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The HYBRIDknife flex is intended for:
· monopolar cutting and coagulation.
· needle-free injection and tissue-selective hydrodissection including lifting mucosal lesions by injection into the submucosa (soft tissue).
The HYBRIDknife flex is used in endoscopic interventions.

The HYBRIDknife flex is a flexible monopolar probe that combines the technologies of hydrosurgery and electrosurgery in one instrument.
Each function can be activated without the need to change instruments. The HYBRIDknife flex is a sterile, single use device which is used with endoscopes with a minimal working channel diameter of 2.8mm. The hydrosurgical function is intended to deliver a pressurized fluid for tissue-selective hydrodissection and needle-free injection whereas the electrosurgical function is intended for cutting and coagulation of tissue. By means of needle-free injection a fluid cushion is formed in the submucosa, which provides a mechanical and thermal protection layer during cutting and coagulation of the target tissue. The elevation thus reduces the risk of perforation. All HYBRIDknife flex probes have a length of 2.3 meters and an outer diameter (OD) of 2.6mm. The only difference between the variants is the electrode type and length. The HYBRIDknife flex is available with a "T-type" electrode and an "I-type" electrode whereas both electrode types are available as a long (i.e. 2mm length) and short (i.e. 1.5mm) version. The protrusion of the T-type electrode gives the user the possibility to hook and move tissue. The instruments are designed for operation with the hydrosurgical unit ERBEJET 2 (K072404; K143306 & K231023) in combination with an Erbe Electrosurgical unit of the "VIO" series (e.g. VIO 3 K190823). HYBRIDknife flex is connected to the units via respective cables/tubings. The settings or adjustment of application parameters is performed via the units. Activation of the instrument is done by using a footswitch.

The provided text is a 510(k) summary for a medical device called HYBRIDknife® flex. This document is a regulatory submission to the FDA, demonstrating that the device is substantially equivalent to legally marketed predicate devices.

Crucially, this document is NOT a study report for an AI/ML medical device. It describes a physical electrosurgical cutting and coagulation device. Therefore, the questions about AI/ML specific acceptance criteria, test sets, ground truth establishment, expert adjudication, MRMC studies, and standalone algorithm performance are not applicable to this document. The term "device" in the context of this document refers to the physical surgical instrument, not an AI model.

The document discusses non-clinical performance testing of the device, which aims to verify its safety and performance based on engineering principles and established standards for electrosurgical equipment. This is distinct from the type of performance study conducted for AI/ML devices, which involves evaluating the performance of an algorithm against a ground truth.

Here's how to address the request based on the provided text, while clarifying the limitations:

Acceptance Criteria and Device Performance (Based on the document for a physical medical device)

The document primarily focuses on demonstrating substantial equivalence to predicate devices rather than defining explicit "acceptance criteria" in the way one might for an AI/ML model's performance metrics (e.g., specific sensitivity/specificity thresholds). Instead, the acceptance is based on demonstrating that the new device does not raise new questions of safety or effectiveness and performs comparably to the predicate devices for its intended use.

The "performance" is verified through various non-clinical tests to ensure the device meets design specifications and relevant industry standards.

1. Table of Acceptance Criteria and Reported Device Performance

As this is not an AI/ML device, a table of acceptance criteria for algorithm performance metrics (like sensitivity, specificity, AUC) is not provided in the document. Instead, the document discusses conformity to standards and comparability to predicate devices. The "performance" here refers to the device's functional integrity and safety.

2. Sample size used for the test set and the data provenance
Not applicable in the context of an AI/ML test set. The testing referenced are non-clinical (e.g., tissue testing, electrical testing, biocompatibility testing, sterilization validation) of a physical device. There isn't a "test set" of patient data in the AI/ML sense. Data provenance would refer to the characteristics of the materials or test conditions used in the lab testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This pertains to AI/ML model validation using expert labels, which is not described here.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. This pertains to AI/ML model validation using expert labels, which is not described here.

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 pertains to AI/ML model validation. The device is a physical surgical instrument, not an AI.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This pertains to AI/ML model validation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable in the AI/ML context. For this physical device, "ground truth" would be established by physical measurements, chemical analyses, biological assays (e.g., for biocompatibility), and direct observation of electrosurgical and hydrodissection effects on tissue models, as per standard engineering and medical device testing protocols. The "truth" is adherence to specifications and standards.

8. The sample size for the training set
Not applicable. This device is not an AI/ML model and does not have a "training set" in that sense.

9. How the ground truth for the training set was established
Not applicable. This device is not an AI/ML model and does not have a "training set" in that sense.

Summary of the Study Proving Device Meets "Acceptance Criteria" (Non-Clinical Performance Testing)

The "study" in this context refers to a series of non-clinical performance tests designed to demonstrate the safety and effectiveness of the HYBRIDknife® flex and its substantial equivalence to predicate devices. These tests were performed rather than a clinical trial or AI/ML validation study.

The primary goal was to show that despite some technological differences (e.g., higher dielectric strength, slightly different dimensions, fixed electrode states vs. adjustable), the device performs its intended functions comparably to existing, legally marketed devices and adheres to relevant safety and performance standards.

The non-clinical performance testing included:

• Functional Testing and Design Controls: To verify overall safety and performance, ensuring the device performs as intended and meets design specifications (in compliance with 21 CFR 820.30).
• Tissue Testing: To validate the cutting and coagulation performance and the waterjet function. This was done by comparing the HYBRIDknife® flex to the predicate device, specifically looking at the creation of equivalent fluid cushions. This would involve in-vitro or ex-vivo tissue models.
• EMC and Electrical Safety Testing: To ensure compliance with international standards (IEC 60601-1, IEC 60601-2-2, IEC 60601-2-18, IEC 60601-1-2). This verifies that the device operates safely electrically and doesn't interfere with other medical equipment.
• Biocompatibility Testing: To ensure the new materials used in the device are safe for contact with the body (in compliance with ISO 10993-1).
• Sterilization Validation: To confirm the device can be consistently sterilized to a specific sterility assurance level (SAL of 10-6) and that ethylene oxide residuals are within safe limits (in compliance with ISO 11135 and ISO 10993-7).
• Packaging and Shelf-life Validation: To ensure the device remains sterile and functional over its intended shelf-life, including accelerated aging tests (in compliance with ISO 11607-1 and ASTM F 1980).

Data Provenance and "Test Set" Details (for a physical device):

The data would originate from laboratory and bench testing conditions. This is typically controlled and prospective, conducted specifically to gather data for regulatory submission. There isn't a "country of origin of the data" in the sense of patient data, but rather the location where the testing labs are.

In conclusion, the provided document is a regulatory submission for a physical medical device, not an AI/ML model. Therefore, many of the specific questions about AI/ML acceptance criteria and study design are not applicable. The "acceptance criteria" for this device are demonstrated through adherence to design specifications, relevant industry standards, and demonstrated substantial equivalence to predicate devices via rigorous non-clinical testing.

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