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The proposed device is a silicone coated stainless steel guidewire. It consists of a coiled wire around a solid stainless steel core wire. The internal core wire is secured at both ends to the outer core wire. These guidewires are used to place intravascular catheters.

AI/ML Overview

The provided submission K041740 is for a Silicone Coated Guidewire, a medical device. This type of device does not involve AI or algorithms, and therefore, many of the requested fields are not applicable. The device's performance is demonstrated through traditional engineering and material science tests rather than studies involving human readers or ground truth established by experts in an AI context.

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document outlines performance tests conducted to demonstrate substantial equivalence to a predicate device. It doesn't explicitly state numerical acceptance criteria, but implies that the new device's performance met the standards set by the predicate device for each test.

Test Performed	Acceptance Criteria (Implied)	Reported Device Performance
Tensile Strength	Substantially equivalent to predicate device performance.	Demonstrated substantial equivalence.
Catheter Compatibility	Substantially equivalent to predicate device performance.	Demonstrated substantial equivalence.
Coating Durability/Lubricity	Substantially equivalent to predicate device performance.	Demonstrated substantial equivalence.
Flexing Test	Substantially equivalent to predicate device performance.	Demonstrated substantial equivalence.
Fracture Test	Substantially equivalent to predicate device performance.	Demonstrated substantial equivalence.
Tip Flexibility	Substantially equivalent to predicate device performance.	Demonstrated substantial equivalence.

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

This information is not provided in the 510(k) summary. For physical medical devices like guidewires, "test set" typically refers to the number of units tested for mechanical properties, not a dataset in an AI context. The tests are laboratory-based, not involving 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):

Not applicable. This device is a physical medical device, not an AI/algorithm-based diagnostic tool. Ground truth is established through physical measurements and engineering standards, not expert assessments of images or other data.

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

Not applicable. Adjudication methods are relevant for subjective interpretations, often in AI or clinical trial settings. The performance tests for a guidewire are objective engineering 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.

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

The "ground truth" for a physical medical device like this is based on engineering specifications, material science properties, and established performance benchmarks for similar predicate devices. For example, tensile strength would be measured against a required specification, not an expert's opinion.

8. The sample size for the training set:

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

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

Not applicable, as there is no training set for a physical guidewire.

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