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The Medline Sure-Snap Safety Syringe is intended for use in the aspiration and injection of fluids for medical purposes. After withdrawal of the needle from the body, the attached needle safety shield can be manually activated to cover the needle immediately after use to minimize risk of accidental needle stick.

The Medline Sure-Snap Safety Needle is intended for use with a luer-lock syringe for aspiration and injection of fluids for medical purposes. After withdrawal of the needle from the body, the attached needle safety shield can be manually activated to cover the needle immediately after use to minimize risk of accidental needle stick.

The Medline Sure-Snap Safety Needle and Medline Sure-Snap Safety Syringe comprises hypodermic single lumen luer-lock safety needles alone (Identified in this submission as Medline Sure-Snap Safety Needles) and a combination of hypodermic single lumen luer-lock safety needles with luer-lock piston syringes (identified in this submission as Medline Sure-Snap Safety Syringes).

The provided text describes a 510(k) premarket notification for the Medline Sure-Snap Safety Needle and Medline Sure-Snap Safety Syringe. This type of submission aims to demonstrate substantial equivalence to legally marketed predicate devices, rather than proving the device meets specific acceptance criteria through a clinical efficacy study. Therefore, much of the requested information regarding clinical study design (sample size, expert ground truth, MRMC studies, training set details) is not applicable or explicitly stated in this document because the regulatory pathway chosen focuses on device characteristics and bench testing.

However, based on the document, here's what can be extracted regarding acceptance criteria and the study performed, focusing on the "Performance Testing (Bench)" and "Usability Testing" sections as these are the closest to performance evaluation.

Acceptance Criteria and Device Performance (Summary based on available information)

The primary "acceptance criteria" from a regulatory perspective for this 510(k) submission is to demonstrate substantial equivalence to predicate devices. This is achieved by showing that the new device has the same intended use, similar technological characteristics, and that any differences do not raise new questions of safety or effectiveness. Performance is evaluated through a series of bench tests and a simulated clinical use study as recommended by FDA guidance.

Table of Acceptance Criteria and Reported Device Performance

Since this is a 510(k) submission based on substantial equivalence and non-clinical testing, explicit numerical "acceptance criteria" and "reported device performance" are presented as compliance with established standards and successful outcomes of specific tests, rather than clinical efficacy metrics.

Study Details

1. Sample sizes used for the test set and the data provenance:

   • Test Set (Simulated Clinical Use Study for Sharps Injury Prevention): 1,000 safety needles were tested (500 per "safety needle type" – though the document details multiple configurations, it doesn't specify if "safety needle type" refers to Sure-Snap Safety Needle vs. Sure-Snap Safety Syringe types or different gauge sizes).
   • Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. Given it's a 510(k) submission, the studies would typically be conducted prospectively as part of the premarket submission process, and are likely to be conducted under a quality system by the manufacturer (Medline Industries, Inc. in Northfield, Illinois, USA).

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

   • For the simulated clinical use study (usability testing), "Participating healthcare professionals assessed the function of the safety needle with a pass/fail criteria and provided feedback." The specific number of professionals or their detailed qualifications (e.g., years of experience, specific role like nurse, phlebotomist) are not specified in the document.

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

   • The document implies a direct "pass/fail criteria" assessed by the participating healthcare professionals during the simulated clinical use study. It does not mention any formal adjudication method (like 2+1 or 3+1 consensus) for the results, suggesting a direct observation of the device's functional activation.

4. 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:

   • No. This is a medical device (syringe and needle) and not an AI/imaging device. Therefore, an MRMC comparative effectiveness study is not applicable and was not conducted.

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

   • Not applicable. This device is a physical medical instrument, not an algorithm. Bench tests evaluate the physical properties and functional aspects of the device itself (e.g., needle sharpness, sheath activation), which could be considered a form of "standalone" performance testing for a physical object.

6. The type of ground truth used (expert concensus, pathology, outcomes data, etc):

   • For the simulated clinical use study, the "ground truth" for the device's safety feature activation was based on direct observation of its functional activation against pre-defined pass/fail criteria by "participating healthcare professionals." It's a performance truth based on observed mechanical function in a simulated setting, rather than a diagnostic truth like pathology or outcome data.
   • For other performance tests (e.g., biocompatibility, functional performance under ISO standards), the "ground truth" is defined by the requirements and test methods specified in the cited international consensus standards. Compliance with these standards indicates the device performs as expected for its class.

7. The sample size for the training set:

   • Not applicable. This device is not an AI/machine learning model, so there is no concept of a "training set" for an algorithm. All listed tests are for device verification/validation.

8. How the ground truth for the training set was established:

   • Not applicable. As there is no training set for an AI model.

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