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The UltiCare™ Safety Syringe is intended to inject fluid into, or withdraw fluid from the body. The safety mechanism aids in the prevention of needle stick injuries.

The UltiCare™ 3 mL Luer Lock Safety Syringes with Needle is a standard piston type syringe with a removable needle and protective shield. This sterile, single-use, disposable 3 ml piston syringes consist of a syringe barrel, plunger rod with gasket, removable single lumen needle, needle cap, and protective shield. The UltiCare Safety Syringes are non-toxic and non-pyrogenic, and will be available in a range of needle gauges and lengths between the smallest (27G x 5/16") and the largest (21G x 1 1/2").

This document is difficult to parse completely and does not contain all the information requested. This looks like a 510(k) summary for a medical device (UltiCare™ 3mL Luer Lock Safety Syringes with Needle), which demonstrates substantial equivalence to a predicate device, rather than a study proving the device meets specific acceptance criteria based on algorithm performance.

However, I can extract information related to the device's performance testing as described in the summary, which is analogous to acceptance criteria for a physical device.

Here's what can be extracted:

1. A table of acceptance criteria and the reported device performance

For a physical medical device like a syringe, "acceptance criteria" often refer to compliance with recognized standards. The document states the device was "designed and successfully tested to meet the applicable requirements" of several ISO standards. Specific, quantitative acceptance criteria and their corresponding performance reported are not explicitly detailed in a table format in the provided text. Instead, the document provides a list of standards the device met.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify the sample sizes used for the performance tests (e.g., how many syringes were tested for compliance with ISO standards). It also does not mention data provenance in terms of country of origin or retrospective/prospective for these engineering and material performance tests.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This is a physical device, not an AI algorithm involving interpretation. Therefore, the concept of "experts establishing ground truth" in the context of radiologists or similar interpretative tasks is not applicable. Compliance with standards would typically be verified by qualified testing laboratories and personnel, but no specific details are provided.

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

Not applicable for physical device testing against engineering standards.

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, as this is not an AI algorithm but a physical medical device. The document explicitly states: "No prospective clinical trials were conducted in support of this Traditional 510(k)."

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

Not applicable, as this is not an AI algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

For the performance testing, the "ground truth" or reference is defined by the specifications and methodologies outlined in the referenced ISO and USP standards. For example, for biocompatibility, the ground truth is "meeting the biocompatibility requirements of ISO 10993" including specific tests like "cytotoxicity, sensitization, irritation/intracutaneous reactivity, acute systemic toxicity testing, and hemocompatibility." For pyrogenicity, it's "successfully passed pyrogenicity testing (USP Rabbit Method)."

8. The sample size for the training set

Not applicable, as this is not an AI algorithm.

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

Not applicable, as this is not an AI algorithm.

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