Retrospectively collected ICU and OR patient waveforms
Retrospective clinical validation of the Smart Wedge algorithm for PAOP identification and measurement accuracy compared to expert clinician consensus.
Retrospective clinical validation: 110 PAOP measurements from 59 patients
3 (experienced health care providers)
Indications for Use
The Smart Wedge algorithm is intended to be used by qualified personnel or trained clinicians in a critical care environment in a hospital setting. The Smart Wedge algorithm is intended to measure and provide accurate pulmonary artery occlusion pressure and to assess the quality of the pulmonary artery occlusion pressure measurement.
Device Story
Algorithm processes pulmonary artery pressure waveforms from Swan-Ganz catheters; inputs via pressure cable/transducer. Transforms waveforms to calculate pulmonary artery occlusion pressure (PAOP) at end-expiration; assesses measurement quality. Outputs PAOP value, quality assessment, and status flags (e.g., 'no wedge detected', 'wedge too long', 'artifact detected'). Used in hospital critical care settings by trained clinicians. Provides quantitative physiological data to support clinical monitoring; not for sole therapeutic decision-making.
Clinical Evidence
No clinical trial performed. Bench testing used retrospective ICU/OR waveforms (n=129 patients for identification; n=59 patients for measurement). Reference standard: consensus of three experienced HCPs. PAOP identification: 100% sensitivity, 96% specificity. PAOP measurement: 1.1 mmHg MAE, 0.4 mmHg bias, 0.98 correlation.
Technological Characteristics
Software-based algorithm for hemodynamic parameter extraction. Operates on pressure waveforms from standard Swan-Ganz catheters/transducers. Connectivity: integrates with patient monitoring systems. Software verification per IEC 62304:2006/A1:2016 and ISO 14971:2019.
Indications for Use
Indicated for critical care patients over 18 years of age receiving advanced hemodynamic monitoring, used in combination with a Swan-Ganz catheter, pressure cable, and pressure transducer. For reference only; not for sole therapeutic decision-making.
Regulatory Classification
Identification
A programmable diagnostic computer is a device that can be programmed to compute various physiologic or blood flow parameters based on the output from one or more electrodes, transducers, or measuring devices; this device includes any associated commercially supplied programs.
{0}------------------------------------------------
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
August 18, 2023
Edwards Lifesciences, LLC Jennifer Wilbur Director, Regulatory Affairs Program Management 1 Edwards Way Irvine. California 92614
Re: K230579
Trade/Device Name: Smart Wedge algorithm Regulation Number: 21 CFR 870.1425 Regulation Name: Programmable Diagnostic Computer Regulatory Class: Class II Product Code: DOK Dated: July 14, 2023 Received: July 14, 2023
Dear Jennifer Wilbur:
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.
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
{1}------------------------------------------------
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) K230579
Device Name Smart Wedge algorithm
#### Indications for Use (Describe)
When used in combination with a Swan-Ganz catheter connected to a pressure transducer, the Edwards Lifesciences Smart Wedge algorithm measures and provides pulmonary artery occlusion pressure and assesses the quality of the pulmonary artery occlusion pressurement. The Smart Wedge algorithm is indicated for use in critical care patients over 18 years of age receiving advanced hemodynamic monitoring. The Smart Wedge algorithm is considered to be additional quantitative information regarding the patient's physiological condition for reference only and no therapeutic decisions should be made based solely on the Smart Wedge algorithm parameters.
Type of Use (Select one or both, as applicable):
| <span style="font-size:100%;">☑ Prescription Use (Part 21 CFR 801 Subpart D)</span> |
|-------------------------------------------------------------------------------------|
| <span style="font-size:100%;">☐ Over-The-Counter Use (21 CFR 801 Subpart C)</span> |
### 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}------------------------------------------------
| I. Submitter | | |
|-----------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Sponsor | Edwards Lifesciences, LLC<br>One Edwards Way<br>Irvine, CA, USA 92614 | |
| Establishment Registration<br>Number | 2015691 | |
| Contact Person | Primary Contact | Secondary Contact |
| | Jennifer Wilbur<br>Director, Regulatory Affairs<br>Program Management<br>One Edwards Way<br>Irvine, CA 92614<br>Telephone: (949) 756-4436<br>Email:<br>jennifer_wilbur@edwards.com | Karen Clement<br>Sr. Director, Regulatory Affairs<br>Edwards Lifesciences<br>One Edwards Way<br>Irvine, CA 92614<br>Telephone: (949) 250-4746<br>Email:<br>Karen Clement@edwards.com |
| Date Prepared | July 14, 2023 | |
| II. Device Information | | |
| Trade Name | Smart Wedge algorithm | |
| Common Name | Pulmonary Artery Occlusion Pressure (PAOP) | |
| Regulation Number/<br>Regulation Name | 21 CFR 870.1425 /<br>Computer, Diagnostic, Programmable | |
| Product Code | DQK | |
| Regulation Class | Class II | |
| III. Predicate Device | | |
| Predicate Device | The GE CARESCAPE B650 Patient Monitor (K213181, cleared April<br>13, 2022) manufactured by GE Healthcare Finland Oy, and its<br>pulmonary artery occlusion pressure measurement are being utilized<br>for substantial equivalence as a predicate to the Smart Wedge<br>algorithm in terms of similar technology (principles of operation,<br>functionality and performance) and same/similar indications/intended<br>use. | |
| IV. Device Description | | |
| Device Description | The Smart Wedge algorithm is designed to provide the value at end-<br>expiration of the pulmonary artery occlusion pressure (PAOP) signal,<br>also called pulmonary wedge pressure, pulmonary capillary wedge<br>pressure (PCWP), or pulmonary artery wedge pressure (PAWP), and<br>to assess the quality of the pulmonary artery occlusion pressure<br>measurement.<br><br>The Smart Wedge algorithm is intended to be used with a Swan-Ganz<br>pulmonary artery catheter connected to a pressure cable and pressure<br>transducer. | |
| V. Indications for Use and Intended Use | | |
| Indications for Use | When used in combination with a Swan-Ganz catheter connected to a<br>pressure cable and pressure transducer, the Edwards Lifesciences<br>Smart Wedge algorithm measures and provides pulmonary artery<br>occlusion pressure and assesses the quality of the pulmonary artery<br>occlusion pressure measurement. The Smart Wedge algorithm is<br>indicated for use in critical care patients over 18 years of age receiving<br>advanced hemodynamic monitoring. The Smart Wedge algorithm is<br>considered to be additional quantitative information regarding the<br>patient's physiological condition for reference only and no therapeutic<br>decisions should be made based solely on the Smart Wedge algorithm<br>parameters. | |
| Intended Use | The Smart Wedge algorithm is intended to be used by qualified<br>personnel or trained clinicians in a critical care environment in a<br>hospital setting. The Smart Wedge algorithm is intended to measure<br>and provide accurate pulmonary artery occlusion pressure and to<br>assess the quality of the pulmonary artery occlusion pressure<br>measurement. | |
| VI. Comparison of Technological Characteristics with Predicate Device | | |
| Comparison to Predicate<br>Device | The subject device and predicate devices are based on the following<br><span style="text-decoration: underline;">same</span> technological elements:<br><br><b>Hemodynamic Parameters & Technological Characteristics:</b><br>The subject device and predicate device (GE CARESCAPE<br>B650 Patient Monitor, K213181, cleared April 13, 2022) both<br>measure and provide pulmonary artery pressure, have software<br>and provide flag/message outputs.<br>The subject device and predicate device (GE CARESCAPE<br>B650 Patient Monitor, K213181, cleared April 13, 2022) both<br>measure and provide pulmonary artery occlusion pressure. | |
{4}------------------------------------------------
{5}------------------------------------------------
## Accessories/Components:
- . The subject device and predicate device (GE CARESCAPE B650 Patient Monitor, K213181, cleared April 13, 2022) both obtain a pressure waveform measurement from a commercially available pulmonary artery catheter connected to a pressure cable and pressure transducer to obtain a pulmonary artery pressure waveform measurement.
# Intended Use/Indications for Use:
- · The subject device and predicate device (GE CARESCAPE B650 Patient Monitor, K213181, cleared April 13, 2022) both have similar intended use/indications for use.
- o The subject device has the same indications/intended purpose as the predicate with respect to its use by trained clinicians in a healthcare environment and with respect to the hemodynamic monitoring of invasive pressure in adult patients.
The following technological differences exist between the subject and predicate device:
# Algorithm Modifications:
- The subject Smart Wedge algorithm provides the following ● functional and safety enhancements over the predicate (GE CARESCAPE B650 Patient Monitor, K213181, cleared April 13. 2022):
- > PAOP Measurement: The subject Smart Wedge algorithm will not only display a PAOP measurement like the predicate device, but it will also display PAOP within mean absolute error < 4 mmHg accuracy.
- A Measurement of PAOP Quality: The subject Smart Wedge algorithm includes a new measurement as to the quality of the PAOP reading. This quality measurement is provided simultaneously with the PAOP value.
- Additional Flag Outputs/Messages: The subject Smart A Wedge algorithm includes additional safety flag outputs/messages for "no wedge detected" and "wedge too long" and an additional "artifact detected" flag output/message.
The subject device continues to have the same overall intended use/indications and fundamental scientific technology.
{6}------------------------------------------------
The following verification activities were performed in support of a substantial equivalence determination for the Smart Wedge algorithm and predicate devices and to ensure safety and effectiveness of the Smart Wedge algorithm:
# Software Verification:
Software verification was performed in accordance with IEC 62304:2006/A1:2016. Medical device software – Software life cvcle processes, ISO 14971:2019, Medical devices, Applications of risk management to medical devices, FDA's Guidance for Industry and FDA Staff, Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (issued May 11, 2005) and FDA's Guidance for Industry and FDA Staff, General Principles of Software Validation (issued January 11, 2002). The Smart Wedge algorithm was tested at the algorithm level to ensure the safety of the device. The verification of the Smart Wedge algorithm was performed using waveforms retrospectively collected from ICU and OR patients. The basis for determination of substantial equivalence included retrospective clinical validation testing as shown in Table 1 for PAOP identification and Table 2 for PAOP measurement, with the references (i.e., consensus) being independent annotations by three experienced health care providers (HCPs). Results for the Smart Wedge algorithm met or exceeded predicate device performance.
## Table 1: Performance Results of PAOP Identification
Data presented as average value with 95% confidence interval (CI). PPV: positive predictive value, NPV: negative predictive value.
| Smart Wedge<br>Algorithm<br>Parameter | Method Used to<br>Obtain Reference<br>Value<br>(Consensus) | Sensitivity<br>(%) | Specificity<br>(%) | PPV<br>(%) | NPV<br>(%) |
|-----------------------------------------------------------------|------------------------------------------------------------|--------------------|--------------------|----------------|-------------------|
| PAOP Identification<br>(225 PAP waveforms<br>from 129 patients) | Mode of three<br>HCP annotations | 100<br>[100,100] | 96<br>[92, 100] | 95<br>[89, 99] | 100<br>[100, 100] |
## Table 2: Performance Results of PAOP Measurements
Data presented as average value with 95% confidence interval (CI). MAE: mean absolute error Std. standard deviation
| Smart Wedge<br>Algorithm<br>Parameter | Method Used to<br>Obtain Reference<br>Value (Consensus) | MAE<br>(mmHg) | Bias<br>(mmHg) | Std<br>(mmHg) | Correlation<br>r |
|--------------------------------------------------------------------|---------------------------------------------------------|-------------------|-------------------|-------------------|------------------|
| PAOP Measurement<br>(110 PAOP<br>measurements from<br>59 Patients) | Average PAOP<br>measurement of<br>three HCPs | 1.1<br>[0.8, 1.5] | 0.4<br>[0.1, 0.7] | 1.7<br>[1.4, 2.0] | 0.98 |
## Clinical Performance:
No clinical trial was performed in support of the subject 510(k).
Device Testing /
Performance Data
{7}------------------------------------------------
| Conclusion | <b>Overall Conclusion:</b><br>The subject Smart Wedge algorithm successfully passed all functional<br>and performance testing, including software verification and<br>validation and bench studies. Completion of all performance<br>verification and validation activities demonstrated that the subject<br>device meets its predetermined design and performance specifications.<br>Verification activities performed confirmed that the differences in the<br>features and design did not adversely affect the safety and<br>effectiveness of the subject device. The testing performed<br>demonstrates that the subject Smart Wedge algorithm is substantially<br>equivalent to its legally marketed predicate. |
|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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.