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The ReForm Pedicle Screw System is intended to provide immobilization and stabilization of spinal segments in skeletally mature patients as an adjunct to fusion in the treatment of the following acute and chronic instabilities or deformities of thoracic, lumbar, and sacral spine: degenerative spondylolisthesis with objective evidence of neurological impairment, fracture, dislocation, scoliosis, kyphosis, spinal tumor, and failed previous fusion (pseudarthrosis).

The ReForm Pedicle Screw System is also intended for non-cervical pedicle screw fixation for the following indications: 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. It is also intended for the following indications: trauma (i.e. fracture or dislocation); spinal stenosis; curvatures (i.e. scoliosis; and/or lordosis) spinal tumor; pseudloarthrosis; and failed previous fusion.

The Reform System is a top-loading, multiple component, posterior spinal fixation system which consists of pedicle screws, rods, cross-connectors, locking cap screws, and cross connectors. All of the components are available in a variety of sizes to match more closely to the patient's anatomy. All components are made from medical grade stainless steel, cobalt chromium alloys, titanium or titanium alloy described by such standards as ASTM F138, ASTM F1537, ISO 5832-12, ASTM F136 or ISO 5832-3.

Here's an analysis of the provided text regarding the acceptance criteria and study for the ReForm Pedicle Screw System:

Based on the provided 510(k) summary, the device is a ReForm Pedicle Screw System, which is a medical device and not an AI/ML-based diagnostic or imaging device. Therefore, the questions related to AI/ML specific performance evaluation metrics, ground truth establishment for AI/ML models, and training/test set sample sizes in the context of AI/ML are not applicable.

The document describes a traditional medical device submission focusing on substantial equivalence to predicate devices, primarily through engineering analysis.

Description of Acceptance Criteria and Study:

The "acceptance criteria" for this device, in the context of a 510(k) submission, are met by demonstrating substantial equivalence to legally marketed predicate devices. The primary method used to prove this is through performance evaluation based on engineering analysis.

Essentially, the device is "accepted" if it can show that its technological characteristics and performance are comparable to (or do not represent a worst-case scenario compared to) already cleared devices with the same intended use.

1. Table of Acceptance Criteria and Reported Device Performance

Components are made from medical grade stainless steel, cobalt chromium alloys, titanium or titanium alloy described by standards such as ASTM F138, ASTM F1537, ISO 5832-12, ASTM F136 or ISO 5832-3. |
| Biocompatibility: Materials used must be biocompatible for implantation. | Materials are standard medical grade alloys (stainless steel, cobalt chromium, titanium/titanium alloy), implying accepted biocompatibility that is equivalent to predicate devices. |
| Fit and Function: New designs and sizes (specifically additional cross connectors) must integrate properly and maintain the intended function of the system. | The purpose of the submission is to make modifications by adding "an additional design and sizes of cross connectors." The engineering analysis confirms these modifications "do not substantially differ from the legally marketed predicate devices." |
| Intended Use: The device must perform effectively for its stated indications. | The intended use and technological features of the modifications/additions "do not substantially differ from the legally marketed predicate devices." The device is intended to provide immobilization and stabilization of spinal segments as an adjunct to fusion for a range of spinal instabilities and deformities, consistent with the predicates. |

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size: Not applicable in the traditional sense of a clinical or imaging study. The "test set" here refers to the specific modifications (additional design and sizes of cross connectors) and existing components that underwent engineering analysis. The number of physical units or designs tested is not specified but would typically involve a sufficient number to validate mechanical properties.
• Data Provenance: Not applicable. The "data" comes from engineering tests and material specifications, not from patient data or clinical trials.

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)

• This is not applicable for this type of device submission. There is no "ground truth" established by medical experts for a test set in a clinical or diagnostic context. The ground truth for mechanical performance relies on established engineering principles, material science, and regulatory standards. Experts involved would be engineers and material scientists conducting the tests and analyses. Their qualifications are not specified in this document.

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

• Not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical trials or reader studies where human interpretation or diagnostic accuracy is being assessed. This submission focuses on engineering equivalence.

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 not an AI/ML device, nor is it a diagnostic tool where human readers' performance with/without AI assistance would be relevant.

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

• Not applicable. This is not an algorithm or an AI/ML device.

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

• The "ground truth" in this context refers to established engineering standards, material specifications, and the mechanical performance of the predicate devices. The new device's components are evaluated against these validated benchmarks.

8. The sample size for the training set

• Not applicable. There is no "training set" as this is not an AI/ML device.

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

• Not applicable. Since there is no training set, the establishment of its ground truth is irrelevant.

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