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The everlinQ® endoAVF System is indicated for the creation of an arteriovenous fistula (AVF) using the ulnar artery and ulnar vein in patients with minimum artery and yein diameters of 2.0 mm and less than 2.0 mm separation between the artery and vein at the fistula creation site who have chronic kidney disease and need hemodialysis.

The everlinQ® endoAVF System (everlinQ®) consists of two single-use disposable magnetic catheters: a venous catheter and an arterial catheter, both of which are 6 Fr in diameter. The venous catheter contains an electrode for delivery of radiofrequency (RF) energy while the arterial catheter contains a ceramic backstop that serves as a mechanical stop for the electrode. The everlinQ® is used with a commercially available electrosurgical unit (ESU) and electrosurgical pencil.

The EverlinQ® endoAVF system is a percutaneous catheter system indicated for the creation of an arteriovenous fistula (AVF) in the arm of patients with chronic kidney disease who need hemodialysis. The device's performance was evaluated through a pivotal study (NEAT Study) and a supportive Global Analysis, encompassing data from multiple clinical studies and commercial use.

Acceptance Criteria and Reported Device Performance

The primary effectiveness endpoint for the device was the percentage of patients with fistula maturation/usability at 3 months post-procedure. This was defined as an endoAVF that is free of stenosis or thrombosis, with brachial artery flow of at least 500 ml/min and at least 4 mm vein diameter (as measured by duplex ultrasound) OR the patient was dialyzed using 2 needles. The performance goal for this endpoint was set at 57.5%, derived from historical surgical AVF failure rates.

The primary safety endpoint was the percentage of patients who experienced one or more serious study device-related adverse events during the first 3 months following AVF creation, as adjudicated by an independent Clinical Events Committee (CEC). There was no formal hypothesis test associated with this safety endpoint.

Here's a table summarizing the acceptance criteria and reported device performance from the NEAT Study:

Study Details Proving Device Meets Acceptance Criteria

The primary study used to demonstrate the device meets acceptance criteria was the Novel Endovascular Access Trial (NEAT Study), supplemented by a Global Analysis that pooled data from NEAT, FLEX, EU PMCF, and EASE studies, as well as commercial use data (COMM).

2. Sample Size and Data Provenance

• Test Set (Clinical Studies):
  • NEAT Study (Pivotal): 60 "study cohort" subjects and 20 "roll-in" subjects. The primary effectiveness and safety analyses were performed on the 60 study cohort subjects.
  • Global Analysis (Supportive):
    • Pooled Safety Analysis Population: 125 subjects (from NEAT (N=60), FLEX (N=33), EU-PMCF (N=32)).
    • Pooled Effectiveness Analysis Population: 157 subjects (from NEAT (N=60), FLEX (N=33), EU-PMCF (N=32), EASE (N=32)).
    • COMM (Commercial data set): 79 subjects (not included in pooled safety/effectiveness due to data unavailability).
• Data Provenance: The clinical studies were conducted in multiple countries:
  • NEAT: Canada, Australia, and New Zealand.
  • FLEX: Paraguay.
  • EU PMCF: Germany, England.
  • EASE: Paraguay.
  • COMM: England, Germany, Netherlands, Switzerland.
• Retrospective/Prospective: All mentioned clinical studies (FLEX, NEAT, EU PMCF, EASE) were prospective, single-arm, multi-center studies. The commercial use data (COMM) was collected retrospectively from treating physicians.

3. Number of Experts and Qualifications for Ground Truth (Clinical Test Sets)

• Clinical Events Committee (CEC): An independent CEC adjudicated all safety events (Serious Adverse Events and Significant Events).
• Number of Experts: The CEC consisted of three independent physicians.
• Qualifications of Experts: The physicians comprising the CEC had expertise in vascular surgery, interventional nephrology, and/or interventional radiology. Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

• CEC Adjudication: The document states that "All procedural safety data and relevant post-procedure events were adjudicated by an independent CEC." The CEC Charter describes the event definitions and the adjudication process. It also mentions that "Each event was classified with respect to: 1. Relationship to the study device, 2. Relationship to the procedure, 3. Relationship to coil embolization, if used, 4. Relationship to a brachial artery closure device, if used, 5. Whether the event was an Unanticipated Adverse Device Effect, 6. Whether the event met the definition of a Significant Event."
• The exact voting mechanism (e.g., 2+1, 3+1) is not explicitly stated beyond stating it was an "independent CEC." However, given the three-expert composition, it is highly likely that a consensus or majority vote mechanism was used.

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

• No MRMC study was performed. This device is a medical device for creating a fistula, not an AI/imaging diagnostic tool. Therefore, a comparative effectiveness study evaluating human readers' improvement with vs. without AI assistance is not applicable to this submission.

6. Standalone Performance (Algorithm Only)

• Not Applicable. The EverlinQ® system is a physical medical device, not an algorithm or software. The document explicitly states: "The everlinQ® endoAVF System does not contain software." Therefore, standalone algorithm performance was not relevant or assessed.

7. Type of Ground Truth Used (Clinical Test Sets)

The "ground truth" for the clinical effectiveness and safety endpoints was primarily based on:

• Clinical Assessments and Measurements:
  • Duplex Ultrasound: Used for measuring brachial artery flow (ml/min) and vein diameter (mm) for the primary effectiveness endpoint.
  • Direct Observation/Confirmation: Fistulography or duplex ultrasound verification confirmed successful endoAVF creation for procedural success.
  • Clinical Usability: Patient was dialyzed using 2 needles (part of the primary effectiveness endpoint and functional cannulation assessments).
  • Adjudicated Events: Safety events (SAEs, significant events) were adjudicated by the independent CEC based on medical records and definitions.
• Outcome Data: Patency rates (primary, assisted primary, secondary, functional) and CVC exposure were tracked based on clinical outcomes.

8. Sample Size for the Training Set

• Not Applicable/Not Explicitly Defined in this Context. The device is a physical medical device, not an AI/ML model that undergoes "training" on a "training set" in the computational sense. The "training" referred to in the document relates to the training of physicians in the proper use of the device, which occurred after initial study completion and was evaluated in a smaller, subsequent cohort.

9. How Ground Truth for Training Set was Established

• Not Applicable. As noted above, there is no "training set" in the AI/ML sense to establish ground truth for. The "training" in the document refers to physician training on device usage. The impact of this physician training was observed in a small cohort, demonstrating a numerical reduction in SAEs related to brachial artery access. This outcome acted as an observed result rather than a "ground truth" derived for a training dataset.

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The ESU-1 Electrosurgical Generator is used to deliver RF energy via an assortment of surgical devices to cut and coagulate different kinds of tissue.

The ESU-1 Electrosurgical Generator is a high frequency isolated generator that utilizes electrical current via an assortment of surgical devices to cut and coagulate different types of tissue. The ESU-1 Electrosurgical Generator features cutting up to 300 watts with 2 cut modes, including "Cut T", a blend mode with 4 levels, 3 coagulation modes and 4 bipolar modes with Auto Bipolar option. "Cut T" mode is a new feature that includes a timing feature which automatically ceases RF activation after a user selectable period of time that can be altered between 0.1 and 3.0 seconds. The RF activation for Cut T mode is initially pre-set at 2 seconds (Note: if the operator changed these settings, the generator will powerup with the mode and setting in which the operator last activated the generator). The generator offers 2 monopolar headpiece outputs, monopolar foot controlled output, bipolar handpiece output, and bipolar foot controlled output. The generator has a return electrode sensing feature allows the user to use either a split or solid return electrode site. The padsensing feature allows the user to use either a split or solid return electrode.

The device consists of a generator and power cord and is packaged with a User's Guide in a cardboard shipping box with protective foam inserts. The main device components are a front panel containing the power button, wattage selection buttons, LED numeric display, alarm and return electrode indicator lights, and connector ports for accessories, a back panel consisting of footswitch ports, volume controls, a power cord outlet and fuse, and internal components (printed circuit boards, speakers, cabling).

The provided FDA 510(k) summary for the ESU-1 Electrosurgical Generator focuses on demonstrating substantial equivalence to a predicate device (Bovie® IDS-310 Electrosurgical Generator) through engineering and performance testing. It does not describe acceptance criteria or a study proving that the device meets those criteria in the context of clinical efficacy or diagnostic accuracy.

This document outlines a regulatory clearance process based on establishing similarity and safety/performance equivalence to a previously cleared device, rather than a de novo clinical study proving a specific performance benefit or diagnostic criterion.

Therefore, many of the requested categories (like sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size) are not applicable to the information provided in this 510(k) summary.

Here's an analysis of what is available:

1. Table of Acceptance Criteria and Reported Device Performance (as far as discernible from the document):

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

• Not applicable. This summary refers to "bench testing" and "design verification and validation" on the ESU-1 or "devices representative of its design." This is not a clinical study with human subjects, so there is no "test set" in the sense of patient data.

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

• Not applicable. No expert ground truth typical of diagnostic or clinical performance studies is mentioned. The "ground truth" here is compliance with engineering standards and design specifications.

4. Adjudication method for the test set:

• Not applicable. No expert review or adjudication process for a test set is mentioned.

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 pertains to an electrosurgical generator, not an AI-assisted diagnostic or therapeutic device that would involve human readers or AI improvement studies.

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

• Not applicable. This device is an electrosurgical generator; it does not involve algorithms for standalone performance in the context of diagnostic AI. The software for the ESU-1 was "verified and validated based on its moderate level of concern," which refers to software functionality and safety within the device, not a performant algorithm.

7. The type of ground truth used:

• For the performance testing, the "ground truth" seems to be compliance with engineering design specifications and recognized international safety and performance standards (e.g., IEC 60601 series). It also includes demonstrating functional equivalence to the predicate device.

8. The sample size for the training set:

• Not applicable. This document does not describe the development of a machine learning algorithm with a training set. The "bench testing" would involve testing the physical device and its software's adherence to specifications.

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

• Not applicable. As no training set for an AI algorithm is mentioned, this question is not relevant.

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