(63 days)
For the quantitative determination of Triglycerides in serum and plasma. Triglyceride measurements are used in the diagnosis and treatment of patients with diabetes mellitus, nephrosis, liver obstruction, other diseases involving lipid merabolism, or various endocrine disorders. Elevated serum triglyceride levels are seen in primary disorders of lipid metabolism or hyperlipoproteinemia secondary to known diseases. Furthermore, in conjunction with high-density lipoprotein and total serum cholesterol, a triglyceride determination provides valuable information for the assessment of coronary heart disease risk. The clinical significance and management of hyperlipoproteinemia depends on the triglyceride distribution among the major serum lipoproteins.
DMA's Triglyceride (GPO) Procedure is intended for in vitro diagnostic use for the quantitative determination of triglycerides in human serum or plasma. It is quite similar to many other assays which have long been used for this purpose.
The provided document describes the DMA's Triglyceride (GPO) Procedure, an in vitro diagnostic device for the quantitative determination of triglycerides in human serum or plasma.
Here's an analysis of its acceptance criteria and the study that proves the device meets them:
1. A table of acceptance criteria and the reported device performance
| Performance Characteristic | Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|---|
| Linearity | Not explicitly stated, but typically a range of concentration over which the method gives results proportional to the concentration of the analyte. | to 1800 mg/dL |
| Precision | ||
| Within-Run (Within Normal Range) | Not explicitly stated, but target CVs are typically low for precision. | C.V. of approximately 0.4% |
| Within-Run (Above Normal Range) | Not explicitly stated. | C.V. of approximately 0.7% |
| Run-to-Run (Within Normal Range) | Not explicitly stated. | C.V. of approximately 4% |
| Run-to-Run (Above Normal Range) | Not explicitly stated. | C.V. of approximately 1.7% |
| Shelf-life | Not explicitly stated, but typical for diagnostic reagents. | 14 months (at 2-8°C) |
| Sensitivity (0.001A) | Not explicitly stated, but typically the lowest concentration of an analyte that the method can reliably detect. | 1.0 mg/dL |
| Interferences | ||
| Bilirubin | Not explicitly stated, but typically a threshold below which interference is insignificant. | Significant above 4.5 mg/dL |
| Hemoglobin | Not explicitly stated. | Significant above 190 mg/dL |
| Expected Values | Not explicitly defined as 'acceptance criteria' but rather as a reference range. | 36 - 173 mg/dL |
Note on Acceptance Criteria: The document does not explicitly state pre-defined acceptance criteria for each performance characteristic. Instead, it "has been shown to have the following performance characteristics". For a 510(k) submission, the comparison is often made against a predicate device, and the implicit acceptance criteria are that the new device's performance is comparable or non-inferior to the predicate.
2. Sample size used for the test set and the data provenance
The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). This level of detail is typically found in the full 510(k) submission, not the summary letter.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not provided in the document. For an in vitro diagnostic device like this, "ground truth" for method performance characteristics (linearity, precision, sensitivity, interferences) is typically established through reference methods, certified calibrators, and control materials, rather than expert interpretation of results. Clinical correlation for "expected values" would involve studies with patient populations, but the details are not available here.
4. Adjudication method for the test set
This is not applicable to the type of performance characteristics described for this in vitro diagnostic device. Adjudication methods (like 2+1, 3+1) are typically used for studies involving expert interpretation of medical images or clinical outcomes, where there might be inter-reader variability.
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
This is not applicable as the DMA Triglyceride (GPO) Procedure is an in vitro diagnostic assay for chemical analysis, not an AI-assisted diagnostic tool that would involve human readers interpreting output.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
This is not applicable. The device is a laboratory assay, not an algorithm, and its performance is inherently "standalone" in the sense that it produces a quantitative result directly. There isn't a human-in-the-loop component in the direct measurement process of this assay.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the performance characteristics described:
- Linearity, Precision, Sensitivity: Ground truth is established using certified reference materials, calibrators, and control samples with known triglyceride concentrations, or comparisons against a recognized reference method.
- Interferences: Ground truth is established by spiking samples with known concentrations of interfering substances (bilirubin, hemoglobin) and observing the impact on triglyceride measurements compared to unspiked controls or reference methods.
- Expected Values: Ground truth for these values would typically come from clinical studies on specific populations to establish reference ranges, often derived statistically from a healthy population.
The document does not provide specifics on how these ground truths were established, only that the device "has been shown to have" these characteristics.
8. The sample size for the training set
The concept of a "training set" is primarily relevant for machine learning or AI models. This is an in vitro diagnostic assay, not an AI model, so there isn't a "training set" in that context. The development and optimization of the assay would involve various experiments and optimizations, but these are not referred to as "training sets."
9. How the ground truth for the training set was established
As there is no "training set" in the context of an AI/ML model for this device, this question is not applicable. The development of the assay would involve standard laboratory practices for developing and validating chemical assays.
§ 862.1705 Triglyceride test system.
(a)
Identification. A triglyceride test system is a device intended to measure triglyceride (neutral fat) in serum and plasma. Measurements obtained by this device are used in the diagnosis and treatment of patients with diabetes mellitus, nephrosis, liver obstruction, other diseases involving lipid metabolism, or various endocrine disorders.(b)
Classification. Class I (general controls). The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to § 862.9.