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The HI-TORQUE Guide Wire is intended for general intravascular use to aid in the selective placement of interventional devices and implantable coronary venous leads in the coronary and/or peripheral vasculature during diagnostic and/or therapeutic procedures.

The HI-TORQUE Guide Wires are steerable guide wires available in a nominal diameter of 0.14".

The provided text describes a 510(k) submission for HI-TORQUE Guide Wires, seeking to expand their indications for use. It primarily focuses on demonstrating substantial equivalence to existing devices rather than presenting a novel device requiring extensive performance acceptance criteria and a dedicated study to prove those criteria.

Here's an analysis based on the provided text, addressing your questions where possible:

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

The submission does not explicitly state formal quantitative acceptance criteria for the expanded indication. Instead, it relies on demonstrating equivalence to predicate devices and showing acceptable performance in in vivo animal and human clinical studies for the specific new intended use (placement of coronary venous pace/sense leads).

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

• Animal Study: The sample size is not specified. The text only mentions "Animal studies were conducted." Data provenance is not specified, but typically animal studies for medical devices are conducted in controlled environments.
• Human Clinical Testing Data: The sample size is not specified. The text states, "HI-TORQUE Guide Wires were evaluated in a clinical investigation." The data provenance is not specified, but it was a clinical investigation, implying a prospective study design.

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)

This information is not provided in the document. Given that this is a 510(k) for an expanded indication and not a de novo device, the focus is on safety and effectiveness as demonstrated through the in vivo studies, rather than a diagnostic device requiring expert interpretation of results to establish ground truth.

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

This information is not provided. As explained above, the nature of this submission (expanded indication for a guide wire) does not typically involve a complex adjudication process for establishing a "ground truth" in the way a diagnostic algorithm might. The evaluation likely focused on procedural success, adverse events, and device performance metrics.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI-powered diagnostic devices, which is not what the HI-TORQUE Guide Wire is. The device is a physical medical instrument whose performance is assessed through its direct application in procedures.

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

No, a standalone algorithm-only performance study was not done. The HI-TORQUE Guide Wire is a physical medical device, not a software algorithm. Its performance is intrinsically linked to its use by a human operator (e.g., a cardiologist).

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

For the human clinical testing, the "ground truth" would likely be successful placement of the compatible coronary venous pace/sense lead and absence of significant adverse events. This would be determined by the treating physician and potentially confirmed through post-procedure imaging or clinical follow-up (outcomes data related to the procedure's success and safety).

8. The sample size for the training set

The concept of a "training set" is not applicable to this device. Training sets are used in machine learning for AI algorithms. This submission concerns a physical medical device.

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

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

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