Algorithm performance verification for adjustable MAP targets and non-surgical indication expansion
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Hypotension Prediction
—
—
—
—
—
—
—
Indications for Use
The Edwards Acumen Hypotension Prediction Index software feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events and the associated hemodynamics. The Acure is intended for use in surgical or non-surgical patients receiving advanced hemodynamic monitoring. The Acumen HPI feature is considered to be additional quantitative information regarding the patient's physiological condition for reference only and is not intended to make therapeutic decisions solely on the Acumen Hypotension Prediction Index (HPI) parameter. The Acumen Hypotension Prediction Index (HPI) software feature used on a compatible monitoring platform is intended to be used by qualified personnel or trained clinicians in a critical care environment in a hospital setting.
Device Story
Acumen HPI software feature provides clinicians with predictive insight into potential future hypotensive events; operates on compatible hemodynamic monitoring platforms. Input data includes patient hemodynamic parameters; core algorithm processes these inputs to calculate HPI parameter; output displayed to clinician as quantitative information. Used in hospital critical care environments by trained clinicians/qualified personnel. Device serves as adjunctive tool; not intended for sole therapeutic decision-making. Benefits include early identification of potential hypotension, allowing proactive clinical intervention. Subject device introduces user-adjustable Mean Arterial Pressure (MAP) targets (55-85 mmHg) for hypotension definition and expands indication to include non-surgical patients for non-invasive technology.
Clinical Evidence
Bench testing and retrospective clinical data analysis. Algorithm verification confirmed performance with adjustable MAP targets (55-85 mmHg) and supported expanded non-surgical indication. Usability study conducted per FDA human factors guidance validated updated instructions and critical task performance, demonstrating no new risks to patient or user safety.
Technological Characteristics
Software-based predictive algorithm feature for hemodynamic monitoring platforms. Operates on existing HPI core algorithm. Connectivity via compatible monitoring systems. Software-based, no specific hardware materials. No energy source or sterilization required as it is a software feature.
Indications for Use
Indicated for adult surgical or non-surgical patients receiving advanced hemodynamic monitoring in a hospital critical care environment to provide insight into the likelihood of future hypotensive events.
Regulatory Classification
Identification
The adjunctive predictive cardiovascular indicator is a prescription device that uses software algorithms to analyze cardiovascular vital signs and predict future cardiovascular status or events. This device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy.
Special Controls
*Classification.* Class II (special controls). The special controls for this device are:(1) A software description and the results of verification and validation testing based on a comprehensive hazard analysis and risk assessment must be provided, including:
(i) A full characterization of the software technical parameters, including algorithms;
(ii) A description of the expected impact of all applicable sensor acquisition hardware characteristics and associated hardware specifications;
(iii) A description of sensor data quality control measures;
(iv) A description of all mitigations for user error or failure of any subsystem components (including signal detection, signal analysis, data display, and storage) on output accuracy;
(v) A description of the expected time to patient status or clinical event for all expected outputs, accounting for differences in patient condition and environment; and
(vi) The sensitivity, specificity, positive predictive value, and negative predictive value in both percentage and number form.
(2) A scientific justification for the validity of the predictive cardiovascular indicator algorithm(s) must be provided. This justification must include verification of the algorithm calculations and validation using an independent data set.
(3) A human factors and usability engineering assessment must be provided that evaluates the risk of misinterpretation of device output.
(4) A clinical data assessment must be provided. This assessment must fulfill the following:
(i) The assessment must include a summary of the clinical data used, including source, patient demographics, and any techniques used for annotating and separating the data.
(ii) The clinical data must be representative of the intended use population for the device. Any selection criteria or sample limitations must be fully described and justified.
(iii) The assessment must demonstrate output consistency using the expected range of data sources and data quality encountered in the intended use population and environment.
(iv) The assessment must evaluate how the device output correlates with the predicted event or status.
(5) Labeling must include:
(i) A description of what the device measures and outputs to the user;
(ii) Warnings identifying sensor acquisition factors that may impact measurement results;
(iii) Guidance for interpretation of the measurements, including a statement that the output is adjunctive to other physical vital sign parameters and patient information;
(iv) A specific time or a range of times before the predicted patient status or clinical event occurs, accounting for differences in patient condition and environment;
(v) Key assumptions made during calculation of the output;
(vi) The type(s) of sensor data used, including specification of compatible sensors for data acquisition;
(vii) The expected performance of the device for all intended use populations and environments; and
(viii) Relevant characteristics of the patients studied in the clinical validation (including age, gender, race or ethnicity, and patient condition) and a summary of validation results.
Acumen Hypotension Prediction Index feature (DEN160044)
Submission Summary (Full Text)
{0}------------------------------------------------
Image /page/0/Picture/0 description: The image shows the logo for the U.S. Food and Drug Administration (FDA). The logo consists of two parts: on the left, there is a symbol representing the Department of Health & Human Services - USA, and on the right, there is the text "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue. The text is arranged in three lines, with "FDA" being the largest and boldest, followed by "U.S. FOOD & DRUG", and then "ADMINISTRATION" in a smaller font size.
June 8, 2023
Edwards Lifesciences LLC Varad Raghuwanshi Manager, Regulatory Affairs One Edwards Way Irvine, California 92614
Re: K230057
Trade/Device Name: Acumen Hypotension Prediction Index (HPI) Regulation Number: 21 CFR 870.2210 Regulation Name: Adjunctive Predictive Cardiovascular Indicator Regulatory Class: Class II Product Code: QAQ Dated: January 6, 2023 Received: January 9, 2023
Dear Varad Raghuwanshi:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
{1}------------------------------------------------
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
# Robert T. Kazmierski -S
for
LCDR Stephen Browning Assistant Director Division of Cardiac Electrophysiology Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
{2}------------------------------------------------
# Indications for Use
510(k) Number (if known) K230057
Device Name Acumen Hypotension Prediction Index
Indications for Use (Describe) Acumen Hypotension Prediction Index:
The Edwards Acumen Hypotension Prediction Index software feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events and the associated hemodynamics. The Acure is intended for use in surgical or non-surgical patients receiving advanced hemodynamic monitoring. The Acumen HPI feature is considered to be additional quantitative information regarding the patient's physiological condition for reference only and is not intended to make therapeutic decisions solely on the Acumen Hypotension Prediction Index (HPI) parameter.
| Type of Use (Select one or both, as applicable) | |
|-------------------------------------------------|--|
|-------------------------------------------------|--|
X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
### CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
### *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.*
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
> Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
{3}------------------------------------------------
# 510(k) Summary – Acumen Hypotension Prediction Index (HPI)
#### I. Submitter:
- Edwards Lifesciences LLC Sponsor: One Edwards Way Irvine, CA 92614 Establishment 2015691 Registration Number: Contact Person: Varad Raghuwanshi Manager, Regulatory Affairs One Edwards Way Irvine, CA 92614 Telephone: (949) 756-4502
Fax: (949) 809-2972
Date Prepared: June 8, 2023
#### II. Device Information:
| Device Name | Acumen Hypotension Prediction Index (HPI) |
|------------------------------------|------------------------------------------------------------------------------------------------------|
| Trade Name: | Acumen Hypotension Prediction Index (HPI) feature for Minimally Invasive and Non-Invasive technology |
| Common Name: | Adjunctive Predictive Cardiovascular Indicator |
| Classification Name: | Adjunctive Predictive Cardiovascular Indicator 21 CFR 870.2210 |
| Product Code and Regulatory Class: | QAQ, Class II |
{4}------------------------------------------------
#### III. Predicate Device
| Primary<br>Predicate Device: | HemoSphere Advanced Monitoring Platform manufactured by Edwards Lifesciences, K203687 cleared May 28th, 2021, utilized for the Acumen Hypotension Prediction Index software feature. |
|-------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Additional<br>Predicate<br>Devices: | Acumen Hypotension Prediction Index feature by Edwards Lifesciences DEN160044, granted March 16, 2018, utilized for the Acumen Hypotension Prediction Index software feature. |
#### IV. Device Description
The Acumen Hypotension Prediction Index parameter (HPI) provides Device Description: the clinician with the likelihood that the patient may be trending toward a hypotensive event. The Acumen HPI feature is intended for use in surgical or non-surgical patients.
> By default, the software defines a hypotensive event as mean arterial pressure (MAP) < 65 mmHg for at least one minute in duration. This MAP target is adjustable and can be changed to 55, 60, 70, 75, 80 or 85 mmHg.
#### Indications for Use: V.
Note: The Indication for Use statement for Acumen Hypotension Prediction is similar to what was previously cleared in K203687 May 28th, 2021, with the exception of removal of the statement to define hypotensive event as the users will now have the option to use the default 65 target or alternatively select a MAP target of 55, 60, 70, 75, 80 or 85 mmHg for hypotension. In addition, the indication for Acumen HPI when used with the non-invasive (ClearSight) technology has been expanded to include non-surgical patients.
# Acumen Hypotension Predication Index (HPI)
The Edwards Acumen Hypotension Prediction Index software feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events and the associated hemodynamics. The Acumen HPI feature is intended for use in surgical or non-surgical patients receiving advanced hemodynamic monitoring.
The Acumen HPI feature is considered to be additional quantitative information regarding the patient's physiological condition for reference
{5}------------------------------------------------
only and is not intended to make therapeutic decisions solely on the Acumen Hypotension Prediction Index (HPI) parameter.
Intended Use: The Acumen Hypotension Prediction Index (HPI) software feature used on a compatible monitoring platform is intended to be used by qualified personnel or trained clinicians in a critical care environment in a hospital setting.
| Parameter | Description | Patient<br>Population | Hospital<br>Environment |
|-----------|----------------------------------------|-----------------------|------------------------------|
| HPI | Acumen Hypotension Prediction<br>Index | Adult only | Surgical and<br>non-surgical |
#### VI. Comparison of Technological Characteristics with the Predicate Device
The subject and predicate devices are based on the following same technological elements:
- Predictive Algorithm: The subject and predicate (initially cleared in DEN160044 and later cleared in K203687 on May 28th, 2021, for Edwards noninvasive technology have the same core predictive algorithm for Acumen Hypotension Predication Index (HPI).
The following technological difference exist between the subject and predicate devices:
- . Acumen HPI algorithm enhancement: An enhancement has been made to the existing HPI software feature cleared in K203687 (May 28th, 2021) to include an option to allow the clinician to adjust the Mean Arterial Pressure (MAP) target for hypotension (55, 60, 70, 75, 80, 85 mmHg) in addition to the existing default MAP target of 65 mmHg without making any changes to the core HPI algorithm and the original HPI algorithm parameters.
The purpose of this 510(k) submission is to obtain clearance for the following modifications to the Acumen Hypotension Prediction Index (K203687 (May 28th, 2021):
{6}------------------------------------------------
- * Modification to the Acumen Hypotension Prediction Index (HPI) software feature to introduce adjustable MAP targets for hypotension (previously cleared in K203687 on May 28th, 2021):
- Algorithm Modification: Update to the existing Acumen™ HPI Algorithm
The existing Acumen Hypotension Prediction Index software feature for Edwards minimally invasive and noninvasive technology has been modified to include an option to allow the clinician to adjust the Mean Arterial Pressure (MAP) target for hypotension (55, 60, 70, 75, 80, 85 mmHg) in addition to the existing default MAP target of 65 mmHg.
- & Modifications to the labelling related to the Acumen Hypotension Prediction Index software feature cleared in K203687, cleared May 28th, 2021):
- Updated Indication for Use statement and the Clinical . validation information to align with the proposed adjustable MAP targets for hypotension:
The current Acumen Hypotension Prediction Index software feature for minimally invasive and noninvasive technology, cleared in K203687 on May 28th, 2021, defines a hypotensive event as mean arterial pressure < 65 mmHg for at least one minute in duration. Due to the proposed change to introduce adjustable MAP targets for hypotension, users will now have the option to use the default 65 target or alternatively select a MAP target of 55, 60, 70, 75, 80 or 85 mmHg. Hence the current definition of a hypotensive event "(defined as mean arterial pressure < 65 mmHg for at least one minute in duration)" is no longer applicable and has been removed from the indication for use statement.
In addition, the clinical validation section for Acumen HPI has been updated to represent the clinical validation results for the proposed adjustable MAP targets for hypotension.
- Indication expansion to include nonsurgical patients for Acumen HPI for noninvasive technology:
{7}------------------------------------------------
The current indication for Acumen Hypotension Prediction Index when used with Edwards ClearSight (Noninvasive) technology has been expanded to include nonsurgical patients.
#### Performance The following verification activities were performed in support of a Data: substantial equivalence determination for the modifications being made as part of this submission.
## Algorithm Verification:
Algorithm performance was tested using clinical data. The results establish that the usage of the HPI algorithm with the adjustable Mean Arterial Pressure (MAP) targets for hypotension (55, 60, 70, 75, 80, 85 mmHg) did not adversely affect the safety and effectiveness of the subject device.
In addition, algorithm verification is completed using non-surgical clinical data collected retrospectively to support expanded non-surgical indication for Acumen Hypotension Prediction Index when used with Edwards ClearSight (Noninvasive) technology.
# Usability Study
Usability study was conducted per FDA's guidance document "Applying Human Factors and Usability Engineering to Medical Devices" to validate the updated instructions and to assess the success of the proposed modification to reduce the risks to acceptable levels without introducing any new unacceptable risks.
The usability study demonstrated that the intended users can perform primary operating functions and critical tasks of the system without any usability issues that may lead to patient or user harm.
### Conclusions
The technological characteristics of the subject and predicate devices are identical. The modified Acumen Hypotension Prediction Index feature with adjustable MAP targets for hypotension algorithm has successfully passed the functional and performance testing including software verification and validation and bench studies. The testing performed demonstrates that the Acumen Hypotension Prediction Index with the subject modification and expanded indication is substantially equivalent to the legally marketed predicates.
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.
