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GDS-DC6 is intended to facilitate the intracardiac placement of interventional devices such as guidewires.

GDS-DC6 is a polymeric, single use, sterile, non-pyrogenic, disposable intracardiac catheter of various sizes and curvatures.

Here's an analysis of the provided text regarding the GDS-DC6 device, focusing on acceptance criteria and supporting studies:

It's important to note that the provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed clinical study results of a novel AI/software medical device. As such, information regarding AI-specific studies (e.g., sample sizes for training/test sets, expert adjudication, MRMC studies) will not be present. The studies mentioned are primarily bench testing, biocompatibility, and packaging/shelf-life.

Acceptance Criteria and Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics in a format typical for software or AI medical devices. Instead, it refers to compliance with general standards and expectations for a cardiac introducer sheath.

Study Details (Based on available information)

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

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

• Sample Size for Test Set: Not specified. The studies mentioned are "Bench testing," "Biocompatibility data," and "Packaging and shelf life testing." These are not typically described with a "test set" in the context of diagnostic performance or AI validation, but rather as tests performed on a defined number of device units or materials.
• Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). These are laboratory/bench studies, not clinical studies.

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

• Not applicable/Not specified. For bench testing and biocompatibility, ground truth is established by standardized testing methods and regulatory standards (e.g., ISO), not by expert consensus on clinical cases.

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

• Not applicable/Not specified. Adjudication methods are relevant for subjective interpretations, typically in clinical imaging or diagnostic studies. The reported studies are objective laboratory tests.

5. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done, and 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 (cardiac introducer sheath), not an AI/software device whose performance would be measured in an MRMC study comparing human readers with and without AI assistance.

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

• No. This is a physical medical device and does not involve an algorithm with standalone performance.

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

• Biocompatibility: Ground truth is defined by the requirements of ISO 10993 (e.g., cytotoxicity, sensitization, irritation).
• Bench Testing: Ground truth is defined by the requirements of ISO 10555-1 (e.g., tensile strength, burst pressure, flow rate, torqueability) and general engineering/medical device performance expectations.
• Packaging and Shelf Life: Ground truth is defined by sterility maintenance, package integrity, and material degradation over time.

8. The sample size for the training set:

• Not applicable. This is not an AI/machine learning device that requires a "training set."

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

• Not applicable. As noted above, there is no training set for this type of device.

Summary of Device Type and Study Context:

The GDS-DC6 is a physical medical device (a cardiac introducer sheath), not a software or AI-driven diagnostic device. Therefore, the types of studies and associated metrics (such as test set sample sizes, expert adjudication, MRMC studies, training data, ground truth for AI models) typically requested for AI-enabled devices are not applicable to the information provided in this 510(k) summary. The studies conducted are standard engineering, materials, and biological safety tests to demonstrate the safety and effectiveness of a physical product by showing substantial equivalence to existing predicate devices.

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