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The Micra introducer is intended to provide a conduit for the insertion of devices into the venous system and to minimize blood loss associated with such insertions.

Micra™ Introducer : . Model: MI2355A

The provided text describes the 510(k) summary for the Medtronic Micra™ Introducer. There is no information on acceptance criteria or a study proving the device meets those criteria in the context of an Artificial Intelligence (AI) or machine learning device. The document is for a medical device (catheter introducer) and focuses on its physical and functional aspects.

Therefore, I cannot provide the requested information as it pertains to an AI/ML device study.

However, I can extract the information related to the performance testing of the Micra™ Introducer as described in the document, which serves a similar purpose to "acceptance criteria" for this type of device.

Here's the information based on the provided text, adapted to the closest relevant details for a non-AI medical device:

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)

• Sample Size: Not specified for any of the in-vitro bench tests. The document only states that "The following in-vitro bench tests were completed on the Micra™ Introducer".
• Data Provenance: The tests are stated as "in-vitro bench tests," implying laboratory testing. No country of origin is specified for these tests. The nature is experimental/prospective for the in-vitro bench tests.

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

• Not Applicable: This device is not an AI/ML device requiring expert ground truth for its performance evaluation in clinical scenarios. The performance evaluation is based on engineering and material testing standards.

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

• Not Applicable: Adjudication methods are typically used for clinical or image-based studies involving human interpretation, not for in-vitro bench testing of a physical medical 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

• Not Applicable: This is not an AI/ML device. The document explicitly states: "No clinical investigation has been performed for this device."

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

• Not Applicable: This is not an AI/ML device. Performance was evaluated via in-vitro bench tests.

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

• Engineering Specifications/Standards: For the in-vitro bench tests, the "ground truth" would be established engineering specifications and performance requirements for each test (e.g., a specific tensile strength or leak rate). The document doesn't detail these specific numerical criteria but states the device "met all specified design and performance requirements."

8. The sample size for the training set

• Not Applicable: This is not an AI/ML device, so there is no training set in the context of an algorithm.

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

• Not Applicable: This is not an AI/ML device.

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