Search Results

The electrosurgical unipolar hook electrode is intended to be used for coagulation and cutting of tissue.

The Hook Electrode is a unipolar electrosurgical device used primarily for cutting, but also usable for coagulation. The device is attached via cable to an electrosurgical generator.

The provided document K964329 describes a 510(k) submission for a Unipolar Electrosurgical Hook Electrode. This device is not a software-driven AI/ML device, and therefore, many of the requested criteria related to AI/ML device performance and study design are not applicable.

Here's an analysis based on the information provided, highlighting the non-applicability of certain AI/ML-specific questions:

1. A table of acceptance criteria and the reported device performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable: This device is a physical electrosurgical hook electrode. The "test set" in an AI/ML context refers to a distinct dataset used for evaluating algorithm performance. For this device, "testing" refers to physical compliance testing.
• The performance data focuses on technical characteristics rather than a clinical "test set" in the AI/ML sense.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable: Given this is a physical medical device, there is no "ground truth" in the context of expert labels for an AI/ML system. Ground truth typically refers to verified labels or annotations for data used to train and evaluate AI models. The "ground truth" of performance for this device comes from engineering and material testing standards.

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

• Not Applicable: Adjudication methods are relevant for resolving discrepancies in expert labeling or diagnoses in clinical studies, particularly for AI/ML development. This device's evaluation does not involve such human-in-the-loop expert adjudication of a test set.

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: MRMC studies are designed to compare the performance of human readers, often with and without AI assistance, on diagnostic tasks using medical images or other data. This device is an electrosurgical tool and does not involve "human readers" interpreting data with or without AI assistance.

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

• Not Applicable: There is no algorithm associated with this physical electrosurgical device, so standalone algorithm performance testing is irrelevant.

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

• Engineering Standards / Physical Property Measurement: The "ground truth" for this device's performance is based on established engineering standards for electrical isolation and validated sterilization protocols. For example, "3000 Volt isolation" would be verified through specific electrical tests.

8. The sample size for the training set

• Not Applicable: This is not an AI/ML device. There is no concept of a "training set" for physical electrosurgical tools.

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

• Not Applicable: As there is no training set for an AI/ML model, there is no ground truth establishment for a training set.

Summary of the Study that Proves the Device Meets Acceptance Criteria:

The provided 510(k) summary states that "Performance Data" was "Tested to assure 3000 volt isolation and validation to recommended sterilization processes." Additionally, it notes the device's "Technological Characteristics" include a "durable powder coating" and that it is "gas and steam sterilizable."

No Clinical Tests: The document explicitly states "No clinical tests performed."

Conclusion: The device's safety and effectiveness were demonstrated through engineering and performance testing against established standards for electrical isolation and sterilization, rather than through clinical trials or AI/ML specific performance studies. The substantial equivalence claim is based on the device's design, intended use, and technological characteristics being comparable to pre-enactment and existing predicate devices, along with the successful completion of these non-clinical performance tests.

Ask a specific question about this device