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The DuoPro™ Safety Syringe (DuoProSS™) is a sterile, single-use, disposable and nonreusable, manual retractable safety syringe intended for injection of fluids into the body, while reducing the risk of sharps injuries and the potential for syringe reuse.

The modified DuoPro™ Safety Syringe (DuoProSS™) is a sterile, single-use, disposable and non-reusable, manual, 3 mL or 5 mL retractable safety syringe, provided with or without needle in various product configurations.

The provided text is a 510(k) summary for a medical device called the DuoPro™ Safety Syringe (DuoProSS™). It describes the device, its intended use, and claims substantial equivalence to predicate devices based on similarities in design, technological, and operational characteristics.

However, the document does not provide specific acceptance criteria or details of a study that proves the device meets such criteria in the format requested by the prompt. The "TESTING" section briefly states:

"Verification and validation testing provided in this premarket notification includes standards conformity, testing according to FDA guidance, biocompatibility, and measurement of latex protein. Testing shows that the performance of the modified DuoProSS™ is equivalent to predicate devices."

This is a high-level statement indicating that testing was performed and concluded equivalence, but it lacks the granular details requested, such as:

• A table of acceptance criteria and reported device performance metrics.
• Sample sizes for test sets, data provenance.
• Number and qualifications of experts for ground truth.
• Adjudication methods.
• Information on MRMC comparative effectiveness studies or standalone performance.
• The type of ground truth used.
• Sample sizes and ground truth establishment for training sets (which would be relevant for an AI/ML device, but this appears to be a mechanical device).

Therefore, based solely on the provided text, I cannot complete the table or answer most of the questions as the detailed information is not present. The document focuses on demonstrating substantial equivalence to predicate devices, which is a regulatory pathway for approval, rather than detailing a study against specific, quantified acceptance criteria for a new AI/ML device.

Summary of missing information based on the prompt's requirements:

The provided 510(k) summary does not contain the detailed information needed to fill out the requested table and answer the study-specific questions. The device in question appears to be a mechanical medical device (safety syringe), not an AI/ML powered device, which explains the absence of data provenance, expert adjudication, MRMC studies, or training/test set details typically associated with AI/ML device evaluations.

The document states "Verification and validation testing provided in this premarket notification includes standards conformity, testing according to FDA guidance, biocompatibility, and measurement of latex protein. Testing shows that the performance of the modified DuoProSS™ is equivalent to predicate devices," but no specific results or acceptance criteria are detailed.

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The DuoPro Safety Syringe (DuoProSS™) is a sterile, single-use, disposable and non-reusable, manual, retractable safety syringe which is intended for injection of fluids into the body, while reducing the risk of sharps injuries and the potential for syringe reuse.

The DuoPro Safety Syringe (DuoProSS™) is a sterile, single-use, disposable and non-reusable, manual, retractable 3 mL safety syringe, provided with or without needle in various product configurations.

The provided text describes a 510(k) submission for a medical device, the DuoPro Safety Syringe (DuoProSS™). However, it does not contain the detailed performance study results, specific acceptance criteria, or the methodology (like expert consensus, sample sizes for training/test sets, or MRMC studies) that would typically be associated with software or AI-driven diagnostic devices.

The document is a premarket notification for a physical medical device (a syringe) and focuses on demonstrating substantial equivalence to a predicate device based on technological characteristics and bench testing of performance, rather than a clinical study evaluating diagnostic accuracy.

Therefore, many of the requested categories for AI/software-driven device evaluation are not applicable or not explicitly stated in this document.

Here's an attempt to answer based on the provided text, highlighting where information is absent:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample Size: Not specified. The document mentions "Bench testing" and "simulated use test" but does not provide the number of units tested.
• Data Provenance: Not applicable in the context of clinical data for an AI/software device. For the physical device, testing was conducted to demonstrate equivalence, likely in a lab setting by the manufacturer (M.K. Meditech Co., Ltd. in Taiwan).

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

• Not applicable. This is not a study requiring expert readers to establish ground truth for a diagnostic image or data set. The performance testing relates to physical device functions and safety mechanisms.

4. Adjudication method for the test set

• Not applicable. As noted above, this is about physical device performance, not diagnostic accuracy evaluation.

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 device is a physical syringe, not an AI software.

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

• Not applicable. This device is a physical syringe, not an AI algorithm.

7. The type of ground truth used

• The "ground truth" for this device would be its functional specifications and safety requirements as defined by regulatory standards (e.g., ISO, FDA guidance) and the performance of the predicate device. For example, a "ground truth" for retraction would be successful, complete retraction every time without user error, as designed. For biocompatibility, it would be the absence of adverse biological reactions.

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device.

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

• Not applicable. This is not an AI/machine learning device.

In summary, the provided 510(k) summary focuses on demonstrating that a new physical medical device is "substantially equivalent" to an already legally marketed predicate device. This is primarily done through comparing design, intended use, technological characteristics, and showing that "bench testing" supports equivalent performance. It is important to note that the depth of detail requested for AI/software devices (e.g., sample sizes for training/test, expert consensus, MRMC studies) is not typically part of a 510(k) summary for a physical, non-diagnostic device.

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