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510(k) Data Aggregation
(273 days)
The RF Passive Attenuator/Splitter Model I 100 I 200 and Cutting/Coagulating Electrode Model R 10 is indicated for the cutting and coagulation of the tissue. This device is intended for use by qualified medical personnel in the use of electrosurgery.
RF Passive Attenuator/Splitter Model I 100, I 200 and Cutting/Coagulating Electrode Model R 10.
1. Table of Acceptance Criteria and Reported Device Performance:
The provided document does not contain any specific acceptance criteria or reported device performance metrics for the RF Passive Attenuator/Splitter (PAS) and Loop Electrode. The letter is a 510(k) clearance stating substantial equivalence to a predicate device, which focuses on device type, indications for use, and regulatory compliance rather than detailed performance specifications.
2. Sample Size Used for the Test Set and Data Provenance:
No information regarding a test set sample size or data provenance is available in this document.
3. Number of Experts Used to Establish Ground Truth and Qualifications:
No information about experts or ground truth establishment is provided.
4. Adjudication Method for the Test Set:
No information regarding an adjudication method is provided.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No information about a MRMC study or its effect size is present in this document.
6. Standalone (Algorithm Only) Performance:
This device is a hardware component (RF Passive Attenuator/Splitter and Loop Electrode), not an algorithm or AI system. Therefore, standalone algorithm performance is not applicable and not discussed.
7. Type of Ground Truth Used:
No information regarding the type of ground truth used is provided. As this is a hardware device clearance, the "ground truth" would likely relate to electrical safety, performance specifications, and clinical effectiveness demonstrated in predicate devices, rather than a diagnostic ground truth.
8. Sample Size for the Training Set:
This device is a hardware component. The concept of a "training set" is not applicable here as it refers to data used to train AI models.
9. How the Ground Truth for the Training Set Was Established:
Not applicable, as this is a hardware device.
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