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The POWERWAND™ Safety Introducer with an Extended Dwell Catheter made of ChronoFlex C® with BioGUARD™ Technology is used to gain access to the vascular system to sample blood and administer fluids intravenously. It may be used for power injection of contrast media up to a rate of 8 ml/sec and at a maximum of 325 psi fluid pressure.

The POWERWAND™ Safety Introducer with an Extended Dwell Catheter made of ChronoFlex C® with BioGUARD™ Technology is an all-in-one preassembled device that combines the functionality of a catheter introducer system with an extended dwell (< 30 days) Intravenous (IV) Catheter. It is intended to provide the clinician with a safe, simple and accelerated approach using the Accelerated Seldinger Technique. The POWERWAND™ is used to gain access to the vascular system to insert the IV Catheter. The IV Catheter may then be left in place for a period of < 30 days and used to sample blood and administer fluids intravenously. It may also be used to power inject contrast media up to a rate of 8 ml/sec and at a maximum of 325 psi fluid pressure. The device incorporates a mechanism that provides passive needle stick safety.

The provided text is a 510(k) summary for a medical device (The POWERWAND™ Safety Introducer with an Extended Dwell Catheter) and focuses on demonstrating substantial equivalence to a predicate device. It is not a study proving the device meets acceptance criteria for a performance evaluation in the way a clinical study or AI/Machine Learning model validation would be described.

Therefore, many of the requested elements (acceptance criteria table, sample sizes, expert qualifications, MRMC studies, standalone performance, training set details, etc.) are not applicable to this type of regulatory submission and information provided.

The document discusses "pre-clinical thrombogenicity tests" to support a labeling claim, but it does not provide the details of these tests in a format that would allow for filling out the requested table or answering questions about sample sizes, adjudication, or ground truth establishment relevant to an AI/ML or diagnostic device performance study.

Here's a breakdown of what can be extracted and what cannot:

Information that can be extracted:

• Type of Study: This is a 510(k) submission primarily focused on demonstrating substantial equivalence to a predicate device, with some pre-clinical testing for a thrombogenicity labeling claim. It is not a clinical trial or AI/ML performance study.
• Sample size for training set: Not applicable (N/A) as this is not an AI/ML device.
• How ground truth for training set was established: N/A as this is not an AI/ML device.

Information that cannot be extracted or is not applicable to this document's content:

1. Table of acceptance criteria and reported device performance: The document states that "A series of pre-clinical thrombogenicity tests were conducted to support a thrombogenicity labeling claim." However, it does not provide specific acceptance criteria values (e.g., "Thrombus formation less than X%") or the quantitative results of these tests. It only states that the device "has shown in vivo to be thromboresistant."
2. Sample sizes used for the test set and the data provenance: The document mentions "72-hour canine jugular vein thromboresistance studies" for the pre-clinical tests, indicating an animal model. However, it does not specify the number of animals or data provenance (e.g., specific country, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. For the pre-clinical thrombogenicity tests, "ground truth" would likely be based on pathological/histological analysis, not expert radiology reads.
4. Adjudication method for the test set: Not applicable.
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 device is not an AI/ML diagnostic or assistive tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the thrombogenicity tests, it implies pathology/histology ("thrombus on the surface of the catheter and thrombus on the wall of the vein"). For the rest of the 510(k), it's a comparison to a predicate device based on device characteristics and indications for use.

In summary, the provided document details a regulatory submission for substantial equivalence of a medical device, including some pre-clinical animal testing for a specific claim. It does not contain the detailed performance data or study design typically associated with validating a diagnostic device or AI/ML product against specific acceptance criteria.

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The POWERWAND® Safety Introducer with an Extended Dwell Catheter is used to gain access to the vascular system to sample blood and administer fluids intravenously. It may be used for power injection of contrast media up to a rate of 8 ml/sec and at a maximum of 325 psi fluid pressure.

The POWERWAND® Safety Introducer with an Extended Dwell Catheter is an all-in-one preassembled intravascular catheter introducer with intravascular catheter that consists of the following principle components: Introducer Needle, Guidewire, Dilator and an Extended Dwell Catheter. It is intended to provide the clinician with a safe, simple and accelerated approach, using the Accelerated Seldinger Technique, to place an in-dwelling intravascular catheter through the skin into the circulatory system. The Extended Dwell Catheter allows for withdrawal of blood and the administration of fluids, including power injection of contrast media. The device also incorporates a mechanism that provides passive needle stick safety.

The provided text describes a 510(k) premarket notification for a medical device called the POWERWAND® Safety Introducer with an Extended Dwell Catheter (3 Fr Model). This device is substantially equivalent to a predicate device and does not involve AI or algorithms, and therefore does not have acceptance criteria or a study design in the context of an AI/ML device.

However, I can extract information related to the device's performance testing to demonstrate its equivalence to the predicate device and satisfaction of product design specifications.

Here's a breakdown of the information that can be extracted, framed as device performance rather than AI acceptance criteria:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a formal "acceptance criteria" table in the AI/ML sense, but it lists various performance tests conducted. For a traditional medical device, these tests are designed to demonstrate that the device meets its design specifications and is safe and effective for its intended use. The Reported Device Performance column would generally indicate that the device passed or met the requirements for each test.

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

• Test Set Sample Size: The document does not specify the exact sample sizes (N) for each individual test conducted. It generically refers to "Prospective testing conducted for the 3 Fr Model POWERWAND®."
• Data Provenance: The document does not indicate the country of origin of the data or whether it was retrospective or prospective in the clinical sense. However, the testing indicated ("Prospective testing conducted for the 3 Fr Model POWERWAND®") implies that the tests were carried out on newly manufactured 3 Fr Model devices (i.e., prospective device testing, not clinical data provenance).

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

• Not Applicable. This is a physical medical device clearance, not an AI/ML device requiring expert ground truth for image interpretation or diagnosis. The "ground truth" for these performance tests is based on engineering specifications and physical measurements.

4. Adjudication Method for the Test Set:

• Not Applicable. As this is not an AI/ML device, there is no need for adjudication of results by multiple experts. Device performance is determined by meeting pre-defined engineering and safety specifications through objective measurements.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

• No, an MRMC study was not done. This type of study is relevant for AI/ML diagnostic devices where human readers' performance is compared with and without AI assistance. This device is an introducer with a catheter; it's a tool for medical procedures, not a diagnostic AI.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

• Not Applicable. This device does not have an algorithm or AI component. Therefore, standalone algorithm performance is not relevant.

7. The Type of Ground Truth Used:

• Engineering Specifications and Physical Measurements. For each test (e.g., strength of union, flow rate, burst pressure), the "ground truth" is established by the documented design specifications and industry standards for medical devices of this type. The device's performance is measured against these objective criteria using calibrated equipment.

8. The Sample Size for the Training Set:

• Not Applicable. This device is not an AI/ML device and therefore does not have a "training set" in the context of machine learning.

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

• Not Applicable. Since there is no training set for an AI/ML model, the concept of establishing ground truth for it is irrelevant for this traditional medical device.

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The POWERWAND® Safety Introducer with an Extended Dwell Catheter is used to gain access to the vascular system to sample blood and administer fluids intravenously. May be used for power injection of contrast media at a rate of 5 ml/sec at up to 300 psi fluid pressure.

The POWERWAND® Safety Introducer with an Extended Dwell Catheter is an all-in-one preassembled intravascular catheter introducer with intravascular catheter that consists of the following basic components: Introducer Needle, Nitinol Guidewire, Dilator and an Extended Dwell Catheter. It is intended to provide the clinician with a safe, simple and accelerated approach, using the Accelerated Seldinger Technique, to place an in-dwelling intravascular catheter through the skin into the circulatory system. The Extended Dwell Catheter allows for withdrawal of blood and the administration of fluids, including power injection of contrast media. The device also incorporates a mechanism that provides passive needle stick safety.

The presented document describes the 510(k) premarket notification for the POWERWAND® Safety Introducer with an Extended Dwell Catheter. This submission is for a modified device with a change in the material of the female Luer hub from Pellathane® (polyurethane) to Makrolon® (polycarbonate). The aim of the submission is to demonstrate substantial equivalence to the predicate device, not to introduce a new AI-powered diagnostic or assistive tool.

Therefore, many of the typical acceptance criteria and study aspects related to AI/ML devices (such as sample size for test/training sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth types) are not applicable to this medical device submission.

Here's an analysis based on the provided text, focusing on the device's performance through engineering verification testing:

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

The document does not explicitly state numerical acceptance criteria for each test. Instead, it describes "performance requirements" and "satisfies requirements of the product design specification," implying that the modified device met pre-defined internal benchmarks based on the predicate device's performance. The reported "performance" is that the device passed these tests and was found to be substantially equivalent to the predicate.

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

• Sample Size: The document does not specify the sample size for any of the performance tests conducted. For device verification testing, sample sizes are typically determined by statistical methods or industry standards.
• Data Provenance: The testing was "prospective" in the sense that it was conducted specifically for this submission to verify the new material. "TABLE 11.1: PROSPECTIVE TESTING OF THE POWERWAND®" indicates the testing was planned and executed for the modified device. The country of origin of the data is not specified, but the submitter is Access Scientific, LLC. (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)

This question is not applicable. The device is a physical medical instrument, and its performance is assessed through engineering and bench testing, not through expert-evaluated clinical data or image interpretation. "Ground truth" in this context refers to the physical properties and performance characteristics measured against established standards or specifications, not expert consensus on medical findings.

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

This question is not applicable. Adjudication methods like 2+1 or 3+1 refer to human expert review processes for clinical data, which were not part of this device's performance testing.

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

This question is not applicable. An MRMC study is relevant to AI/ML-driven diagnostic or assistive devices involving human readers (e.g., radiologists interpreting images). This submission is for a physical medical device (an introducer with a catheter) and does not involve AI or human readers for diagnosis.

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

This question is not applicable. The device is a physical medical instrument and does not involve an algorithm working in "standalone" mode.

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

The "ground truth" for this device's performance is based on established engineering and materials science standards, regulatory requirements (e.g., ISO 10993-1 for biocompatibility), and internal product design specifications derived from the predicate device's performance. It is not based on expert consensus, pathology, or outcomes data in the medical diagnostic sense.

8. The sample size for the training set

This question is not applicable. This is a modified physical medical device, not an AI/ML model that requires a training set.

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

This question is not applicable. As this is not an AI/ML device, there is no training set or associated ground truth in that context.

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