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The Vial2Bag is indicated to serve as a cornecting part between the IV bag and an external IV Line. The Vial2Bag has a built in connector which makes it possible to admix drugs into the infusion solution using a Swabable Valve.

The Vial2Bag is designed to serve as a connecting part between the IV bag and an external IV Line while allowing safe and easy transfer of drugs/diluents from and into an IV bag. The product allows quick transfer of the contents of a syringe or vial into an IV bag. The Vial2Bag is an assembly of three components a spike, a Swabable valve and a twist-off.

The provided text describes the "Vial2Bag" device and its 510(k) submission, confirming its substantial equivalence to predicate devices. However, the document does not contain a detailed study demonstrating quantitative acceptance criteria or specific performance metrics.

Here's an breakdown of the information that can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided text.

The document states: "All finished products are tested and must meet all required release specifications prior to distribution. The array of testing required for release include but are not limited to; Physical testing and visual examination (in-process and finished product)." However, it does not specify what these "required release specifications" or "acceptance criteria" are, nor does it report any quantitative performance data (e.g., flow rate, leak rates, durability metrics, etc.) for the Vial2Bag or the predicate devices.

2. Sample Size Used for the Test Set and Data Provenance

Not available in the provided text.

The document mentions "testing" but does not specify sample sizes for any tests, nor does it describe the origin of any data (e.g., country of origin, retrospective or prospective nature).

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Not applicable.

This information is relevant for studies involving the interpretation of data where a medical expert's judgment forms the ground truth (e.g., image analysis, diagnosis). The Vial2Bag is a medical device for fluid transfer, and its evaluation would typically involve engineering and functional testing rather than expert interpretation for ground truth.

4. Adjudication Method for the Test Set

Not applicable.

As expertise-based ground truth is not relevant for this device, adjudication methods are also not applicable.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a MRMC comparative effectiveness study was not done.

The document focuses on substantial equivalence based on indications for use, design, material, sterility, and packaging compared to predicate devices. It does not describe any study involving human readers or an AI component, nor does it discuss human performance improvement with or without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No, a standalone study was not done.

This device does not have an algorithm or AI component, so a standalone performance study in that context is not relevant.

7. Type of Ground Truth Used

Functional and Safety Testing.

While not explicitly called "ground truth" in the AI/data science sense, the "ground truth" for this device would be established through:

• Physical testing and visual examination: Ensuring the device meets its design specifications, is free from defects, and functions as intended (e.g., no leaks, proper connection, sterile).
• Material compatibility testing: Adherence to ISO 10993-1 and/or USP VI requirements.
• Sterility testing: Ensuring the product is sterile.

These are established standards and laboratory test results, not expert consensus, pathology, or outcomes data in the typical clinical study sense.

8. Sample Size for the Training Set

Not applicable.

A training set is relevant for machine learning algorithms. This device does not involve such algorithms.

9. How the Ground Truth for the Training Set Was Established

Not applicable.

As there is no training set for an algorithm, this question is not relevant.

In summary, the provided submission focuses on establishing substantial equivalence to previously cleared predicate devices for regulatory approval, rather than demonstrating performance against specific quantitative acceptance criteria through a detailed clinical or performance study with reported metrics.

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