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510(k) Data Aggregation
(191 days)
THE METRIX COMPANY
The device is intended to deliver liquid nutritional formulas or water to a patient's enteral access device (feeding tube).
The sets are constructed from flexible, medical grade, Non-DEHP tubing in various configurations with a stepped connector at one end. One configuration may include an Enteral solution container constructed of a laminate material with a stepped connector to connect to a gastric tube (or an extension set) or another configuration may simply be an administration set which connects the patient gastric tube to the nutrition liquid container.
The document describes Gravity Enteral Feeding Sets, which are intended to deliver liquid nutritional formulas or water to a patient's enteral access device (feeding tube). The submission is a Traditional 510(k) for substantial equivalence to legally marketed predicate devices.
Here's an analysis of the acceptance criteria and the study data provided:
1. Table of Acceptance Criteria and Reported Device Performance:
Acceptance Criteria Category | Specific Acceptance Criteria | Reported Device Performance |
---|---|---|
Form/Construction | Stepped Adaptor meets AAMI/ANSI ID54:1996/(R)2012 | Device meets the requirements of AAMI/ANSI ID54:1996/(R)2012 |
Form/Construction | Safety Screw Connector meets AAMI/ANSI/ISO 80369-1 | Device meets the requirements of AAMI/ANSI/ISO 80369-1 |
Drop Factor Accuracy | Accuracy of the current drop factor on gravity feed sets | "A study of the accuracy of the current drop factor given on gravity feed sets" (Validation 703V was performed). Specific quantitative results are not provided in this summary. |
Manufacturing Process | Qualification of the manufacturing process for Gravity Set w/ Bag | "A Study to qualify the process to manufacture Gravity Set w/ Bag" (Validation Protocol 868V was performed). Specific details of the qualification are not provided in this summary. |
Substantial Equivalence | Equivalent in principle of materials, operation, and intended use to commercially marketed Abbott Nutrition sets. | The Gravity Enteral Feeding Sets are "substantially equivalent to commercially marketed Abbott Nutrition sets in terms of principle of materials, operation, and intended use." Minor or no differences in design, materials, or chemical composition compared to predicate devices. |
2. Sample size used for the test set and the data provenance:
- Sample Size: The document does not explicitly state the sample sizes used for "Validation 703V" (drop factor accuracy) or "Validation Protocol 868V" (manufacturing process qualification).
- Data Provenance: The studies are described as "bench test reports" performed by The Metrix Company, the submitter, to support the performance characteristics. No information is provided regarding the country of origin of the data, nor whether it was retrospective or prospective, though bench tests are generally prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This analysis is not applicable to the provided information. The studies described are bench tests focused on engineering specifications (e.g., connector standards, drop factor accuracy, manufacturing process qualification) rather than clinical evaluations requiring expert interpretation or ground truth establishment in a clinical context.
4. Adjudication method for the test set:
- This is not applicable. The studies are bench tests for engineering compliance and manufacturing process qualification, not clinical studies requiring adjudication of outcomes or interpretations.
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. The device is a physical medical device (enteral feeding sets), not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study with human readers and AI assistance is irrelevant to this submission.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- This is not applicable. The device is a physical medical device, not an algorithm.
7. The type of ground truth used:
- Bench Test Standards: The "ground truth" for the stepped adaptor and safety screw connector appears to be the requirements stipulated by recognized international standards (AAMI/ANSI ID54:1996/(R)2012 and AAMI/ANSI/ISO 80369-1).
- Internal Validation: For the drop factor accuracy and manufacturing process qualification, the "ground truth" would be the pre-defined internal specifications and acceptance limits established by The Metrix Company for these performance characteristics.
8. The sample size for the training set:
- This is not applicable. The device is a physical medical device, not a machine learning or AI model that requires a training set. The submission focuses on demonstrating substantial equivalence through comparison of technological characteristics and performance testing to established standards and predicate devices.
9. How the ground truth for the training set was established:
- This is not applicable, as there is no training set for a physical device like this.
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(12 days)
METRIX CO.
An empty container with sterile fluid path used to hold an admixture of compatible fluids for administration to a patient. Medication transfer is done using aseptic technique.
EVA Empty Solution Container
The provided text is a 510(k) premarket notification letter from the FDA for a device called "EVA Empty Solution Container." This document is a regulatory approval letter and does not contain any information regarding acceptance criteria, study details, or performance metrics for a device that uses an algorithm or AI.
The device described is an "empty container with sterile fluid path used to hold an admixture of compatible fluids for administration to a patient." This is a physical medical device, not a software or AI-driven system.
Therefore, I cannot provide the requested information about acceptance criteria, study design, or performance metrics related to an algorithm's performance, as this information is not present in the given text.
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