K061257 · Ameritek USA, Inc. · JHI · May 4, 2007 · Clinical Chemistry
Device Facts
Record ID
K061257
Device Name
DBEST HCG PANEL TEST KIT
Applicant
Ameritek USA, Inc.
Product Code
JHI · Clinical Chemistry
Decision Date
May 4, 2007
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1155
Device Class
Class 2
Indications for Use
dBest hCG Panel Test Kit is a simple one step immunochromatographic assay for rapid, semi-quantitative detection of hCG in urine with cutoffs of 25, 100, 500, 2,000 and 1.0,000 mlU/mL. The dBest hCG Panel Test Kits are for professional, physician's offices laboratory and OTC use, for the early detection of pregnancy.
Device Story
dBest hCG Panel Test Kit; one-step immunochromatographic assay; detects human chorionic gonadotropin (hCG) in urine samples. Provides semi-quantitative results at specific cutoff concentrations (25, 100, 500, 2,000, 10,000 mIU/mL). Used for early pregnancy detection in professional, physician office, and OTC settings. User applies urine sample to test device; visual interpretation of color bands indicates presence/concentration of hCG. Results assist healthcare providers or individuals in confirming pregnancy status.
Clinical Evidence
No clinical data provided; substantial equivalence based on bench testing of the immunochromatographic assay performance.
Technological Characteristics
Immunochromatographic assay; sandwich and competitive binding principles. Five embedded test strips in a disk format. Reagents: mouse monoclonal antibodies, goat anti-mouse/anti-rabbit antibodies. Standardized to WHO 3rd I.S. No electronic components or software.
Indications for Use
Indicated for the early detection of pregnancy in humans via semi-quantitative detection of hCG in urine. Intended for professional, physician office laboratory, and over-the-counter (OTC) use. Cutoff levels: 25, 100, 500, 2,000, and 10,000 mIU/mL.
Regulatory Classification
Identification
A human chorionic gonadotropin (HCG) test system is a device intended for the early detection of pregnancy is intended to measure HCG, a placental hormone, in plasma or urine. A human chorionic goadotropin (HCG) test system is a device intended for any uses other than early detection of pregnancy (such as an aid in the diagnosis, prognosis, and management of treatment of persons with certain tumors or carcinomas) is intended to measure HCG, a placental hormone, in plasma or urine.
Submission Summary (Full Text)
{0}
1
510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY ONLY TEMPLATE
A. 510(k) Number:
k061257
B. Purpose for Submission:
New device
C. Measurand:
Human chorionic gonadotropin
D. Type of Test:
Semi-quantitative
E. Applicant:
Ameritek USA, Inc.
F. Proprietary and Established Names:
dBest hCG Panel Test Kit
G. Regulatory Information:
1. Regulation section:
21 CFR 862.1155
2. Classification:
Class II
3. Product code:
LCX, JHI
4. Panel:
Chemistry (75)
{1}
H. Intended Use:
1. Intended use(s):
See Indication(s) for use below.
2. Indication(s) for use:
The dBest hCG Panel Test Kit is a simple one step immunochromatographic assay for rapid, semi-quantitative detection of hCG in urine with cutoff of 25, 100, 500, 2,000 and 10,000 mIU/mL. The dBest hCG Panel Test Kits are for professional, physician’s offices laboratory and OTC use, for the early detection of pregnancy.
3. Special conditions for use statement(s):
The device is for both over-the-counter and professional use.
4. Special instrument requirements:
None required
I. Device Description:
The dBest hCG Panel Test Kit contains the following items: dBest test disk sealed in foil pouch, urine specimen collection container, and instructions for use. The test disk contains 5 embedded test strips (zones), each with a different cutoff. The 25, 100, and 500 mIU/mL zones contain mouse monoclonal antibodies and goat anti-mouse antibody (control line). The 2,000 and 10,000 mIU/mL zones contain mouse monoclonal antibodies and goat anti-rabbit antibody (control line).
J. Substantial Equivalence Information:
1. Predicate device name(s):
Biocheck HCG Enzyme Immunoassay Test Kit
dBest hCG Pregnancy Test Kits, dBest hCG 2 IU/mL
2. Predicate 510(k) number(s):
k991741
k953606, k001215
3. Comparison with predicate:
{2}
| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicates |
| Indications for Use | Early detection of pregnancy | Same |
| Intended End Use Population | Professional and OTC use | Professional (k991741 & k001215); OTC (k953606) |
| Principle | Sandwich and competitive assay | Sandwich (k991741 & k953606); competitive (k001215) |
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Type of Test | Semi-quantitative | Qualitative (k953606 & k001215); quantitative (k991741) |
| Specimen Type | Urine | Serum (k991741) |
| Test Design/Format | Multiple test strips embedded in test disk | Single test strip(s) (k953606 & k001215) |
K. Standard/Guidance Document Referenced (if applicable):
None were referenced.
L. Test Principle:
The test principle is based on the sandwich technique (for three of the strips) and competitive binding (for two of the strips).
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
One hundred twenty hCG free urine specimens collected in-house were divided into six groups of twenty each. Five groups of urine were spiked with hCG to 25, 100, 500, 2,000, and 10,000 mIU/mL, and one group remained unspiked. The specimens were then blind labeled and tested with the dBest hCG Panel Test Kit at three physician’s office laboratories and a reference
{3}
laboratory. The results obtained from the three POL sites agreed 99% with the expected results. The results obtained from the reference laboratory agreed 100% with the expected results. The overall agreement was 99.5%.
Reproducibility was evaluated at three different sites. Urine samples containing hCG at 0, 25, 100, 500, 2,000 and 10,000 mIU/mL were tested twice a day in two different assays, each day for twenty days. This evaluated between day, between assay, and within-day. The results of the three sites yielded 100% agreement.
b. Linearity/assay reportable range:
Not applicable
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
The device was standardized to the World Health Organization (WHO) 3rd I.S.
d. Detection limit:
The dBest hCG Panel Test Kit will detect hCG in urine at concentrations of 25, 100, 500, 2,000, and 10,000 mIU/mL. For each detection concentration, three samples were prepared by spiking hCG to concentrations, at the cutoff, +25% above the cutoff and -25% below the cutoff and tested using the dBest hCH Panel Test Kit. The results are as follows:
| -25 % | Results | Cutoff | Results | +25% | Results |
| --- | --- | --- | --- | --- | --- |
| | | | | | |
| 18.75 mIU/mL | 20/20 negative | 25 mIU/mL | 20/20 positive | 31.25 mIU/mL | 20/20 positive |
| 75 mIU/mL | 20/20 negative | 100 mIU/mL | 20./20 positive | 125 mIU/mL | 20./20 positive |
| 375 mIU/mL | 20/20 negative | 500 mIU/mL | 19/20 positsive | 625 mIU/mL | 20/20 positive |
| 1500 mIU/mL | 20/20 negative | 2000 mIU/mL | 19/20 positive | 2500 mIU/mL | 20/20 positive |
| 7500 mIU/mL | 20/20 negative | 10000 mIU/mL | 19/20 positive | 12500 mIU/mL | 20/20 positive |
e. Analytical specificity:
Cross reactivity studies were performed on urine samples spiked with the following structurally and physiologically related hormones referenced to WHO: 500 mIU/mL luteinizing hormone, 1000 mIU/mL follicle stimulating hormone, and 1000 μIU/mL thyroid stimulating hormone. All zones of the
{4}
pregnancy test yielded the expected (negative) results.
Potentially interfering substances such as prescription and OTC drugs, protein and glucose were added to normal urine specimens devoid of hCG as well as specimens containing 25, 100, 500, 2,000, and 10,000 mIU/mL hCG. All samples without hCG consistently gave negative results. All samples with the various hCG concentrations consistently gave positive results.
f. Assay cut-off:
See Detection limit above.
2. Comparison studies:
a. Method comparison with predicate device:
An initial method comparison study using sixty (60) negative urine samples spiked with hCG at three different concentrations (0, 25, and 2000 mIU/mL) was conducted. The samples were blind labeled and tested with the subject device and two commercially available dBest hCG products. Testing was performed at three physician's office laboratories and a reference laboratory. The results showed greater than 99% agreement.
An additional study was performed to demonstrate method comparison across all dBest cutoffs. Five groups of urines were spiked with hCG to concentrations equal to the cutoff, 25% above the cutoff, and 25% below the cutoff. These were tested on the dBest hCG Panel Test Kit and commercially available pregnancy tests and challenged the precision of the device. The dBest hCG Panel Test Kit was in complete agreement with the commercially available pregnancy tests at -25% of the cutoff and at +25% of the cutoff for all five cutoff levels, and at the cutoff level of 25 and 100 mIU/mL. There was 98% agreement between the tests at the 500, 2,000, and 10,000 mIU/mL cutoff level.
To assess method comparison with natural, unspiked patient samples, a study was conducted using forty (40) non-pregnant and pregnant urine and serum samples. The patient's urine sample was assayed on the dBest test and their serum sample was run on an hCG ELISA. The results were as follows:
| Patients (n) | dBest test zone mIU/mL | ELISA mIU/mL |
| --- | --- | --- |
| 20 | < 25 | Negative < 5 |
| 4 | 25 | 26 – 48 |
| 6 | 500 | 98 – 620 |
| 10 | 2,000 – 10,000 | 1,980 – 30,020 |
{5}
See other clinical supportive data below for additional comparisons.
b. Matrix comparison:
Not applicable
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):
Clinical Study
A clinical study was conducted to evaluate the accuracy of the dBest hCG Panel Test Kit. The primary objectives were to observe hCG concentrations to determine the accuracy of the test by comparing urine and serum results from the same patient, assayed on the dBest hCG Panel Test Kit and an ELISA test, respectively. Samples from one hundred and twenty (120) women aged 18 years or older, forty (40) at three sites, were used. Nurses performed the urine tests and lab technicians performed the serum tests.
The results of the comparison of hCG concentrations are presented below:
| Patients (n) | dBest test zone mIU/mL | ELISA mIU/mL |
| --- | --- | --- |
| 20 | 25 | 28 – 78 |
| 24 | 100 | 78 – 250 |
| 25 | 500 | 386 – 7,240 |
| 18 | 2,000 | 1,684 – 7,829 |
| 33 | 10,000 | 8,640 – 51,980 |
Most of the hCG concentrations fell in the appropriate dBest test zone. One patient had an hCG ELISA result of 7,240 mIU/mL, but the dBest HCG Panel Test Kit showed 500 mIU/mL. One other hCG ELISA result at 9829 was almost five times the cutoff of 2,000. However, the dBest test correctly produced a positive result for the 2000 mIU/mL cutoff level.
{6}
7
# Consumer Studies
A consumer study of persons with various age, racial, educational, and professional backgrounds was conducted. hCG free urine specimens were divided into six groups of twenty each. Five groups of urines were spiked with hCG to 25, 100, 500, 2,000 and 10,000 mIU/mL, and one group remained unspiked. All the specimens (60 each for the consumers and technicians of the reference laboratory) were blind labeled and tested. At the 0, 100, and 500 mIU/mL levels, the results all agreed between the consumers and reference laboratory. At each of the 25, 2,000, and 10,000 mIU/mL levels, two results were read as negative by consumers, resulting in an overall agreement of 54/60 or 90%.
To supplement the study above, hCG free urine specimens collected in-house were divided into six groups of forty each. Five groups of samples were spiked with hCG to 25, 100, 500, 2,000, and 10,000 mIU/mL and one remained unspiked. Those (240) specimens were blind labeled and tested, with half (120) done by consumers and the other half (120) done by laboratory personnel. After the consumers completed their test, they were asked to complete a survey to assess their understanding of the revised package insert instructions. The results were as follows:
At 0, 100, and 500 mIU/mL, there was 100% agreement between the consumer and laboratory results. At 25, 2,000, and 10,000 mIU/mL, three consumers read a positive sample as negative. Therefore, the overall agreement between the consumers and professionals was 117/120 or 98.75%.
Out of 120 consumers, 64 thought the instructions were good, 16 thought they were very good, and 37 thought they were average. This demonstrated an acceptable readability of the new package insert.
4. Clinical cut-off:
Not applicable
5. Expected values/Reference range:
The expected values are based on literature.
N. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
{7}
O. Conclusion:
The submitted information in this premarket notification is complete and supports substantial equivalence decision.
8
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.