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The Upstream GoBack Crossing Catheter is intended to be used in conjunction with steerable guidewires to access discrete regions of the peripheral vasculature. It may be used to facilitate placement and exchange of guidewires. The Upstream GoBack Crossing Catheter is not intended for use in the coronary, cerebral or carotid vasculature.

The Upstream GoBack Crossing Catheter is a sterile, single-use, single lumen crossing catheter. The Upstream GoBack Crossing Catheter is intended for use with 0.014" coated or noncoated guidewires. The effective length of the GoBack Crossing Catheter is 80 cm or 120 cm with an outer diameter of either 0.96 mm (2.9 Fr) or 1.4 mm. (4.0 Fr). The GoBack Crossing Catheter is made from three lavers; a reinforced polyimide shaft with stainless steel distal tip (in the 2.9 Fr device) or stainless steel and Nylon 12 distal tip (in the 4.0 Fr device), nitinol hypotube, and PTFE polymer sleeve over the nitinol hypotube inside the shaft. The nitinol hypotube has a pre-shaped curved lancet tip at the distal end and a hub at the proximal end for guidewire access. The nitinol tube / needle can move at limited displacement inside the shaft by moving a sliding knob in the catheter handle. The nitinol tube (with the PTFE sleeve) and the polyimide shaft may rotate together using a rotation knob on the catheter handle.

The provided text describes a 510(k) premarket notification for a medical device called the "Upstream GoBack Crossing Catheter." This document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study proving the device meets specific acceptance criteria for a novel AI or diagnostic algorithm.

Therefore, the information required to answer the prompt (acceptance criteria, specific performance metrics, sample sizes for test and training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for AI/diagnostic algorithms) is not present in the provided text.

The text details the following regarding performance testing and a clinical study, but these are geared towards demonstrating equivalence, not proving a device meets a pre-defined acceptance criterion for an AI/diagnostic system:

Performance Testing Summary (Non-Clinical):

• Biocompatibility Testing: Performed per ISO 10993-1:2018 and FDA guidance, including cytotoxicity, sensitization, irritation/intracutaneous reactivity, systemic toxicity (acute), hemocompatibility (hemolysis, complement activation and thromboresistance), LAL, and Material Mediated pyrogenicity.
• Device Dimensional and Functional Testing:
  • Performed on sterile 2.9 Fr and 4 Fr models: Particulates, Torque (at break and transfer), Force at break, Delivery, Radio-opacity, Surface, Needle tip protrusion, Catheter dimensions.
  • Performed on a sterile 2.9 Fr model: Air leakage, Liquid leakage, Force at break, Radio-opaque, RO marker movement, Bend to kink, Needle penetration, Transfer torsional forces.
• Other Performance Testing:
  • Demonstrated no coating abrasion or peeling when polymer-coated guidewires were passed through the catheter.
  • Established a 2-year shelf life.

Clinical Testing Summary:

• Study Design: Retrospective data.
• Sample Size: 151 patients.
• Data Provenance: Not specified (e.g., country of origin).
• Purpose: Demonstrated that the GoBack Crossing Catheter performed equivalently to the predicate in subintimal re-entry procedures. It also validated that the device can be used for both intraluminal lesion crossing and subintimal re-entry.
• Reported Performance:
  • Intraluminal crossing (62 subjects): Technical success rate of 88.7%.
  • Subintimal re-entry crossing (89 subjects): Technical success rate of 88.8%.
  • Major Adverse Event (MAE) rate across all procedures: 0%.
• Ground Truth: Implied clinical outcomes/procedural success, but not explicitly defined with expert consensus, pathology, or adjudication.
• Experts/Adjudication: Not mentioned.
• MRMC Study: Not applicable/not performed for this type of device submission.
• Standalone Performance: Not applicable/not performed.
• Training Set: Not applicable, as this is a medical device, not an algorithm requiring a training set.

In summary, the provided document does not contain the information required to populate the fields of the request, as it pertains to a traditional medical device (catheter) rather than an AI/diagnostic algorithm.

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The Upstream GoBack Crossing Catheter is intended to be used in conjunction with steerable guidewires to access discrete regions of the peripheral vasculature. It may be used to facilitate placement and exchange of guidewires.

The Upstream GoBack Crossing Catheter is not intended for use in the coronary, cerebral or carotid vasculature.

The Upstream GoBack Crossing Catheter is a sterile, single lumen support catheter, that consists of a reinforced polyimide shaft with a stainless steel tip, and PTFE polymer coated nitinol hypotube inside the shaft. The nitinol tube has a pre-shaped lancet tip at the distal end and a hub at the proximal end for guidewire access. The nitinol tube can move at limited displacement inside the shaft, by moving a sliding knob in the catheter handle.

The Upstream GoBack Crossing Catheter is intended for use with 0.014" and 0.018" non-coated quidewires and the effective length of the catheter is 120 cm with an outer diameter of 1.4 mm.

The medical device described in the document is the Upstream GoBack Crossing Catheter.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document details various performance tests conducted on the Upstream GoBack Crossing Catheter. The "acceptance criteria" for these non-clinical tests are generally implied to be that the device "functioned as intended" and "meets its intended design and performance specifications." For the clinical study, the acceptance criteria are clearly defined as primary safety and effectiveness endpoints.

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

• Sample Size for Clinical Test Set: 25 subjects.
• Data Provenance: Retrospective evaluation of clinical cases.
• Country of Origin: Leipzig University Medical Center and Bad-Krozingen Heart-Center, both in Germany.

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

The document mentions that the primary effectiveness endpoint (placement of a guidewire in the true lumen distal to a CTO) was "confirmed by the angiography core lab." It does not specify the number of experts, nor their specific qualifications (e.g., "radiologist with 10 years of experience"). However, the term "core lab" implies a specialized group responsible for blinded and standardized evaluation.

4. Adjudication Method for the Test Set

The document does not explicitly state an adjudication method (like 2+1, 3+1). It states that the effectiveness endpoint was "confirmed by the angiography core lab," suggesting a standard review process by the lab, but the specifics of how discrepancies among reviewers (if any) were handled are not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance.

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted. This device is a physical medical device (a catheter), not an AI-powered diagnostic or assistive tool. Therefore, the concept of human readers improving with AI assistance does not apply here.

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

No, a standalone algorithm performance test was not done. As mentioned, this is a physical medical device.

7. The Type of Ground Truth Used

For the clinical study:

• Technical Success (Effectiveness): Angiography core lab confirmation.
• Safety (MAEs): Clinical observation and assessment by medical professionals during and 24 hours post-procedure; likely based on standard clinical diagnostic criteria for adverse events.

8. The Sample Size for the Training Set

The document describes a retrospective clinical evaluation to support substantial equivalence. This is not a study to train an algorithm. Therefore, there is no training set used in the context of an AI/algorithm study. The 25 subjects were part of the clinical test set designed to evaluate the physical device's performance.

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

As there was no training set for an algorithm, this question is not applicable.

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The speX Support Catheter is intended to be used in conjunction with steerable guidewires to access discreet regions of the peripheral vasculature. It may be used to facilitate placement and other interventional devices and provide a conduit for the delivery of saline solutions or diagnostic/therapeutic agents.

The speX Support Catheter is a device intended to provide additional support to a steerable guidewire when accessing discrete regions of the peripheral and/or coronary vasculature. The device consists of a support catheter body with a luer end. The through-lumen of the device can serve as a conduit for the delivery of diagnostic and therapeutic agents.

The provided document is a 510(k) summary for the speX Support Catheter, a medical device. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving that an AI-driven device meets specific acceptance criteria.

As such, the information requested in the prompt, which is typically relevant for AI/ML medical devices, is largely absent from this document. The document describes a physical medical device (a support catheter), and the "performance data" refers to physical and mechanical tests of the catheter, not the performance of an algorithm.

Therefore, I cannot provide most of the requested information based on the provided text.

Here is what I can extract:

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

Based on the document, specific numerical acceptance criteria and reported device performance are not explicitly detailed in a table format. The document states:

• "The modified speX Support Catheter met all specified criteria and did not raise new safety or performance questions."
• "Based on the performance testing the modified speX Support Catheter was found to be substantially equivalent to the predicate device."

The types of tests performed were:

• Simulated Use Testing
• Component/Assembly Integrity Testing
• Corrosion Resistance Testing
• Lubricity Testing

2. Sample sized used for the test set and the data provenance:

• This information is not available in the provided text, as the study involves physical device testing, not AI data analysis.

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

• This information is not applicable/not available, as the study pertains to physical device performance and not diagnostic or interpretive tasks requiring expert ground truth in the context of AI.

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

• This information is not applicable/not available for this type of physical device 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 information is not applicable. This document describes a physical medical device, not an AI system that assists human readers.

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

• This information is not applicable. This document describes a physical medical device, not an algorithm.

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

• This information is not applicable. For physical device testing, "ground truth" would typically refer to established engineering specifications, mechanical properties, and functional requirements, as opposed to medical diagnoses.

8. The sample size for the training set:

• This information is not applicable/not available as this is a physical medical device, not an AI model requiring a training set.

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

• This information is not applicable/not available as this is a physical medical device, not an AI model.

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The Wingman 18 Crossing Catheter is intended to be used in conjunction with steerable guidewires to access discreet regions of the peripheral and/or coronary vasculature. It may be used to facilitate placement and exchange of guidewires and other interventional devices and provide a conduit for the delivery of saline solutions or diagnostic agents.

The Wingman 18 Crossing Catheter is a device intended to provide additional support to a steerable guidewire when accessing discrete regions of the peripheral and coronary vasculature.

The device consists of a support catheter, with a concealed radiopaque beveled guide-tip, and activating handle. The through-lumen of the device can serve as a conduit for the delivery of diagnostic and therapeutic agents.

This document is a 510(k) Premarket Notification from the FDA regarding the "Wingman 18 Crossing Catheter." It focuses on demonstrating substantial equivalence to predicate devices, not on proving new clinical effectiveness or safety in a comprehensive standalone study like an AI algorithm would require.

Therefore, many of the requested elements for describing the acceptance criteria and the study that proves the device meets them (especially those pertaining to AI algorithms, clinical trials with human readers, and detailed ground truth establishment) are not applicable to this type of medical device submission.

Here's an attempt to answer the questions based on the provided document, highlighting where information is not available or not relevant to a 510(k) for a physical medical device like a catheter:

Acceptance Criteria and Device Performance for Wingman 18 Crossing Catheter (K160848)

As this is a 510(k) submission for a physical medical device (catheter) and not an AI algorithm, the "acceptance criteria" discussed are primarily related to demonstrating substantial equivalence to legally marketed predicate devices through engineering and performance testing, rather than complex clinical outcomes or AI performance metrics.

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

The document states:
"The Wingman 18 Crossing Catheter met all specified criteria and did not raise new safety or performance questions."
"Based on the performance testing the Wingman 18 Crossing Catheter was found to be equivalent to the predicate device."
"The design testing performed for the Wingman 18 Crossing Catheter demonstrated that the performance of the device is equal to the legally marketed predicate devices."

However, the specific quantitative acceptance criteria and detailed reported performance metrics are not provided in this summary document. Typically, these would be detailed in the full submission, but only the types of performance data are listed.

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

The document does not specify the sample sizes for the "Particulate Characterization," "Simulated Use," or "Predicate Device Comparison Evaluation."

Regarding data provenance: These are likely laboratory/engineering tests performed by the manufacturer, Reflow Medical, Inc., in the United States, as the company is based in San Clemente, California. The studies are prospective in the sense that they are conducted specifically to support this regulatory submission, testing the device under controlled conditions. This is not clinical data provenance in the sense of patient cohorts.

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

This concept is not applicable to this type of device submission. "Ground truth" established by experts (e.g., radiologists, pathologists) is relevant for diagnostic devices or AI algorithms that interpret medical images/data. For a physical device like a catheter, performance is evaluated through engineering bench testing and simulated use, not through expert interpretation of clinical "truths."

4. Adjudication method for the test set

This concept is not applicable. Adjudication methods (like 2+1, 3+1) are used in clinical trials, especially for medical imaging or AI studies, where human expert disagreement on interpretation needs a defined resolution process. For physical device performance testing, predefined engineering specifications and measurement techniques are used.

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, an MRMC comparative effectiveness study was not conducted and is not applicable for this device. This type of study is specifically designed for diagnostic aids, particularly AI algorithms, to measure their impact on human reader performance. The Wingman 18 Crossing Catheter is a physical interventional tool, not a diagnostic aid or AI.

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

No, a standalone algorithm performance study was not done and is not applicable. This device is a physical catheter, not an algorithm.

7. The type of ground truth used

The "ground truth" for this device's performance relies on pre-defined engineering specifications, material properties, and functional benchmarks established through testing and comparison with predicate devices. This involves:

• Engineering specifications: Meeting dimensions, material strength, radiopacity, and other design parameters.
• Performance metrics: Demonstrating successful navigation, guidewire support, fluid delivery capability, and resistance to kinking or damage during simulated use.
• Predicate device equivalence: Showing that its performance is comparable to an established, legally marketed device for the same intended use.

It is not based on expert consensus, pathology, or clinical outcomes data in the way an AI diagnostic device would be.

8. The sample size for the training set

This concept is not applicable. "Training set" refers to data used to train machine learning models. This device is a physical product, not an AI, so there is no training set.

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

This concept is not applicable as there is no training set for this physical device.

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