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The Codman HAKIM Programmable Valves (CHPV) are implantable devices that provide constant intraventricular pressure and drainage of CSF for the management of hydrocephalus.

The SIPHONGUARD device can be used as a component of hydrocephalus shunt systems to shunt CSF from the ventricles of the brain into the peritoneal cavity or right atrium of the heart. The SIPHONGUARD device is designed to reduce the potential hazards of excessive lowering of intraventricular pressure (with respect to atmospheric pressure) when a patient is in an upright position.

The Codman HAKIM Programmable Valve (CHPV) is a variable pressure setting hydrocephalus valve, that provides constant intraventricular pressure and drainage of cerebrospinal fluid for the management of hydrocephalus and other conditions in which CSF flow and absorption are impaired. The valve settings can be changed non-invasively by applying an external programming system.

An accessory to the Codman HAKIM Programmable Valve is the SIPHONGUARD CSF Control Device. This flow regulating antisiphon device can be used as an integral component of the Codman HAKIM Programmable Valve shunt system.

The provided text does not contain information about acceptance criteria or a study that proves the device meets specific performance criteria in the way typically associated with AI/software devices.

This document is a 510(k) Summary for a medical device: the Codman® HAKIM™ Programmable Valve and SIPHONGUARD™ CSF Control Device. This is a physical, implantable device (a hydrocephalus shunt system), not an AI or software-driven diagnostic tool.

The "Performance Data" section explicitly states:

"Bench testing has been completed and supports the safety and effectiveness of the proposed device for its intended use."

This indicates that standard engineering bench tests were conducted to ensure the physical device functions as intended. However, it does not provide:

• A table of specific acceptance criteria.
• Reported device performance metrics (e.g., sensitivity, specificity, accuracy) like those found in AI studies.
• Details about sample sizes for test sets in a clinical or image-based context.
• Data provenance (country of origin, retrospective/prospective).
• Number or qualifications of experts for ground truth.
• Adjudication methods.
• MRMC comparative effectiveness studies.
• Standalone algorithm performance.
• Type of ground truth (pathology, outcomes data).
• Sample size for training sets.
• How ground truth for training sets was established.

Therefore, based on the provided text, I cannot complete the requested table and answer the specific questions related to AI/software device performance criteria and studies. The device described is a physical medical device, and its clearance relies on bench testing and substantial equivalence to predicate devices, not on the kind of performance studies you're inquiring about for AI.

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