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The Premier Hb9210™ system is intended for the quantitative measurement of hemoglobin A1c (HbA1c) in human capillary and venous whole blood. HbA1c is used for the monitoring of long-term glycemic control in individuals with diabetes mellitus. For in vitro diagnostic use only.

The Premier Hb9210™ is an update of the predicate HPLC device, the Ultra2, which is the current model under K891235. The Premier Hb9210™ is a compact, integrated HPLC system and workstation with the Trinity Biotech AFFINITY Software for the quantitative determination of glycated hemoglobin using the patented boronate affinity chemistry with high performance liquid chromatography.

Here's an analysis of the provided information, addressing your requested points:

Device: Trinity Biotech Premier Hb9210™ HbA1c Analyzer

The Premier Hb9210™ is an automated High-Performance Liquid Chromatography (HPLC) system designed for the quantitative measurement of HbA1c in human capillary and venous whole blood. This device uses boronate affinity chemistry for HbA1c measurement, building upon the technology of its predicate device, the Ultra2 (K891235).

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" for the performance metrics in a pass/fail format. Instead, it presents the results of performance tests aimed at demonstrating substantial equivalence to a predicate device. For the purpose of this response, I will interpret the reported performance from the precision and accuracy studies as the device's demonstrated performance.

Note: The document focuses on demonstrating substantial equivalence to a predicate device (Ultra2, K891235), not necessarily meeting specific pre-defined acceptance criteria for novel device approval.

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

• Sample Size for Precision Test Set:
  • Three hemolysate samples, each representing normal, decision point, and abnormal levels of %HbA1c.
  • Each of these three samples was analyzed 80 times per site (2 analyses per run, 2 runs per day, over 20 non-consecutive days) across 3 sites.
  • Total replicates: 240 replicates per HbA1c level (3 HbA1c levels * 80 replicates per site * 3 sites) if referring to individual measurements contributing to the overall analysis. The document states "a total of 80 replicates of each level per site, 240 replicates overall".
  • Total observations for precision study: 1200 total observations (implicitly across the 3 HbA1c levels and 3 sites).
• Sample Size for Accuracy Test Set (vs. predicate): 51 samples.
• Data Provenance: Not explicitly stated, but the study was conducted at one internal and two external sites. The phrase "aliquotted and frozen whole blood" suggests controlled sample handling, but the origin country of the patient samples or whether they were retrospective or prospective samples is not specified. Given the context of a 510(k) submission, it's typically based on controlled laboratory studies rather than a full clinical trial with diverse patient populations and retrospective/prospective designations.

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

This device is an in vitro diagnostic (IVD) for quantitative measurement, not an AI/ML-driven diagnostic requiring human expert interpretation for ground truth. Therefore, the concept of "experts establishing ground truth" in the way it applies to image interpretation or clinical diagnosis by human readers does not apply in this context.

• Ground truth for the HbA1c levels in the precision study samples would have been established by a highly accurate reference method or certified reference materials, not by human expert consensus or adjudication.
• For the accuracy study comparing to the predicate device, the predicate device itself served as the reference for comparison of the 51 samples.
• For the accuracy study against IFCC HbA1c Standards, the standards themselves provide the ground truth.

4. Adjudication Method for the Test Set

Not applicable. As described in point 3, this is a quantitative measurement device, not one where human interpretation requires adjudication.

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

Not applicable. This device is an automated standalone in vitro diagnostic analyzer, not an AI-assisted diagnostic tool that aids human readers. Therefore, an MRMC study is not relevant.

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

Yes, the performance studies described (precision, accuracy, linearity) are inherently standalone performance studies for the Premier Hb9210™ analyzer. The device performs the measurement and outputs the HbA1c value without human interpretative input in the measurement process itself.

7. The Type of Ground Truth Used

• Precision Study: Hemolysate samples representing different HbA1c levels. The "actual" concentrations were likely assigned using a reference method or certified values.
• Accuracy Study (IFCC HbA1c Standards): Certified IFCC HbA1c Standards. These are internationally recognized reference materials providing an agreed-upon "true" value for comparison.
• Accuracy Study (against predicate): The predicate device (Ultra2) results were used as the comparator for the 51 samples. While the predicate device itself is not "ground truth" in the strictest sense of a gold standard, it serves as the benchmark against which substantial equivalence is claimed.

8. The Sample Size for the Training Set

Not applicable. This document describes an in vitro diagnostic device using a well-established chemical and physical principle (boronate affinity HPLC). It is not an AI/ML device that requires a "training set" of data in the common sense of machine learning. The device's operational parameters are determined through engineering and chemical optimization, not through data-driven training of an algorithm.

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

Not applicable, as there is no "training set" for this type of IVD device in the context of an AI/ML algorithm.

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