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The Interlab Acid Hemoglobin Electrophoresis is a qualitative test system intended for the electrophoretic separation of hemoglobins to confirm the identity of clinically relevant hemoglobins such as A, F, S and C. It is to be used in conjunction with the Interlab Alkaline Hemoglobin Electrophoresis test kit. The Acid Hemoglobin test kit employs cellulose acetate supported on Mylar® as the medium and is for in vitro diagnostic use. The test can be automated on the Microtech 672 PC and Microtech 648 ISO instruments.

The InterLab Acid Hemoglobin test kits for the electrophoretic separation of hemoglobin in whole blood and are intended for In-Vitro diagnostic use only. The InterLab Acid Hemoglobin Electrophoresis Test Devices provide qualitative identification of abnormal hemoglobin bands visualized by staining of the fractions. The principle of hemoglobin electrophoresis is based upon the visualization of specific hemoglobin bands following separation by electrophoresis. Dilutions of a patient's specimen are placed on separate tracks (fingers) on a cellulose acetate slide six fingers shaped, and the major hemoglobin groups are separated by electrophoresis. The migration rate depends on the temperature, pH, ionic force of the solution and proportions of the reactants. After electrophoresis, the slide is processed to remove excess soluble materials through a washing step. Fractionated hemoglobins are stained. The excess of stain is removed by a destaining step. The slides visually read to identify the bands present.

Here's a breakdown of the acceptance criteria and study information for the InterLab Acid Hemoglobin Electrophoresis device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Comparative Study (Primary Equivalence Study): 71 samples (combined normal and pathological).
• Data Provenance: Samples were obtained from "normal and suspected pathological patients submitted for routine testing to the clinical or hospital laboratory." The studies were run at two clinical facilities. The raw geographical origin of the samples (e.g., country) is not specified. The data is retrospective as it involved samples "submitted for routine testing."
• Sample Size for Analytical Sensitivity: Not explicitly stated as a single number. Samples were "serially diluted" to determine detection limits.
• Sample Size for Precision (Within Slide): 3 different serum samples, each run in replicate (12 or 8 replicates per sample, depending on the kit).
• Sample Size for Precision (Slide to Slide): 3 different serum samples, each run in triplicate on multiple separate slides (30, 33, or 36 replicates per sample, depending on the kit).

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

• Number of Experts: Not explicitly stated. The determination of ground truth relied on "the laboratory's routine commercially available test system following the laboratory's procedure." This implies trained laboratory personnel interpreted the results of these reference methods, but specific numbers or qualifications of individual experts are not provided.
• Qualifications of Experts: Not specified beyond the implication that they are trained laboratory personnel operating "routine commercially available test system" in clinical or hospital laboratories.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly described. The text states "Comparison was accomplished exclusively by visual inspection of the electrophoretic patterns" against reference methods. For the primary equivalence study, there was a "100% agreement to the reference methods for the observed bands at both sites," suggesting a direct comparison or concordance rather than a separate adjudication process beyond the visual comparison.

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

• No MRMC comparative effectiveness study was done. This device is an in-vitro diagnostic test, not an AI-assisted diagnostic tool for human readers. The assessment focused on the device's performance against established laboratory methods.

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

• This device is not an algorithm, but a laboratory test system. The "InterLab Acid Hemoglobin Electrophoresis" system involves a physical process of electrophoresis, followed by visual inspection of stained bands. Therefore, a standalone algorithm performance study is not applicable. The device itself, when operated, performs the separation and produces the bands that are then visually interpreted. The performance reported (e.g., 100% agreement) is of the combined system's output.

7. The Type of Ground Truth Used

• Ground Truth Type: For the primary equivalence study, the ground truth was established by comparison to existing "commercially available test system[s]" (reference methods) in the clinical laboratory setting.
  • Site one's reference: "HPLC analysis of blood samples displays values of hemoglobin fractions that are outside the reference ranges...electrophoresis is required as an additional confirmatory test."
  • Site two's reference: "commercially available Alkaline Hemoglobin Electrophoresis system to screen the patient samples. Fractions identified as potentially abnormal are run on the Acid Hemoglobin test for confirmation."

8. The Sample Size for the Training Set

• The document implies that this is a 510(k) submission for a device, and the studies described are validation studies for device performance, not training for a machine learning algorithm. Therefore, there is no explicit "training set" mentioned in the context of the device's development or evaluation as described here.

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

• Since there is no explicit "training set" for an algorithm, this question is not applicable in the context of the provided document. The device operates based on the physical-chemical principles of electrophoresis, not on a machine learning model trained on data.

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