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The Nipro SafeTouch Needle is indicated for general purpose injection of fluid from vials, and to and from parts of the body below the surface of the skin. It includes a needle shield to prevent against accidental needlestick injuries. The needle is compatible with standard Luer-lock syringes.

The Nipro Syringe with SafeTouch Needle is indicated for general purpose injection of fluid from vials, and to and from parts of the body below the surface of the skin. It includes a needle shield to prevent against accidental needlestick injuries.

The Nipro SafeTouch Needle is a disposable hypodermic single lumen needle with attached safety device. The safety device is a needle shield that covers the needle post treatment eliminating accidental needlestick injuries. It is provided with and without a piston syringe.

The Nipro SafeTouch Needle is available in gauges of 18-30, lengths of ½". The needles are available individually or attached to a luer lock syringe in volumes of 1, 3, 5 and 10mL.

The device is sterile, single use only, non-toxic, and non-pyrogenic. It is sterilized by Ethylene Oxide gas and has a shelf-life of 5 years.

The provided text describes specific acceptance criteria and study details for the Nipro SafeTouch Needle and Nipro Syringe with SafeTouch Needle, but it does not describe a study proving the device meets acceptance criteria in the context of an AI/ML device. Instead, it outlines a 510(k) premarket notification for a traditional medical device, comparing it to a predicate device.

The document discusses non-clinical tests and a simulated clinical study, but these are for a physical medical device, not an AI/ML diagnostic or therapeutic system. Therefore, I cannot provide information on items such as multi-reader multi-case studies, standalone algorithm performance, ground truth establishment for AI training sets, or sample sizes for AI training sets, as these concepts are not relevant to the provided text.

However, I can extract the acceptance criteria and performance related to the physical medical device and the simulated clinical study.

Here's the information based on the provided text, focusing on the device's physical and functional properties:

Table of Acceptance Criteria and Reported Device Performance

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To inject fluids into or withdraw fluids from the body.

The NIPRO Syringe is a piston syringe consisting of graduated barrel, plunger rod, and gasket. It is provided in luer slip, luer lock and eccentric luer slip tips, with and without attached hypodermic needles are available in ranges of 20-27G, and 3/8 to 1 ½" in length. Gauges are color coded for easy differentiation. Its function is mechanical. The syringe is sterile, single use only, non-toxic, non-pyrogenic and sterilized by Ebeam radiation. The shelf-life has been determined to be 5 years.

The provided text is a 510(k) summary for a medical device, specifically a Nipro Syringe. It describes a conventional medical device, not an AI/ML-driven device. Therefore, the information requested in the prompt regarding acceptance criteria, study details, expert involvement, and ground truth for an AI/ML device is not present in the provided document.

The document discusses:

• Device Description: A piston syringe with varied sizes, gauges, and tips.
• Indications for Use: To inject or withdraw fluids from the body.
• Technological Characteristics: Materials, design, sterilization, expiry dating, and dimensions.
• Non-Clinical Performance Testing: A comprehensive list of biocompatibility, visual inspection, dimensional, mechanical, chemical, sterilization, transportation, pyrogen, and shelf-life tests performed to demonstrate substantial equivalence to a predicate device.
• Clinical Study Conclusion: Explicitly states "No clinical Study is included in this submission."

Since the prompt is specifically about the acceptance criteria and study that proves the device meets the acceptance criteria (implying an AI/ML device context), and the document describes a physical medical device (syringe), it does not contain the information necessary to answer the questions about AI/ML device performance, ground truth, expert consensus, or MRMC studies.

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to inject fluids into or withdraw fluids from the body

The NIPRO Syringe is a piston syringe consisting of graduated barrel, plunger rod, and gasket. It is provided in luer slip, luer lock and eccentric luer slip tips, with and without attached hypodermic needles are available in ranges of 20-25G, and 3/8 to 1 ½" in length. Gauges are color coded for easy differentiation. Its function is mechanical. The syringe is sterile, single use only, non-toxic, non-pyrogenic and sterilized by Ebeam radiation. The shelf-life has been determined to be 5 years. This device is not intended for patients less than 2 years of age.

The Nipro Syringe is a medical device and thus the provided document is a 510(k) summary, which outlines its substantial equivalence to a predicate device rather than a study proving unmet acceptance criteria in the context of AI/ML performance. Therefore, most of the requested information regarding AI/ML clinical study specifics (such as expert involvement, adjudication, MRMC studies, standalone performance, and ground truth establishment for training and test sets) is not applicable or cannot be extracted from this document.

However, I can extract the acceptance criteria related to the device's physical and performance characteristics, and how the device's performance was evaluated against these criteria.

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes non-clinical tests performed to ensure the Nipro Syringe meets established standards. The acceptance criteria are implicit in the "specifications of the standards listed," and the reported device performance is that these tests were "performed within the specifications" and that the device "performs equivalent to the predicate device."

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

This information is not explicitly provided in the document. The document refers to non-clinical tests performed to specific standards, but it doesn't detail the sample sizes used for each test or the provenance of any data (e.g., country of origin, retrospective/prospective). As this is a physical medical device, not an AI/ML system, "test set" in the context of data for model evaluation is not directly applicable.

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

Not applicable. This device is a physical syringe, not an AI/ML system requiring expert consensus for ground truth establishment. The "ground truth" for this device's performance is determined by meeting the specifications of established engineering and biological standards.

4. Adjudication Method for the Test Set:

Not applicable for a physical device. The compliance with standards and their specifications serves as the evaluation basis, not human adjudication of AI output.

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

Not applicable. This is not an AI-assisted diagnostic or treatment device, so there is no human-in-the-loop performance improvement with or without AI to measure.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study:

Not applicable. This is a physical medical device, not an algorithm. Its performance is inherent to its design and manufacturing, evaluated through non-clinical testing against established standards.

7. Type of Ground Truth Used:

The "ground truth" for the Nipro Syringe is compliance with internationally recognized and industry-accepted standards (ISO, ASTM, USP) for medical devices, specifically for piston syringes and needles. This includes performance benchmarks for:

• Physical dimensions and integrity
• Mechanical function
• Sterility
• Biocompatibility
• Chemical characteristics
• Shelf-life

8. Sample Size for the Training Set:

Not applicable. This is a physical device, not an AI/ML model, so there is no "training set."

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 concept of establishing ground truth for it is irrelevant in this context.

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