of physical specimens is not provided.
Data Provenance: Not applicable in the context of clinical data provenance. The data generated is from laboratory-based mechanical testing.

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, and "ground truth" in this context refers to established engineering and material science principles and performance benchmarks for predicate devices, rather than expert interpretation of clinical data.

4. Adjudication method for the test set:

Not applicable. The evaluation is based on objective mechanical testing results and comparison to predicate device performance. There is no human adjudication process described.

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 document pertains to a mechanical bone fixation system, not an AI/ML diagnostic or assistive device.

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

Not applicable. This is not an algorithm-only device.

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

The "ground truth" for this device's evaluation is the established mechanical performance and material properties of the predicate devices, as determined through engineering and material science standards and testing. Finite Element Analysis (FEA) and dynamic loading testing are used to compare the new device to these established benchmarks.

8. The sample size for the training set:

Not applicable. This is not an AI/ML device that requires a training set. The "training" in the engineering context would be the design and development process informed by engineering principles and previous device designs.

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

Not applicable. As above, this is not an AI/ML device with a training set and ground truth in the AI sense.

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