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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.

• Dialysate Temperature Accuracy
• Fluid Removal Accuracy
• Chemical Disinfection
• Heat Disinfection
• Related Alarms |
  | Human Factors/Usability: No negative impact on usability. | Modifications to hydraulics do not impact usability. No new Human Factors validation study deemed necessary. |
  | Clinical Performance: No need for new clinical studies. | No clinical studies were conducted as the changes were deemed not to require them for substantial equivalence. |

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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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 Tablo Hemodialysis System is also indicated for use in the home.

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

• Tablo Console, a single module consisting of multiple fluidic systems that perform the activities of a water purification system (WPS) and a conventional dialysis delivery system (DDS), and
• Table Cartridge

The provided text is a 510(k) premarket notification summary for the Tablo® Hemodialysis System (software version 4.8). This document primarily focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a detailed clinical study for a new device requiring a comprehensive performance evaluation against defined acceptance criteria.

Therefore, the information required to answer your specific questions about acceptance criteria and study details (like sample size, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth types, and training set information for an AI/software device) is not present in this type of FDA submission.

This document describes a software update (version 4.8) to an existing hemodialysis system. The performance data provided is limited to bench testing, biocompatibility, electrical safety, and software verification and validation testing. The software is considered "major" level of concern, and verification and validation were conducted. However, the document does not detail specific acceptance criteria for performance metrics that would be relevant to an AI/ML-driven diagnostic device.

Here's an attempt to answer based on the limited information available in the provided text:

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

The document provides very high-level acceptance criteria for specific non-clinical tests, rather than detailed performance metrics for an AI/ML system.

For an AI/ML device, you would expect detailed performance metrics like sensitivity, specificity, AUC, F1-score, etc., with associated acceptance thresholds for "Pass." This is not present here.

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

This information is not provided in the document as it is not a clinical study on patient data for an AI/ML diagnostic. The software V&V would involve testing against various scenarios and inputs, but the "sample size" in the context of patient data for AI model evaluation is not applicable here.

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 information is not provided. Ground truth establishment by experts is relevant for diagnostic AI/ML systems where human-annotated data is used for evaluation. This document describes a software update for a hemodialysis system, not an AI diagnostic.

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

This information is not provided, as it pertains to expert consensus on ground truth in studies of diagnostic AI/ML systems.

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 MRMC study was conducted or reported. The document explicitly states: "No clinical studies were conducted to support the modified device." MRMC studies are typically performed for diagnostic AI/ML tools to assess their impact on human reader performance.

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

While "Software Verification and Validation Testing" was conducted, the document does not specify standalone algorithm performance in terms of diagnostic metrics. It only states that the testing "passed" and "supports safety and effectiveness." The software's function is to control a hemodialysis system, not to perform a standalone diagnostic task.

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

This information is not provided. Ground truth in the context of this device's software V&V would relate to the correct functional behavior of the system under various conditions, not diagnostic outcomes based on expert consensus, pathology, or outcomes data.

8. The sample size for the training set

This information is not provided. Training set details are relevant for AI/ML model development. This document is about a software update for a medical device's control system, not the development of a predictive AI model.

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

This information is not provided. As above, this is relevant for AI/ML model training, which is not the focus of this 510(k) submission.

In summary: The provided document is an FDA 510(k) clearance letter and summary for a software update to an existing hemodialysis system. It demonstrates substantial equivalence to a predicate device through non-clinical testing and verification/validation of software changes. It does not contain the detailed performance study information, particularly for AI/ML-driven diagnostics, that your questions are designed to elicit. The "acceptance criteria" presented are for general device performance and regulatory compliance, not for algorithmic diagnostic accuracy.

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