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The Y2K2 Enteral In-Line Filter is intended for use to filter liquid feeding solutions prior to delivery into a patient's pre-inserted feeding tube, to minimize the risk of tube occusion by macro particulates.

This will be applicable to any size or length pediatric or adult feeding tube (e.g., nasogastric, nasoduodenal, nasojejunal, gastrostomy, jejunostomy, transgastric duodenal, or transgastic jejunal).

The proposed and predicate devices are of essentially the same size, construction, and function. They are made of comparable (Re: Pall) or identical (Re: Cobe Cardiovascular) inert biomaterials. The Y2K2 Enteral In-Line Filter differs in having a larger pore size, to remove coarse (but not fine) particulates from enterally delivered fluids.

Here's the analysis of the provided text regarding the Y2K2 Enteral In-Line Filter:

Acceptance Criteria and Device Performance Study

The provided 510(k) summary (K051206) for the Y2K2 Enteral In-Line Filter does not contain a detailed study report with specific acceptance criteria and performance data in the format typically seen for algorithm-based devices. This document is a premarket notification for a Class II medical device, primarily focused on establishing substantial equivalence to predicate devices.

The "study" in this context refers to the comparison made for substantial equivalence to predicate devices based on technical characteristics and function, rather than a clinical performance study with statistical endpoints.

1. Table of Acceptance Criteria and Reported Device Performance

Summary of the "Study" for Substantial Equivalence:

The document describes the device and states that its technical characteristics, particularly its size, construction, function, and materials, are "essentially the same" as, or "comparable" to, the predicate devices (Pall PharmAssure Capsule Filter K943127 and Cobe Cardiovascular Pre-bypass Filter K850139). The primary difference highlighted is the larger pore size of the Y2K2 filter, designed to remove "coarse" rather than fine particulates. This comparison forms the basis of the "study" for establishing substantial equivalence, indicating that because it is similar to already approved/cleared devices, it meets the necessary safety and effectiveness standards for its intended use.

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

• Sample Size: Not applicable in the context of this 510(k) summary. There is no traditional "test set" of patient data in the document for the performance of an algorithm. The evaluation is based on a technical comparison to predicate devices and potentially bench testing (not detailed in this summary) to demonstrate filtration capability.
• Data Provenance: Not applicable. The "data" here refers to the specifications and characteristics of the device itself and its comparison to predicate devices, not patient data from a particular country or retrospective/prospective study.

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

• Number of Experts: Not applicable. This is not an AI/algorithm-based device where experts would establish ground truth for a test set. The evaluation is primarily engineering and regulatory in nature.
• Qualifications: If any expert input was involved, it would likely be from engineers, materials scientists, and regulatory affairs specialists who assessed the device specifications against regulatory requirements and predicate devices.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. There is no test set in the sense of medical images or other data requiring expert adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, a Multi-Reader Multi-Case comparative effectiveness study was not done. This type of study is relevant for diagnostic imaging AI devices where human readers' performance with and without AI assistance is evaluated. The Y2K2 is an in-line filter, not a diagnostic AI device.
• Effect Size: Not applicable.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: No, a standalone performance study for an algorithm was not done. The device itself is a physical filter, not a software algorithm. Its "performance" would be assessed through fluid dynamics, particulate retention, and material compatibility testing, not typically through an algorithm-only study.

7. Type of Ground Truth Used

• Type of Ground Truth: The "ground truth" in this context is the established safety and performance profile of the predicate devices and the general understanding of filtration principles and biomaterial compatibility. The Y2K2 device is deemed to perform acceptably because it is "essentially the same" or "comparable" to devices already deemed safe and effective by the FDA. Compliance with manufacturing standards and ISO standards (though not explicitly detailed for filtering capability in this summary) would also contribute to this.

8. Sample Size for the Training Set

• Sample Size: Not applicable. This is not an AI or machine learning device that requires a training set.

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

• Ground Truth Establishment: Not applicable. As there is no training set, there is no ground truth to establish for it.

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