(53 days)
ISE Compensator is for use in the calibration of Ion Selective Electrodes on Roche/Hitachi analyzers.
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Here's a breakdown of the requested information based on the provided 510(k) summary:
This document is a 510(k) summary for a medical device called "ISE Compensator," a calibrator for Ion Selective Electrodes on Roche/Hitachi analyzers. The summary focuses on demonstrating substantial equivalence to a predicate device, the "ISE Compensation Sera (K870379)." It does not contain the detailed performance study results, acceptance criteria, or ground truth establishment methods typically found in full submissions or clinical study reports.
Therefore, many of your requested points cannot be answered directly from the provided text. I will indicate where the information is "Not Available in Provided Text."
1. Table of Acceptance Criteria and Reported Device Performance
Not Available in Provided Text.
The document states: "The ISE Compensator was evaluated for value assignment and stability. Performance characteristics." However, it does not provide the specific acceptance criteria, the methodology for this evaluation, or the results of the performance characteristics (e.g., value assignment accuracy, stability data). It primarily focuses on comparing the characteristics of the new device to the predicate device to establish substantial equivalence.
2. Sample Size Used for the Test Set and Data Provenance
Not Available in Provided Text.
The summary mentions "evaluation for value assignment and stability" but does not detail the sample size (e.g., how many batches, how many runs, how many different samples were tested) or the provenance of any testing data. Given the device is a calibrator, "test set" might refer to the number of calibration events or lots tested, but this is not specified.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
Not Applicable (for this type of device, as 'ground truth' for human interpretation is not relevant) and Not Available in Provided Text.
For a calibrator, the "ground truth" would typically be derived from highly accurate reference methods or certified reference materials, not expert human interpretation. The document does not describe how the target values for the calibrator (referenced as "Refer to target value sheet of package insert") were established.
4. Adjudication Method for the Test Set
Not Applicable (for this type of device) and Not Available in Provided Text.
Adjudication methods (like 2+1 or 3+1) are used in studies where human readers interpret data, often for diagnostic imaging or pathology. For a calibrator, there is no human interpretation of a "test set" in the sense of a diagnostic decision.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance
Not Applicable.
This device is an in vitro diagnostic calibrator. It does not involve human readers interpreting cases or AI assistance in diagnostic decisions. Therefore, an MRMC comparative effectiveness study is irrelevant for this product.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Not Applicable.
This device is a calibrator, not an algorithm. The "performance" here relates to its ability to accurately calibrate an analyzer, its stability, and its formulation. There is no "algorithm only" performance to speak of in the context of this device.
7. The Type of Ground Truth Used
Indirectly indicated as "defined concentrations" for components.
The document states, "Human serum matrix preparation with defined Sodium, Potassium and Chloride concentrations." This suggests that the ground truth for these analytes is based on these "defined concentrations," likely established through highly accurate analytical methods or certified reference materials. The "Reactive Components" table also mentions "Refer to target value sheet of package insert," implying that specific, established values serve as the ground truth against which the calibrator's performance is measured.
8. The Sample Size for the Training Set
Not Applicable / Not Available in Provided Text.
Calibrators are not "trained" in the same way machine learning models are. Product development and formulation involve various experiments and optimization, but there isn't a "training set" in the context of AI/ML. If this question refers to the samples used to develop the calibrator's formulation or establish initial values, that information is not provided.
9. How the Ground Truth for the Training Set Was Established
Not Applicable / Not Available in Provided Text.
See answer to point 8.
§ 862.1150 Calibrator.
(a)
Identification. A calibrator is a device intended for medical purposes for use in a test system to establish points of reference that are used in the determination of values in the measurement of substances in human specimens. (See also § 862.2 in this part.)(b)
Classification. Class II (special controls). The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.