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The Sharp Chute TM is an over-the-counter, single-use, disposable, non-sterile sharps container intended to be used with medical sharps including, but not limited to, hypodermic needles, syringes, lancets, and blood needles. The containers can be used in any area requiring sharps collection prior to their final disposal.

When the container is filled to the max-capacity indicator, it is intended to be permanently locked and ultimately disposed of.

The Sharp Chute ™ is a portable, 1.5 quart sharps container designed to be used in . environments where larger containers are not desired. In addition, it is designed to fit into Heathrow Scientific's Droplet™ Blood Collection Tray.
The Sharp Chute ™ is available in either translucent red or translucent yellow.
Each component of the container assembly is made of injection molded polypropylene.
The end user will be required to attach the dome assembly to the base by inserting the . connection tabs into their corresponding slots.
The Sharp Chute "1 is designed to withstand punctures by syringes, pen needles, and . lancets.
The Sharp Chute "M is autoclavable and incineratable. .
The Sharp Chute TM is NOT reusable. .

This document describes a 510(k) submission for the "Sharp Chute" sharps container. However, it does not contain information about specific acceptance criteria, study designs, sample sizes for testing, ground truth establishment methods, or the use of experts in the context of device performance evaluation as typically requested for AI/ML-based devices or studies requiring such detailed clinical validation.

The information provided focuses on the device's substantial equivalence to predicate devices, its intended use, technological characteristics, and compliance with general FDA regulations.

Therefore, I cannot fulfill your request for the specific details outlined in your prompt because the provided input document does not contain this information. The document focuses on regulatory approval based on substantial equivalence, not on a detailed clinical performance study with the metrics you've asked for.

Here's what I can extract based on the provided text, and where I must state "Not applicable" or "Not provided":

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size: Not provided. The document mentions "tests against various standards" but does not specify the number of units or conditions tested.
• Data provenance: Not explicitly stated as "country of origin" or "retrospective/prospective." The testing was conducted by a third-party review company, Intertek, located in Grand Rapids, MI.

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

• Not applicable/Not provided. This device is a physical sharps container, not an AI/ML diagnostic tool that would typically involve expert-established ground truth for a test set. Evaluation would likely involve engineering and materials science experts conducting specific tests.

4. Adjudication method for the test set:

• Not applicable/Not provided. Adjudication methods (like 2+1, 3+1) are typically used for interpreting ambiguous results in studies involving human interpretation or subjective assessments, which is not the context for this physical device.

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 a physical sharps container, not an AI/ML system, so an MRMC study is irrelevant.

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

• Not applicable. This is a physical sharps container, not an AI algorithm. Its performance is evaluated through physical and material testing, not algorithmic standalone performance.

7. The type of ground truth used:

• Not explicitly stated in terms of "expert consensus, pathology, outcomes data." For a physical device like a sharps container, ground truth would likely be based on established engineering standards, material properties, and regulatory requirements (e.g., ability to resist puncture as defined by a standard, mechanical strength for a handle, proper functioning of locking mechanisms).

8. The sample size for the training set:

• Not applicable/Not provided. This is a physical device, not an AI/ML model that requires training data in the typical sense.

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

• Not applicable/Not provided. As above, this is not an AI/ML model.

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