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510(k) Data Aggregation
(54 days)
UREA NITROGEN (BUN) LIQUID REAGENT
Intended for the In Vitro, quantitative determination of urea nitrogen (BUN) in human serum on automated chemistry analyzers.
Urea Nitrogen measurements obtained by this device are used in the diagnosis and treatment of certain renal and metabolic diseases.
This Reagent is intended for the in vitro quantitative determination of urea nitrogen in human serum.
This document is a 510(k) summary for a diagnostic reagent, not a study report for a medical device with an algorithm or AI. Therefore, most of the requested information regarding acceptance criteria, study design, expert ground truth, and AI-specific details is not directly applicable or available in this type of submission.
However, I can extract the relevant information concerning the device's performance justification from the provided text, focusing on the concept of "substantial equivalence" as applicable to this type of device.
Key takeaway: The submission focuses on demonstrating "substantial equivalence" of the new reagent to legally marketed predicate devices, primarily through correlation studies comparing their performance on human serum samples. This is a common approach for in vitro diagnostic reagents where performance standards are often established by comparison to existing, accepted methods.
Here's an attempt to address the points based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Implied by Substantial Equivalence) | Reported Device Performance |
---|---|
Acceptable correlation/result comparisons with predicate devices on human serum. | "Correlation studies on human serum demonstrated acceptable result comparisons between these methods, which all use similar normal ranges." (Specific metrics like correlation coefficient, bias, or acceptable difference ranges are not provided in this summary). |
Similar intended use to predicate devices. | "The JAS Urea Nitrogen (BUN) Liquid Reagent's intended use is identical to predicate Devices." |
Acceptable performance on automated chemistry analyzers tested. | "its performance acceptable on the automated chemistry analyzers tested." (Specific analyzer types or performance metrics are not provided in this summary). |
Similar normal ranges as predicate devices. | "Correlation studies... which all use similar normal ranges." |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: Not specified. The document only states "human serum" was used for correlation studies.
- Data Provenance: Not specified (e.g., country of origin). The document implies the data was collected as part of the validation for this specific 510(k) submission.
- Retrospective or Prospective: Not specified, but typically, these correlation studies would be prospective or involve freshly collected samples for evaluation.
3. Number of Experts Used to Establish Ground Truth and Qualifications
- Not Applicable. For a reagent comparing its performance to predicate reagents, "ground truth" is typically established by the results of the legally marketed predicate device(s) or an established reference method. There is no mention of "experts" in the sense of clinical reviewers establishing ground truth for individual cases. The expertise lies in the analytical method comparison.
4. Adjudication Method for the Test Set
- Not Applicable. There is no mention of an adjudication process as would be used for image interpretation or clinical diagnosis. The "adjudication" here is implied by the quantitative comparison of results between the new reagent and predicate reagents.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
- Not Applicable. This is a diagnostic reagent for quantitative measurement, not an AI-assisted device for human interpretation like an imaging algorithm. Therefore, an MRMC study is not relevant to this type of device.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
- Not Applicable. This is a reagent. It performs its function (chemical reaction for quantitative measurement) independently once applied to the sample on an automated analyzer. There is no "algorithm" in the sense of AI or image processing. Its performance is inherently "standalone" in operating on the sample.
7. The Type of Ground Truth Used
- For this type of device, the "ground truth" (or reference standard) is implicitly the results obtained from the predicate devices (Roche Diagnostics BUN (Urea Nitrogen) Reagent for the Cobas Mira analyzers and Pointe Scientific Urea Nitrogen (BUN) Reagent). The study aims to show that the new reagent's results align "acceptably" with these established methods.
8. The Sample Size for the Training Set
- Not Applicable. In the context of a diagnostic reagent, there is no "training set" in the sense of machine learning. The reagent's formulation and manufacturing process are developed through R&D, not trained on data.
9. How the Ground Truth for the Training Set Was Established
- Not Applicable. See point 8.
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(21 days)
UREA NITROGEN (BUN) LIQUID REAGENT
For the Kinetic Quantitative determination of Urea Nitrogen (MUN) in serum. Urea Nitrogen determination is an indicator of liver and kidney functions, such as; Mephritis, Acute Liver Destruction and Urinary Obstruction.
Urea Nitrogen (BUN) Liquid Reagent - Kinetic Method
This document is a 510(k) clearance letter from the FDA for a Urea Nitrogen (BUN) Liquid Reagent Set. It confirms that the device is substantially equivalent to legally marketed predicate devices.
The document does not contain information about the acceptance criteria or a study that proves the device meets those criteria in the context of device performance as typically discussed for AI/ML-driven medical devices. Instead, it focuses on the regulatory clearance process for an in vitro diagnostic reagent set.
Therefore, I cannot provide the requested information for the following reasons:
- No acceptance criteria: The letter itself does not state specific performance acceptance criteria for the reagent set. It refers to the device being "substantially equivalent" to predicate devices, implying that its performance is comparable, but doesn't quantify specific metrics like sensitivity, specificity, or accuracy targets.
- No study details: The letter does not describe any specific study conducted to demonstrate the device's performance against detailed acceptance criteria. It's a regulatory clearance, not a clinical or performance study report.
- Nature of the device: This is a diagnostic reagent set, not an AI/ML-driven device that would typically involve test sets, ground truth derived from experts, MRMC studies, or standalone algorithm performance.
The "study" referenced in the context of this document is the 510(k) submission itself, where the manufacturer provides data (e.g., analytical performance, comparison to predicate) to demonstrate substantial equivalence, but the details of such a study are not included in this FDA clearance letter.
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