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The Quantikine™ IVD™ sTFR Enzyme linked immunosorbent assay is intended for the measurement of sTfR concentration in human serum or plasma as an aid in the diagnosis of iron deficiency anemia, especially the differential diagnosis of iron deficiency anemia and anemia of chronic disease.

Device Description

The product is a microtiter-plate-based sandwich enzyme immunoassay for soluble transferrin receptor.

AI/ML Overview

Acceptance Criteria and Study for Quantikine™ IVD™ sTfR ELISA kit

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document does not explicitly state quantitative acceptance criteria in a dedicated table format. However, it outlines performance characteristics that were tested. I will infer the implied acceptance criteria based on the descriptions provided.

Performance Characteristic	Implied Acceptance Criteria (Inferred)	Reported Device Performance
Precision	Demonstrate reliable and reproducible measurements. (Specific CV% or SD not stated)	Testing performed. Implied acceptable as device was cleared.
Linearity	Show consistent response across the expected range of sTfR concentrations. (Specific range or R² not stated)	Testing performed. Implied acceptable as device was cleared.
Specificity	Accurately detect sTfR without significant interference from other substances. (Specific cross-reactivity limits not stated)	Testing performed. Implied acceptable as device was cleared.
Sensitivity	Detect low concentrations of sTfR. (Specific limit of detection not stated)	Testing performed. Implied acceptable as device was cleared.
Stability (Kit)	Maintain performance for at least 13 weeks when stored at 2-8°C.	Established at 13 weeks when stored at 2-8℃ and handled according to instructions.
Stability (Opened/Diluted Reagents)	Maintain performance for up to 4 weeks when stored at 2-8°C (within kit expiration).	Good for up to 4 weeks when stored at 2-8℃, provided it's within expiration date.
Stability (Reconstituted Controls)	Maintain performance for a minimum of 4 weeks.	Stable for a minimum of 4 weeks.
Intended Use	Aid in the diagnosis of iron deficiency anemia and differential diagnosis.	Stated as intended use, implying performance supports this claim.
Substantial Equivalence	Performance characteristics similar to predicate Sanofi Diagnostics ferritin assay.	Performance testing "centered on the attributes of precision, linearity, specificity, sensitivity and stability." Technologies are similar.

2. Sample Sizes Used for the Test Set and Data Provenance:

The document does not specify the sample sizes used for the test set for precision, linearity, specificity, sensitivity, or stability studies.

The data provenance (e.g., country of origin, retrospective or prospective) is also not mentioned in the provided text.

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

The document does not mention using experts to establish ground truth for the test set. The performance characteristics (precision, linearity, specificity, sensitivity) typically rely on laboratory-based analytical validation, not expert consensus on clinical cases.

4. Adjudication Method for the Test Set:

Since the ground truth for the test set, in terms of clinical cases or diagnoses, is not mentioned as being established by experts, there is no adjudication method described for the test set. The evaluation seems to be based on analytical performance metrics.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or is not mentioned in this 510(k) summary. This type of study is more common for imaging devices where human interpretation plays a significant role. The Quantikine™ IVD™ sTfR ELISA kit is an in vitro diagnostic assay, which typically focuses on analytical performance characteristics rather than human reader improvement with AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance:

The device described is an in vitro diagnostic (IVD) ELISA kit, which is inherently a "standalone" device in the sense that its output is a quantitative measurement of sTfR concentration. There isn't an "algorithm" in the typical AI sense, nor is there a "human-in-the-loop" interaction during the assay's execution. The result is generated by the biochemical reaction, and then a human interprets that numerical result in a clinical context.

7. Type of Ground Truth Used:

For the performance characteristics described:

Precision: Likely assessed by repeated measurements of control samples or patient samples.
Linearity: Assessed by diluting samples with known concentrations or by spiking samples.
Specificity: Assessed by testing for interference from various substances or cross-reactivity with related molecules.
Sensitivity: Assessed by determining the lowest detectable concentration of sTfR.
Stability: Assessed by testing reagents and kits over time under specified storage conditions.

In these contexts, the "ground truth" is typically established by:

Reference materials/standards: For accuracy and calibration.
Pre-established analytical methods: For defining what constitutes a "true" concentration or a valid measurement.
Spiking experiments: Where a known amount of analyte is added to a sample.

Pathology, expert consensus, or outcomes data are not mentioned as directly being used to establish the ground truth for the performance characteristics reported in this 510(k) summary. Given its nature as an IVD, the ground truth relates to the analytical performance of the assay itself.

8. Sample Size for the Training Set:

The document does not mention a "training set" in the context of machine learning or AI algorithms. This is an IVD kit, which typically does not involve machine learning models that require training data. The development of such an assay involves optimization of reagents and protocols, which is an iterative process but not typically referred to as "training" in this context.

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

As there is no mention of a training set in the context of an AI/ML algorithm, the question of how its ground truth was established is not applicable based on the provided text. The development of an ELISA assay involves extensive R&D to define optimal antibody pairs, reagent concentrations, incubation times, etc., but this is a different paradigm from AI model training.

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