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LAP-iX is a sterile, single-patient-use electrosurgical accessory intended to conduct electrosurgical current for cutting and coagulation of tissue and/or to provide suction and irrigation functions to the surgical site.

The LAP-iX provides suction or irrigation and conducts high-frequency monopolar electrosurgical energy from compatible electrosurgical generators to a surgical site during laparoscopic and endoscopic procedures. It delivers sterile irrigation fluids to surgical site and evacuates blood and body fluids from the surgical site to aid visualization. They are used during open, endoscopic, and laparoscopic surgical procedures to ablate, remove, resect, and coagulate soft tissue where associated hemostasis is required. Depending on the shape of the handle, there are two types, PISTOL Type and TRUMPET Type. Each type also offer both Unlock Type and Lock Type. There are 8 models in total. The electrode offers two types: L-HOOK and SPOON Type. The voltage should not exceed 175Vrms (3002 standard), and set to minimum power (100W, 3002 standard). The connector (banana jack) of the subject device is compatible with all suction/irrigation pumps and electrosurgical generator in the market which have the connecting tubes or connectors of Ø10mm (Suction), Ø7mm(Irrigation) and Ø4mm(Electrode).

The provided document is a 510(k) summary for the LAP-iX electrosurgical accessory. It outlines the device's indications for use, its description, and the performance data that supports its substantial equivalence to a predicate device. However, it does not describe an AI-based device, nor does it conduct a study where device performance is measured against acceptance criteria in the way typically expected for AI/ML medical devices.

The document discusses various performance tests relevant to an electrosurgical device, such as sterilization validation, shelf-life validation, biocompatibility tests, and electrical/mechanical performance tests. These are to ensure the LAP-iX is safe and effective for its intended use, and substantially equivalent to its predicate.

Therefore, many of the requested categories for AI/ML device studies cannot be addressed using the provided text.

Here's a breakdown based on the information available and an explanation where information is not available due to the nature of the device:

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

The document lists performance tests, but it does not specify acceptance criteria in a quantitative manner as typically seen for AI/ML device performance (e.g., sensitivity, specificity thresholds). Instead, it states that tests were performed "in accordance with" standards or for specific engineering parameters.

Study Proving Device Meets Acceptance Criteria:

The document explicitly states: "The following tests were performed on the subject device and the test results support that the subject device is substantially equivalent to the predicate devices." This implies that the device successfully met the internal acceptance criteria set for each test, which were designed to demonstrate its safety and effectiveness in line with the predicate device and relevant standards.

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: The document does not specify the sample size for individual performance tests. For instance, it doesn't say how many units were tested for sterilization or tensile strength.
• Data Provenance: Not specified. These are engineering and bench tests, not clinical data sets from specific countries. The manufacturer is in the Republic of Korea.
• Retrospective/Prospective: Not applicable as this submission pertains to an electrosurgical accessory, not a diagnostic or prognostic data-driven device.

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. This device is not an AI/ML diagnostic or predictive device that requires expert-established ground truth for a test set. The "ground truth" for these tests would be the physical properties of the device meeting predetermined engineering specifications and international standards.

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

Not applicable. Adjudication methods are typically for clinical studies, especially those involving expert review of diagnostic images or interpretations. The tests performed are engineering and laboratory tests.

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-assisted device.

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

Not applicable. This is not an algorithm-based device.

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

The "ground truth" for this device's performance tests would be the established engineering specifications, safety standards (e.g., ISO, electrical safety limits), and functional requirements for an electrosurgical device accessory. It does not involve expert consensus on medical findings, pathology, or outcomes data in the way an AI diagnostic device would.

8. The sample size for the training set

Not applicable. This device does not use an AI/ML algorithm that requires a training set.

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

Not applicable. This device does not use an AI/ML algorithm that requires a training set.

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