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The Libra Pedicle Screw System is intended for immobilization of the posterior thoracic, lumbar and sacral/iliac spine (T1-S1/Ilium) in skeletally mature patients as an adjunct to the following indications: degenerative disc disease (defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radies), spondylolisthesis, trauma (i.e., fracture or dislocation), spinal stenosis, curvatures (i.e., scoliosis, kyphosis, or lordosis), tumor, pseudarthrosis, and/or failed previous fusion.

The Libra Pedicle Screw System consists of longitudinal members (rods), anchors (screws) and fasteners in a variety of sizes to accommodate differing anatomic requirements.

This document is a 510(k) premarket notification for the "Libra Pedicle Screw System," specifically for adding a cobalt chrome rod series. It does not contain information about a study proving the device meets acceptance criteria in the way a clinical trial or algorithm performance study would. The acceptance criteria and "study" are related to demonstrating substantial equivalence to a predicate device through non-clinical performance data (e.g., theoretical analysis).

Here's the breakdown of the information requested, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document only discusses "performance data" in the context of demonstrating substantial equivalence, not specific quantitative acceptance criteria with reported numerical performance values like sensitivity/specificity for a diagnostic device. The acceptance criterion is essentially "does not create a new worst case" or "maintains existing performance."

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

Not applicable in the context of a clinical study. The "test set" here refers to the theoretical analysis performed on the design of the cobalt chrome rod and its integration into the system. It's a theoretical analysis, not a study involving human subjects or a large dataset. No data provenance in the sense of patient data is mentioned, as this is a materials/mechanical evaluation.

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

Not applicable. "Ground truth" in this context would refer to established engineering principles, material science standards (e.g., ASTM F1537), and possibly expert engineering analysis to determine if the new component "does not create a new worst case." The document does not specify the number or qualifications of experts involved in this theoretical analysis, but it would typically be conducted by qualified engineers and material scientists within Spinal Balance, Inc. or their consultants.

4. Adjudication method for the test set

Not applicable. There's no mention of an adjudication method as would be used for image review or clinical assessments. The "adjudication" is inherent in the internal engineering review and FDA's assessment of the 510(k) 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 device is a pedicle screw system for spinal fusion, not an AI-powered diagnostic or assistive tool. Therefore, MRMC studies and AI-related metrics are irrelevant.

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

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

7. The type of ground truth used

The "ground truth" used for this type of submission would be established engineering principles, material science standards (e.g., ASTM F136 for titanium, ASTM F1537 for cobalt chrome), and biomechanical testing standards (though direct testing results are not detailed here, theoretical analysis relies on such principles). The "ground truth" for showing substantial equivalence is that the new material change does not negatively impact the safety and effectiveness profile of the already cleared device, as assessed through engineering analysis.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. See point 8.

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The Libra Pedicle Screw System is intended for immobilization of the posterior thoracic, lumbar and sacral/iliac spine (TI-S1/Ilium) in skeletally mature patients as an adjunct to the following indications: degenerative disc disease (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, or lordosis), tumor, pseudarthrosis, and/or failed previous fusion.

The Libra Pedicle Screw System consists of longitudinal members (rods), anchors (screws) and fasteners in a variety of sizes to accommodate differing anatomic requirements.

This document describes the FDA's clearance of the Libra Pedicle Screw System (K151770) based on substantial equivalence to predicate devices, rather than a study and acceptance criteria for a novel device's performance. Therefore, the requested information about device performance, sample sizes, ground truth establishment, expert adjudication, and MRMC studies is not directly available in this text.

However, I can extract information related to the performance data provided for substantial equivalence and the acceptance criteria implicitly met through comparison with predicates.

Implicit Acceptance Criteria and Reported Device Performance (Table)

Since this is a 510(k) summary for a substantial equivalence determination for a medical device (pedicle screw system), the "study" is primarily focused on bench testing to demonstrate that the new device performs as safely and effectively as legally marketed predicate devices, not clinical studies with human performance metrics as one might see for AI/software devices. Therefore, many of your specific questions are not directly applicable or answerable from this document.

Here's an attempt to address your other points based on the provided text, acknowledging the nature of a 510(k) submission for a physical implantable device:

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

• Test Set Sample Size: The document does not specify the exact number of Libra Pedicle Screw System constructs tested for mechanical performance. It generally refers to "worst case Libra Pedicle Screw System constructs." For a 510(k) for a physical device, this typically involves a representative number of samples (e.g., typically 3 to 5 per test condition) to satisfy the standard (ASTM F1717). The specific number is usually detailed in the full 510(k) submission, not summarized at this level.
• Data Provenance: The data is from bench testing (mechanical testing), conducted by the manufacturer, Spinal Balance Inc., to evaluate the physical components of the device. It is not clinical data, and thus concepts like "country of origin of the data" or "retrospective/prospective" do not apply in the same way they would for clinical or AI data.

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

• Not applicable in this context. For mechanical bench testing, "ground truth" is established by the specifications and pass/fail criteria of the referenced ASTM standards (ASTM F1717). Engineers and technicians conduct the tests and determine if the results meet the criteria, comparing them against the performance of similar predicate devices. There isn't "expert adjudication" of test results in the sense of clinical image review for diagnostic accuracy.

4. Adjudication method for the test set

• Not applicable. See point 3. Testing against an industry standard (ASTM F1717) provides objective pass/fail criteria.

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 device is a physical spinal implant, not an AI software. Therefore, MRMC studies and the concept of "human readers improving with AI assistance" are irrelevant to this submission.

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

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

7. The type of ground truth used

• For mechanical testing, the "ground truth" is adherence to the performance standards and specifications outlined in ASTM F1717, and the comparative performance to predicate devices as demonstrated by their own cleared mechanical testing data. The goal is to show equivalent, safe, and effective mechanical properties.

8. The sample size for the training set

• Not applicable. This is a physical medical device, not a machine learning model, so there is no training set in the AI sense.

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

• Not applicable. See point 8.

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