Search Results

The Diacap Pro Dialyzer is designed for single use in acute and chronic hemodialysis.

The Diacap Pro dialyzer is a polysulfone high flux dialyzer with the surface areas 1.3 sqm, 1.6 sqm, 1.9 sqm. It is designed for single use in acute and chronic hemodialysis. The dialyzer is gamma sterilized, with a non pyrogenic fluid path, and does not contain natural rubber latex.

This document is a 510(k) summary for the Diacap Pro Dialyzer. It focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific acceptance criteria through a study with a defined ground truth, a common practice for AI/ML devices. Therefore, a direct response to your request, specifically sections 1-9 as they apply to AI/ML device studies, cannot be fully provided from the given text.

However, I can extract the relevant performance testing that was done and the comparison to the predicate device to illustrate how equivalence was demonstrated for this medical device, which is a key part of its acceptance for market.

Here's a breakdown based on the information provided:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a 510(k) for a non-AI/ML device, the "acceptance criteria" are generally related to demonstrating substantial equivalence to a predicate device through functional and performance testing, rather than a specific numeric threshold for an AI model's output. The "reported device performance" is a comparison of the proposed device's characteristics and performance to the predicate device.

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

The document mentions "functional and performance testing" and "comparative testing" on "the proposed Diacap Pro dialyzers" and "the proposed and predicate device." It also states "The following in-vitro testing was performed on the proposed device..." and "The following comparative testing was performed on the proposed and predicate device..." and "The following clinical testing was performed on the proposed device..."

However, specific sample sizes for these tests (e.g., number of dialyzers tested for each model) are not explicitly provided in this 510(k) summary. The summary refers to the methods in FDA Guidance and ISO 8637, implying that standard testing protocols were followed, which would include appropriate sample sizes.

Data provenance: Not specified, but likely laboratory testing conducted by the manufacturer or a contracted lab. This is not retrospective or prospective patient data in the context of an AI/ML study, but rather in vitro and in vivo (clinical) testing of the physical device.

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

This concept is not applicable here as this is not an AI/ML device study. Performance is assessed through physical and chemical measurements (e.g., ultrafiltration rate, clearances, pressure drops, hemolysis) and clinical testing, not human expert interpretation of an AI output.

4. Adjudication method for the test set

Not applicable as this is not an AI/ML device study requiring expert adjudication of results.

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. No AI component is described in this device.

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

Not applicable. No AI component is described in this device.

7. The type of ground truth used

For the functional and performance testing, the "ground truth" would be the:

• Physical measurements and chemical analyses: e.g., precisely measured ultrafiltration rates, clearance values, pressure drops, and assessment of hemolysis, according to established scientific and engineering standards (e.g., ISO 8637).
• Clinical data: for in-vivo ultrafiltration coefficient.

This is fundamentally different from a human-labeled ground truth for an AI/ML algorithm.

8. The sample size for the training set

Not applicable. As this is not an AI/ML device, there is no "training set." The device is physically manufactured, not trained.

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

Not applicable. No AI/ML training set.

Ask a specific question about this device