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The Sterispine™ PS system is intended to provide immobilization of spinal segments in skeletally mature patients as an adjunct of fusion. Sterispine™ PS system is intended for posterior non-cervical, pedicle and nonpedicle fixation 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 ; tumor ; pseudoarthrosis and failed previous fusion.

The cleared range of Sterispine™ PS system includes multiaxial screws and cannulated multiaxial screws with or without extended head (Ø5.5, 6.5 and 7.5mm, lengths from 25 to 85mm) and straight and prebent rods (Ø5.5, 6.5 and 7.5mm, lengths from 30 to 380mm). Sterispine™ PS implants are supplied sterile with a sterile single-use set of surgical instruments supplied in kits. Bacterial endotoxin testing as specified in USP standard is used for pyrogenicity testing to achieve the Endotoxin limit of 20 EU / device.

Here's an analysis of the provided text regarding acceptance criteria and device performance.

Important Note: The provided document is a 510(k) summary for a medical device (Sterispine™ PS) and focuses on demonstrating substantial equivalence to a predicate device. It does not present a study proving an AI device meets acceptance criteria. The document pertains to a traditional orthopedic implant system, not an AI-powered diagnostic or therapeutic device. Therefore, many of the requested elements for an AI device (like sample size for test/training sets, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable to this document.

The document primarily discusses non-clinical mechanical testing of a physical implant (pedicle screw system).

Based on the provided text, here's what can be extracted and what cannot:

1. A table of acceptance criteria and the reported device performance

The document mentions specific non-clinical mechanical tests and states the general outcome. It does not provide a quantitative table of specific acceptance criteria values and corresponding performance results.

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 specified quantitatively. The tests are mechanical in nature, likely on a set number of implants/components per test (e.g., n=5 or n=10 per ASTM standard).
• Data Provenance: Not explicitly stated regarding country of origin or retrospective/prospective. This refers to lab testing of physical devices, not clinical data from patients.

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)

• Not applicable. This document describes mechanical device testing against engineering standards, not clinical diagnosis or AI model evaluation requiring human expert ground truth.

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

• Not applicable. Adjudication methods are relevant for subjective human interpretations, typically in clinical studies or AI model ground truth establishment. This is mechanical testing.

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 relates to AI-assisted human performance in diagnostic tasks. The device in question is a surgical implant.

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

• Not applicable. This relates to the performance of an AI algorithm as a standalone diagnostic tool. The device is a surgical implant.

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

• The "ground truth" for this device's performance is adherence to established mechanical testing standards (e.g., ASTM F1798, ASTM F1717) and functional engineering requirements. It's engineering/mechanical performance standards, not clinical ground truth.

8. The sample size for the training set

• Not applicable. This refers to AI model training data.

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

• Not applicable. This refers to AI model training data.

Summary regarding the provided document:

The provided K201648 510(k) summary is for a traditional surgical implant (pedicle screw system). The "acceptance criteria" and "study" described are focused on non-clinical mechanical and functional testing to demonstrate the device's physical properties and performance against established engineering standards, and its substantial equivalence to previously cleared predicate devices. It does not involve AI technology or clinical performance studies in the way envisioned by the posed questions.

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The Sterispine™ PS system is intended to provide immobilization of spinal segments in skeletally mature patients as an adjunct of fusion.

Sterispine™ PS system is intended for posterior, non-cervical pedicle and non-pedicle fixation 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; tumor; pseudoarthrosis and failed previous fusion.

The cleared range of Sterispine™ Ps system include multiaxial screws and cannulated multiaxial screws with or without extended head (Ø5.5, 6.5 and 7.5mm, lengths from 25 to 60mm) and straight and prebent rods (Ø5.5, 6.5 and 7.5mm, lengths from 30 to 380mm). Components of Sterispine™ PS range of products is supplied sterile with a sterile single-use set of surgical instruments.

This looks like a 510(k) summary for a medical device called "Sterispine™ PS", which is a thoracolumbosacral pedicle screw system. From the information provided, it's clear that this is not a software device or an AI/ML powered device, and therefore does not have acceptance criteria or a study related to software performance.

The document describes premarket notification for a traditional medical device (implants for spinal fusion) and focuses on demonstrating substantial equivalence to previously cleared predicate devices. The "Discussion of testing" section refers to mechanical and biocompatibility testing for the physical device components, not software performance.

Here's why the requested information about acceptance criteria and studies for device performance (in the context of AI/ML) cannot be found in this document:

• Device Type: This is a physical implant (pedicle screw system), not a diagnostic algorithm, image analysis tool, or any other type of software that would typically have performance metrics like sensitivity, specificity, or AUC.
• Regulatory Pathway: A 510(k) for a physical medical device like this often relies on demonstrating substantial equivalence to legally marketed predicate devices through material comparisons, mechanical testing, and functional similarities, rather than clinical performance studies of a software output.
• "Device Performance" Context: When the document refers to "testing," it's discussing the physical properties of the implant (e.g., static compression, torsion, bacterial endotoxin) to ensure it's safe and performs as intended mechanically, not the accuracy of an algorithm.

Therefore, since the request is based on the assumption of an AI/ML driven device, which this is not, I cannot extract the requested information.

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