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The K-Shield Winged Collection Set with Multisample Luer Adapter and Antineedle Stick Protector intended use is for the access of peripheral veins for blood collection. The antineedle stick protector is an integral, active safety device intended to minimize accidental needle stick injuries when used to shield the needle.

The K-Shield Small Vein Infusion Set with Antineedle Stick Protector intended use is for the access of peripheral veins for solution infusion. The antineedle stick protector is an integral, active safety device intended to minimize accidental needle stick injuries when used to shield the needle.

The K-Shield Small Vein Infusion Set with Antineedle Stick Protector and the K-Shield Winged Collection Set with Multisample Luer Adapter and Antineedle Stick Protector are sterile, single use devices commonly used to access a patient's veins for blood collection or solution infusion. Both devices are comprised of a needle and wing assembly with tubing and a female luer connector. The Multisample Luer Connector is used to transfer blood from the Winged Collection Set to a vacuum tube. Both devices incorporate an integral antineedle stick protector used to prevent accidental needlestick injuries.

The provided document details a 510(k) premarket notification for a medical device (Kawasumi Laboratories Small Vein Infusion Set with Antineedle Stick Protector and Winged Collection Set with Multisample Luer Adapter and Antineedle Stick Protector). This is for a device modification summary, not an AI/ML device, and therefore the provided document does not contain information typically associated with AI/ML model evaluations such as:

• Acceptance criteria and reported device performance in terms of AI metrics (e.g., sensitivity, specificity, accuracy).
• Sample sizes for test sets in an AI context (e.g., number of images, patient cases).
• Data provenance for AI/ML training/test sets.
• Number and qualifications of experts for ground truth establishment for AI/ML.
• Adjudication methods for AI/ML ground truth.
• Multi-reader multi-case (MRMC) comparative effectiveness studies for AI.
• Standalone performance for an AI algorithm.
• Type of ground truth (beyond product testing results).
• Training set sample size for an AI model.
• How ground truth for a training set was established for an AI model.

Instead, the document focuses on the mechanical and functional performance of a medical device (a winged collection set and small vein infusion set with an antineedle stick protector) and its substantial equivalence to predicate devices.

Based on the provided text, here is an analysis of the acceptance criteria and study for this physical medical device:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document implicitly defines "PASS" as meeting the acceptance criteria for the internal tests. For the simulated use study, the stated "successful" outcome and specific results serve as the performance and meet the implied acceptance criteria.

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

• Test Set: Not explicitly stated as a numerical sample size. The "simulated clinical observations" involved a "simulated use study," but the number of participants or simulated uses is not provided.
• Data Provenance: The tests were "Kawasumi Internal Test" and "Simulated Clinical Observations" conducted by Kawasumi Laboratories, indicating an internal, prospective study environment for the modification assessment. The country of origin for the data is Japan (Kawasumi Laboratories, Inc. is based in Tokyo) for the internal tests, and potentially the US for the simulated use study (Kawasumi Laboratories America, Inc. is in Tampa, FL), though this is not explicitly stated.

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

There were no "experts" in the sense of medical professionals establishing a diagnostic ground truth for an AI/ML model. The "ground truth" here is the physical performance and safety features of the device, assessed through internal engineering tests and a simulated use study. The "ground truth" was established by the test results themselves as outlined in the table above.

4. Adjudication Method for the Test Set

Not applicable as this is not an AI/ML model evaluation requiring expert consensus or adjudication. The internal tests have objective Pass/Fail criteria, and the simulated use study collected observations directly.

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. The study involves a physical medical device and its safety features.

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

Not applicable. This is not an AI/ML algorithm.

7. The Type of Ground Truth Used

The ground truth used was based on:

• Objective measurements and outcomes from internal engineering tests (e.g., verifying wing activation, deactivation, and defeat locking mechanism).
• Direct observation of events during a simulated clinical use study (e.g., absence of needle sticks).
• User feedback collected via questionnaires during the simulated use study.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device, so there is no "training set." The device was modified and then tested.

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

Not applicable, as there is no training set for an AI/ML model. The "ground truth" for the device's design and intended function was established through engineering specifications, previous predicate device performance, and the modifications made.

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