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Flexiva Pulse and Flexiva Pulse TracTip laser fibers are intended to be used as a device that transmits Ho: YAG laser energy from cleared laser consoles to urological anatomy. Flexiva Pulse and Flexiva Pulse TracTip laser fibers are indicated for urologic applications for which the laser systems are cleared, limited to endoscopic procedures involving vaporization, ablation, hemostasis, coagulation, excision, incision of soft tissue, and lithotripsy of urinary calculi. The fiber is designed for use with a standard SMA-905 connector and has been cleared for surgical use.

Flexiva Pulse ID and Flexiva Pulse ID TracTip laser fibers are intended to be used as a device that transmits Ho:YAG laser energy from cleared laser consoles to urological anatomy. Flexiva Pulse ID and Flexiva Pulse ID TracTip laser fibers are indicated for urologic applications for which the laser systems are cleared, limited to endoscopic procedures involving vaporization, ablation, hemostasis, coagulation, excision, resection, incision of soft tissue, and lithotripsy of urinary calculi. The fiber is designed for use with a standard SMA-905 connector and has been cleared for surgical use.

The Flexiva Pulse Laser Fiber, Flexiva Pulse TracTip Laser Fiber, Flexiva Pulse ID Laser Fiber, and Flexiva Pulse ID TracTip Laser Fiber are fiber optic laser energy delivery devices consisting of a SMA connector (Black Hole design), and an ETFE jacketed silica core fiber. The Flexiva Pulse and Flexiva Pulse ID fibers are equipped with a polished, flat output tip (242um, 365um, 550um and 910um size) and the Flexiva Pulse TracTip and Flexiva Pulse ID TracTip fibers are equipped with a polished and reinforced ball-shaped output tip (242um size).

For the Flexiva Pulse ID and the Flexiva Pulse ID TracTip laser fibers, an RFID (radio-frequency identification) tag enables read/write data storage for compatible RFID-equipped laser systems (closed systems).

The provided document is a 510(k) summary for the Flexiva Pulse Laser Fibers. It describes the device, its intended use, and how it demonstrates substantial equivalence to predicate devices. However, this document does not contain a formal study that establishes specific acceptance criteria and then proves the device meets those criteria for the performance of the device in a clinical or simulated clinical setting. Instead, it focuses on demonstrating that the new device is as safe and effective as pre-existing, legally marketed predicate devices through a comparison of technological characteristics and extensive bench testing.

Therefore, it's not possible to populate the requested table and answer many of the specific questions about a "study that proves the device meets the acceptance criteria" in the way one might for a novel AI/software medical device or a device requiring clinical performance validation against specific endpoints.

Here's an attempt to address the request based only on the information provided in the given text, highlighting where information is absent:

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

The document does not explicitly state acceptance criteria in a quantitative format for clinical performance or sensitivity/specificity typical of diagnostic studies. Instead, the acceptance criteria are implicitly that the new device performs at least as well as, or equivalently to, the predicate devices in various bench tests and meets biocompatibility standards.

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 for test set: Not explicitly stated for each bench test. The testing involved "samples aged at T=0 and T=3 year accelerated aging," but the number of samples for each test is not provided.
• Data provenance: Bench evaluations conducted by Boston Scientific. The country of origin and whether it's retrospective or prospective are not applicable in the context of bench testing.

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)

• Not applicable as this is a device clearance based on substantial equivalence through bench testing, not a study evaluating human interpretation or a diagnostic algorithm against expert-established ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) 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

• No, an MRMC comparative effectiveness study was not done. This device is a laser fiber for surgical use, not an AI/software diagnostic device.

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

• Not applicable. This is a physical medical device (laser fiber), not an algorithm.

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

• The "ground truth" for this submission are the established engineering and safety standards (e.g., ISO 10993-1, IEC 60601-1) and the performance characteristics of the predicate devices. The tests were designed to confirm that the new device meets these standards and performs comparably to or better than the predicate.

8. The sample size for the training set

• Not applicable. This is a physical medical device, not a machine learning model requiring a training set.

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

• Not applicable.

Summary of why information is missing:

This document is a 510(k) summary for a physical medical device (laser fiber), not a software or AI-based diagnostic device. The clearance is based on demonstrating "substantial equivalence" to legally marketed predicate devices. This typically involves:

• Comparing the intended use and technological characteristics.
• Conducting extensive bench testing to ensure the new device meets safety and performance standards and performs comparably to the predicate.
• Confirming biocompatibility.

Therefore, the study described is a series of engineering and material performance tests, not a clinical trial or a diagnostic performance study, which would involve concepts like sample size for test/training sets, experts for ground truth, MRMC studies, or standalone algorithm performance.

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