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When intended to promote fusion of the cervical spine and the thoracic spine, (CI-T3), the NexLink Spinal Fixation System is indicated for the following:

DDD (neck pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies), spondylolisthesis, spinal stenosis, fracture, dislocation, failed previous fusion and/or tumors.

Hooks and rods are also intended to provide stabilization to promote fusion following reduction of fracture/dislocation or trauma in the cervical/upper thoracic (C1-T3) spine.

The use of multiaxial screws is limited to placement in T1-T3 in treating thoracic conditions only. The multiaxial screws are not intended to be placed in the cervical spine.

The Nex-Link Spinal Fixation System is intended for fixation to, and stabilization of, the cervicothoracic spine (C1-T3). The system consists of a series of longitudinal members, anchors, transverse connectors, and instruments for inserting and securing the implants.

The subject devices are the result of design modifications made to previously existing Abbott Spine implants intended for use in the posterior spine. The subject devices share the same intended use and fundamental scientific technology as the predicates.

Here's an analysis of the provided text regarding the Koro634 device, focusing on acceptance criteria and supporting studies:

Based on the provided document (KORO634, Nex-Link Spinal Fixation System), it appears this submission is for a 510(k) premarket notification of intent to market, which relies on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting new clinical effectiveness data.

Therefore, the typical structure for reporting acceptance criteria and a study proving device performance (especially for AI/standalone device cases) is not fully applicable here. However, I can extract the relevant information regarding performance and the type of evidence provided.

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in the format one might expect for a new performance study. Instead, the "acceptance" for this 510(k) relies on demonstrating substantial equivalence to a predicate device. The performance data presented is focused on non-clinical (bench) testing to support this substantial equivalence.

Study Details (Based on the provided text)

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

   • Sample Size: Not applicable. The document refers to "Laboratory and bench testing results" but does not specify sample sizes for these tests (e.g., number of implants tested for fatigue, static bending, etc.).
   • Data Provenance: Not specified. It's safe to assume these were conducted in a laboratory setting, likely in the US where the submitter is located. This would be retrospective in the sense that the tests are performed on manufactured parts, not in vivo clinical data.

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

   • Not applicable. For mechanical bench testing, "ground truth" is typically established by engineering standards (e.g., ASTM, ISO) or internal specifications, not by expert consensus on diagnostic images or clinical outcomes.

3. Adjudication method for the test set:

   • Not applicable. Adjudication methods (like 2+1 or 3+1) are relevant for clinical endpoint determination or expert consensus on image interpretation, which are not part of the non-clinical performance data described here.

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:

   • No. This document is for a spinal fixation system (physical implant), not an AI device or imaging software. Therefore, an MRMC study is not relevant.

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

   • No. This is a physical medical device. "Standalone" performance as an algorithm is not applicable.

6. The type of ground truth used:

   • The "ground truth" for the non-clinical performance data would be engineering specifications and established mechanical testing standards (e.g., strength, stiffness, fatigue life). The results of these bench tests are compared against the predicate device's known performance or established industry standards to demonstrate equivalence.

7. The sample size for the training set:

   • Not applicable. This device is a physical implant, not an AI algorithm requiring a training set.

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

   • Not applicable. As above, no training set for an algorithm is involved.

Summary of Clinical Data (or lack thereof):

The document explicitly states: "Clinical data and conclusions were not needed for this submission." This further emphasizes that the basis for approval (substantial equivalence) rests solely on the non-clinical, laboratory, and bench testing, rather than human clinical trials or performance data.

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