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The CODMAN® Single Lumen Skull Bolt Kit is designed to achieve cranial access and to introduce and secure a sensor in place for intracranial monitoring applications.

The CODMAN® Double Lumen Skull Bolt Kit is designed to achieve cranial access and to introduce and secure sensors in place for intracranial monitoring applications.

The CODMAN® Single and Double Lumen Skull Bolt Kits consist of bolts and associated components designed to achieve cranial access and facilitate the introduction and securing of intracranial sensors. Additional accessories supplied in the kits include a sensor introducer, connectors, drill bits, and other associated components supplied for the convenience of the user. All parts and accessories found in the CODMAN® Single and Double Lumen Skull Bolt Kits are manufactured from biocompatible materials suitable for their uses in these kits.

The provided text describes a 510(k) summary for medical devices, specifically the "CODMAN® Single and Double Lumen Skull Bolt Kits." These are Class II devices intended for intracranial pressure monitoring applications.

The submission primarily relies on bench testing to demonstrate performance characteristics and equivalence to predicate products. This means the device's acceptance was based on engineering and material performance rather than clinical studies involving human patients or complex AI algorithms.

Therefore, many of the typical acceptance criteria and study details relevant to AI-powered diagnostics or clinical performance studies (e.g., sample size for test set, MRMC studies, expert qualifications, training set details) are not applicable to this type of device submission.

Here's a breakdown of the requested information based on the provided text, highlighting where information is not available or not relevant:

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

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

• Sample Size for Test Set: Not specified, as the testing involved bench tests (e.g., mechanical stress tests) rather than patient data.
• Data Provenance: Not applicable, as no patient data was used.

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. Ground truth for bench testing is typically established by engineering specifications and physical measurements, not clinical expert consensus.

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

• Not applicable. Adjudication methods are relevant for clinical image interpretation or diagnostic tasks involving human judgment.

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

• No MRMC study was done. This device is a mechanical bolt kit, not an AI diagnostic tool that assists human readers.

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

• Not applicable. This device is hardware, not an algorithm.

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

• The "ground truth" for the device's performance was established through engineering specifications and physical measurements demonstrating the structural integrity and functionality (torque resistance, pullout strength, leak prevention) of the bolts and components.

8. The sample size for the training set

• Not applicable. Training sets are used for machine learning models.

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

• Not applicable. Training sets and their associated ground truth are used for machine learning models.

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