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PureLift GLOW is intended for facial and neck stimulation, treatment of wrinkles, treatment of mild to moderate inflammatory acne, and indicated for over-the-counter cosmetic use.

PureLift GLOW is a hand-held device intended to apply electrical impulses to strategic locations on the face and Light Emitting Diode (LED) technology that is intended for the treatment of wrinkles and mild to moderate inflammatory acne. The PureLift GLOW probes are designed for optimal contact with the LED technology is not intended to come into contact with the user. The device continually alternates between the positive probes and allows the user to adjust the settings for personalized comfort level by pressing the intensity starts at (1) and continues to (10). The LED treatment area is approximately 36.3cm2 and available five levels of blue (465nm) and red (634nm) wavelengths. The device housing is injection molded of biocompatible thermoplastic resin and the probes consist of chrome-plated spheres. The device, powered by a 3.7-volt rechargeable battery, produces low-level current that is transmitted through the two fixed, smooth spherical probes. To turn the device on, the power button is pressed, and a green light illuminates to indicate that the unit is ready for use. Users then follow the instructions for use. The two probes gently glide over the skin to deliver low-level to strategic locations on the face and neck with the use of a conductive gel and the LED light is directed to the treatment area.

The document does not contain information regarding acceptance criteria or a study proving the device meets acceptance criteria. The document is an FDA 510(k) clearance letter for the PureLift GLOW device, which primarily discusses its substantial equivalence to predicate devices based on technological characteristics and intended use.

While the document states that "Clinical testing was not required to support a substantial equivalence determination" (page 6), it does not describe any specific acceptance criteria for performance metrics (such as sensitivity, specificity, or accuracy for medical devices often associated with AI/ML solutions) nor does it provide details of a study demonstrating the device meets such criteria.

The information provided pertains to bench performance testing to ensure safety and electrical performance, and a comparison table highlighting technological aspects with predicate devices. None of these describe acceptance criteria or a study in the context you've requested.

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The Tablo® Hemodialysis System is indicated for use in patients with acute and/or chronic renal failure, with or without ultrafiltration, in an acute or chronic care facility. Treatments must be administered under physician's prescription and observed by a trained individual who is considered competent in the use of the device. The Tablo Hemodialysis System is also indicated for use in the home. Treatment types available include Intermittent Hemodialysis (IHD), Sustained Low Efficiency Dialysis (SLED/ SLEDD), Prolonged Intermittent Renal Replacement Therapy (PIRRT), and Isolated Ultrafiltration.

The Tablo Hemodialysis System is a self-contained hemodialysis system intended for acute and chronic dialysis therapy, with or without ultrafiltration, in an acute, chronic care facility or in the home. The Tablo Hemodialysis System consist of:

1. Tablo Console
2. Tablo Cartridge

This appears to be a 510(k) summary for a medical device (Tablo Hemodialysis System) that has undergone a modification. The document states that the device has been found substantially equivalent to its predicate device (Tablo Hemodialysis System, K223248), specifically due to changes in the hydraulic material.

Crucially, this document is NOT a study report for a novel AI device or a device that required extensive clinical or human factors validation for its primary function. The modifications were related to material changes in the hydraulics, and the FDA determined that these changes did not impact the device's fundamental performance, safety, or effectiveness. Therefore, many of the typical acceptance criteria and study components you've listed for AI/human-in-the-loop devices are not applicable or were explicitly deemed unnecessary in this context.

I will address the questions based on the information provided, explicitly stating when a piece of information is not available or relevant to this specific submission.

Here's an analysis of the provided text in relation to your questions:

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

The document doesn't provide a direct "acceptance criteria" table in the format typically seen for novel device performance or AI algorithms. Instead, the acceptance criteria for this submission revolve around demonstrating substantial equivalence to the predicate device despite the hydraulic material changes. Performance was demonstrated through various non-clinical tests to confirm the new materials didn't negatively impact the established performance of the device.

Since this submission is about material changes validated through bench testing, the "performance" is about maintaining the original specifications rather than achieving a new performance threshold.

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

This document describes bench testing, biocompatibility testing, electrical safety/EMC analysis, and software/human factors assessments for a modification to an existing device. It's not a typical "test set" in the sense of a dataset for an AI algorithm or a patient cohort for a clinical trial.

• Sample Size for Bench Testing/Biocompatibility: The specific sample sizes for each type of bench test (e.g., number of units tested for dialysate temperature accuracy, number of samples for biocompatibility) are not provided in this 510(k) summary. These details would be in the full submission, but not in this public summary.
• Data Provenance: Not applicable in the context of patient data provenance for a test set. The tests described are laboratory-based and engineering assessments.

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 is not applicable. Ground truth, expert consensus, or clinical interpretation by medical experts are not detailed because this submission is about physical/material modificationsvalidated through non-clinical testing, not diagnostic performance or clinical outcomes directly assessed by experts interpreting data.

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

This is not applicable. Adjudication methods are typically used in studies where human readers or interpreters are involved in generating or confirming ground truth, such as in imaging studies. This document concerns engineering and material changes validated through bench 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

No, an MRMC study was not conducted. This submission is for modifications to a hemodialysis system, not an AI-powered diagnostic or assistive tool where human reader performance would be a relevant metric. The document explicitly states "No clinical studies were conducted."

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

Not applicable in the context of an AI algorithm. The device is a hemodialysis system, not an AI algorithm. Its performance is inherent to its mechanical, electrical, and material properties.

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

The "ground truth" in this context refers to the established performance specifications and safety profiles of the predicate device (K223248) and the relevant regulatory standards (e.g., ISO 10993-1, FDA guidance for hemodialysis delivery systems). The studies conducted (bench testing, biocompatibility) aim to demonstrate that the modified device continues to meet these established performance and safety requirements.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. As above, this is not an AI/machine learning device.

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