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The Prelude® Sheath Introducer is intended to provide access and facilitate the percutaneous introduction of various devices into veins and/or arteries while maintaining hemostasis for a variety of diagnostic and therapeutic procedures.

The Prelude® Sheath Introducer consists of a sheath introducer with compatible vessel dilator that snaps securely into the sheath introducer hub. The sheath is equipped with a side arm terminating in a 3-way stopcock. The sheath hub contains an integral hemostasis valve and a suture ring. The subject sheath introducer has a radiopaque marker tip. The device is marketed with and without an appropriately sized guide wire.

The document provided is a 510(k) Pre-market Notification Summary for a medical device (Prelude® Sheath Introducer), not a study analyzing the performance of an AI/ML powered device. Therefore, it does not contain information related to AI/ML device performance, acceptance criteria for such a device, sample sizes, ground truth establishment, or expert involvement as requested.

The document indicates that the device is a physical medical device (Vessel Dilator for Percutaneous Catheterization) and the 510(k) submission is for a minor change to an existing predicate device (specifically, "The only change that was made was to the radiopaque marker tip material.").

The "Acceptance Criteria" and "Study" described in the document are related to the physical and biological safety and performance of the medical device itself, not to a diagnostic or analytical algorithm.

Here's an attempt to extract relevant information, acknowledging that it pertains to a physical device and not an AI/ML algorithm:

1. Table of acceptance criteria and the reported device performance:

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
The document does not specify sample sizes for each test. The tests are general performance and biocompatibility tests for a physical medical device. Data provenance (country of origin, retrospective/prospective) is not applicable or specified for these types of engineering and biological tests, which are typically performed in a laboratory setting by the manufacturer.

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 is not applicable to a physical device performance and biocompatibility study. "Ground truth" in the context of expert consensus is relevant for diagnostic accuracy studies, typically involving human interpretation of medical images or data. For this device, "ground truth" refers to established scientific principles, regulatory standards (like ISO and ASTM), and pre-defined pass/fail criteria for physical and biological properties.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable. Adjudication methods like '2+1' or '3+1' are used for resolving disagreements among multiple human readers in diagnostic accuracy studies. For physical device testing, results are typically objective measurements against engineering specifications and biological standards.

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 document describes the safety and performance testing for a physical medical device (sheath introducer), not an AI/ML-powered diagnostic tool. Therefore, MRMC studies and AI assistance are not relevant here.

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 the device's performance is based on established international standards (ISO, AAMI, ASTM, USP) and FDA guidance documents for medical device testing. These standards define the methodologies and acceptance criteria for various physical, chemical, and biological properties.

8. The sample size for the training set:
Not applicable. There is no AI/ML algorithm involved, so no "training set."

9. How the ground truth for the training set was established:
Not applicable. There is no AI/ML algorithm involved, so no "training set" or ground truth establishment for it.

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The Merit Prelude™ Sheath Introducer is intended to provide access and facilitate the percutaneous introduction of various devices into veins and/ or arteries while maintaining hemostasis for a variety of diagnostic and therapeutic procedures.

Merit Medical System's Prelude™ Sheath Introducer consists of a sheath introducer with compatible vessel dilator that snaps securely into the sheath introducer hub. The sheath is equipped with a sideport attached to a segment of extension tubing terminating in a 3-way stopcock. The sheath hub contains an integral hemostasis valve and suture ring. The device is marketed with and without an appropriately sized guide wire and/ or access needle.

The provided text is a 510(k) Premarket Notification for the Merit Prelude™ Sheath Introducer and does not contain the detailed information necessary to answer all parts of your request regarding acceptance criteria and a study proving device performance in the context of clinical metrics or AI performance.

This document describes a medical device (a sheath introducer) and its submission for FDA clearance based on substantial equivalence to a predicate device. The "Performance Testing" section states: "Verification and Validation Studies, as identified in the Clinical Risk Assessment, were completed and demonstrated that the modified devices met all of their pre-determined acceptance criteria." However, it does not provide the specific acceptance criteria or the reported device performance in a quantifiable manner (e.g., sensitivity, specificity, accuracy, or other clinical metrics).

Crucially, this is not an AI/ML device, so questions related to AI performance, such as human reader improvement with AI, standalone algorithm performance, training set details, or ground truth establishment for an AI model, are not applicable.

Here's a breakdown of what can be extracted from the provided text, along with explanations for the unanswerable questions:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not provide specific quantifiable acceptance criteria (e.g., "burst pressure > X psi", "hemostasis valve leakage

Ask a specific question about this device

The Merit Prelude™ Sheath Introducer is intended to provide access and facilitate the percutaneous introduction of various devices into veins and/or arteries while maintaining hemostasis for a variety of diagnostic and therapeutic procedures.

Merit's Prelude consists of a sheath introducer with side port extension and stopcock. The sheath hub includes a hemostasis valve and a suture ring. A 3-way stopcock is affixed to the proximal end of the side port extension. The Prelude assembly includes a vessel dilator that snaps securely into the sheath introducer hub.

The provided document is a 510(k) summary for the Merit Prelude™ Sheath Introducer, submitted by Merit Medical Systems, Inc. This document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving device performance against specific acceptance criteria in the context of AI/ML or diagnostic accuracy.

Therefore, many of the requested sections regarding AI/ML study specifics (e.g., sample size for test sets and training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, data provenance) are not applicable to this type of regulatory submission for a medical device like a sheath introducer.

This 510(k) summary describes bench testing to establish equivalence, not a clinical study involving human readers or AI algorithms for diagnostic purposes.

Here's the information that can be extracted or inferred from the provided text, adapted to the questions:

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

The document does not present a formal table of acceptance criteria with corresponding performance results in the way typically seen for diagnostic accuracy studies or AI/ML evaluations. Instead, it describes comparative testing to demonstrate substantial equivalence to the predicate device.

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

• Test set sample size: Not specified. The testing was "bench testing" of the physical device, not related to patient data or image sets.
• Data provenance: Not applicable. The testing was conducted in-house by Merit Medical Systems, Inc. ("Merit's in-house protocols") in the USA.

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 sheath introducer, not an AI/ML diagnostic tool. Ground truth for its performance would involve engineering specifications, physical measurements, and materials science, not expert medical opinion on diagnostic images.

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

• Not applicable. Adjudication methods are relevant for subjective interpretations, typically in diagnostic imaging or clinical studies. This involved 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

• No MRMC study was done. This is not an AI/ML 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.

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

• The "ground truth" for the performance of the sheath introducer was based on engineering specifications, physical measurements, and comparison to the characteristics of the legally marketed predicate device (Cordis Avanti®+ Catheter Sheath Introducer System). This is a "substantial equivalence" determination based on technical and performance characteristics of similar devices.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device and thus does not have a "training set."

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

• Not applicable. This is not an AI/ML device.

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