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The Micro-Stick® Set is indicated for percutaneous introduction of up to a 0.038 inch guidewire or catheter into the vascular system following a small 21 gauge needle stick. The Micro-Stick® Set is not intended for use in the coronary or cerebral vasculature.

The Micro-Stick® Set is designed to provide dilation of the initial entry point and provide a channel for attaining vascular access. The coaxial introducer consists of an inner dilator within a slightly shorter outer sheath.

The kit contains a 21 gauge introducer needle, a .018" diameter guidewire, and a 4F or 5F coaxial introducer. The coaxial introducer is offered in a standard and stiff version.

The Micro-Stick® Set is packaged sterile.

Here's an analysis of the provided 510(k) summary regarding the acceptance criteria and study proving the device meets them:

No AI/ML device is described in the provided text. The document describes a medical device called the "Micro-Stick® Set," which is an introducer set used for vascular access. The testing performed is in-vitro bench testing to ensure reliable design and performance, not clinical studies involving human readers or AI algorithms.

Therefore, many of the requested sections related to AI/ML device studies (sample sizes for test/training sets, expert ground truth, adjudication methods, MRMC studies, standalone performance, etc.) are not applicable to this document.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes in-vitro bench testing for the Micro-Stick® Set. It states that the device was tested "to assure reliable design and performance in accordance with ISO standards and/or internal procedures." However, specific numerical acceptance criteria or detailed performance results (e.g., exact force at break in Newtons, precise leakage rates) are not provided in this summary. It only lists the types of tests performed and a general conclusion of conformance.

Note: The specific numerical or descriptive acceptance levels for these tests are not detailed in the summary. The summary only confirms that the "devices meet the performance criteria of design verification as specified by ISO standards and test protocols."

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

• Sample Size: Not specified in the document. The testing was in-vitro bench testing, so there isn't a "test set" in the context of patient data.
• Data Provenance: The testing was "in-vitro" and conducted as "bench performance data." This implies laboratory testing of the physical device components, not involving patient data from a specific country or retrospective/prospective collection.

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

Not applicable. This is not an AI/ML device, and the testing was in-vitro bench testing. No human experts were used to establish ground truth for this type of performance evaluation.

4. Adjudication method for the test set

Not applicable. This is not an AI/ML device, and no human readers/experts were involved in assessing the 'ground truth' of the in-vitro performance.

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 does not describe an AI/ML device, nor does it conduct MRMC studies.

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

Not applicable. This document does not describe an AI/ML algorithm.

7. The type of ground truth used

The "ground truth" for the in-vitro tests would be the established ISO standards and internal procedures/specifications for physical device performance (e.g., a specific leakage rate is acceptable, a certain force is required for breakage, a guidewire must pass smoothly). These are engineering and material science metrics, not clinical ground truth like pathology or expert consensus.

8. The sample size for the training set

Not applicable. This document does not describe an AI/ML device, and therefore there is no training set mentioned.

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

Not applicable. There is no training set for an AI/ML device described here.

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The Percutaneous Introducer Set is intended for percutaneous introduction, manipulation, and removal of stimulation leads.

The Percutaneous Introducer Set is a single use device allowing for introduction, manipulation, and removal of stimulation leads after percutaneous entry is gained with a needle. The sheath is made of HDPE (High Density Polyethylene) with a HDPE hub. It is slightly tapered at the distal end to make a smooth transition to the dilator. The dilator is made of 304 stainless steel tubing tapered at the distal end for smooth insertion. It has a molded HDPE hub. The guidewire directional guide is made of 304 stainless steel wire with radiuses at each end. It has depth markings etched into the surface along the distal end.

This document, K013120, is a 510(k) summary for a Percutaneous Introducer Set. The device is intended for the introduction, manipulation, and removal of stimulation leads.

The document indicates that the device's substantial equivalence is based on its similarity to a predicate device, the MedAmicus Epidural Introducer (K994097), in terms of intended use, basic design, manufacturing methods, and materials.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document
does NOT list specific acceptance criteria with quantifiable metrics, nor does it provide a detailed table of reported device performance against such criteria.

Instead, it offers a general statement: "Performance data indicates that the Percutaneous Introducer Set meets the functional requirements and specifications for this device."

To infer potential "acceptance criteria" based on the provided information, we can consider the aspects of similarity to the predicate device and relevant material properties:

2. Sample Size Used for the Test Set and Data Provenance

The document does not provide information on a specific "test set" with a defined sample size or data provenance (e.g., country of origin, retrospective or prospective). The submission relies on establishing substantial equivalence to a predicate device, and the "performance data" mentioned is a general statement, not a detailed study report.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not provided in the document. The submission focuses on device equivalence rather than a study requiring expert-established ground truth for a test set.

4. Adjudication Method

This information is not provided in the document. As no specific test set or expert ground truth establishment is described, neither is an adjudication method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

A MRMC comparative effectiveness study was not performed or reported in this 510(k) submission. The document aims for substantial equivalence based on physical and functional characteristics, not on the impact of the device on human readers' performance with or without AI assistance.

6. Standalone Performance Study

A standalone (algorithm-only without human-in-the-loop performance) study was not performed or reported in this 510(k) submission. This is a medical device, not an AI/algorithm-based diagnostic tool. The "performance data" mentioned is a general statement about meeting functional requirements.

7. Type of Ground Truth Used

The concept of "ground truth" as typically used in the context of diagnostic performance studies (e.g., expert consensus, pathology, outcomes data) does not apply directly to this 510(k) submission. The "truth" for this submission is based on the demonstration of substantial equivalence to a legally marketed predicate device and the "identicality" of materials to those previously approved.

8. Sample Size for the Training Set

This information is not applicable and therefore not provided. This is not an AI/machine learning device that requires a training set.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable and therefore not provided. As there is no training set for an AI/machine learning model, there is no ground truth establishment for such a set.

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