Search Results

Cardinal Health DuraBlue™ Sterilization Wrap is intended to enclose another medical device that is to be sterilized by a health care provider in the Lumen, and Flexible Cycles in the Amsco® V-PRO® 1, Amsco® V-PRO® 1 Plus and Amsco® V-PRO® maX Low Temperature Sterilization Systems. The wrap is intended to allow sterilization of the enclosed medical device(s) and to maintain sterility of the enclosed device(s) for 30 days. The DuraBlue™ Sterilization Wrap was validated to be effectively aerated during the pre-programmed Amsco® V-PRO® sterilization cycles.

Cardinal Health DuraBlue™ Sterilization Wraps are double layer sterilization wraps made from 100% polypropylene spunbond-meltblown-spunbond (SMS) fabric. They are intended to be used to enclose another medical device that is to be sterilized by a health care provider in the Lumen, or Flexible Cycles in the Amsco® V-PRO® 1, Amsco® V-PRO® 1 Plus and Amsco® V-PRO® maX Low Temperature Sterilization Systems. This wrap design allows for use of the simultaneous doublewrapping technique and also allows for a sterilized pack to be opened aseptically.

This submission covers six different models of Cardinal Health DuraBlue™ Sterilization Wrap. Each model is made from material of a different basis weight, though all models utilize the same material technology.

The provided document describes the Cardinal Health DuraBlue™ Sterilization Wrap, a medical device intended to enclose other medical devices for sterilization. The submission is a 510(k) premarket notification, which means the manufacturer is demonstrating that their device is "substantially equivalent" to an already legally marketed device (the predicate device) and therefore does not require a new Premarket Approval (PMA) application.

It's important to understand that a 510(k) notification primarily focuses on demonstrating substantial equivalence, meaning the new device is as safe and effective as the predicate device. The information provided about acceptance criteria and studies reflects this context.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" in a table format with specific numerical targets for each performance metric, which is common in a rigorous clinical validation study for novel devices. Instead, it describes general compliance with regulatory guidance and substantial equivalence to a predicate device. The performance is reported in terms of demonstrating efficacy and equivalence.

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

The document does not specify a "test set" in the context of a dataset with a specific sample size of cases for an AI/algorithm-based device. For this type of physical device (sterilization wrap), the "testing" involves laboratory and functional performance tests.

• Sample Size: Not explicitly stated as a number of "cases" as would be in AI/imaging studies. The testing involved "all models of DuraBlue™ Sterilization Wrap" across various Amsco® V-PRO® cycles and load configurations. The phrase "extensive performance testing" is used.
• Data Provenance: The studies are "performance testing" of the product itself, likely conducted in a laboratory setting by Cardinal Health or a contracted testing facility. There is no mention of country of origin of data or whether it was retrospective or prospective in the same way an AI study would report. It's inherent to device testing that it's prospective testing of the device's performance.

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

This section is not applicable to this type of device. The "ground truth" for a sterilization wrap is established by standardized testing protocols (e.g., microbial challenge tests, physical property evaluations) and adherence to regulatory guidance, not by expert consensus on "cases" as in diagnostic AI.

4. Adjudication Method for the Test Set

This section is not applicable to this type of device. Adjudication methods like "2+1, 3+1" are characteristic of clinical studies involving human observers interpreting data (e.g., radiology reads) where discrepancies need to be resolved. For a sterilization wrap, performance is typically measured against objective physical or biological criteria.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. This type of study assesses improvements in human reader performance (e.g., diagnostic accuracy) with and without AI assistance, which is irrelevant for a physical sterilization wrap. The "comparison" is to a predicate device's performance through substantial equivalence testing, not against human performance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Not Applicable. This device is not an algorithm or AI system. It is a physical product (sterilization wrap).

7. The Type of Ground Truth Used

For this device, the "ground truth" is established through:

• Standardized Sterilization Efficacy Testing: This involves challenging the wrap with known biological indicators (spores) and verifying their inactivation after sterilization. "Successful completion of the sterilization performance tests" indicated direct measurement of sterilization effectiveness.
• Physical Property Measurements: Objective measurements of material strength, porosity, barrier properties, etc., before and after sterilization.
• Biocompatibility Testing: Adherence to standards like ISO 10993, which involves specific chemical and biological assays.
• Event-Related Sterility Maintenance: Demonstrating the ability to maintain a sterile barrier over time, often through microbial challenge and package integrity testing.

8. The Sample Size for the Training Set

Not Applicable. This device does not use machine learning or AI, and therefore does not have "training data" in that sense. The "training set" for manufacturing and quality control would involve internal testing of material batches and finished products, but not as part of an AI model's development.

9. How the Ground Truth for the Training Set Was Established

Not Applicable. As there is no AI training set, there is no ground truth established for it. The performance of the device itself (its "ground truth") is established through the comprehensive testing described in point 7.

Ask a specific question about this device