K213230 · Etiometry, Inc. · PPW · Jun 22, 2022 · Cardiovascular
Device Facts
Record ID
K213230
Device Name
T3 Platform Software
Applicant
Etiometry, Inc.
Product Code
PPW · Cardiovascular
Decision Date
Jun 22, 2022
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 870.2200
Device Class
Class 2
Attributes
Software as a Medical Device, Real-World Evidence, Pediatric
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K213230 · Jun 22, 2022
T3 Platform Software
Etiometry, Inc.
Retrospective de-identified patient clinical data from 11 US clinical sites
Retrospective clinical data was used to validate the performance of the new ACD and HLA indices, assessing discriminatory power, range utilization, resolution/limitation, and robustness against established acceptance criteria.
HLA Index Validation Study; Retrospective validation study
Post-surgical patients 0 to 12 years of age; Sample Size: 3,496 patients (58,168 whole blood lactate measurements); Number of Sites: 11
Not applicable for this study
Discriminatory power, range utilization, resolution/limitation, and robustness
ACD Index Validation Study; Retrospective validation study
Invasively ventilated patients 0 to 12 years of age; Sample Size: 1,858 patients (24,431 arterial blood pH measurements); Number of Sites: 11
Not applicable for this study
Discriminatory power, range utilization, resolution/limitation, and robustness
Indications for Use
The T3 Data Aggregation & Visualization software module is intended for the recording and display of multiple physiological parameters of the adult, pediatric, and neonatal patients from supported bedside devices. The software module is not intended for alarm notification or waveform display, nor is it intended to control any of the independent bedside devices to which it is connected. The software module is intended to be used by healthcare professionals for the following purposes: To remotely consult regarding a patient's status, and To remotely review other standard or critical near real-time patient data in order to aid in clinical decisions and deliver patient care in a timely manner.
Device Story
T3 Platform software aggregates, stores, and visualizes physiologic data from bedside devices in ICU settings. Inputs include numeric physiologic parameters (e.g., BP, HR, SpO2, CO2, airway pressures) and laboratory measurements (blood gases, CBC, lactate). The T3 Risk Analytics Engine (v8.0) processes these inputs using physiological models to calculate four indices: IDO2 (inadequate oxygen delivery), IVCO2 (inadequate CO2 ventilation), ACD (acidemia), and HLA (hyperlactatemia). The system provides a web-based interface for clinicians to remotely review patient status. Outputs are qualitative, adjunctive indicators; they do not trigger alarms or control bedside devices. Clinicians use these indices alongside primary data to aid clinical decision-making. The platform includes a Continuous Performance Assessment (CPA) module for remote monitoring of index performance. Benefits include centralized, near real-time visibility into patient physiological trends to support timely care.
Clinical Evidence
Retrospective clinical validation using data from 11 US sites. HLA Index validated on 58,168 lactate measurements from 3,496 patients (31% infants, 33% children). ACD Index validated on 24,431 pH measurements from 1,858 patients (40% infants, 26% children). Indices evaluated against acceptance criteria for discriminatory power, range utilization, resolution/limitation, and robustness. All results met predefined criteria. No adverse effects noted.
Technological Characteristics
Software-only solution; web-based visualization. Operates on standard browsers. Integrates with bedside devices for data aggregation. Uses physiological model-based algorithms (Risk Analytics Engine v8.0) to compute indices. Connectivity via network integration with existing bedside monitors. Moderate level of concern software.
Indications for Use
Indicated for healthcare professionals managing adult, pediatric, and neonatal patients in intensive care. IDO2 and HLA indices indicated for post-surgical patients 0-12 years (≥2 kg). IVCO2 and ACD indices indicated for invasively ventilated patients 0-12 years (≥2 kg).
Regulatory Classification
Identification
The adjunctive cardiovascular status indicator is a prescription device based on sensor technology for the measurement of a physical parameter(s). 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) Software description, verification, and validation based on comprehensive hazard analysis must be provided, including:
(i) Full characterization of technical parameters of the software, including any proprietary algorithm(s);
(ii) Description of the expected impact of all applicable sensor acquisition hardware characteristics on performance and any associated hardware specifications;
(iii) Specification of acceptable incoming sensor data quality control measures; and
(iv) Mitigation of impact of user error or failure of any subsystem components (signal detection and analysis, data display, and storage) on accuracy of patient reports.
(2) Scientific justification for the validity of the status indicator algorithm(s) must be provided. Verification of algorithm calculations and validation testing of the algorithm using a data set separate from the training data must demonstrate the validity of modeling.
(3) Usability assessment must be provided to demonstrate that risk of misinterpretation of the status indicator is appropriately mitigated.
(4) Clinical data must be provided in support of the intended use and include the following:
(i) Output measure(s) must be compared to an acceptable reference method to demonstrate that the output measure(s) represent(s) the predictive measure(s) that the device provides in an accurate and reproducible manner;
(ii) The data set must be representative of the intended use population for the device. Any selection criteria or limitations of the samples must be fully described and justified;
(iii) Agreement of the measure(s) with the reference measure(s) must be assessed across the full measurement range; and
(iv) Data must be provided within the clinical validation study or using equivalent datasets to demonstrate the consistency of the output and be representative of the range of data sources and data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment.
(5) Labeling must include the following:
(i) The type of sensor data used, including specification of compatible sensors for data acquisition;
(ii) A description of what the device measures and outputs to the user;
(iii) Warnings identifying sensor reading acquisition factors that may impact measurement results;
(iv) Guidance for interpretation of the measurements, including warning(s) specifying adjunctive use of the measurements;
(v) Key assumptions made in the calculation and determination of measurements;
(vi) The measurement performance of the device for all presented parameters, with appropriate confidence intervals, and the supporting evidence for this performance; and
(vii) A detailed description of the patients studied in the clinical validation (
*e.g.,* age, gender, race/ethnicity, clinical stability) as well as procedural details of the clinical study.
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June 22, 2022
Etiometry, Inc. Tim Hanson VP of RA/QA 280 Summer St, 4th Floor Boston, Massachusetts 02210
Re: K213230
Trade/Device Name: T3 Platform Software Regulation Number: 21 CFR 870.2200 Regulation Name: Adjunctive Cardiovascular Status Indicator Regulatory Class: Class II Product Code: PPW Dated: September 27, 2021 Received: September 29, 2021
Dear Tim Hanson:
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 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
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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,
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
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# Indications for Use
510(k) Number (if known) K213230
Device Name T3 Platform™ software
#### Indications for Use (Describe)
The T3 Platform™ software features the T3 Data Aggregation & Visualization software module version 5.0 and the T3 Risk Analytics Engine software module version 8.0.
The T3 Data Aggregation & Visualization software module is intended for the recording and display of multiple physiological parameters of the adult, pediatric, and neonatal patients from supported bedside devices. The software module is not intended for alarm notification or waveform display, nor is it intended to control any of the independent bedside devices to which it is connected. The software module is intended to be used by healthcare professionals for the following purposes:
- To remotely consult regarding a patient's status, and
- To remotely review other standard or critical near real-time patient data in order to aid in ● clinical decisions and deliver patient care in a timely manner.
The T3 Data Aggregation & Visualization software module can display numeric physiologic data captured by other medical devices:
- · Airway flow, volume, and pressure
- · Arterial blood pressure (invasive and non-invasive, systolic, diastolic, and mean)
- Bispectral index (BIS, signal quality index, suppression ratio) .
- Cardiac Index
- . Cardiac output
- Central venous pressure .
- . Cerebral perfusion pressure
- End-tidal CO2 .
- · Heart rate
- Heart rate variability .
- Intracranial pressure .
- . Left atrium pressure
- Oxygen saturation (intravascular, regional, SpO2) .
- Premature ventricular counted beats .
- · Pulmonary artery pressure (systolic, diastolic, and mean)
- Pulse pressure variation
- · Pulse Rate
- · Respiratory rate
- Right atrium pressure .
- Temperature (rectal, esophageal, tympanic, blood, core, nasopharyngeal, skin)
- · Umbilical arterial pressure (systolic, diastolic, and mean)
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The T3 Data Aggregation & Visualization software module can display laboratory measurements including arterial and venous blood gases, complete blood count, and lactic acid. T3 Data Aggregation & Visualization software module can display information captured by the T3 Risk Analytics Engine software module,
The T3 Risk Analytics Engine software module calculates four indices: the IDO2 Index™ for inadequate delivery of oxygen, the IVCO2 Index™ for inadequate ventilation of carbon dioxide, the ACD Index™ for acidemia, and the HLA Index™ for hyperlactatemia.
The IDO2 Index™ is indicated for use by health care professionals with post-surgical patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The IDO2 Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation & Visualization software module. When the IDO2 Index™ is increasing, it means that there is an increasing risk of inadequate oxygen delivery and attention should be brought to the patient. The IDO2 Index™ presents partial quantitative information about the patient's cardiovascular condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The IVCO2 Index™ is indicated for use by health care professionals with invasively ventilated patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The IVCO2 Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation and Visualization software module. When the IVCO2 Index™ is increasing, it means that there is an increasing risk of inadequate carbon dioxide ventilation and attention should be brought to the IVCO2 Index™ presents partial quantitative information about the patient's respiratory condition, and no therapy or drugs can be administered based solely on the internets.
The ACD Index™ is indicated for use by health care professionals with invasively ventilated patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The ACD Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation and Visualization software module. When the ACD Index™ is increasing, it means that there is an increasing risk of acidemia and attention should be brought to the patient. The ACD Index™ presents partial quantitative information about the patient's respiratory condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The HLA Index™ is indicated for use by health care professionals with post-surgical patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The HLA Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation & Visualization software module. When the HLA Index™ is increasing, it means that there is an increasing risk of hyperlactaternia and attention should be brought to the patient. The HLA Index™ presents partial quantitative information about the patient's cardiovascular condition, and no therapy or drugs can be administered based solely on the interpretation statements.
# WARNINGS:
- · Do not use the T3 Platform software as an active patient monitoring system.
- · Do not use the T3 Platform software to replace any part of the hospital's device monitoring.
- · Do not rely on the T3 Platform software as the sole source of patient status information.
- · Do not use any of the T3 Platform indices as a substitute for taking blood samples.
- · The indices present qualitative and potentially imperfect information of the patient's condition and in certain scenarios, the indices may contradict each other. The primary data should be reviewed as part of standard patient evaluations and no decisions should be solely based on the indices.
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Blank space
Type of Use (Select one or both, as applicable)
2 Prescription Use (Part 21 CFR 801 Subpart D)
— Over-The-Counter Use (21 CFR 801 Subpart C)
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May 13, 2022
This 510(k) summary has been prepared in accordance with Title 21 CFR §807.92 and FDA's guidance document, "The 510(k) Program: Evaluating Substantial Equivalence in Premarket Notifications 510(k)" July 28, 2014
9.1 510(k) Submitter
Timothy Hanson, VP of Regulatory Affairs and Quality Assurance 280 Summer St., 4th Floor Boston, MA 02210 Tel: 857.366.9333 ext. 2020 Email: THanson@etiometry.com
#### 9.2 Device
| Item | Description |
|--------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device Trade Name | T3 Platform™ software |
| Device Common/Usual Name | Clinical Decision Support Software (without alarms) |
| Classification Name | Adjunctive cardiovascular status indicator |
| Classification Number | 870.2200 |
| Regulatory Class | Class II with special controls - the primary code is PPW: The adjunctive<br>cardiovascular status indicator is a prescription device based on sensor<br>technology for the measurement of a physical parameter(s). This device is<br>intended for adjunctive use with other physical vital sign parameters and<br>patient information and is not intended to independently direct therapy. |
Table 97: Device Information
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# 9.3 Predicate Devices
The primary predicate device is the CipherOx CRI, cleared under DEN160020, and the supportive predicate device is the T3 Platform™ software featuring the T3 Data Aggregation & Visualization software module version 5.0 and the T3 Risk Analytics Engine software module version 6.0, cleared under K202306. These predicates have not been subject to a design-related recall. No reference devices were used in this submission.
# 9.4 Device Description
The Tracking, Trajectory, Trigger (73) intensive care unit software solution allows clinicians and quality improvement teams in the ICU to aggregate data from multiple sources, store it in a database for analysis, and view the streaming data. System features include:
- Adjunctive status indicators
- Customizable display of physiologic parameters over entire patient stay
- Configurable annotation
- Web-based visualization that may be used on any standard browser
- Minimal IT footprint
- Software-only solution no new bedside hardware required
- Highly reliable and robust operation
- Auditable data storage
# 9.5 Indications for Use
The T3 Platform™ software features the T3 Data Aggregation & Visualization software module version 5.0 and the T3 Risk Analytics Engine software module version 8.0.
The T3 Data Aggregation & Visualization software module is intended for the recording and display of multiple physiological parameters of the adult, pediatric, and neonatal patients from supported bedside devices. The software module is not intended for alarm notification or waveform display, nor is it intended to control any of the independent bedside devices to which it is connected. The software module is intended to be used by healthcare professionals for the following purposes:
- To remotely consult regarding a patient's status, and
- To remotely review other standard or critical near real-time patient data in order to utilize this information to aid in clinical decisions and deliver patient care in a timely manner.
The T3 Data Aggregation & Visualization software module can display numeric physiologic data captured by other medical devices:
- Airway flow, volume, and pressure
- Arterial blood pressure (invasive and non-invasive, systolic, diastolic, and mean)
- · Bispectral index (BIS, signal quality index, suppression ratio)
- Cardiac Index
- Cardiac output
- Central venous pressure
- · Cerebral perfusion pressure
- End-tidal CO2
- Heart rate
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- Heart rate variability
- Intracranial pressure
- Left atrium pressure
- · Oxygen saturation (intravascular, regional, SpO2)
- Premature ventricular counted beats
- Pulmonary artery pressure (systolic, diastolic, and mean)
- Pulse pressure variation
- Pulse Rate
- · Respiratory rate
- Right atrium pressure
- Temperature (rectal, esophageal, tympanic, blood, core, nasopharyngeal, skin)
- · Umbilical arterial pressure (systolic, diastolic, and mean)
The T3 Data Aggregation & Visualization software module can display laboratory measurements including arterial and venous blood gases, complete blood count, and lactic acid.
The T3 Data Aggregation & Visualization software module can display information captured by the T3 Risk Analytics Engine software module.
The T3 Risk Analytics Engine software module calculates four indices: the IDO2 Index™ for inadequate delivery of oxygen, the IVCO2 Index™ for inadequate ventilation of carbon dioxide, the ACD Index™ for acidemia, and the HLA Index™ for hyperlactatemia.
The IDO2 Index™ is indicated for use by health care professionals with post-surgical patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The IDO2 Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation & Visualization software module. When the IDO2 Index™ is increasing, it means that there is an increasing risk of inadequate oxygen delivery and attention should be brought to the patient. The IDO2 Index™ presents partial quantitative information about the patient's cardiovascular condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The IVCO2 Index™ is indicated for use by health care professionals with invasively ventilated patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The IVCO2 Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation and Visualization software module. When the IVCO2 Index™ is increasing, it means that there is an increasing risk of inadequate carbon dioxide ventilation and attention should be brought to the patient. The IVCO2 Index™ presents partial quantitative information about the patient's respiratory condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The ACD Index™ is indicated for use by health care professionals with invasively ventilated patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The ACD Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation and Visualization software module. When the ACD Index™ is increasing, it means that there is an increasing risk of acidemia and attention should be brought to the patient. The ACD Index™ presents partial quantitative information about the patient's respiratory condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The HLA Index™ is indicated for use by health care professionals with post-surgical patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The HLA Index™ is derived by mathematical
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manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation & Visualization software module. When the HLA Index™ is increasing, it means that there is an increasing risk of hyperlactatemia and attention should be brought to the patient. The HLA Index™ presents partial quantitative information about the patient's cardiovascular condition, and no therapy or drugs can be administered based solely on the interpretation statements.
# WARNINGS:
- Do not use the T3 Platform™ software as an active patient monitoring system. ●
- Do not use the T3 Platform™ software to replace any part of the hospital's device ● monitoring.
- Do not rely on the T3 Platform™ software as the sole source of patient status information.
- Do not use any of the T3 Platform™ indices as a substitute for taking blood samples.
- The indices present qualitative and potentially imperfect information of the patient's condition and in certain scenarios, the indices may contradict each other. The primary data should be reviewed as part of standard patient evaluations and no decisions should be solely based on the indices.
9.6 Comparison of Technological Characteristics with the Predicate Device
The primary predicate device, having the product code PPW, is intended for use as a multiparameter monitor that uses sensor technology to measure a specific parameter. The devices that fall under this regulation product code (Adjunctive cardiovascular status indicator 21 CFR 870.2200) do not have alarms and do not have a set decision point, matching the functionalities of the subject device. The regulation product code of the primary predicate device includes special controls that were applied to the subject T3 Platform™ software. The regulation product codes between the subject T3 Platform™ software and supportive predicate T3 Platform™ software were unchanged. The subject T3 Platform™ software and supportive predicate T3 Platform™ software have the same Intended Use adding the ACD and HLA Indices.
| Feature/Improvement | Description |
|---------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| ACD Index | The underlying physiology model of the Risk Analytics Engine (version<br>8.0) has been updated to afford the computation of a new index which<br>is a measure of the likelihood that an arterial blood gas will indicate<br>acidemia defined as arterial pH less than 7.25. The new index has been<br>subject to the same performance testing as the predicate IDO2 and<br>IVCO2 indices. Specifically, the enclosed 510(k) application includes<br>performance test results using clinical data, covering the indicated<br>patient age range: 0 to 12 years of age. |
| Feature/Improvement | Description |
| HLA Index | Additional changes to the underlying physiology model of the Risk<br>Analytics Engine (version 8.0) enable the computation of a second new<br>index which is a measure of the likelihood that a laboratory result will<br>indicate hyperlactatemia defined as whole blood lactate level<br>concentration above 4 mmol / L. The new index has been subject to the<br>same performance testing as the predicate IDO2 and IVCO2 indices.<br>Specifically, the enclosed 510(k) application includes performance test<br>results using clinical data, covering the indicated patient age range: 0 to<br>12 years of age. |
| Tidal Volume to Minute Ventilation Input<br>Change | The Risk Analytics Engine (version 8.0) employs direct measurements of<br>minute ventilation provided by the ventilator instead of relying on the<br>indirect calculation of minute ventilation accomplished by multiplying<br>tidal volume and respiratory rate. |
| Removal of EtCO2 as required input for<br>IVCO2 | The IVCO2 Index included as part of the Risk Analytics Engine (version<br>8.0) no longer requires EtCO2 to be available as part of the minimum<br>data. More specifically, the software utilizes blood gas measurements,<br>arterial or venous pCO2 collected at a minimum of once every 12 hours,<br>interchangeably with EtCO2 measurements. When blood gases are not<br>available, the software processes available EtCO2 measurements to<br>satisfy the minimum data set required as was the case in previous<br>cleared releases. |
| Continuous Performance Assessment | In order to continually monitor the performance of the Risk Indices in<br>different operating environments and clinical settings, the Continuous<br>Performance Assessment module (CPA) was developed, which<br>periodically computes all critical performance metrics for a site and<br>reports these metrics via email to the Etiometry Support team. If the<br>CPA tool indicates that the performance of the Risk indices at a<br>particular site is out of specification, the support team can use this<br>information to take action, investigate the root cause, and apply<br>mitigation measures as needed. |
| Repair to the Risk Algorithm Engine response<br>to Reinitialization | As part of the required behavior, when a Risk index is initialized on an<br>individual patient, the index is not reported before the minimum data<br>set is achieved and the index is calibrated (5 minutes post initialization).<br>This behavior was not propagated to the rare instances of algorithm<br>reinitialization, which did not match the original requirement. The Risk<br>Analytics Engine (version 8.0) provides a repair that satisfies the original<br>requirement. |
| Feature/Improvement | Description |
| IVCO2 Index patient population | The patient population in the indications for use was expanded from 29<br>days to 12 years of age to 0 to 12 years of age for the IVCO2 Index in<br>the Risk Analytics Engine (version 8.0). |
The subject and predicate devices differ with respect to several technological features. (see Table 98).
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rable 98: Summary of Changes
#### 9.7 Summary of Non-Clinical Performance Testing
Software documentation was provided in accordance with the 2017 FDA guidance document Software as a Medical Device (SAMD): Clinical Evaluation section 5.3 Analytical Validation of a SaMD to support device software with a moderate level of concern and to confirm and provide objective evidence that the software was correctly constructed.
Cybersecurity information was provided in accordance with the 2014 FDA guidance document Content of Premarket Submissions for Management of Cybersecurity in Medical Devices.
Additional summative evaluations were completed to demonstrate the consistency of the output, representative of the range of data sources and data quality, likely to be encountered.
Human factors testing was used to support that device users could safely use the device.
# 9.8 Summary of Clinical Performance Testing
All of the four indices are a product of a model-based approach to risk estimation. The approach is designed based on principles of physiology, and parameters are chosen to reflect those specified in the medical literature and employed development testing data sets and validation sets. Development testing sets are used to evaluate the impact of the development changes during the development process. Validation sets are then used after all development is complete to validate that performance holds on an independent data set.
The four indices were validated utilizing validation sets that included data from eleven different clinical sites in the US. The clinical study data were obtained by the T3 Platform software. No adverse effects and complications were noted. The indices were retrospectively computed on all de-identified patients. The new indices were evaluated against the same acceptance criteria as the supportive predicate device, being discriminatory power, range utilization, resolution/limitation, and robustness.
A patient cohort was used to validate the HLA Index. The distribution of the points included in the HLA study among the participating centers totaling 58,168 whole blood lactate measurements from 3,496 patients was included in that validation data set. The demographics were 31% infants, and 33% children.
A patient cohort was used to validate the ACD Index. The distribution of the points included in the ACD study among the participating centers totaling 24,431 arterial blood pH measurements from 1,858 patients was included in the validation data set. The demographics were 40% infants, and 26% children.
Additionally, subpopulations studies (neonates, infants, and children) under each of the HLA study and ACD study were completed.
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All results met acceptance criteria for discriminatory power, range utilization, resolution/limitation, and robustness.
Software documentation was provided in accordance with the 2017 FDA guidance document Software as a Medical Device (SAMD): Clinical Evaluation section 5.3 Analytical Validation of a SaMD to support device software with a moderate level of concern and to yield a clinically meaningful output associated to the target use of the output in the target health care situation identified in the definition statement.
#### 9.9 Summary
Based on the clinical performance, the T3 Platform™ software was found to have a safety and effectiveness profile that is similar to the predicate devices.
# 9.10 Conclusions
Substantial equivalence of the T3 Platform™ software is demonstrated through performance testing and clinical evaluation and through the special controls of the PPW product code of the primary predicate device. The T3 Platform™ software has the equivalent design, features, and functionality as the supportive predicate T3 Platform™ software with few exceptions. These exceptions do not affect the safety or effectiveness of the system. No new questions of safety or effectiveness are raised as a result of the differences when compared to the predicate devices. The software verification demonstrates that the T3 Platform™ software performs as intended in the specified use conditions. The clinical evaluation demonstrates that the T3 Platform™ software performs comparably to the predicate devices that are currently marketed for the same intended use.
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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.