K Number
K173741
Manufacturer
Date Cleared
2018-03-05

(88 days)

Product Code
Regulation Number
878.4400
Panel
SU
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Reprocessed ArthroCare Ablation Wands are indicated for resection, ablation, and coagulation of soft tissue and hemostasis of blood vessels in arthroscopic and orthopedic procedures.

Device Description

Reprocessed ArthroCare Ablation Wands are radiofrequency surgical devices intended for resection, ablation, and coagulation of soft tissue and hemostasis of blood vessels in arthroscopic and orthopedic procedures. Ablation wands are powered by a radiofrequency generator or controller. The device variations include various diameters, lengths, or electrode configurations. The materials of construction are generally polycarbonate handles, stainless steel shafts, PET insulation, tungsten electrodes, alumina ceramic tips and PVC suction lines. The electrode design contributes to the performance differences across different model devices.

AI/ML Overview

This document is a 510(k) summary for a reprocessed medical device, specifically "Reprocessed ArthroCare Ablation Wands." It does not contain information about an AI/ML-driven device or study that uses acceptance criteria in the typical sense of measuring algorithm performance against ground truth in a clinical or diagnostic context.

Instead, the "acceptance criteria" and "study" mentioned here refer to the validation of the reprocessing process to demonstrate that the reprocessed device is substantially equivalent to the original, new device. The "performance" being reported is related to the physical and functional integrity of the reprocessed wands.

Therefore, many of the requested fields are not applicable in this context (e.g., sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth for AI, etc.) because this is not an AI/ML device.

Here's an interpretation based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Demonstrated by Testing)Reported Device Performance
Cleaning: Residual Protein, Carbohydrates, Visual Inspection, Cleaning Performance Qualification meet predetermined standards.Cleaning tests confirmed devices meet established safety and cleanliness standards for reprocessing.
Functional: Thermal Effects, Probe Bending, Probe Drop Performance are equivalent to the predicate (new) device.The subject (reprocessed) devices performed equivalently to the predicate (new) devices in thermal effects, probe bending, and probe drop tests.
Sterilization & Packaging: EtO Sterilization, EtO Residuals, Simulated Shipment Testing meet safety and effectiveness requirements.Tests confirmed effective sterilization, acceptable EtO residuals, and packaging integrity after simulated shipment.
Product Stability: Accelerated aging demonstrates 1-year shelf life. (Real-time studies ongoing.)Accelerated aging demonstrated a 1-year shelf life. Real-time studies are ongoing.
Biocompatibility: Cytotoxicity, Irritation, Acute Systemic, Material Mediated Pyrogenicity, Sensitization meet ISO 10993 standards.Biocompatibility tests (cytotoxicity, irritation, acute systemic, pyrogenicity, sensitization) confirmed material safety.
Electrical Safety & EMC: IEC 60601-1-2 EMC Testing and IEC 60601-2-2 Electrical Safety Testing (high frequency equipment/accessories) are met.Electrical safety and EMC tests confirmed compliance with relevant IEC standards.

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

  • Test Set Sample Size: The document does not specify the exact sample sizes for each type of benchtop performance test (e.g., how many wands were subjected to thermal effects testing, how many for bending, etc.). It generally refers to "the subject devices" and "predicate devices" being tested.
  • Data Provenance: The data is from benchtop performance testing conducted by ReNovo, Inc. (the submitter), comparing their reprocessed devices against the predicate (OEM) devices. This is prospective testing for the 510(k) submission. No country of origin is explicitly stated for the "data," but the submitter is based in Bend, OR, USA.

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

  • Not Applicable. This is not an AI/ML device, and "ground truth" in the diagnostic context is not relevant here. The "ground truth" for these tests are objective, measurable physical and chemical properties and functional performance characteristics, often against established industry standards. These are not established by human experts in a subjective manner.

4. Adjudication method for the test set:

  • Not Applicable. As this is not an AI/ML device, there's no diagnostic output requiring expert adjudication. Performance is measured against predefined, objective pass/fail criteria or equivalence to a predicate device.

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 is not an AI/ML device. No human-in-the-loop studies or MRMC studies were performed.

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

  • Not Applicable. This is not an AI/ML device. There is no algorithm.

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

  • The "ground truth" here is the established physical, chemical, and functional performance characteristics of the original, new (predicate) medical device and compliance with relevant engineering and biocompatibility standards (e.g., ISO 10993, IEC 60601). The "ground truth" for cleaning effectively would be specific limits on residual protein/carbohydrates, for example. For functional performance, it would be the performance of the new device.

8. The sample size for the training set:

  • Not Applicable. This is not an AI/ML device. No training set was used.

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

  • Not Applicable. This is not an AI/ML device. No training set was used.

§ 878.4400 Electrosurgical cutting and coagulation device and accessories.

(a)
Identification. An electrosurgical cutting and coagulation device and accessories is a device intended to remove tissue and control bleeding by use of high-frequency electrical current.(b)
Classification. Class II.