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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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