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The Everest Spinal System if used in conjunction with the Range (Mesa and Denali) Spinal Systems are:

Non-cervical, pedicle screw fixation devices for posterior stabilization as an adjunct to fusion for the following indications: Trauma ( i.e. fracture or dislocation ); spinal stenosis; curvatures (i.e. scoliosis, kyphosis; and/or lordosis); tumor; pseudoarthrosis; and failed previous fusion. It is also indicated for the treatment of severe spondylolisthesis ( grades 3 and 4 ) of the L5-S1 vertebra in skeletally mature patients receiving fusion by autogenous bone graft having implants attached to the lumbar and sacral spine ( L3 to sacrum) with removal of the implants after the attainment of a solid fusion.

Non-cervical, non-pedicle spinal fixation devices intended for posterior or anterolateral thoracolumbar screw stabilization as an adjunct to fusion for the following indications: degenerative disc disease (DDD ) (defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies ); spondylolisthesis; trauma ( i.e. fracture or dislocation ); spinal stenosis; curvatures ( i.e. scoliosis, kyphosis; and/or lordosis); tumor; pseudoarthrosis; and failed previous fusion.

The Everest Spinal System is a top-loading, multiple component, posterior (thoracic-lumba) spinal fixation system which consists of pedicle screws, rods, locking set screws, and hooks. The purpose of this submission is to increase the range of screw sizes and to add connectors to enable use with Range Spinal System conponents.

Materials: The devices are manufactured from Titanium Alloy and Chrome per ASTM and ISO standards.

Function: The system functions as an adjunct to fusion to provide immobilization of the posterior thoracic and lumbar spine.

The provided 510(k) summary for the "Everest Spinal System" is for a physical medical device (spinal fixation system) and not for an AI/ML-driven device or software. Therefore, the questions regarding acceptance criteria, study design, ground truth, and reader studies that are typically applicable to AI/ML device performance evaluation do not directly apply in this context.

This summary focuses on demonstrating substantial equivalence to existing predicate devices based on mechanical performance and material compatibility.

Here's an analysis of the provided information, framed as closely as possible to your request, but highlighting the differences for a physical device:

Acceptance Criteria and Device Performance (for a physical medical device)

Summary of Device Evaluation and Study for Substantial Equivalence:

The study presented is not an AI/ML algorithm validation study, but rather a comparative engineering and design study to demonstrate substantial equivalence of a physical medical device.

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

   • This is not applicable in the context of an AI/ML study. For a physical device, "test set" refers to physical prototypes or components of the Everest Spinal System. The document doesn't specify the exact number of components tested but implicitly suggests sufficient samples were used to conduct the required ASTM F1717 mechanical tests.
   • Data Provenance: The tests were conducted according to ASTM and ISO standards, implying a controlled laboratory environment. The "country of origin of the data" would be where these tests were performed, but this detail is not provided. It is a prospective generation of test data from manufactured components.

2. 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):

   • This is not applicable. The "ground truth" for a mechanical device is established by objective, verifiable physical measurements and engineering standards (ASTM F1717, ISO standards). There are no human "experts" establishing a subjective ground truth in this type of study.

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

   • Not applicable. Mechanical tests are typically evaluated against predefined quantitative limits set by standards like ASTM F1717, not through human adjudication.

4. 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 physical device, and no human "readers" or AI assistance are involved in its performance evaluation.

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

   • Not applicable. This is a physical device, not an algorithm.

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

   • For this physical device, the "ground truth" is defined by established engineering performance standards (ASTM F1717) and material specifications (ASTM and ISO standards for Titanium Alloy and Chrome). The performance of the device is directly compared to these objective standards and to the performance of existing legally marketed predicate devices under the same test conditions.

7. The sample size for the training set:

   • Not applicable. There is no AI/ML model being trained.

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

   • Not applicable. No AI/ML model training occurred.

Conclusion for this Device:

The K2M Everest Spinal System demonstrated substantial equivalence by:

• Showing that its mechanical performance (static compression, static torsion, dynamic compression) was "equally to or better than" the predicate devices when tested according to ASTM F1717.
• Confirming its design features and sizing were "substantially the same" as predicate systems.
• Verifying its materials (Titanium Alloy and Chrome) met the relevant ASTM and ISO standards.
• Confirming its intended use aligns with the predicate devices.

This allows the FDA to conclude there are no significant differences that would adversely affect the product's use, thus granting 510(k) clearance based on substantial equivalence.

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