Search Results

The Disposable Trocars have application in a variety of endoscopic procedures to provide a port of entry for endoscopic instruments and/or endoscope.

The Disposable Trocars includes Normal trocars (model A), Balloon trocars (model B), Thread trocars (model C) and Single-port trocars (model E). They are generally composed of cannula and obturator, with or without filter/cleaning ring/protector. The Disposable Trocars have application in a variety of endoscopic procedures to provide a port of entry for endoscopic instruments and/or endoscope. If needed, the CO2 can be infused through the valve. The product is sterilized by Ethylene oxide and is a single-use product.

The provided text is a 510(k) summary for a medical device (Disposable Trocars) seeking FDA clearance. It outlines the substantial equivalence to predicate devices based on various characteristics and non-clinical testing. However, it does not contain information about a study proving the device meets acceptance criteria related to AI/algorithm performance, human reader improvement with AI assistance, or the establishment of ground truth by expert consensus.

The document primarily focuses on bench testing and material biocompatibility for traditional medical device components, not software or AI performance. The details requested in the prompt, such as sample sizes for test sets, data provenance for AI studies, number of experts for ground truth, adjudication methods, MRMC studies, standalone algorithm performance, and training set details, are not present in this type of FDA submission for a device like a trocar.

Therefore, I cannot provide the detailed information requested in the prompt based on the given text. The text describes the testing of the physical device's performance properties (e.g., obturator compatibility, air leakage, balloon rigidity) and biocompatibility, not the performance of an AI or algorithmic component.

If the request refers to the performance criteria for the physical device itself (the trocars), then I can extract some relevant information, though it won't align perfectly with the AI/algorithm-focused questions in the prompt.

Based on the provided text, and assuming "device performance" refers to the physical attributes and functionalities of the Disposable Trocars, here's what can be extracted, acknowledging that many of your specific questions are not addressed by this type of document:

The Disposable Trocars are physical medical instruments used in endoscopic procedures. The "acceptance criteria" and "device performance" discussed in this document relate to their physical and biological properties, not AI or algorithmic performance.

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

The document states that "All the test results were 'PASS'." This implies that the device met pre-defined acceptance criteria for each test. However, the specific quantitative acceptance criteria values are not explicitly listed, only the type of tests performed.

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

• Sample Size: Not specified in the provided text. The document mentions "performance studies and bench testing" but does not give the number of units tested.
• Data Provenance: Not applicable in the context of clinical data for AI. The tests are bench tests performed by the manufacturer, Hangzhou Kangji Medical Instrument Co., Ltd., which is based in China. The data would be prospective in the sense that the company specifically conducted these tests for the submission.

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

• Not applicable. This document describes testing of a physical medical device. Ground truth as understood in AI/image analysis (e.g., expert radiologist consensus) is not relevant here. The ground truth for these tests would be established by validated test methods and measurement standards for physical properties. The tests were evaluated by their "Design Engineer."

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

• Not applicable. This is for AI/image analysis. The "adjudication" for these physical tests would be the measurement against a pre-defined specification or standard.

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. This is a physical medical device, not an AI or software device that assists human readers.

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

• No. This is a physical medical device.

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

• For biocompatibility: ISO and USP standards (e.g., cell cultures for cytotoxicity, animal models for systemic toxicity).
• For performance: Engineering specifications and test methods for physical properties (e.g., force measurements for insertion, pressure measurements for air leakage).

8. The sample size for the training set:

• Not applicable. This is a physical medical device, not an AI model requiring a training set.

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

• Not applicable.

Ask a specific question about this device