The sponsor used an existing adjudicated clinical cohort to evaluate the device's prognostic value for 12-month risk stratification of all-cause mortality, cardiac-related mortality, and heart-related hospitalization in patients with new onset or worsening heart failure.
Adjudicated cohort of 861 subjects prospectively followed for 6 and 12 months.
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Indications for Use
The Alere NT-proBNP for Alinity i assay is a chemiluminescent microparticle immunoassay (CMIA) used for the in vitro quantitative determination of N-terminal pro B-type natriuretic peptide (NT-proBNP) in human serum and plasma on the Alinity i system. The Alere NT-proBNP for Alinity i assay can also be used as an aid in 12-month risk stratification for prognosis of all-cause mortality, cardiac-related mortality, and heart-related hospitalization in patients presenting to the emergency department, diagnosed with new onset or worsening HF. The assay may further be used in the risk stratification of patients with acute coronary syndrome (ACS).
Device Story
Automated two-step chemiluminescent microparticle immunoassay (CMIA) for quantitative NT-proBNP measurement in human serum/plasma; used on Alinity i system in clinical laboratory settings. Sample incubated with anti-NT-proBNP coated paramagnetic microparticles; washed; incubated with acridinium-labeled anti-NT-proBNP conjugate; washed; trigger solutions added. Chemiluminescent reaction measured as relative light units (RLU) proportional to analyte concentration. Results interpreted by clinicians alongside medical history and physical exam to aid HF diagnosis and risk-stratify patients for 12-month adverse outcomes (mortality/hospitalization) or ACS. Benefits include objective prognostic data for ED triage and management of HF/ACS patients.
Clinical Evidence
Prospective 12-month follow-up study of 861 subjects with adjudicated HF diagnosis presenting to the ED. Primary endpoint: composite of all-cause mortality, cardiac-related mortality, or heart-related hospitalization. Kaplan-Meier analysis and Cox proportional hazards regression showed statistically significant association between higher NT-proBNP quartiles and increased risk of composite events. Adjusted hazard ratios for Q4 vs Q1 were 1.56 (95% CI: 1.14, 2.12) for composite outcome and 8.24 (95% CI: 2.66, 25.50) for cardiac-related mortality. Nonclinical performance (precision, linearity, specificity) previously established in K241176.
Technological Characteristics
Chemiluminescent microparticle immunoassay (CMIA); quantitative measurement; sandwich immunoassay principle. Measuring interval: 15.8 to 35,000.0 pg/mL. No hook effect up to 372,620 pg/mL. Designed for use on the Alinity i system. Traceability per CLSI EP32-R.
Indications for Use
Indicated for patients presenting to the emergency department with clinical suspicion of new onset or worsening heart failure (HF) for diagnostic aid, and for patients diagnosed with new onset or worsening HF for 12-month risk stratification of mortality and hospitalization. Also indicated for risk stratification of patients with acute coronary syndrome (ACS).
Regulatory Classification
Identification
The B-type natriuretic peptide (BNP) test system is an in vitro diagnostic device intended to measure BNP in whole blood and plasma. Measurements of BNP are used as an aid in the diagnosis of patients with congestive heart failure.
Special Controls
*Classification.* Class II (special controls). The special control is “Class II Special Control Guidance Document for B-Type Natriuretic Peptide Premarket Notifications; Final Guidance for Industry and FDA Reviewers.”
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FDA
U.S. FOOD & DRUG
ADMINISTRATION
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
ASSAY ONLY
## I Background Information:
A 510(k) Number
K253539
B Applicant
Axis-Shield Diagnostics Limited
C Proprietary and Established Names
Alere NT-proBNP for Alinity i
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| NBC | Class II | 21 CFR 862.1117 - B-Type Natriuretic Peptide Test System | CH - Clinical Chemistry |
## II Submission/Device Overview:
A Purpose for Submission:
Expansion of Indications for Use
B Measurand:
NT-proBNP
C Type of Test:
Quantitative immunoassay
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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K253539 - Page 2 of 8
# III Intended Use/Indications for Use:
## A Intended Use(s):
See Indications for Use below.
## B Indication(s) for Use:
The Alere NT-proBNP for Alinity i assay is a chemiluminescent microparticle immunoassay (CMIA) used for the in vitro quantitative determination of N-terminal pro B-type natriuretic peptide (NT-proBNP) in human serum and plasma on the Alinity i system.
The Alere NT-proBNP for Alinity i assay can also be used as an aid in 12-month risk stratification for prognosis of all-cause mortality, cardiac-related mortality, and heart-related hospitalization in patients presenting to the emergency department, diagnosed with new onset or worsening HF.
The assay may further be used in the risk stratification of patients with acute coronary syndrome (ACS).
## C Special Conditions for Use Statement(s):
Rx – For Prescription Use Only
## D Special Instrument Requirements:
Alinity i system
# IV Device/System Characteristics:
## A Device Description:
Unchanged since K241176
## B Principle of Operation:
Unchanged since K241176
## V Substantial Equivalence Information:
## A Predicate Device Name(s):
Elecsys ProBNP II Stat Immunoassay
## B Predicate 510(k) Number(s):
K092649
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K253539 - Page 3 of 8
C Comparison with Predicate(s):
| Device & Predicate Device(s): | K251440 | K092649 |
| --- | --- | --- |
| Device Trade Name | Alere NT-proBNP for Alinity i | Elecsys proBNP II STAT Immunoassay |
| General Device Characteristic Similarities | | |
| Intended Use/Indications For Use | For the in vitro quantitative determination of N-terminal pro B-type natriuretic peptide (NT-proBNP) in human serum and plasma. This assay may be used in the risk stratification of patients with acute coronary syndrome (ACS). | Same |
| Specimen Type | Human serum and plasma | Same |
| Test Principle | Sandwich immunoassay | Same |
| Measurement Type | Quantitative | Same |
| Detection Technology | Chemiluminescence | Same |
| General Device Characteristic Differences | | |
| Principle of Operation | Chemiluminescent microparticle immunoassay (CMIA) | Electro chemiluminescent microparticle immunoassay (ECLIA) |
| Measuring Interval | 15.8 to 35,000.0 pg/mL | 5 to 35,000 pg/mL |
| Hook Effect | No hook effect up to 372,620 pg/mL | No hook effect up to 300,000 pg/mL |
VI Standards/Guidance Documents Referenced:
CLSI EP32-R (Formerly X05-R): Metrological Traceability and Its Implementation; A Report
CLSI EP09c 3rd Edition: Measurement Procedure Comparison and Bias Estimation Using Patient Samples
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VII Performance Characteristics (if/when applicable):
A Analytical Performance:
1. Precision/Reproducibility:
Unchanged since K241176.
2. Linearity:
Unchanged since K241176.
3. Analytical Specificity/Interference:
Unchanged since K241176.
4. Detection Limit and Assay Reportable Range:
Unchanged since K241176.
5. Traceability, Stability, Expected Values (Controls, Calibrators, or Methods):
Unchanged since K241176.
6. Assay Cut-Off:
Unchanged since K241176.
B Comparison Studies:
1. Method Comparison with Predicate Device:
Not applicable.
2. Matrix Comparison:
Unchanged since K241176.
C Clinical Studies:
1. Clinical Sensitivity:
Not applicable.
2. Clinical Specificity:
Not applicable.
K253539 - Page 4 of 8
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K253539 - Page 5 of 8
3. Clinical Cut-Off:
See “Other Clinical Supportive Data (When 1. and 2. Are Not Applicable)”.
4. Other Clinical Supportive Data (When 1. and 2. Are Not Applicable):
Risk of Adverse Events in Patients Diagnosed with New Onset or Worsening HF Presenting to the ED
A clinical study was performed to evaluate the candidate device as an aid in 12-month risk stratification for prognosis of all-cause mortality, cardiac-related mortality, and heart-related hospitalization in patients presenting to the emergency department, diagnosed with new onset or worsening HF using the adjudicated cohort described in K241176. Of the 880 subjects with an adjudicated diagnosis, 861 were prospectively followed for 6±1 and 12±2 months after the initial ED admission. (The remaining 19 subjects did not have a follow-up evaluation.) The study included 495 (57.5%) male subjects and 366 (42.5%) female subjects, with an overall mean age of 62.0 years. Specimens were collected at admission to the ED and tested with the Alere NT-proBNP for Alinity i assay. Study population quartiles for NT-proBNP were calculated in pg/mL from the included population (n = 861):
| Study Population Quartile | First Quartile (Q1) | Second Quartile (Q2) | Third Quartile (Q3) | Fourth Quartile (Q4) |
| --- | --- | --- | --- | --- |
| NT-proBNP Concentration (pg/mL) | ≤ 1214.7 | > 1214.7 to 3261.3 | > 3261.3 to 7031.3 | > 7031.3 |
The primary outcome was a composite outcome, defined as the first occurrence of all-cause mortality, cardiac-related mortality, or heart-related hospitalization. The secondary outcomes included the individual components of the composite outcome. The prognostic value of NT-proBNP quartiles was assessed via Kaplan-Meier survival analysis, Cox proportional hazards regression, and event rate analysis (absolute risk) for the primary and secondary outcomes.
Kaplan-Meier Survival Analysis
The Kaplan-Meier curves demonstrate that the risk of the composite outcome within 12 months is higher for higher NT-proBNP population quartiles.
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NT-proBNP Q1 -Q2 Q3 Q4
# Absolute Risk
Absolute risk of each outcome at 12 months was estimated using univariable Cox proportional hazards models. All evaluated outcomes (all-cause mortality, cardiac-related mortality, heart-related hospitalization, and the composite) demonstrate an increasing trend across NT-proBNP quartiles. The results are summarized in the following table.
| Outcome | Absolute Risk (%) (95% CI) | | | |
| --- | --- | --- | --- | --- |
| | Q1 | Q2 | Q3 | Q4 |
| Composite Outcome | 44.03 (36.86, 50.39) | 49.40 (42.25, 55.66) | 56.49 (49.37, 62.60) | 63.08 (55.99, 69.02) |
| Mortality | 10.21 (5.97, 14.25) | 11.45 (7.03, 15.66) | 18.94 (13.41, 24.12) | 25.50 (19.33, 31.19) |
| Cardiac Mortality | 2.03 (0.04, 3.97) | 6.84 (3.31, 10.24) | 7.24 (3.51, 10.83) | 15.78 (10.50, 20.75) |
| Heart-Related Hospitalization | 39.69 (32.44, 46.16) | 46.74 (39.43, 53.17) | 47.89 (40.34, 54.49) | 53.41 (45.55, 60.13) |
K253539 - Page 6 of 8
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Cox Proportional Hazards Regression
Univariable results and multivariable results are summarized for the composite outcome and each individual outcome in the table below.
| Outcome | NT-proBNP Quartile^{a} | Unadjusted Hazard Ratio (95% CI) | Adjusted Hazard Ratio (95% CI)^{b} |
| --- | --- | --- | --- |
| Composite | Q2 | 1.17 (0.89, 1.56) | 1.16 (0.86, 1.56) |
| | Q3 | 1.43 (1.09, 1.89) | 1.44 (1.08, 1.93) |
| | Q4 | 1.72 (1.31, 2.25) | 1.56 (1.14, 2.12) |
| All-Cause Mortality | Q2 | 1.13 (0.63, 2.03) | 1.15 (0.63, 2.10) |
| | Q3 | 1.95 (1.15, 3.32) | 1.89 (1.08, 3.30) |
| | Q4 | 2.73 (1.65, 4.53) | 2.13 (1.19, 3.80) |
| Cardiac-Related Mortality | Q2 | 3.46 (1.14, 10.52) | 3.69 (1.19, 11.42) |
| | Q3 | 3.67 (1.21, 11.15) | 3.84 (1.22, 12.04) |
| | Q4 | 8.39 (2.96, 23.77) | 8.24 (2.66, 25.50) |
| Heart-Related Hospitalization | Q2 | 1.25 (0.92, 1.68) | 1.23 (0.89, 1.69) |
| | Q3 | 1.29 (0.95, 1.75) | 1.30 (0.94, 1.80) |
| | Q4 | 1.51 (1.12, 2.04) | 1.44 (1.02, 2.03) |
a NT-proBNP Q1 is the reference category for the hazard ratios presented for Q2, Q3, and Q4.
b The multivariable model was adjusted for age, sex, BMI, smoking, diabetes mellitus, hypertension, eGFR, and NYHA class. Only subjects with complete data for all covariates (n=816) were included
## Risk Stratification of Patients with Acute Coronary Syndrome (ACS)
The sponsor provided information to support the risk stratification of patients with ACS claim based on the following clinical guideline and peer-reviewed literature references:
- Rao SV, O'Donoghue ML, Ruel M, et al. 2025 ACC/AHA/ACEP/NAEMSP/SCAI guideline for the management of patients with acute coronary syndromes: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2025;151:e771-e862.
K253539 - Page 7 of 8
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- Jernberg T, Stridsberg M, Venge P, et al. N-terminal pro brain natriuretic peptide on admission for early risk stratification of patients with chest pain and no ST-segment elevation. J Am Coll Cardiol 2002;40(3):437-445.
- James SK, Lindahl B, Siegbahn A, et al. N-terminal pro-brain natriuretic peptide and other risk markers for the separate prediction of mortality and subsequent myocardial infarction in patients with unstable coronary artery disease; a Global Utilization of Strategies to Open occluded arteries (GUSTO)-IV substudy. Circulation 2003;108(3):275-281.
## D Expected Values/Reference Range:
Unchanged since K241176.
## 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.
K253539 - Page 8 of 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.
