The Glucose2 assay is used for the quantitation of glucose in human serum, plasma, urine, or cerebrospinal fluid (CSF) on the ARCHITECT c System. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.
Device Story
Glucose2 is an enzymatic assay for the ARCHITECT c8000 clinical chemistry analyzer. It uses human serum, plasma, urine, or CSF samples. The assay employs a hexokinase/G-6-PDH methodology: glucose is phosphorylated by hexokinase in the presence of ATP and magnesium to form glucose-6-phosphate; G-6-PDH then oxidizes this to 6-phosphogluconate, reducing NAD to NADH. The resulting NADH is measured spectrophotometrically at 340 nm. The increase in absorbance is proportional to glucose concentration. The device is used in clinical laboratory settings by trained technicians. Results are provided to physicians to assist in diagnosing and managing carbohydrate metabolism disorders. The assay is traceable to NIST SRM 965.
Clinical Evidence
Bench testing only. Studies included within-laboratory precision (20-day), system reproducibility, accuracy against NIST SRM 965b, linearity, interference testing (endogenous/exogenous), and method comparison against the predicate (n=130-148 samples per matrix). All performance metrics met pre-defined acceptance criteria.
Indicated for the quantitation of glucose in human serum, plasma, urine, or CSF to aid in the diagnosis and treatment of carbohydrate metabolism disorders, including diabetes mellitus, neonatal hypoglycemia, idiopathic hypoglycemia, and pancreatic islet cell carcinoma.
Regulatory Classification
Identification
A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.
Special Controls
*Classification.* Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.
Predicate Devices
Glucose (k060383)
Submission Summary (Full Text)
{0}
FDA
U.S. FOOD & DRUG
ADMINISTRATION
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
ASSAY ONLY
## I Background Information:
A 510(k) Number
K252357
B Applicant
Abbott Ireland
C Proprietary and Established Names
Glucose2
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| CFR | Class II | 21 CFR 862.1345 - Glucose Test System | CH - Clinical Chemistry |
## II Submission/Device Overview:
A Purpose for Submission:
New device
B Measurand:
Glucose
C Type of Test:
Quantitative enzymatic assay based on Hexokinase/G-6-PDH methodology
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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K252357 - Page 2 of 13
# III Intended Use/Indications for Use:
## A Intended Use(s):
See Indications for Use below.
## B Indication(s) for Use:
The Glucose2 assay is used for the quantitation of glucose in human serum, plasma, urine, or cerebrospinal fluid (CSF) on the ARCHITECT c System.
Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.
## C Special Conditions for Use Statement(s):
Rx - For Prescription Use Only
## D Special Instrument Requirements:
ARCHITECT c8000
# IV Device/System Characteristics:
## A Device Description:
The Glucose2 assay kit consists of two ready to use reagent solutions, R1 and R2.
R1: Buffer solution containing 6.300 g/L b-NADP, disodium salt, 2.420 g/L adenosine triphosphate (ATP) and sodium azide as a preservative.
R2: Substrate solution containing hexokinase 19.200 KU/L, glucose-6-phosphate dehydrogenase 6.400 KU/L and sodium azide as a preservative.
## B Principle of Operation:
Glucose is phosphorylated by Hexokinase (HK) in the presence of adenosine triphosphate (ATP) and magnesium ions to produce glucose-6-phosphate (G-6-P) and adenosine diphosphate (ADP). Glucose-6-phosphate dehydrogenase (G-6-PDH) specifically oxidizes G-6-P to 6-phosphogluconate with the concurrent reduction of nicotinamide adenine dinucleotide (NAD) to nicotinamide adenine dinucleotide reduced (NADH). One micromole of NADH is produced for each micromole of glucose consumed. The NADH produced absorbs light at 340 nm and can be detected spectrophotometrically as an increased absorbance.
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V Substantial Equivalence Information:
A Predicate Device Name(s): Glucose
B Predicate 510(k) Number(s): K060383
C Comparison with Predicate(s):
| Device & Predicate Device(s): | K252357 | K060383 |
| --- | --- | --- |
| Device Trade Name | Glucose2 | Glucose |
| General Device Characteristic Similarities | | |
| Intended Use/Indications For Use | The assay is used for the quantitation of glucose used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma. | Same |
| Specimen type | Human serum, plasma, urine, or cerebrospinal fluid (CSF). | Same |
| Analytical Measuring Interval (AMI) | Serum/Plasma: 5–800 mg/dL
Urine: 1–800 mg/dL | Same |
| General Device Characteristic Differences | | |
| Analytical Measuring Interval (AMI) | CSF: 2–800 mg/dL | CSF: 1–800 mg/dL |
| Limits of Measurement | Serum/Plasma:
Limit of Blank: 0.17 mg/dL
Limit of Detection: 0.30 mg/dL
Limit of Quantitation: 1.16 mg/dL
Urine
Limit of Blank: 0.15 mg/dL
Limit of Detection: 0.29 mg/dL | Serum:
Limit of Detection: 2.5 mg/dL
Limit of Quantitation: 5.0 mg/dL
Urine/CSF:
Limit of Detection: 1.0 mg/dL |
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| Device & Predicate Device(s): | K252357 | K060383 |
| --- | --- | --- |
| | Limit of Quantitation: 0.47 mg/dL
CSF
Limit of Blank: 0.23 mg/dL
Limit of Detection: 0.35 mg/dL
Limit of Quantitation: 1.25 mg/dL | Limit of Quantitation: 1.0 mg/dL |
## Planned modifications by PCCP:
In addition to the similarities and differences between the candidate and the predicate device listed in the table above, the candidate device has an authorized predetermined change control plan (PCCP) for modifications to the device to enable use of specimens collected in potassium fluoride/EDTA tubes. The PCCP included the testing protocol, comparator sample type (i.e., serum), proposal to support sample stability, and pre-defined acceptance criteria. The protocol to validate potassium fluoride/EDTA tubes in the PCCP was consistent with the study conducted for validation of other sample types claimed through a matrix comparison study (see section VII.B.2 below). The acceptance criteria reviewed included criteria for slope, intercept, and predicted differences at medical decision limits with confidence and it was determined that if the results meet the acceptance criteria, the use of samples collected in potassium fluoride/EDTA tubes on the candidate device (i.e., Glucose2 assay on ARCHITECT c8000) would remain as safe and effective as the predicate device. Following verification of this additional specimen collection tube, the device labeling will be updated in accordance with the authorized PCCP to provide users with current information regarding compatible specimen collection tubes for the Glucose2 assay on the ARCHITECT c8000.
## VI Standards/Guidance Documents Referenced:
Clinical and Laboratory Standards Institute (CLSI) EP05-A3: Evaluation of Precision of Quantitative Measurement Procedures; Approved Guideline - Third Edition.
CLSI EP06: Evaluation of the Linearity of Quantitative Measurement Procedures – Second Edition.
CLSI EP07: Interference Testing in Clinical Chemistry- Third Edition.
CLSI EP09c – Measurement Procedure Comparison and Bias Estimation Using Patient Samples. Third Edition.
CLSI EP17-A2: Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures; Approved Guideline - Second Edition
CLSI EP37: Supplemental Tables for Interference Testing in Clinical Chemistry- First Edition
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VII Performance Characteristics (if/when applicable):
A Analytical Performance:
1. Precision/Reproducibility:
The sponsor provided separate precision studies supporting use of: (1) serum, (2) urine, and (3) CSF. The Glucose2 assay was evaluated in accordance with CLSI EP05-A3.
Within-Laboratory Precision
Serum and Urine: Each of the five samples was tested on three ARCHITECT c8000 instruments for serum and urine and one ARCHITECT c8000 instrument for CSF using three lots of the Glucose2 reagents. Two controls and 3 human serum, urine, and CSF panels were tested in duplicates per run, two runs per day, over 20 days for a total of 80 measurements per instrument/lot, where a unique reagent lot and a unique calibrator lot are paired with one instrument. The performance from a representative combination is shown in the tables below. The within-laboratory SD and %CV includes within-run, between-run, and between-day variance components.
Serum
| Sample | n | Mean (mg/dL) | Within-Run (Repeatability) | | Within-Laboratory | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV |
| Control Level 1 | 80 | 43 | 0.5 | 1.2 | 0.5 | 1.3 |
| Control Level 2 | 80 | 132 | 1.0 | 0.8 | 1.3 | 1.0 |
| Panel 1 | 80 | 10 | 0.1 | 1.1 | 0.1 | 1.1 |
| Panel 2 | 80 | 20 | 0.2 | 1.3 | 0.4 | 1.9 |
| Panel 3 | 80 | 740 | 4.1 | 0.5 | 5.9 | 0.8 |
Urine
| Sample | n | Mean (mg/dL) | Within-Run (Repeatability) | | Within-Laboratory | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV |
| Control Level 1 | 80 | 41 | 0.4 | 1.0 | 0.5 | 1.2 |
| Control Level 2 | 80 | 338 | 2.5 | 0.7 | 2.8 | 0.8 |
| Panel 1 | 80 | 3 | 0.0 | 0.0 | 0.0 | 0.0 |
| Panel 2 | 80 | 100 | 0.8 | 0.8 | 1.1 | 1.1 |
| Panel 3 | 80 | 732 | 6.0 | 0.8 | 8.2 | 1.1 |
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CSF
| Sample | n | Mean (mg/dL) | Within-Run (Repeatability) | | Within-Laboratory | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV |
| Control Level 1 | 80 | 64 | 0.6 | 1.0 | 0.7 | 1.1 |
| Control Level 2 | 80 | 32 | 0.4 | 1.2 | 0.5 | 1.5 |
| Panel 1 | 80 | 10 | 0.1 | 1.1 | 0.1 | 1.1 |
| Panel 2 | 80 | 253 | 1.9 | 0.8 | 2.4 | 1.0 |
| Panel 3 | 80 | 744 | 5.3 | 0.7 | 7.0 | 0.9 |
## Reproducibility
Each of the five samples was tested using one lot of the Glucose2 reagents on three ARCHITECT c8000 instruments. Each instrument was operated by a different technician, and each individual sample set was prepared independently. Two controls and 3 human serum, urine, and CSF panels were tested in 3 replicates at 2 separate times per day on 5 different days. Reproducibility study results are summarized below:
Serum
| Sample | n | Mean (mg/dL) | Repeatability | | Within-Laboratorya | | Reproducibility^{}[] b | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV | SD | %CV |
| Control Level 1 | 90 | 42 | 0.4 | 1.0 | 0.5 | 1.2 | 0.8 | 1.8 |
| Control Level 2 | 90 | 132 | 1.0 | 0.7 | 1.7 | 1.3 | 1.7 | 1.3 |
| Panel 1 | 90 | 10 | 0.3 | 2.6 | 0.3 | 2.8 | 0.3 | 2.9 |
| Panel 2 | 90 | 20 | 0.1 | 0.7 | 0.2 | 0.9 | 0.2 | 0.9 |
| Panel 3 | 90 | 745 | 6.9 | 0.9 | 7.9 | 1.1 | 8.0 | 1.1 |
Urine
| Sample | n | Mean (mg/dL) | Repeatability | | Within-Laboratorya | | Reproducibility^{}[] b | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV | SD | %CV |
| Control Level 1 | 90 | 40 | 0.6 | 1.4 | 0.6 | 1.5 | 0.8 | 1.9 |
| Control Level 2 | 90 | 338 | 2.8 | 0.8 | 3.4 | 1.0 | 3.4 | 1.0 |
| Panel 1 | 90 | 3 | 0.1 | 4.4 | 0.2 | 6.9 | 0.2 | 6.9 |
| Panel 2 | 90 | 99 | 0.8 | 0.8 | 1.1 | 1.1 | 1.5 | 1.5 |
| Panel 3 | 90 | 733 | 5.6 | 0.8 | 6.5 | 0.9 | 7.3 | 1.0 |
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CSF
| Sample | n | Mean (mg/dL) | Repeatability | | Within-Laboratory1 | | Reproducibility | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV | SD | %CV |
| Control Level 1 | 90 | 63 | 0.9 | 1.4 | 1.1 | 1.7 | 1.3 | 2.0 |
| Control Level 2 | 90 | 32 | 0.4 | 1.4 | 0.6 | 1.8 | 0.6 | 1.9 |
| Panel 1 | 90 | 10 | 0.1 | 1.1 | 0.1 | 1.1 | 0.1 | 1.1 |
| Panel 2 | 90 | 244 | 2.3 | 0.9 | 2.9 | 1.2 | 2.9 | 1.2 |
| Panel 3 | 90 | 751 | 5.9 | 0.8 | 7.5 | 1.0 | 7.6 | 1.0 |
<a>1</a> Includes within-run, between-run, and between-day variability
<a>2</a> Includes within-run, between-run, between-day, and between-instrument variability
## 2. Linearity:
Linearity studies were performed according to the CLSI EP06-2nd edition guideline. Thirteen (13) levels of samples were prepared by mixing different portions of high sample and a blank sample. Each sample was tested in replicates of four (serum), seven (urine), and eight (CSF) on a single instrument using three reagent lots (serum and urine) and one reagent lot (CSF) in a single run. The results were analyzed using weighted least squares linear regression analysis, with the intercept forced through zero. Results are summarized in the table below:
| Sample | Slope | R | Range Tested (mg/dL) | Max absolute Deviation of samples (mg/dL)a | Max percent Deviation of samplesb |
| --- | --- | --- | --- | --- | --- |
| Serum | 1.0366 | 0.9995 | 2-844 | 0 | 5.2 |
| Urine | 1.0270 | 0.9996 | 1-866 | 0 | 3.0 |
| CSF | 1.0223 | 0.9996 | 2-850 | 0 | 2.7 |
<a>1</a> Samples <17 mg/dL (serum), <10 mg/dL (urine), and <13 mg/dL (CSF) were evaluated against the absolute deviation from linearity.
<a>2</a> Samples ≥17 mg/dL (serum), ≥10 mg/dL (urine), and ≥13 mg/dL (CSF) were evaluated against the percent deviation from linearity.
Based on the results, the sponsor concluded that the Glucose2 test system demonstrated linearity over the claimed range of 5 - 800 mg/dL for serum, 2 - 800 mg/dL for CSF, and 1 - 800 mg/dL for urine.
## Dilution Recovery Study
A dilution study was performed to support the claimed extended measuring range. Five high concentration serum samples were diluted manually and by the instrument using saline in a 1:5 ratio. The data support the 1:5 dilution claim in the labeling.
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3. Analytical Specificity/Interference:
The effect on the quantitation of analyte in the presence of potentially interfering substances using the Glucose2 assay was determined using serum and urine samples.
Glucose levels of approximately 40 mg/dL and 220 mg/dL in serum and approximately 15 mg/dL and 90 mg/dL in urine were tested. Each sample was assayed in 10 replicates. The tables below summarize the results for serum and urine samples indicating the highest interferent level at which the percent interference was within ± 6% for serum and ± 10% for urine. For any substance, if the difference between the test and control means was greater than the allowed difference, dose response testing and analysis was conducted to assess the highest concentration limit below which no significant interference is expected.
Endogenous Interference
Serum
| Potential Interferent | Highest Concentration Tested Without Significant Interference |
| --- | --- |
| Unconjugated Bilirubin | 40 mg/dL |
| Conjugated Bilirubin | 40 mg/dL |
| Hemoglobin | 1,000 mg/dL |
| Total Protein | 12 g/dL |
| Triglycerides | 1,070 mg/dL |
Urine
| Potential Interferent | Highest Concentration Tested Without Significant Interference |
| --- | --- |
| Ascorbate | 200 mg/dL |
| Protein | 50 mg/dL |
| Sodium Oxalate | 60 mg/dL |
Exogenous Interference
Serum
| Potentially Interfering Substance | Highest Concentration Tested Without Significant Interference |
| --- | --- |
| Acetaminophen | 16 mg/dL |
| Acetylcysteine | 15 mg/dL |
| Acetylsalicylic acid | 3 mg/dL |
| 5-amino-4-imidazole-carboxamide (AIC) | 0.3 mg/dL |
| Ampicillin-Na | 8 mg/dL |
| Ascorbic acid | 6 mg/dL |
| Biotin | 3510 ng/mL |
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| Potentially Interfering Substance | Highest Concentration Tested Without Significant Interference |
| --- | --- |
| Ca-dobesilate | 6 mg/dL |
| Cefoxitin | 660 mg/dL |
| Cyclosporine | 0.2 mg/dL |
| Doxycycline | 2 mg/dL |
| Eltrombopag | 30 mg/dL |
| Ibuprofen | 22 mg/dL |
| Levodopa | 0.8 mg/dL |
| Methyldopa | 2.5 mg/dL |
| 3-methyl-(triazen-1-yl) imidazole-4-carboxamide (MTIC) | 0.06 mg/dL |
| Metronidazole | 13 mg/dL |
| Phenylbutazone | 33 mg/dL |
| Rifampicin | 5 mg/dL |
| Sodium heparin | 4 U/mL |
| Sulfapyridine | 30 mg/dL |
| Sulfasalazine | 30 mg/dL |
| Temozolomide | 2 mg/dL |
| Tetracycline | 3 mg/dL |
| Theophylline (1,3-dimethylxanthine) | 6 mg/dL |
Urine
| Potentially Interfering Substance | Highest Concentration Tested Without Significant Interference |
| --- | --- |
| Acetic acid (8.5N) | 6.25 mL/dL |
| Boric acid | 250 mg/dL |
| Hydrochloric acid (6N) | 2.5 mL/dL |
| Nitric acid (6N) | 5.0 mL/dL |
| Sodium carbonate | 1.25 g/dL |
| Sodium fluoride | 400 mg/dL |
4. Assay Reportable Range:
Assays reportable ranges are 5 - 800 mg/dL for serum, 2 - 800 mg/dL for CSF, and 1 - 800 mg/dL for urine.
5. Traceability, Stability, Expected Values (Controls, Calibrators, or Methods):
This assay is traceable to SRM 965 National Institute of Standards and Technology (NIST) Standard Reference Material.
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6. Detection Limit:
The limit of blank (LoB), limit of detection (LoD), and limit of quantitation (LoQ) studies were performed in accordance with CLSI EP17-A2.
Limit of blank (LoB) study was performed by testing 5 blank samples, using 3 reagent lots over 3 days on 2 different instruments. Each day, for each reagent lot, 10 replicate measurements were recorded (60 results per reagent lot). The LoB was calculated non-parametrically at the 95th percentile for each lot. The higher LoB of the 3 reagent lots was chosen as the assay's LoB.
Limit of detection (LoD) study was performed by testing 5 low level samples using 3 reagent lots over 3 days on 2 instruments. Each day, for each reagent lot, 10 replicate measurements were recorded (60 results per reagent lot). LoD was calculated non-parametrically. The higher LoD of the 3 lots was chosen as the assay's LoD.
Limit of quantitation (LoQ) study was performed using 5 low level samples measured over 3 days on 2 instruments using 3 reagent lots. Each day, for each reagent lot, 10 replicate measurements were recorded (60 results total). The sponsor defined the LoQ as the lowest concentration at which the maximum allowable precision of 20 %CV was met.
The studies supported the following detection limit claims:
| Sample Type | Units | LoB | LoD | LoQ |
| --- | --- | --- | --- | --- |
| Serum | mg/dL | 0.17 | 0.30 | 1.16 |
| Urine | mg/dL | 0.15 | 0.29 | 0.47 |
| CSF | mg/dL | 0.2 | 0.4 | 1.25 |
7. Assay Cut-Off:
Not applicable.
B Comparison Studies:
1. Method Comparison with Predicate Device:
Method comparison studies were performed in accordance with CLSI EP09c comparing the results from the candidate device to the predicate device. A minimum of 100 samples with analyte concentrations within the claimed analytical measurement ranges were evaluated for each sample matrix type respectively over four days. Passing-Bablok regression analysis was performed using the first replicate of the candidate device results compared to the mean of the duplicate results from the comparator device, and results are summarized in the table below.
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| Sample Type | N | Slope | Intercept | R | Concentration Range (mg/dL) |
| --- | --- | --- | --- | --- | --- |
| Serum | 130 | 0.97 | 6 | 1.00 | 6 -797 |
| Urine | 148 | 0.98 | 4 | 1.00 | 1- 800 |
| CSF | 135 | 1.00 | 3 | 1.00 | 3 - 772 |
2. Matrix Comparison:
A matrix comparison study was performed to evaluate the performance of $\mathrm{K}_2\mathrm{EDTA}$ , $\mathrm{K}_3\mathrm{EDTA}$ , Lithium heparin, Lithium heparin plasma separator, Sodium heparin, Sodium fluoride/EDTA, Sodium fluoride/potassium oxalate, and Potassium fluoride/citrate/EDTA samples compared to serum samples for the Glucose2 test. Sixty nine (69) paired samples were evaluated for each combination and less than $12\%$ of the total samples were altered to cover the entire claimed measurement range. Each sample was assayed in duplicate and Passing-Bablok regression analysis was performed using the first replicate of the evaluation tube compared to the mean of the control serum measurement, and results are summarized in the table below.
| Evaluation Tube Type | N | Concentration Range (mg/dL) | Correlation Coefficient (r) | Intercept | Slope |
| --- | --- | --- | --- | --- | --- |
| Dipotassium EDTA | 69 | 5 - 755 | 1.00 | 3 | 1.00 |
| Lithium heparin | 69 | 5 - 740 | 1.00 | 3 | 1.00 |
| Sodium heparin | 69 | 5 - 750 | 1.00 | 2 | 1.01 |
| Lithium heparin plasma separator | 69 | 5 - 755 | 1.00 | 3 | 1.01 |
| Serum separator, plastic | 69 | 5 -750 | 1.00 | 1 | 1.01 |
| Tripotassium EDTA | 69 | 5 -757 | 1.00 | 1 | 1.01 |
| Sodium fluoride/EDTA | 69 | 5 -758 | 1.00 | 2 | 1.01 |
| Potassium Fluoride/Citrate/EDTA | 69 | 5 - 755 | 1.00 | 5 | 1.00 |
| Sodium Fluoride/Potassium Oxalate | 69 | 5 - 756 | 1.00 | 0 | 1.02 |
C Clinical Studies:
1. Clinical Sensitivity:
Not applicable.
K252357 - Page 11 of 13
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2. Clinical Specificity:
Not applicable.
3. Other Clinical Supportive Data (When 1. and 2. Are Not Applicable):
Not applicable.
D Clinical Cut-Off
Not applicable.
E Expected Values/Reference Range:
The sponsor’s claimed Expected values/ Reference range were derived from *literature.
Reference Range (Serum/Plasma)*
| Fasting | Range (mg/dL) | Range* (mmol/L) |
| --- | --- | --- |
| Cord | 45–96 | 2.50–5.33 |
| Premature | 20–60 | 1.11–3.33 |
| Neonate | 30–60 | 1.67–3.33 |
| Newborn 1 Day | 40–60 | 2.22–3.33 |
| Newborn > 1 Day | 50–80 | 2.78–4.44 |
| Child | 60–100 | 3.33–5.55 |
| Adult | 74–100 | 4.11–5.55 |
| Adult > 60 Years | 82–115 | 4.55–6.38 |
| Adult > 90 Years | 75–121 | 4.16–6.72 |
Urine
| | Range | Range |
| --- | --- | --- |
| Random* | 1–15 mg/dL | 0.06–0.83 mmol/L* |
| 24 Hour Urine Sample** | < 0.5 g/day | < 2.78 mmol/day |
CSF
| | Range (mg/dL) | Range+ (mmol/L) |
| --- | --- | --- |
| Infant, Child | 60–80 | 3.33–4.44 |
| Adult | 40–70 | 2.22–3.89 |
+ Alternate result units were calculated by Abbott.
*Adeli K, Ceriotti F, Nieuwesteeg M. Reference information for the clinical laboratory. In: Rifai N, Horvath AR, Wittwer CT, editors. Tietz Textbook of Clinical Chemistry and Molecular Diagnostics. 6th ed. Elsevier; 2018:1745-1818.
** Wu AHB, editor. Tietz Clinical Guide to Laboratory Tests. 4th ed. Saunders Elsevier; 2006:448.
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# 24-Hour Urinary Excretion
To convert results from mg/dL to g/day (24 hour urinary excretion)
24-hour excretion = [(V × c) ÷ 100 000] g/day
Where:
V = 24 hour urine volume (mL)
c = analyte concentration (mg/dL)
To convert results from mmol/L to mmol/day (24-hour urinary excretion):
24-hour excretion = [(V × c) ÷ 1000] mmol/day
Where:
V = 24 hour urine volume (mL)
c = analyte concentration (mmol/L)
The sponsor recommends that each laboratory determine its own reference range based upon its particular locale and population characteristics.
# VIII Proposed Labeling:
The labeling supports the finding of substantial equivalence for this device.
# IX Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.