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The Arrow Sheath Adapter is utilized in conjunction with onepiece Percutaneous Sheath Introducer to permit venous access and catheter introduction into the central circulation.

The proposed device is an accessory to Arrow's existing Percutaneous Sheath Introducer (PSI) (K780532). The adapter is attached to the hemostasis valve of the sheath introducer allowing a broader range of device sizes to be placed through the introducer.

The provided text describes a 510(k) summary for a "Sheath Adapter" and the FDA's clearance letter. This type of device (a catheter Introducer accessory) is a physical medical device and not an AI/ML or imaging device. Therefore, many of the requested categories in the prompt, such as "multi reader multi case (MRMC) comparative effectiveness study," "standalone performance," "ground truth," "training set," "adjudication method," and "experts," are not applicable.

However, I can still extract information about the acceptance criteria and the study that proves the device meets them based on the provided text.

Here's the breakdown of the information that can be extracted:

Acceptance Criteria and Recorded Device Performance

Note: The document states that "Tests were performed to demonstrate substantial equivalence in the following areas," implying that the device's performance in these areas was comparable to the predicate devices and thus met the acceptance criteria by demonstrating this equivalence. The specific quantitative values or thresholds for "acceptance" are not detailed in this summary, nor are the specific results beyond the statement of substantial equivalence.

Study Details (Applicable to Physical Device Clearance)

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

   • The document mentions "laboratory tests" were performed, but does not specify the sample size for these tests or the data provenance.

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

   • Not applicable as this is a physical device and not an AI/ML or imaging device that requires expert ground truth. The "ground truth" for a physical device is typically defined by engineering specifications and objective measurements against those specifications.

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

   • Not applicable. This concept is relevant for reconciling discrepancies in expert assessments for AI/ML ground truth, which is not relevant here.

4. 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 type of study is relevant for AI/ML-assisted diagnostic devices, not for a physical shealth adapter.

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

   • Not applicable. This concept is relevant for AI/ML algorithms. The performance tests ("Leak resistance," "Insertion / drag force," "Cap torsion") are inherently "standalone" in the sense that they are physical tests of the device itself, without human interpretation of an output like an image.

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

   • For this physical device, the "ground truth" for the performance tests would be defined by engineering specifications and objective measurements against those specifications for attributes like leak resistance, insertion/drag force, and cap torsion, likely compared to predicate device performance or industry standards. These are not typically established by expert consensus or pathology in the way AI/ML devices require.

7. The sample size for the training set:

   • Not applicable. This concept is relevant for AI/ML devices.

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

   • Not applicable. This concept is relevant for AI/ML devices.

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