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The Tablo® Hemodialysis System and TabloCart™ is indicated for use in patients with acute and/or chronic renal failure, with or without ultration, 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. 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 consists of: Tablo Console and Software, Tablo Cartridge. The TabloCart™ is an optional accessory to the Tablo Hemodialysis System that raises the height of the Tablo console and includes larger wheels that rotate and lock in more functional directions than the Tablo console without a cart, aiding in overall system mobility. When configured with a Prefiltration Drawer, the cart has replaceable, large-capacity cartridge filters (sediment and/or carbon) that serve as "prefilters" to help remove major sediment and chlorine/chloramines from supply water before it enters the Tablo console's water purification system. The cart with prefiltration also includes backflow prevention and a booster pump to transport water from the incoming water supply to the Tablo console. The TabloCart with Prefiltration Drawer consists of: Tablo Cart Wheeled Platform, Fluidics Drawer and Software.

The provided document is an FDA 510(k) Premarket Notification review letter for the Tablo® Hemodialysis System; TabloCart™ with Prefiltration Drawer (K232776). This document primarily focuses on demonstrating substantial equivalence to a predicate device (Tablo Hemodialysis System, K223248) rather than detailing specific acceptance criteria and a study proving the device meets those criteria in the context of device performance metrics (e.g., accuracy, sensitivity, specificity for an AI/algorithm-based device).

The "acceptance criteria" and "study that proves the device meets the acceptance criteria" as requested in the prompt typically refer to a device's performance against predefined metrics (e.g., clinical accuracy, diagnostic performance, or a specific functional output) which are common for AI/algorithm-based devices. However, the Tablo Hemodialysis System and its accessory cart are not an AI/algorithm-based device in the common sense (e.g., for image analysis or disease diagnosis). Instead, it's a medical device for renal replacement therapy, and the 510(k) submission focuses on demonstrating that the new accessory (the cart with prefiltration) does not alter the fundamental safety and effectiveness of the existing, cleared hemodialysis system.

Therefore, many of the specific questions in the prompt (e.g., sample size for test/training sets, number/qualifications of experts, adjudication methods, MRMC studies, standalone performance, type of ground truth) are not applicable to this type of device and submission. The "study" proving acceptance criteria here is primarily a series of bench performance tests, biocompatibility testing, electromagnetic compatibility (EMC) and electrical safety testing, and software verification and validation testing to confirm that the addition of the cart does not negatively impact the established safety and performance of the base hemodialysis system.

Here's an attempt to address the prompt based on the available information, highlighting what is applicable and what is not:

Acceptance Criteria and Study Proving Device Meets Acceptance Criteria for the Tablo® Hemodialysis System with TabloCart™ with Prefiltration Drawer (K232776)

Given that this 510(k) submission is for an accessory cart to an already cleared hemodialysis system, the "acceptance criteria" revolve around demonstrating that the modified device (system with cart) maintains the same safety and effectiveness as the predicate device (system without cart). The "study" is a compilation of various engineering and performance tests rather than a single clinical trial or AI validation study.

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device and submission, the acceptance criteria are largely implied by demonstrating substantial equivalence to the predicate device. They are not typically laid out as quantitative performance metrics (like accuracy or sensitivity) as would be for an AI diagnostic device. Instead, they relate to maintaining fundamental safety, performance, and functionality.

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

• Not applicable in the context of typical AI/algorithm test sets. The "test set" here refers to the physical device and its components undergoing engineering and functional verification.
• Data Provenance: The testing was conducted by the manufacturer, Outset Medical, Inc., presumably in their facilities (San Jose, CA, USA). The studies are prospective in the sense that they were designed and executed specifically to support this 510(k) submission for the modified device.

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

• Not applicable. This is not an AI/diagnostic device where expert consensus defines a "ground truth" for disease states in a dataset. "Ground truth" for this device is based on engineering specifications, physical measurements, chemical analysis (for water purity), and functional performance verification against design requirements. The "experts" involved would be engineers, quality control personnel, and regulatory specialists within Outset Medical, Inc.

4. Adjudication method for the test set:

• Not applicable. Adjudication methods (like 2+1, 3+1) are for resolving discrepancies in expert interpretations of data (e.g., medical images). For engineering tests, results are typically objective measurements or pass/fail criteria based on predefined specifications.

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 is not an AI-assisted diagnostic device, so MRMC studies are irrelevant.

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

• Not applicable. This device is a physical hemodialysis system with an accessory, not a standalone algorithm.

7. The type of ground truth used:

• Engineering Specifications and Physical/Chemical Standards: For example, the ground truth for water quality would be established by relevant water quality standards for hemodialysis (e.g., AAMI standards). For mechanical aspects, it would be the design specifications (dimensions, mobility, filter capacity). For software, it would be the functional requirements and safety standards.

8. The sample size for the training set:

• Not applicable. This refers to machine learning models, which is not what this device is.

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

• Not applicable. See point 8.

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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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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

The provided document is a 510(k) summary for the Tablo® Hemodialysis System, specifically for a new software version. This document focuses on demonstrating substantial equivalence to a predicate device (K211370), rather than a study defining acceptance criteria for AI or a detailed performance study as would be required for a novel AI device.

Therefore, the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of AI performance metrics (like sensitivity, specificity, etc.) is not directly applicable to this document. The document primarily discusses verification and validation of software changes and bench performance testing to support the extension of treatment duration.

However, I can extract the relevant information from the document regarding the device's performance data and the types of studies conducted to support its substantial equivalence.

Here's a breakdown based on the provided text, reinterpreting "acceptance criteria" as the deemed "substantial equivalence" established through various tests:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) for a software update to an existing device, the "acceptance criteria" are implicitly tied to maintaining or improving the safety and effectiveness of the device as cleared under the predicate (K211370) and extending the treatment duration. The "reported device performance" is primarily about the successful completion of various tests to demonstrate this.

Information not directly applicable or available from the provided text, as it relates to AI-specific studies:

2. Sample size 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 as the document describes a 510(k) for a software update to a hemodialysis system, not an AI/ML device with a distinct "test set" in the context of an algorithm's performance. The "test set" would implicitly be the entire system undergoing the verification and validation processes.

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 to the type of device and study described. Ground truth in this context would be defined by engineering specifications, regulatory standards, and established medical safe use practices for hemodialysis machines.

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

• Not applicable, as there's no "ground truth" derived from expert consensus for an AI algorithm's output.

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. This device is a hemodialysis system, not an imaging or diagnostic AI tool. The "Human Factors validation data" mentioned relates to the usability and safety of the system's interface for operators, not to AI-assisted interpretation by human readers.

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

• Standalone performance in the AI sense is not explicitly discussed. The device itself (Tablo Hemodialysis System) performs its function either autonomously or with user interaction, but it's not described as an AI algorithm in the context of image analysis or diagnostic support. The software performance here refers to the operating system controlling the device's functions.

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

• The "ground truth" for the performance of the hemodialysis system software and hardware would be based on engineering specifications, adherence to ISO/IEC standards, regulatory requirements, and safe operational parameters for dialysis treatment. For the extended 24-hour treatment capability, the ground truth would be the ability to maintain specified performance (e.g., fluid removal, solute clearance, alarm responsiveness) over that duration without compromise to safety.

8. The sample size for the training set

• This information is not applicable to a traditional software update for a hemodialysis machine. "Training set" typically refers to data used to train AI/ML models, which is not the subject of this 510(k). Verification and validation are performed against requirements, not a "training set" in the AI sense.

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

• Not applicable, see point 8.

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