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The ELEOSTM/ELEOSx™ Limb Salvage System is indicated for resection and replacement of the proximal femur, intercalary portion of the femur, total femur, distal femur. and proximal tibia in skeletally mature patients with the following conditions: 1) Non-inflammatory degenerative joint disease such as osteoarthritis, traumatic arthritis, avascular necrosis, ankylosis, protrusion acetabuli, and painful hip dysplasia; 2) Inflammatory degenerative joint disease such as rheumatoid arthritis; 3) Correction of functional deformity; 4) Revision procedures where other treatments or devices have failed: and. 5) Treatment of fractures that are unmanageable using other techniques. The ELEOS™/ELEOSx™ Limb Salvage System is also indicated for procedures where resection and replacement of the proximal femur, intercalary portion of the femur, total femur, distal femur, and proximal tibia is required with the following conditions: 1) Patients suffering from severe arthropathy of the hip and/or knee that does not respond to any conservative therapy or better alternative surgical treatment; 2) Surgical intervention for severe trauma, revision hip or knee arthroplasties, and/or Oncology indications. 3) Metastatic diseases. The ELEOSx™ MDPB coating, where applied, is intended to reduce bacterial contamination prior to implantation resulting from deposition in the operating room on the surface of the device components. The clinical impact associated with the MDPB coating, including prevention of infection or reduction of infection risk in patients, has not been evaluated in human clinical trials. The MDPB coating is not intended to treat existing infections and does not act within or on the body.

The Onkos Surgical ELEOSx™ Limb Salvage System consists of components that are used in the reconstruction of the lower limb. The systems include components manufactured from cobalt-chrome alloy (CoCr), titanium alloy (TAV), and ultra-high molecular weight polyethylene (UHMWPE). Non-articulating CoCr component surfaces are coated with 12-Methacryloyloxydodecyl Pyridinium Bromide (MDPB), which is intended to reduce bacterial contamination on the surface of the device components prior to implantation resulting from deposition in the operating room. Based on in vitro testing, this coating may result in immobilization and/or lysis of some challenge organisms. The MDPB coated CoCr stems are for cemented use in the reconstruction/replacement of the lower limb. The reconstruction applications are proximal femur, intercalary portion of the femur, distal femur, total femur, proximal tibia, and hinged knee. The ELEOS™ Limb Salvage components are femoral head, proximal femur, female stem, mid-section, stem, distal femur, tibial hinge component, axial pin. tibial poly spacer, tibial baseplate, malemale mid-section, resurfacing femur, proximal tibia, tapered screws, patella, stem extension, tibial wedges, and augments. Instruments included in the Onkos ELEOSx™ Limb Salvage System are used in implantation and removal of the system components.

The provided text describes a De Novo classification request for a medical device, the ELEOSx™ Limb Salvage System, which includes a quaternary ammonium compound coating. The document focuses on regulatory information, device description, non-clinical/bench studies, and risk assessment to support its classification.

However, the input text does not describe a study involving an AI/Machine Learning device or an "algorithm only" performance study. It details the acceptance criteria and the studies that prove the mechanical, chemical, and biological performance of a physical medical implant, specifically focusing on the MDPB coating's integrity, effects on range of motion, cement interface pull-out strength, fretting and corrosion, antimicrobial performance, and physicochemical characterization.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone algorithm performance, training set sample size, ground truth establishment) are not applicable to the information provided because the device in question is a physical implant, not an AI or algorithm-based system.

Below, I will extract the relevant information from the provided text regarding the acceptance criteria and the studies that prove the device meets these criteria, as described for this physical medical device.

Acceptance Criteria and Device Performance for ELEOSx™ Limb Salvage System

The acceptance criteria for the ELEOSx™ Limb Salvage System are defined by a series of non-clinical (bench) studies, biocompatibility evaluations, sterilization validation, and material characterization, with the overarching goal of demonstrating the device's safety and performance, particularly concerning the novel MDPB coating. The studies primarily aim to show that the MDPB coating does not negatively impact the device's mechanical integrity or biocompatibility, and that it effectively reduces bacterial contamination prior to implantation without affecting the body internally.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Test Sets: The document refers to various bench studies. Specific sample sizes are not detailed for each mechanical test (e.g., "stems were inserted," "proximal femurs").
• Data Provenance: The studies are described as "non-clinical/bench studies," which implies laboratory testing. The text does not specify the country of origin of the data
  (e.g., US, Europe, Asia) nor whether they were retrospective or prospective, as these terms are typically used for clinical data or AI model development. These are lab-based, controlled experiments.

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

This is not applicable. The "ground truth" for these physical device tests is based on established engineering and material science standards (e.g., ISO standards, ANSI/AAMI standards) and direct measurements/observations in controlled laboratory environments. It does not involve expert readers interpretating images or data for AI model validation.

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

This is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies or AI model validation where human interpretation and consensus are required to establish ground truth or resolve discrepancies. These bench studies rely on objective measurements and established protocols.

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:

This is not applicable. An MRMC study is designed to evaluate the impact of an AI system on human reader performance, typically in diagnostic imaging. The ELEOSx™ Limb Salvage System is a physical medical implant, not an AI or diagnostic imaging device.

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

This is not applicable. This question pertains to the performance of an AI algorithm in isolation. The ELEOSx™ Limb Salvage System is not an algorithm.

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

The "ground truth" for this device's performance is established through objective measurements and adherence to recognized international standards and test methods. For example:

• Mechanical properties: Measured against established engineering specifications and comparative data to uncoated devices.
• Biocompatibility: Demonstrated by passing standardized in vitro and in vivo (animal) tests (e.g., per ISO 10993 series).
• Sterility and Pyrogenicity: Verified through validated sterilization processes and bacterial endotoxin testing (e.g., per ISO 11137, ANSI/AAMI ST72).
• Antimicrobial Performance: Demonstrated in vitro through simulated use testing.

8. The sample size for the training set:

This is not applicable. The concept of a "training set" refers to data used to train an AI or machine learning model. This is a physical medical device. The manufacturing process and materials testing involve quality control and validation, but not machine learning training sets in the AI sense.

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

This is not applicable for the reasons stated above.

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