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The Lagis Endoscopic Instruments Disposable Grasper has application in a variety of general, urologic, gyneoologic and endoscopic procedure for grasping and clamping of tissue and small tubular structures.

The Lagis Endoscopic Instruments Disposable Grasper with 5mm diameter insulated shaft, 33cm in length, is designed for introduction and use through all appropriately sized trocar sleeves or larger sized trocar sleeves with the use of a converter. Same as predicate devices, the Lagis Endoscopic Instruments Disposable Grasper has a pair of plastic handles, which are compressed and released to close or open the instrument forceps. The rotation knob located on the handle rotates the shaft 360 degrees in either direction. Due to different functional requirements, the instrument forceps can be of various designs such as fenestrated/atraumatic/flat/ Endo-Clinch/Babcock/CROCE-OLMI grasping forceps. The materials of construction are similar to the predicate devices and are satisfactorily tested for cytotoxicity, sensitization, intracutaneous reactivity and systematic toxicity per ISO 10993 and 21 CFR, Part 58 requirements.

The provided text is a 510(k) Summary for the Lagis Endoscopic Instruments Disposable Grasper. It describes the device, its intended use, and states that performance bench tests were conducted. However, it does not contain the detailed information necessary to complete most of the requested fields regarding acceptance criteria and the specifics of a study proving device performance in the context of AI/medical imaging.

Here's an attempt to answer based only on the provided text, with clear indications of what information is missing:

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

Note: The document generally states "acceptable results" or "safe, effective and performs well as intended" without providing specific thresholds or metrics for the acceptance criteria.

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

• Sample Size for Test Set: Not specified. The document mentions "performance bench tests" but does not detail the number of devices or trials.
• Data Provenance: Not specified. The document describes bench tests which are typically laboratory-based, not patient data.

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)

• This information is not applicable and not provided. The study described involved "performance bench tests" of a physical medical instrument, not an AI or imaging device requiring expert ground truth establishment from medical data.

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

• This information is not applicable and not provided, as the study was bench testing of a physical 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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This study pertains to a physical surgical instrument, not an AI system or imaging device requiring human reader analysis.

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

• This information is not applicable. The device is a physical endoscopic grasper, not an algorithm. The "performance bench tests" can be considered "standalone" in that they evaluate the device itself.

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

• The concept of "ground truth" as typically applied to medical imaging/AI is not directly relevant here. For the bench tests, the "ground truth" would be established engineering specifications, material properties, and functional requirements against which the device's performance was measured. The document states tests were conducted to "verify design characteristics and to ensure that the device can be used as intended."

8. The sample size for the training set

• This information is not applicable and not provided. The device is a physical medical instrument, not a machine learning model that requires a training set.

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

• This information is not applicable and not provided (see point 8).

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