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The Clearum™ HS 17 is intended for use in acute or chronic renal failure patients requiring hemodialysis

The Clearum™ HS 17 dialyzer is consisting of a cylindrical polypropylene body containing a bundle of microporous hollow fibers made of polyethersulfone (PES) secured to the ends by means of hot-melt polyurethane resin.
The modifed Clearum™ HS 17 dialyzer is substantially equivalent to the predicate Clearum™ HS 17 dialyzer manufactured by Bellco (K193542, cleared on October 8, 2020).
The device is characterized by a membrane surface area equivalent to 1.7 m², and by an outer housing total height of 306 mm and a maximum outside diameter of 44 mm.
ldentical to the predicate Clearum™ HS 17, blood and dialysate flow in a countercurrent in their respective compartments. In this process, toxins and fluid are transferred across the semipermeable membrane from the blood to the dialysate compartment.
The dialyzers are sterilized using moist heat with saturated steam, have a non-pyrogenic fluid path, and are labeled for single use.

The provided text describes a 510(k) premarket notification for a medical device called Clearum™ HS 17, a high permeability hemodialysis system. The submission seeks to demonstrate substantial equivalence to a predicate device (also Clearum™ HS 17, K193542) despite a minor modification in fiber undulation amplitude and effective fiber length.

This document does not contain information about an AI/ML-based medical device or a study involving human readers and AI assistance. Therefore, it is impossible to extract the requested information regarding acceptance criteria and a study proving the device meets those criteria for an AI/ML context.

The document focuses on the equivalence of a physical medical device (a dialyzer) based on in-vitro test results. The "study" referenced is a series of non-clinical, in-vitro tests comparing the modified device to its predicate.

To directly address your request as if it were for an AI/ML device, I would need a different source document. However, based solely on the provided text, I can only report on the non-AI/ML aspects related to the Clearum™ HS 17 dialyzer.

Here's a breakdown of what can be extracted, framed within the closest possible interpretation of your request for this non-AI/ML device:

Acceptance Criteria and Device Performance (for a physical hemodialyzer)

The document states that "The modified Clearum™ HS 17 has the same fundamental technological characteristics, principles of operation and control mechanisms as the predicate device." The acceptance criterion, implicitly, is that the modified device performs comparably to the predicate device in key in-vitro performance metrics, demonstrating substantial equivalence and not raising new safety or effectiveness concerns.

Study Details (for a physical hemodialyzer)

• 1. A table of acceptance criteria and the reported device performance: (See table above)

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

  • Sample Size: Not explicitly stated for each test, but in-vitro testing was conducted on "both the modified and predicate Clearum™ HS 17 for comparative purpose." This implies multiple units were tested to generate the reported performance data. Specific numbers of dialyzers tested for each metric are not provided.
  • Data Provenance: The tests were conducted internally by Bellco S.r.l. or a contracted lab. The country of origin is Bellco S.r.l. in Mirandola (MO), Italy. The data is from in-vitro testing, not retrospective or prospective human clinical data.

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

  • This question is not applicable as the "ground truth" for a physical device's performance is established by standardized in-vitro measurements, not expert consensus or human reading. The "experts" would be the scientists and engineers conducting and interpreting the physical and chemical tests, presumably adhering to ISO standards.

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

  • Not applicable. This concept applies to human interpretation or algorithm output, not to objective physical measurements of a device.

• 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/ML device. No MRMC study was performed.

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

  • Not applicable. This is not an AI/ML device, so there is no algorithm to evaluate in standalone mode.

• 7. The type of ground truth used:

  • In-vitro performance metrics: The "ground truth" for this device's performance is derived from objective physical and chemical measurements (e.g., clearance rates, ultrafiltration coefficients, pressure drops) performed in controlled laboratory settings according to established scientific and engineering principles and international standards (ISO 8637-1:2017).

• 8. The sample size for the training set:

  • Not applicable. This is not an AI/ML device, so there is no training set in the context of machine learning. The device design and manufacturing process are based on engineering principles and material science.

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

  • Not applicable. As above, there's no training set for an AI/ML model.

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