Search Results

The AXINON® LDL-o Test System is intended to measure lipoprotein particles to quantify LDLp) using nuclear magnetic resonance (NMR) spectroscopy that measures the 600 MHz proton nuclear magnetic resonance (NMR) spectrum of a human serum sample. LDL-p concentration values are used in conjunction with other lipid measurements and clinical evaluation to aid in the management of lipoprotein disorders associated with cardiovascular disease. This test system is for professional use only.

The AXINON® LDL-p Test System involves measurement of the 600 MHz proton NMR spectrum of a serum sample, deconvolution of the composite signal at approximately 0.85 ppm to produce signal amplitudes of lipoprotein subclass proportions that contribute to the composite serum signal, and conversion of these subclass signal amplitudes to lipoprotein subclass concentrations. The 0.85 ppm serum NMR signal arises mainly from the methyl group protons of the lipids carried in the VLDL, LDL and HDL subclasses of varying diameters. The NMR signals from the various lipids within the lipoprotein subclasses have unique and distinctive shapes and frequencies, uncovered by the granular decomposition of the composite serum signal. Each of these lipid signal representatives is proportional to the number of subclass particles emitting the signal, which enables subclass particle concentrations to be calculated from the subclass signal amplitudes derived from the spectral deconvolution analysis. LDL subclass particle concentrations, in units of nanomoles of particles per liter (nmol/L), are summed to give the reported total LDL particle concentration (LDL-p).

The AXINON® LDL-p Test System including the AXINON® Analyzer is a clinical laboratory analyzer that employs nuclear magnetic resonance spectroscopic detection to quantify multiple analytes in biological fluid specimens, specifically human serum.

The AXINON® Analyzer system is distributed across two separate computers:

The workstation running AXINON® Software is the main host of the system. It controls user interfaces, data handling, results calculation, schedules and manages all activities required to process a sample, and manages remote access to the NMR system.

In addition, AXINON® Analyzer comes with the optional software utility AXINON® Sample Wizard that supports manual sample preparation procedures.

The NMR workstation controls all magnet operations and the hardware in the sample handler.

Here's a breakdown of the acceptance criteria and study information for the AXINON® LDL-p Test System, based on the provided text:

Acceptance Criteria and Reported Device Performance

*n.d. = not disclosed in the provided text for the predicate device.

Study Details

1. Sample sizes used for the test set and the data provenance:

   • Linearity Study: 11 levels, five replicates for each level (total 55 measurements). Data provenance is not explicitly stated but implies laboratory-controlled samples.
   • Precision Study: Six concentration levels, measured in duplicates in two runs each day over a period of 20 days with three lots of reagents. Each sample ID (Pool) had 80 measurements (80 replicates across the duration of the study). Data provenance implies pooled patient samples and commercial control.
   • Method Comparison: 102 samples from volunteers against the comparative method, distributed over three different sites. Data provenance: Volunteers.
   • Limit of Quantitation: 20 replicates from 4 different serum pools of low concentration, measured within 3 days. Data provenance implies pooled serum samples.
   • Limit of Blank: 30 samples with three lots of reagents. Data provenance implies laboratory-controlled samples.
   • Limit of Detection: Three sample pools measured in eight dilution levels per pool in replicates of seven over three days. Data provenance implies laboratory-controlled samples.
   • Interfering Substances: Two human serum specimens with different LDL-p concentrations for each substance, in five replicates each with a single lot of reagents on a single device. Data provenance implies human serum.
   • Expected Values: 40 serum samples from apparently healthy subjects (20 men, 20 women, residents in the United States). Data provenance: United States.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • This device is an in-vitro diagnostic (IVD) test system intended to quantify a biomarker (LDL-p). The "ground truth" is established through analytical methods and comparison to a legally marketed predicate device, rather than expert interpretation of images or clinical findings. Therefore, no "experts" in the sense of clinicians or radiologists were used to establish the ground truth for the test set as would typically be the case for AI imaging devices. The predicate device's established performance serves as the comparative "truth" for demonstrating substantial equivalence.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable. This is an IVD device measuring an analyte, not an imaging device requiring adjudication of findings by multiple readers.

4. 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 is an IVD device measuring an analyte, not an AI-assisted diagnostic imaging device for human readers.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, the performance data presented (linearity, precision, detection limits, interference) is for the device operating in a standalone, algorithm-only mode. It measures LDL-p directly from serum samples using NMR spectroscopy and computational analysis without human intervention in the measurement process itself. The system is "for professional use only," meaning it's operated by trained laboratory professionals, but its core function of quantifying LDL-p is automated.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The ground truth for the analytical validation (linearity, precision, etc.) is established through reference analytical methods and comparison to predetermined values or a legally marketed predicate device. For instance, linearity is shown against known concentrations, and method comparison is against the NMR LipoProfile® test on the Vantera Clinical Analyzer. The reference interval for expected values was transferred from a published scientific paper (Matyus et al., Clinical Biochemistry 47 (2014) 203-210), implying a form of published scientific literature/data-based ground truth for expected clinical ranges.

7. The sample size for the training set:

   • The document describes a "Test System" for measurement, which implies a fixed algorithm rather than a continuously learning AI model. Therefore, "training set" in the context of deep learning models is not directly applicable here. The analytical validation studies described use various sample sets for verification and validation of the established algorithm's performance.

8. How the ground truth for the training set was established:

   • As explained above, this is not a machine learning model in the sense of requiring a "training set" with ground truth labels. The underlying principles of NMR spectroscopy and the deconvolution algorithms are based on established scientific and mathematical principles. The analytical performance is verified against established laboratory standards and comparisons to a predicate device.

Ask a specific question about this device