(27 days)
The AuST Steerable Sheath is intended for the introduction of diagnostic and therapeutic devices into the human vasculature, including but not limited to intracardiac, renal or other peripheral placements. Do not use this device for neural placements.
The modified AuST Steerable Sheath is a single-use percutaneous catheter intended to provide a pathway through which diagnostic and therapeutic devices are introduced in the human vasculature. The catheter is not intended for neural placements.
The modified AuST Steerable Sheath product family consists of a variety of configurations to accommodate different anatomies and/or devices being introduced into the human vasculature. Each of the sheaths in the product family is comprised of a braid-reinforced catheter shaft, bi-directional deflectable segment, radiopaque distal tip, a handle with a 3-way stopcock for flushing and aspiration, and a hemostasis valve to prevent air and fluid leakage.
The provided FDA 510(k) Clearance Letter for the AuST Steerable Sheath (K251051) does not describe an AI/Software as a Medical Device (SaMD). Instead, it describes a physical medical device – a catheter introducer sheath.
Therefore, many of the requested criteria related to AI/SaMD performance studies, such as sample sizes for test/training sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, or standalone algorithm performance, are not applicable to this type of device submission.
The clearance letter focuses on demonstrating substantial equivalence to a predicate physical device through engineering and performance testing rather than clinical effectiveness studies for an AI algorithm.
Here's an analysis based on the information provided for a physical medical device:
Acceptance Criteria and Device Performance for AuST Steerable Sheath (K251051)
Since this is a submission for a physical medical device (catheter introducer) and not an AI/SaMD, the "acceptance criteria" discussed are primarily related to general device safety and performance standards for such devices, demonstrating substantial equivalence to a predicate device. The study design described is engineering and bench testing, not a clinical trial involving patient data or expert interpretation of AI output.
1. Table of Acceptance Criteria and Reported Device Performance
The submission focuses on ensuring the modified device meets established safety and performance benchmarks for catheter introducers and is substantially equivalent to its predicate. The "acceptance criteria" are implied by the successful completion of the listed tests.
| Acceptance Criteria (Implied by Test Type) | Reported Device Performance |
|---|---|
| Sterilization Validation (per ANSI/AAMI/ISO 11135) | Device passed sterilization validaiton. |
| Visual Inspection | Device passed visual inspection. |
| Simulated Use Testing (including compatibility with ancillary devices) | Device passed simulated use testing. |
| Valve Liquid Leak Test | Device passed valve liquid leak test. |
| Tensile Tests | Device passed tensile tests. |
| Sheath and Dilator Dimensional Verification | Device passed dimensional verification. |
| Dilator Removal Force | Device passed dilator removal force test. |
| Biocompatibility (per ISO 10993-1) | All test results met the requirements of ISO 10993-1, demonstrating no adverse biocompatibility risks. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Not explicitly stated. The document mentions "test units representative of finished devices" for engineering tests. For physical device performance testing, sample sizes are typically determined by statistical methods for engineering verification, but specific numbers are not provided in this summary.
- Data Provenance: The data is generated from in-vitro (bench) testing of the manufactured medical device components and finished product, adhering to recognized standards (e.g., ISO, ANSI/AAMI). Since it's a physical device, there's no "country of origin of data" in the sense of patient data, nor is it retrospective or prospective clinical data.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This criterion is not applicable for this physical device. Ground truth, in the context of an AI/SaMD, refers to accurate diagnostic labels or measurements. For a physical device, "ground truth" is typically defined by engineering specifications, validated test methods, and industry standards. No human experts are described as establishing "ground truth" in this context.
4. Adjudication Method for the Test Set
This criterion is not applicable for this physical device. Adjudication methods (e.g., 2+1, 3+1) are common in clinical trials or AI performance evaluations where expert disagreement on ground truth or interpretation needs resolution. For engineering testing, adherence to a test protocol and meeting predefined specifications are the primary "adjudication."
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, an MRMC study was not done. MRMC studies are specific to evaluating the diagnostic performance of imaging systems or AI algorithms, often comparing human readers with and without AI assistance to measure reader improvement (effect size). This is a physical device, and such a study is not relevant.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
No, this is not applicable. This is a physical medical device. "Standalone performance" refers to the performance of an AI algorithm without human input, which is not relevant to a catheter introducer sheath.
7. The Type of Ground Truth Used
The "ground truth" for this physical device is defined by:
- Engineering Specifications: The design parameters and performance characteristics that the device is designed to meet.
- Standard Test Methods: Validated methodologies (e.g., per ISO or AAMI standards) used to assess physical properties and performance (e.g., strength, leak resistance, dimensions, biocompatibility).
- Predicate Device Performance: The modified device is compared to a legally marketed predicate device (AuST Steerable Sheath, K242106), implying that the predicate's established performance serves as a benchmark for substantial equivalence.
8. The Sample Size for the Training Set
This criterion is not applicable. "Training set" refers to data used to train machine learning models. This device is a physical medical device, not an AI or software product.
9. How the Ground Truth for the Training Set Was Established
This criterion is not applicable. As there is no AI component, there is no "training set" or ground truth establishment relevant to machine learning.
§ 870.1340 Catheter introducer.
(a)
Identification. A catheter introducer is a sheath used to facilitate placing a catheter through the skin into a vein or artery.(b)
Classification. Class II (performance standards).