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The Fresenius APD Luer-Lock Adapter is intended for use with an Automated Peritoneal Dialysis cycler for the exchange of peritoneal dialysis solution. The single-use device is designed to connect any Fresenius cycler set with a Safe-Lock® connector to a peritoneal dialysis solution bag equipped with a standard luer-lock connector.

The Fresenius APD Luer-Lock Adapter, Catalog number 050-95018, is designed to connect a peritoneal dialysis bag equipped with a luer-lock connector to a Fresenius Automated Peritoneal Dialysis (APD) cycler set that uses the Fresenius Safe-Lock® connector (e.g., Liberty® cycler, Newton IQ® cycler).

The provided document is a 510(k) summary for the Fresenius APD Luer-Lock Adapter. It describes the device, its intended use, and indicates that performance testing was conducted to demonstrate substantial equivalence to a predicate device. However, it does not contain specific acceptance criteria, detailed study results, or the methodological details typically associated with studies proving a device meets acceptance criteria, particularly for AI/ML-based medical devices.

The document pertains to a physical medical device (an adapter) and its performance evaluation through standard engineering and biocompatibility tests, not an AI/ML diagnostic or prognostic algorithm. Therefore, many of the requested categories (e.g., sample size for test set, number of experts, MRMC studies, standalone performance, training set details) are not applicable to this type of device and submission.

Here's a breakdown of what can be extracted or inferred from the provided text, and where information is missing or not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: The document states what types of tests were performed but does not provide the specific quantitative acceptance criteria (e.g., minimum tensile strength, maximum leakage rate) or the exact numerical results obtained from these tests. It only reports that the testing "provided a sound basis for comparison" and demonstrated 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)

• Not Applicable / Not Provided for this Device Type: This information is typically relevant for studies evaluating the performance of diagnostic algorithms or imaging devices with clinical data. For a physical adapter, testing involves bench-top engineering tests (e.g., tensile strength, leak tests) and biocompatibility studies, not clinical "test sets" in the sense of patient data. The document does not specify the number of adapters tested for each performance criterion. Data provenance like "country of origin" or "retrospective/prospective" is also not applicable to this type of engineering and biocompatibility testing.

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)

• Not Applicable: This is relevant for AI/ML devices where human expert consensus often establishes ground truth for diagnosis/prognosis. For a physical adapter, "ground truth" is established by adherence to engineering specifications, physical integrity, and biological safety standards, evaluated by laboratory methods and qualified technicians/scientists, not by clinical experts reviewing cases for a diagnosis.

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

• Not Applicable: Adjudication methods are used in clinical studies, particularly for diagnostic accuracy, where disagreements between experts need to be resolved to establish a definitive ground truth. This concept does not apply to the performance testing of a physical medical device like an adapter.

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: MRMC studies are specifically designed to evaluate the performance of diagnostic imaging aids (often AI-powered) by comparing human reader performance with and without the aid. This is entirely irrelevant to an APD Luer-Lock adapter.

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

• Not Applicable: This question pertains to the performance of an AI algorithm in isolation. Since the device is a physical adapter, there is no AI algorithm to evaluate.

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

• Engineering/Physical Standards & Biological Safety Standards: For this device, "ground truth" refers to meeting established engineering specifications for structural integrity (e.g., bond strength, leak-proof nature), functional compatibility (connecting Luer-Lock to Safe-Lock), and adherence to biological safety standards (biocompatibility, sterility, nonpyrogenicity). This is confirmed through laboratory testing against predefined criteria, not clinical outcomes or expert consensus on diagnosis.

8. The sample size for the training set

• Not Applicable: "Training set" refers to data used to train an AI/ML model. This device is a physical adapter and does not involve AI/ML.

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

• Not Applicable: As there is no AI/ML model or training set, this question is not applicable.

Conclusion:

The provided document is a 510(k) summary for a physical medical device (an adapter). The "study" mentioned refers to a series of engineering, biological safety, and functional tests conducted to demonstrate substantial equivalence to a predicate device, as required for 510(k) clearance. The focus of these tests is on the device's physical properties, safety, and functional compatibility.

Many of the questions posed (especially those related to sample sizes for test/training sets, experts, adjudication, MRMC studies, and AI/ML performance) are highly specific to the evaluation of AI/ML-based diagnostic or prognostic medical devices and are not relevant to the type of device and submission described in this document. The document confirms that testing was done and that the device meets equivalence criteria based on those tests, but it does not provide the granular detail of a clinical trial or algorithm validation study.

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