BD PROBETEC NEISSERIA GONORRHOEAE (GC) Q AMPLIFIED DNA ASSAY
K081825 · Becton, Dickinson & CO · LSL · Dec 11, 2008 · Microbiology
Device Facts
Record ID
K081825
Device Name
BD PROBETEC NEISSERIA GONORRHOEAE (GC) Q AMPLIFIED DNA ASSAY
Applicant
Becton, Dickinson & CO
Product Code
LSL · Microbiology
Decision Date
Dec 11, 2008
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 866.3390
Device Class
Class 2
Attributes
Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K081825 · Dec 11, 2008
BD PROBETEC NEISSERIA GONORRHOEAE (GC) Q AMPLIFIED DNA ASSAY
Becton, Dickinson & CO
Clinical specimens (endocervical swabs, urethral swabs, vaginal swabs, urine) collected from patients in routine clinical settings (OB/GYN, STD, and family planning clinics)
Clinical performance evaluation (sensitivity and specificity) of the BD ProbeTec GC Qx Assay compared to a patient infected status (PIS) algorithm based on reference NAAT testing.
Clinical performance; Diagnostic accuracy; Routine clinical setting; Multi-site study
Clinical Evidence
Study Design
Population
Comparator
Key Endpoints
Multi-site clinical evaluation of diagnostic performance
1059 female and 479 male subjects attending OB/GYN, STD, and family planning clinics; symptomatic and asymptomatic; Sample Size: 1466 total compliant subjects (994 female, 472 male); Number of Sites: 7
Patient Infected Status (PIS) algorithm based on two reference NAATs (BD ProbeTec ET GC/AC assay and another commercially available NAAT)
Sensitivity and specificity of the BD ProbeTec GC Qx Assay by specimen type and symptomatic status
Indications for Use
The BD ProbeTec™ Neisseria gonorrhoeae (GC) Q Amplified DNA Assay, when tested with the BD Viper™ System in Extracted Mode, uses Strand Displacement Amplification technology for the direct, qualitative detection of Neisseria gonorthoeae DNA in clinician-collected female endocervical and male urethral swab specimens, patient-collected vaginal swab specimens (in a clinical setting), and male and female urine specimens (both UPT and Neat). The assay is indicated for use with asymptomatic and symptomatic females and symptomatic males to aid in the diagnosis of gonococcal urogenital disease.
Device Story
Device performs automated DNA extraction and qualitative detection of Neisseria gonorrhoeae DNA. Input: clinician-collected endocervical/urethral swabs, patient-collected vaginal swabs, or urine. Process: specimens undergo chemical lysis; DNA binds to ferric oxide particles via magnetic extraction; purified DNA eluted into SDA-compatible buffer; transferred to priming microwells; reaction mixture moved to amplification microwells; sealed; incubated in thermally-controlled fluorescent readers. System uses Strand Displacement Amplification (SDA). Output: positive, negative, or EC failure result based on peak fluorescence (MaxRFU) compared to threshold. Used in clinical settings; operated by laboratory personnel. Healthcare providers use results to aid in diagnosis of gonococcal urogenital disease, enabling timely clinical decision-making and patient treatment.
Clinical Evidence
Multi-center clinical study (7 sites, 1059 female/479 male subjects). Performance compared to Patient Infected Status (PIS) algorithm using reference NAATs. Total 5387 results analyzed. Overall sensitivity 99.3% (577/581) and specificity 99.4% (4779/4806). Subgroup analysis by specimen type and symptomatic status provided. Analytical performance included reproducibility, LoD (<50-100 cells/mL), and cross-reactivity/interference testing.
Technological Characteristics
Uses Strand Displacement Amplification (SDA) with fluorescently-labeled detector probes. Reagents provided in disposable microwells. Automated processing via BD Viper System using paramagnetic particle extraction. Detects N. gonorrhoeae DNA via MaxRFU thresholding. Includes internal extraction control.
Indications for Use
Indicated for qualitative detection of N. gonorrhoeae DNA in clinician-collected female endocervical/male urethral swabs, patient-collected vaginal swabs, and male/female urine. Population: asymptomatic and symptomatic females, symptomatic males. Aids diagnosis of gonococcal urogenital disease.
Regulatory Classification
Identification
Neisseria spp. direct serological test reagents are devices that consist of antigens and antisera used in serological tests to identify Neisseria spp. from cultured isolates. Additionally, some of these reagents consist of Neisseria spp. antisera conjugated with a fluorescent dye (immunofluorescent reagents) which may be used to detect the presence of Neisseria spp. directly from clinical specimens. The identification aids in the diagnosis of disease caused by bacteria belonging to the genus Neisseria, such as epidemic cerebrospinal meningitis, meningococcal disease, and gonorrhea, and also provides epidemiological information on diseases caused by these microorganisms. The device does not include products for the detection of gonorrhea in humans by indirect methods, such as detection of antibodies or of oxidase produced by gonococcal organisms.
Predicate Devices
BD ProbeTec ET CT/NG Amplified DNA Assays (K984631)
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.