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The intended use for the Swabsite Swabbable Valve is to allow access to IV administration sets, medication vials. blood types, and solution bags with one convenient device without the use of needles or blunt cannulas.
The SWABSITE injection port is an IV administration set accessory that allows needleless luer connections to luer access devices (syringes, etc.)

The Swabsite Swabbable Valve is a needle free valve that allows the user to add medication into IV sets without the use of a needle. When the valve is in the closed position it has a flat, smooth surface for cleaning. When the male connector of a syringe or secondary line is pushed into the valve, the silicone stem opens in the middle creating a fluid path. When the male connector is removed from the valve, the body of the valve forces the stem shut and maintains a sealed fluid path. A cap is not required to seal the valve or to maintain sterility.

This document describes a 510(k) premarket notification for the "Swabsite Swabbable Valve." It's a needle-free valve for IV administration, asserting substantial equivalence to a predicate device (Smartsite Access Pin, K970485). The submission focuses on non-clinical data to prove this equivalence.

Here's an analysis of the provided information concerning acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, the submission focuses on demonstrating "substantial equivalence" to a predicate device rather than defining specific quantitative acceptance criteria for performance in the clinical sense (e.g., sensitivity, specificity for a diagnostic device). The acceptance criteria were primarily related to safety and effectiveness, as determined by non-clinical testing data to show equivalence to the predicate.

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

• Sample Size: Not specified in the provided text. The document only mentions "non-clinical performance testing data."
• Data Provenance: Not specified, but given it's non-clinical testing, it would be laboratory-based data, not human patient data.

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

• Number of Experts: Not applicable. This was a non-clinical device performance and safety evaluation. Experts might have designed or overseen the testing, but there's no mention of experts establishing a "ground truth" for a test set in the way one would for, say, image analysis or diagnostic studies.
• Qualifications of Experts: Not applicable for establishing ground truth in this context.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. There was no "test set" requiring adjudication in the context of human interpretation or diagnostic accuracy. The testing was non-clinical.

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

• MRMC Study: No. This was a non-clinical device safety and performance evaluation, not a study involving human readers or diagnostic interpretation.
• Effect Size: Not applicable.

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

• Standalone Study: Yes, in the sense that the device's performance was evaluated independently through non-clinical laboratory testing. There is no "algorithm" here, but the device's physical/mechanical/biological properties were tested directly. The results of these tests (performance, biocompatibility, microbial barrier) were then used to justify substantial equivalence.

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth was based on objective measurements and established standards for device performance, biocompatibility, and microbial barrier integrity as determined through non-clinical laboratory testing. The implicit "ground truth" for substantial equivalence was the performance of the predicate device.

8. Sample Size for the Training Set

• Sample Size: Not applicable. There is no "training set" in the context of this device. This is a physical medical device, not an AI or machine learning algorithm that requires training data.

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

• Ground Truth Establishment: Not applicable, as there is no training set.

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