The Calcium assay is used for the quantitation of Calcium in human serum, plasma, or urine.
Device Story
In vitro diagnostic assay for quantitative measurement of calcium in human serum, plasma, or urine. Uses Arsenazo-III dye methodology; dye reacts with calcium in acid solution to form blue-purple complex. Color intensity measured spectrophotometrically at 660 nm; absorbance proportional to calcium concentration. Used in clinical laboratory settings on automated systems (AEROSET and ARCHITECT c8000). Healthcare providers use results to diagnose and monitor parathyroid, bone, and renal diseases, and tetany. Provides objective quantitative data to support clinical decision-making regarding patient metabolic status.
Clinical Evidence
Bench testing only. Precision evaluated per CLSI EP5-A and EP10-A (total CV ≤ 3%). Linearity established from 2 to 24 mg/dL. Analytical specificity tested against common interferents (bilirubin, hemoglobin, Intralipid, etc.); interference < 5% for most. Method comparison studies (n=47 to 121 samples) against predicate showed high correlation (r > 0.99).
Indicated for the measurement of total calcium levels in human serum, plasma, and urine. Used in the diagnosis and treatment of parathyroid disease, bone diseases, chronic renal disease, and tetany.
Regulatory Classification
Identification
A calcium test system is a device intended to measure the total calcium level in serum. Calcium measurements are used in the diagnosis and treatment of parathyroid disease, a variety of bone diseases, chronic renal disease and tetany (intermittent muscular contractions or spasms).
Predicate Devices
Abbott Clinical Chemistry Calcium assay (k981578)
Submission Summary (Full Text)
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510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY ONLY TEMPLATE
A. 510(k) Number:
k062855
B. Purpose for Submission:
New Device
C. Measurand:
Calcium
D. Type of Test:
Quantitative
E. Applicant:
Abbott Laboratories
F. Proprietary and Established Names:
Abbott Clinical Chemistry Architect/Aeroset Calcium
G. Regulatory Information:
1. Regulation section:
21 CFR § 862.1145 Calcium Test System
2. Classification:
Class II
3. Product code:
CJY
4. Panel:
Clinical Chemistry
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H. Intended Use:
1. Intended use(s):
A calcium test system is a device intended to measure the total calcium level in serum, plasma, and urine.
2. Indication(s) for use:
A calcium test system is a device intended to measure the total calcium level in serum, plasma, and urine. Calcium measurements are used in the diagnosis and treatment of parathyroid disease, a variety of bone diseases, chronic renal disease and tetany (intermittent muscular contractions or spasms).
3. Special conditions for use statement(s):
Prescription Use Only
4. Special instrument requirements:
Abbott Architect / Aeroset analyzers only
I. Device Description:
The Abbott Clinical Chemistry Architect/Aeroset Calcium assay is supplied as a liquid, ready-to-use single reagent kit containing Arsenazo-III dye at a concentration of 348 µmol/L and sodium acetate at a concentration of 90 mmol/L.
The 41 mL reagent will produce approximately 10,000 tests and the 74 mL reagent will produce approximately 19,000 tests.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Abbott Clinical Chemistry Calcium assay
2. Predicate 510(k) number(s):
k981578
3. Comparison with predicate:
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| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Analyte Measured | Calcium | Same |
| Intended Use | The Calcium assay is used for the quantitation of Calcium in human serum, plasma, or urine. | Same |
| Assay Principle | Arsenazo-III dye reacts with calcium in an acid solution to form a blue-purple complex. The color developed is measured at 660 nm and is proportional to the calcium concentration in the sample. | Same |
| Detection of Analyte | Endpoint | Same |
| Matrices | Serum, plasma, or urine | Same |
| Reference Ranges | Serum/Plasma (mg/dL): • Cord 8.2 to 11.2 • Newborn -Premature 6.2 to 11.0 -0 to 10 days 7.6 to 10.4 -10 days to 24 months 9.0 to 11.0 • Child, 2 to 12 years 8.8 to 10.8 • Adult 8.4 to 10.2 • Male > 60 years 8.8 to 10.0 Urine: 100 – 300 mg/day | Same |
| Analysis Medium | Aqueous solution | Same |
| Use of Calibrators | Yes | Yes |
| Use of Controls | Yes | Yes |
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Estimated number of tests per kit: | 41 mL kit: 10,000 74 mL kit: 19,000 | 84 mL kit: 3, 032 |
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K. Standard/Guidance Document Referenced (if applicable):
CLSI Document EP5-A: Evaluation of Precision Performance of Clinical Chemistry Devices; Approved Guideline
CLSI Document EP9-A2: Method Comparison and Bias Estimation Using Patient Samples; Approved Guideline – Second Edition
CLSI Document EP10-A: Preliminary Evaluation of Quantitative Clinical Laboratory Methods; Approved Guideline – Second Edition
CLSI document NCCLS EP17-A: Protocols for Determination of Limits of Detection and Limits of Quantitation; Approved Guideline
L. Test Principle:
Arsenazo-III dye reacts with calcium in an acid solution to form a blue-purple complex. The color developed is measured at 660 nm and is proportional to the calcium concentration in the sample.
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Serum: the total precision as well as the precision for each component of variation (between-day, between-run, and within-run) was estimated in accordance with CLSI Document EP5-A. A minimum of two control levels at normal and abnormal analyte concentrations were tested. These controls were evaluated over 20 days, two runs per day, and two replicates per run. Precision was reported as the total percent CV.
Urine: five day precision studies were conducted on the AEROSET and ARCHITECT c8000 Systems in accordance with CLSI Document EP10-A. This study was intended to supplement data obtained from the twenty-day serum precision study and provides a limited assessment of the performance of the assay with the urine matrix. A minimum of two control levels at normal and abnormal analyte concentrations were tested. These controls were evaluated over five days, two runs per day, and five replicates per run. Precision was reported as the total %CV.
The precision of the Calcium assay is ≤ 3% total CV for serum and urine.
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b. Linearity/assay reportable range:
A minimum of nine samples at various concentrations spanning the desired linear range of the assay were run in a minimum of four replicates. At least one level was included which exceeded the desired linear range. The percent recovery for each sample was determined by dividing the mean observed result by the expected value. The sponsor’s acceptable difference between the observed result and expected value was within ±5% or ±0.2 mg/dL of the accepted values from 2 to 18 mg/dL and within ±10% of expected values from 18 to 24 mg/dL for serum and urine.
Data generated indicate Calcium is linear from 2 to 24 mg/dL for both serum and urine matrices.
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
The reagent calibration stability was determined by the recovery method on multiple lots of Calcium reagent. Fresh reagent was calibrated with fresh calibrators on Day 0. Control material and a prepared test sample near the linear high were analyzed on Day 0, 1, 7, 14, 15, 21, 29, 30, 31, and 33. The target for % recovery was 95 to 105% of the Day 0 results. All test points up to and including Day 33 met the target for % recovery. The resulting calibration stability claim is 30 days.
The reagent open onboard stability was determined by the recovery method on multiple lots of Calcium reagent. Fresh reagent was calibrated with fresh calibrators on Day 0. Control material and a prepared test sample near the linear high were analyzed on Day 0, 1, 7, 14, 15, 21, 29, 30, 31, and 33. All test points up to and including Day 33 met the target for % recovery. The open onboard stability claim is 30 days.
d. Detection limit:
To determine the Limit of Quantitation (LOQ), test levels near the linear low for the Calcium assay were run in replicates of 10, on three instruments, two runs per instrument. The limit of quantitation is the concentration of analyte which has imprecision less than or equal to 20% CV. The Limit of Detection (LOD) testing for Calcium was performed using a study design based on CLSI protocol EP17-A. The LOQ and LOD for calcium were calculated to be 1.0 and 0.5 mg/dL, respectively. When marketed, the assay will report values down to 2.0 mg/dL as the default setting. However, the sponsor states that some customers may require the information on LOD and LOQ and therefore the sponsor has elected to leave this information in the labeling.
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e. Analytical specificity:
For serum samples, the sponsor evaluated the effects of bilirubin, hemoglobin, and Intralipid. For urine samples the sponsor evaluated the effects of acetic acid, ascorbate, boric acid, glucose, hydrochloric acid (HCl), nitric acid, and protein. Human serum samples at the medical decision level of the analyte and urine samples were spiked with various levels of interferents. A minimum of four replicates of each interferent level and four replicates of reference sample were run. The percent recovery was determined by dividing the mean result of each interferent sample by the mean result of the reference sample. According to the sponsor, the level of interference was considered acceptable if there was no more than ± 5% difference between the interferent result and the reference result. Testing was performed using the AEROSET System.
The percent interference was within ± 5% difference for serum samples containing 60 mg/dL bilirubin; 2,000 mg/dL hemoglobin; and 500 mg/dL Intralipid at Medical Decision Level 1 (7 to 8 mg/dL) and Medical Decision Level 2 (10 to 12 mg/dL).
The percent interference was within ± 5% difference for urine samples containing 200 mg/dL ascorbate, 250 mg/dL boric acid, 500 mg/dL glucose, 2.5 mL/dL hydrochloric acid (6 N), and 50 mg/dL protein.
The percent interference was > 10% difference for urine samples containing 6.25 mL/dL acetic acid (8.5 N) and 5.0 mL/dL nitric acid (6 N).
f. Assay cut-off: Not applicable.
2. Comparison studies:
a. Method comparison with predicate device:
A method comparison study was conducted in accordance with CLSI Document EP9-A2. As part of these studies, a total of 10 serum samples and 7 urine samples were spiked with calcium carbonate to generate high analytical levels. A linear regression analysis was performed comparing the results for each method with the following results:
AEROSET vs. predicate device – serum
One-hundred two serum samples ranging from 2.4 to 24.6 mg/dL were run and compared using the new reagent vs. the predicate:
Slope 0.96
Y-intercept 0.31
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Corr. Coeff. 0.9993
AEROSET vs. predicate device – urine
Forty-seven urine samples ranging from 2.2 to 25.2 mg/dL were run and compared using the new reagent vs. the predicate:
Slope 0.95
Y-intercept 0.17
Corr. Coeff. 0.9994
ARCHITECT vs. predicate device – serum
Ninety-six serum samples ranging from 2.4 to 24.6 mg/dL were run and compared using the new reagent vs. the predicate:
Slope 0.96
Y-intercept 0.31
Corr. Coeff. 0.9989
ARCHITECT vs. predicate device – urine
Forty-seven urine samples ranging from 2.2 to 25.2 mg/dL were run and compared using the new reagent vs. the predicate:
Slope 0.94
Y-intercept 0.17
Corr. Coeff. 0.9986
ARCHITECT vs. AEROSET – serum
One hundred twenty-one serum samples ranging from 2.3 to 23.4 mg/dL were run and compared using the new reagent only:
Slope 1.00
Y-intercept 0.04
Corr. Coeff. 0.9979
ARCHITECT vs. AEROSET – urine
Forty-seven urine samples ranging from 2.2 to 23.9 mg/dL were run and compared using the new reagent only:
Slope 0.99
Y-intercept 0.00
Corr. Coeff. 0.9991
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b. Matrix comparison:
To establish the compatibility of specimen collection tubes with the Calcium assay, fifteen samples were tested using each of the collection tubes to be evaluated. The serum tube used for the baseline was the glass tube; all other specimen tubes were plastic. The sponsor defined the acceptable differences as $\pm 5\%$ or $\pm 0.2\mathrm{mg / dL}$ difference from the serum baseline tube, whichever is greater. Testing was performed using the AEROSET System. Using this criteria, comparability with the plain glass serum tube was observed for lithium heparin (Li Hep) (with or without gel barrier), sodium heparin (Na Hep), and Serum Separator Tubes (SST) for the Calcium assay.
3. Clinical studies:
a. Clinical Sensitivity:
Not applicable.
b. Clinical specificity:
Not applicable.
c. Other clinical supportive data (when a. and b. are not applicable):
4. Clinical cut-off:
Not applicable.
5. Expected values/Reference range:
SERUM/PLASMA
| | Range (mg/dL) | Range (mmol/L) |
| --- | --- | --- |
| Cord | 8.2 to 11.2 | 2.05 to 2.80 |
| Newborn | | |
| Premature | 6.2 to 11.0 | 1.55 to 2.75 |
| 0 to 10 days | 7.6 to 10.4 | 1.90 to 2.60 |
| 10 days to 24 mo | 9.0 to 11.0 | 2.25 to 2.75 |
| Child 2 to 12 years | 8.4 to 10.2 | 2.20 to 2.70 |
| Adult | 8.8 to 10.0 | 2.10 to 2.55 |
| Male > 60 years | 8.8 to 10.0 | 2.20 to 2.50 |
URINE
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| Calcium in diet | Range (mg/day) | Range (mmol/day) |
| --- | --- | --- |
| Calcium-free | 5 to 40 | 0.13 to 1.00 |
| Low to average | 50 to 150 | 1.25 to 3.75 |
| Average | | |
| (800 mg or 20 mmol/day) | 100 to 300 | 2.50 to 7.50 |
# 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.