HITACHI CLINICAL ANALYZER S TEST REAGENT CARTRIDGE GLUCOSE (GLU)
K120369 · Hitachi Chemical Diagnostics, Inc. · CFR · May 10, 2012 · Clinical Chemistry
Device Facts
Record ID
K120369
Device Name
HITACHI CLINICAL ANALYZER S TEST REAGENT CARTRIDGE GLUCOSE (GLU)
Applicant
Hitachi Chemical Diagnostics, Inc.
Product Code
CFR · Clinical Chemistry
Decision Date
May 10, 2012
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1345
Device Class
Class 2
Indications for Use
The S TEST reagent cartridge for glucose is intended for the quantitative measurement of glucose in serum, lithium heparin plasma, K3 EDTA plasma, and sodium citrate plasma on the Hitachi Clinical Analyzer. The test system is intended for use in clinical laboratories or physician office laboratories. For in vitro diagnostic use only. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus and idiopathic hypoglycemia.
Device Story
The Hitachi Clinical Analyzer is a bench-top, automated wet chemistry system for clinical or physician office laboratories. It utilizes single-use plastic reagent cartridges containing two reagents (R1 and R2) and a reaction cell. The operator places sample cups and reagent cartridges into the analyzer carousels. The system automatically pipettes samples and reagents, mixes them, and incubates the reaction. A multi-wavelength photometer measures absorbance at 340/450 nm. The device uses an enzymatic hexokinase method: glucose is phosphorylated to glucose-6-phosphate, which is then converted to 6-phosphogluconic acid by G6PD, reducing NADP to NADPH. The resulting change in absorbance at 340 nm is proportional to glucose concentration. The analyzer calculates and displays results in approximately 15 minutes. The output assists clinicians in diagnosing and managing carbohydrate metabolism disorders. Reagent cartridges include a dot code label containing chemistry parameters and calibration factors.
Clinical Evidence
Clinical performance was evaluated at three external physician office laboratory (POL) sites. The study assessed precision and accuracy (method comparison) using 50-53 blinded serum samples per site compared against the Roche cobas 6000. Accuracy results showed high correlation (r=0.99) with slopes ranging from 0.97 to 1.05. Precision studies (n=30 results per level) demonstrated within-run %CVs ranging from 0.8% to 4.5% and total %CVs from 1.1% to 4.6% across low, intermediate, and high concentration samples.
Technological Characteristics
Bench-top wet chemistry analyzer. Reagent cartridges: plastic, 13.5mm x 28mm x 20.2mm. Sensing: multi-wavelength photometer (340/450 nm). Energy: electrical. Connectivity: dot code label for parameter/calibration data. Sterilization: N/A. Software: embedded firmware for analyzer control and photometric data processing.
Indications for Use
Indicated for quantitative glucose measurement in serum, lithium heparin, K3 EDTA, and sodium citrate plasma for patients requiring diagnosis or treatment of carbohydrate metabolism disorders, including diabetes mellitus and idiopathic hypoglycemia. For use in clinical or physician office laboratories.
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.
{0}
1
510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY
A. 510(k) Number:
k120369
B. Purpose for Submission:
New device
C. Measurand:
Glucose
D. Type of Test:
Quantitative Photometric
E. Applicant:
Hitachi Chemical Diagnostics, Inc
F. Proprietary and Established Names:
Hitachi Clinical Analyzer S TEST Reagent Cartridge for Glucose
G. Regulatory Information:
1. Regulation section:
21 CFR § 862.1345- glucose test system
2. Classification:
Class II
3. Product code:
CFR
4. Panel:
Chemistry (75)
{1}
H. Intended Use:
1. Intended use(s):
See indications for use below
2. Indication(s) for use:
The S TEST reagent cartridge for glucose is intended for the quantitative measurement of glucose in serum, lithium heparin plasma, K3 EDTA plasma, and sodium citrate plasma on the Hitachi Clinical Analyzer. The test system is intended for use in clinical laboratories or physician office laboratories. For in vitro diagnostic use only. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus and idiopathic hypoglycemia.
3. Special conditions for use statement(s):
Prescription use only
4. Special instrument requirements:
Hitachi Clinical Analyzer (previously cleared in k111753)
I. Device Description:
The Hitachi Clinical Analyzer is an automatic, bench-top, wet chemistry system intended for use in clinical laboratories or physician office laboratories. The analyzer unit includes a single probe, an incubation rotor, carousels for sample cups and reagent cartridges, and a multi-wavelength photometer. The single-use reagent cartridges may be placed in any configuration on the carousel, allowing the user to develop any test panel where the reagent cartridges are available.
The S TEST reagent cartridges are made of plastic and include two small reservoirs capable of holding two separate reagents (R1 and R2), separated by a reaction cell/photometric cuvette. The cartridges also include a dot code label that contains all chemistry parameters, calibration factors, and other production-related information, e.g., expiration dating. The dimensions of the reagent cartridges are: 13.5 mm (W) × 28 mm (D) × 20.2 mm (H).
GLU Reagent (1):
- Hexokinase (Yeast) 4.0 U/mL
- Nicotinamide adenine dinucleotide phosphate (oxidized form) 3.0 g/L
- Glucose-6-phosphate dehydrogenase (E.coli) 2.0 U/mL
- 2-Amino-2-hydroxymethyl-1,3-propanediol Buffer (pH7.2) 0.1 mol/L
GLU Reagent (2):
- 2'-Deoxyadenosine-5'-triphosphate sodium salt 5.0 mmol/L
- 2-Amino-2-hydroxymethyl-1,3-propanediol Buffer (pH8.4) 0.1 mol/L
{2}
J. Substantial Equivalence Information:
1. Predicate device name(s):
Roche cobas 8000
2. Predicate 510(k) number(s):
k100853
3. Comparison with predicate:
| Characteristic | Hitachi S TEST Systems | PREDICATE(S) |
| --- | --- | --- |
| Glucose Test System | K number- k120369 | Roche K number- k100853 |
| Intended Use | Quantitative determination of glucose | Same |
| Testing Environment | Physician office or clinical lab | Clinical lab- cobas |
| Test Principle | Enzymatic method (Hexokinase method) | UV Test- enzymatic reference method with hexokinase |
| Specimen Type | Human serum or plasma | Human serum, plasma, CSF, or urine |
| Reportable Range | 5 to 500 mg/dL | 2 to 750 mg/dL |
| Detection Wavelength | 340/450 nm | 700/340 nm |
| Detection Limit | 5 mg/dL | 2 mg/dL |
| Linearity | 5 to 500 mg/dL | 2 to 750 mg/dL |
| Precision | %CVs ranged from 2.1% to 3.9% | %CVs range from 0.7% to 1.3%
(from product labeling) |
K. Standard/Guidance Document Referenced (if applicable):
CLSI - Protocols for Determination of Limits of Detection and Limits of Quantitation - EP17-A
CLSI - Evaluation of Precision Performance of Clinical Chemistry Devices - EP05-A2
CLSI - Interference Testing in Clinical Chemistry - EP07-A2
L. Test Principle:
Glucose is phosphorylated to glucose-6-phosphate by hexokinase (HK) in the presence of ATP. When the glucose-6-phosphate is converted into 6-phosphogluconic acid by glucose-6-phosphate dehydrogenase (G6PD), NADP is converted into NADPH with an increase in absorbance at 340 nm. The concentration of glucose can be determined by measuring the amount of change in absorbance of NADPH.
{3}

# M. Performance Characteristics (if/when applicable):
# 1. Analytical performance:
# a. Precision/Reproducibility:
Three levels of serum samples (low, middle, and high levels of GLU) were tested in duplicate with 2 cartridges, twice a day, for 20 days, for a total of 80 results per level to assess in-house precision. The precision estimates are described below.
GLU- Low, Level 1, Summary
| GLU | Within-Run | Total |
| --- | --- | --- |
| Mean (mg/L) | 73.0 | 73.0 |
| SD (mg/L) | 2.86 | 2.88 |
| %CV | 3.9% | 3.9% |
GLU- Middle, Level 2, Summary
| GLU | Within-Run | Total |
| --- | --- | --- |
| Mean (mg/dL) | 213.8 | 213.8 |
| SD (mg/dL) | 3.11 | 4.49 |
| %CV | 1.5% | 2.1% |
GLU- High, Level 3, Summary
| GLU | Within-Run | Total |
| --- | --- | --- |
| Mean (mg/L) | 306.1 | 306.1 |
| SD (mg/L) | 3.33 | 9.20 |
| %CV | 1.1% | 3.0% |
{4}
Three levels of serum samples (A= low, B= medium, and C= high) were tested at three POL sites, six times a day for five days. The precision estimates are described below.
Glucose (mg/dL)
n = 30 replicates per sample per site
| Site | Sample | Mean | Within-run Precision | | Total Precision | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | SD (mg/dL) | %CV | SD (mg/dL) | %CV |
| Site 1 | A | 59.3 | 2.6 | 4.5% | 2.8 | 4.6% |
| Site 2 | A | 59.1 | 0.7 | 1.1% | 1.0 | 1.7% |
| Site 3 | A | 59.1 | 1.2 | 2.1% | 1.4 | 2.3% |
| | | | | | | |
| Site 1 | B | 117.3 | 4.0 | 3.4% | 4.4 | 3.7% |
| Site 2 | B | 117.7 | 0.9 | 0.8% | 1.3 | 1.1% |
| Site 3 | B | 114.9 | 1.6 | 1.4% | 1.7 | 1.7% |
| | | | | | | |
| Site 1 | C | 358.7 | 11.5 | 3.2% | 12.8 | 3.6% |
| Site 2 | C | 354.8 | 3.5 | 1.0% | 6.8 | 1.9% |
| Site 3 | C | 343.9 | 7.1 | 2.1% | 10.2 | 3.0% |
b. Linearity/assay reportable range:
11 serum samples (0, 1.5, 4.0, 6.5, 8.0, 15.0, 29.0, 132, 251, 468, 690 mg/dL) were assigned their reference values arithmetically and were tested in duplicate by the Hitachi Clinical Analyzer, and the mean Hitachi results (y-axis) were plotted against the assigned values (x-axis).
| | Linearity (assigned) | Regression analysis | reportable range (within linearity) |
| --- | --- | --- | --- |
| GLU | 2 mg/dL and 655 mg/dL | y = 1.038x-0.4173
R² = 0.9992 | 5 mg/dL and 500 mg/dL |
The data supported the sponsor's claimed range of the device (5-500 mg/dL).
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
Glucose S Test cartridge lot is calibrated using standard material traceable to ReCCS (Reference Material Institute for Clinical Chemistry Standards) standard serum JCCRM 521.
Shelf life/ stability of the cartridge:
Real-time, shelf-life stability studies for the GLU reagent cartridge were performed. A two-level control set, (92 and 212 mg/dL, respectively) was tested in replicates of
{5}
five with three lots of cartridges across six analyzers according to standard procedure.
Testing occurred at Time 0 (baseline), and again at approximately, 6, 9, 11, 12 and 13 months; the storage condition was refrigerated (2 to 8 °C). The studies supported the sponsor’s claimed shelf life of 12 months at 2 to 8 °C.
d. Detection limit:
Per CLSI EP17-A, blank samples for each reagent system were assayed 20 times per day for three days for a total of 60 replicate results to determine LOB and LOD. Low samples were assayed 20 times with the specific reagent cartridges to determine the detection limit below:
LoD for GLU: 0.3 mg/dL
LoB for Glu: (mean of the 57th and 58 point) -0.28
LoQ study was performed as follows: three clinical samples were diluted to target 5.5 mg/dL glucose. Each sample was tested with one lot of cartridges 6x/day on 3 different days with three different analyzers for a total of 54 replicate results per sample. From these data, the means, standard deviations (SDs), and percent coefficients of variation (%CVs) were calculated. The % CVs ranged from 14.5 to 17.5 % with all three < 20 %. The data supported the sponsor’s claimed LoQ of 5 mg/dL.
e. Analytical specificity:
The studies followed CLSI EP7-A2. The data demonstrated that GLU was not affected by the following substances at the levels noted below. No significant interference is defined by the sponsor as the highest level of interferent that is within 10% of the neat sample.
The interference studies demonstrated that the S TEST for GLU was resistant to high levels of ascorbic acid (up to 50 mg/dL), hemoglobin up to 500 mg/dL for low (50 mg/dL) glucose levels and 1000 mg/dL for high (200 mg/dL) glucose levels, unconjugated bilirubin up to 6.25 mg/dL for low (50 mg/dL) glucose levels and 50 mg/dL for high (50 mg/dL) glucose levels, and triglycerides (up to 800 mg/dL).
f. Assay cut-off:
Not applicable
2. Comparison studies:
a. Method comparison with predicate device:
The in-house method comparison study evaluated 100 serum samples; matched aliquots
6
{6}
were assayed with both the Hitachi Clinical Analyzer with S TEST GLU reagent cartridge and the Roche/Hitachi cobas 6000. The data were analyzed by least squares linear regression (Hitachi = y-axis), and the results were as follows:
## Glucose (mg/dL)
n= 100
y= 0.99x -2.7
correlation coefficient (r) = 0.999
95% confidence interval of the slope = 0.98 to 1.02; 95% confidence interval of the y-intercept = -5.5 to 0.8
Range (serum) = 12 to 441 mg/dL
Method comparison at POL sites:
| Site # | n | Range (mg/dL) | Regression equation | CI slope | CI intercept | r |
| --- | --- | --- | --- | --- | --- | --- |
| 1 | 53 | 75 to 375 | y = 1.01x - 1.1 | 0.99 to 1.02 | -2.7 to 0.6 | 0.99 |
| 2 | 52 | 69 to 361 | y = 0.97x -0.1 | 0.96 to 0.99 | -2.1 to 1.9 | 0.99 |
| 3 | 51 | 75 to 399 | y = 1.05x - 2.5 | 1.03 to 1.07 | 1.03 to 1.07 | 0.99 |
## b. Matrix comparison:
Serum/Plasma Comparison Study
A study was performed to validate the use of sodium citrate (Na citrate), lithium heparinized, and K3 EDTA plasma as alternatives to serum for the Hitachi Clinical Analyzer with S TEST GLU reagent cartridges Thirty-eight (38) matched serum/plasma samples that spanned the glucose dynamic range were assayed in singleton and the results were compared using least squares liner regression (plasma = y-axis). The performance characteristics were as follows.
N = 38
Range (serum) = 12 to 441 mg/dL
| | Na Citrate Plasma | Heparinized Plasma | K3 EDTA Plasma |
| --- | --- | --- | --- |
| Slope (95% CIs) | 0.98 (0.96 to 1.00) | 1.00 (0.98 to 1.02) | 1.00 (0.99 to 1.02) |
| y-intercept (95% CIs) | -4.6 (-8.2 to -0.8) | -2.1 (-5.8 to 1.6) | -0.3 (-3.1 to 2.6) |
| r | 0.99 | 0.99 | 0.99 |
## 3. Clinical studies:
a. Clinical Sensitivity:
{7}
Not Applicable
b. Clinical specificity:
Not Applicable
c. Other clinical supportive data (when a. and b. are not applicable):
None
4. Clinical cut-off:
Not applicable
5. Expected values/Reference range:
Reportable range: 5 - 500 mg/dL
Reference range (US, fasting serum): 60 – 95 mg/dL*
It is recommended that each laboratory determine the expected values for its particular population.
* Tietz, Tietz Fundamentals of Clinical Chemistry, 4th Edition, WB Saunders Company, (1996
N. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
O. 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.