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Safety Insulin Pen Needle is intended to be used with Insulin Pen for hypodermic injection of insulin and medicinal fluids.

The proposed device, Safety Insulin Pen Needle is intended to be used with Insulin Pen for hypodermic injection of insulin and medicinal fluids. It consists of needle tube, needle hub, spring, needle hub sheath, safety protective sheath, positioning ring, outer protective cap and sealing paper. The needle hub is clear, and the positioning ring and sealing paper contains colorants for the different gauge sizes. The Safety insulin needle for single use is offered in various gauge sized and length. The proposed device is available in EO sterilized to achieve a Sterility Assurance Level (SAL) of 10-6.

The provided text does not describe a device that uses AI or machine learning, nor does it detail acceptance criteria related to such a device's performance based on a test set. Instead, it is a 510(k) premarket notification for a medical device (Safety Insulin Pen Needles), primarily focusing on demonstrating substantial equivalence to a predicate device through non-clinical performance and biocompatibility testing against established ISO and ASTM standards.

Therefore, I cannot extract the information required to populate the table and answer the questions about AI/ML device performance, ground truth, expert consensus, sample sizes for training/test sets, or MRMC studies. The document explicitly states: "No data from human clinical studies have been included to support the substantial equivalence of the proposed device, Safety Insulin Pen Needle, as clinical studies are not required for this medical device."

However, I can provide the acceptance criteria and performance data as presented in the document, which are related to non-clinical tests for a physical medical device, not an AI/ML diagnostic or predictive tool.

Here's a summary of the non-clinical performance data and criteria as per the document:

A. Table of Acceptance Criteria and Reported Device Performance (Non-Clinical)

B. Information Not Applicable to this Submission (AI/ML Specifics)

The following information is not present in the provided document, as it pertains to AI/ML device studies, which this submission does not involve:

1. Sample size used for the test set and data provenance: Not applicable. The tests are physical/chemical evaluations of the device, not performance on a data set.
2. Number of experts used to establish the ground truth for the test set and their qualifications: Not applicable, as there is no "ground truth" established by experts in the context of an AI/ML model for this device. The ground truth refers to the physical and chemical properties conforming to established engineering and biological standards.
3. Adjudication method for the test set: Not applicable.
4. If a multi reader multi case (MRMC) comparative effectiveness study was done, and its effect size: Not applicable. This is for AI-assisted human reading performance.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is a physical medical device.
6. The type of ground truth used: For this device, the "ground truth" is defined by compliance with the referenced ISO, ASTM, and USP standards for manufacturing quality, performance characteristics (e.g., fluid flow, needle strength), sterility, and biocompatibility.
7. The sample size for the training set: Not applicable, as this is not an AI/ML device.
8. How the ground truth for the training set was established: Not applicable.

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The Disposable Insulin Pen Needle is intended for use with pen injector devices for the subcutaneous injection of insulin.

The proposed device, Disposable Insulin Pen Needle, is a single use device, which is designed for used with a pen injector for the subcutaneous injection of insulin. It consist of needle tube, inner sheath, cup, hub and sealed paper. The hub can be connected screwed onto the insulin pen. The proposed device is available in following specifications: Gauge 33G, 32G, 31G, 30G, 29G, 28G and Length (mm) 4mm, 6mm, 8mm, 12mm.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Disposable Insulin Pen Needle:

This document is a 510(k) summary for a medical device seeking market clearance, specifically a Disposable Insulin Pen Needle. For such a device, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" are generally based on compliance with recognized consensus standards and non-clinical performance testing rather than clinical trials or AI/software performance metrics.

1. Table of Acceptance Criteria and Reported Device Performance:

The document outlines a comprehensive set of non-clinical tests and biocompatibility tests. The acceptance criteria are implicit in verifying that the proposed device "met all design specifications" and that "the test result comply with the related standard requirements."

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

The document states, "Non clinical tests were conducted to verify that the proposed device met all design specifications as was Substantially Equivalent (SE) to the predicate device." It also mentions "aging samples" for shelf life evaluation and testing of "all proposed models" for needle gauge differences.

• Sample Size: The exact sample sizes for each specific test are not provided in this summary. However, for medical device testing against standards, specified sample sizes are typically defined within the standards themselves or agreed upon with regulatory bodies.
• Data Provenance: The tests were conducted by Zhejiang Kindley Medical Devices Co.,Ltd in China (PRC), as they are the submitter. The data is retrospective in the sense that the tests were performed on the device prototypes and models before submission for clearance.

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

This type of information is not applicable to this document. The "ground truth" for a medical device like an insulin pen needle is established by its physical and functional properties meeting recognized international standards (e.g., ISO, ASTM). It does not involve expert clinical assessment of images or data in the way AI performance studies would.

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

This is not applicable to this type of device and study. Adjudication methods like 2+1 or 3+1 are used in clinical trials or diagnostic studies where there's a need for expert consensus on patient outcomes or diagnoses, particularly when dealing with subjective interpretations or complex clinical endpoints. For a mechanical device tested against engineering standards, the results are typically objective measurements.

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:

This is not applicable. An MRMC study is relevant for AI-powered diagnostic tools where human readers (e.g., radiologists) interpret cases with and without AI assistance. This document describes a physical medical device (insulin pen needle) and its non-clinical performance against engineering standards. There is no AI component or human reader interpretation involved in its evaluation.

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

This is not applicable. This describes a physical medical device, not an algorithm.

7. The type of ground truth used:

The "ground truth" for this device's performance is derived from compliance with established international consensus standards (e.g., ISO 7864, ISO 9626, ISO 11608-2, ISO 10993, ANSI/AAMI/ISO 11135-1, ASTM F88/F88-15, ASTM F1929-15, USP <85>). These standards define the acceptable physical, mechanical, chemical, and biological properties for hypodermic needles and pen needles.

8. The sample size for the training set:

There is no training set in the context of this device's evaluation. "Training set" refers to data used to train machine learning models. This is about physical device testing.

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

This is not applicable as there is no training set for this type of device evaluation.

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