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510(k) Data Aggregation
(28 days)
The ELM PTA Balloon Dilatation Catheter is indicated for use in Percutaneous Transluminal Angioplasty of the femoral, iliac, and the renal arteries and for the treatment of obstructive lesions of native or synthetic arteriovenous dialysis fistulae. This catheter is not for use in coronary arteries.
The ELM is a coaxial PTA Balloon Dilatation Catheter with a distal inflatable balloon. One lumen is used for inflation of the balloon with contrast medium; the other lumen permits the use of a guide wire to facilitate advancement of the catheter to and through the stenosis to be dilated. Two radiopaque marker bands indicate the dilating section of the balloon and aid in the balloon placement. The marker bands also indicate the nominal length of the balloon. The catheter tip is designed to ease entry into the peripheral arteries and to facilitate the crossing of tight stenoses.
The provided text describes a Special 510(k) Summary for the ELM PTA Balloon Dilatation Catheter, focusing on demonstrating substantial equivalence to a previously cleared device (K102645). This type of submission is for modifications to an already cleared device, not for a new device requiring extensive clinical trials for performance validation. Therefore, the study described is primarily focused on design verification and validation testing rather than human clinical trials or AI algorithm performance studies.
Here's the breakdown of the information requested, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of quantitative acceptance criteria with corresponding performance metrics like accuracy, sensitivity, or specificity. Instead, it refers to "design verification and validation testing" performed according to ISO 10993 Part 1 for biocompatibility and a list of specific engineering tests. The "reported device performance" is implicitly that the device met these engineering test criteria, allowing for a substantial equivalence determination.
Acceptance Criteria Category | Reported Device Performance |
---|---|
Biocompatibility (ISO 10993 Part 1) | Devices determined to be biocompatible. |
Balloon burst and compliance | (Implied: Met pre-defined engineering specifications for burst and compliance.) |
Multiple inflation | (Implied: Met pre-defined engineering specifications for multiple inflation cycles.) |
Catheter and packaging inspection | (Implied: Met pre-defined engineering specifications for inspection.) |
Balloon inflation and deflation | (Implied: Met pre-defined engineering specifications for inflation/deflation characteristics.) |
Bond tensile testing | (Implied: Met pre-defined engineering specifications for bond strength.) |
Catheter performance testing | (Implied: Met pre-defined engineering specifications for overall catheter performance.) |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: The document does not specify a distinct "test set" sample size in terms of clinical cases or patient data. The tests performed are described as "non-clinical design verification/validation tests and analyses." These tests typically involve a sample of manufactured devices (e.g., a certain number of catheters for burst testing, or a specific quantity of material for biocompatibility). The exact number of units or samples tested for each engineering parameter is not mentioned.
- Data Provenance: The data provenance is from non-clinical design verification/validation testing conducted by the manufacturer, Creagh Medical, in Ireland. It is not patient or human data, so terms like "retrospective" or "prospective" do not apply in a clinical sense.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
Ground truth as defined by expert consensus or interpretations is not applicable here, as the study is a non-clinical device validation. The "ground truth" for these engineering tests would be established by validated test methods, industry standards (e.g., ISO), and internal specifications, not by human expert interpretation of clinical data. Therefore, no experts in a clinical context were used for this purpose.
4. Adjudication Method for the Test Set
Adjudication methods like "2+1" or "3+1" are relevant for expert review of clinical cases. Since this study involves non-clinical engineering tests, these methods are not applicable. The "adjudication" for these tests would involve comparing test results against pre-defined engineering specifications and acceptance criteria.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC comparative effectiveness study was done. This type of study (comparing human readers with and without AI assistance) is relevant for AI algorithms interpreting medical images, not for evaluating the mechanical performance of a medical device like a balloon catheter.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
A standalone study, implying an AI algorithm's performance, was not conducted. The device in question is a physical medical instrument (a catheter), not a software algorithm.
7. Type of Ground Truth Used
The "ground truth" for the non-clinical engineering tests was based on:
- Engineering Specifications: Internal design requirements and performance limits for the device.
- Industry Standards: Compliance with relevant international standards, such as ISO 10993 Part 1 for biocompatibility.
- Validated Test Methods: Established laboratory procedures for measuring characteristics like burst pressure, tensile strength, and inflation/deflation times.
8. Sample Size for the Training Set
A "training set" as understood in machine learning (used to train an AI algorithm) is not applicable here. The device does not involve an AI algorithm, and the manufacturing process does not typically involve a "training set" of data in this context. The production and testing are based on established engineering principles and quality control.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no training set for an AI algorithm.
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