(226 days)
Cerebral Autoregulation Index (CAI) Algorithm is an informational index intended to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired as expressed by the level of coherence or lack thereof between Mean Arterial Pressure (MAP) and the Absolute Levels of Blood Oxygenation Saturation (StO2) in patient's cerebral tissue. MAP is acquired by the HemoSphere pressure cable and StO2 is acquired by the ForeSight oximeter cable. CAI is intended for use in patients over 18 years of age receiving advanced hemodynamic monitoring. CAI is not indicated to be used for treatment of any disease or condition and no therapeutic decisions should be made based solely on the Cerebral Autoregulation Index (CAI) Algorithm.
The Cerebral Adaptive Index (CAI) Algorithm is being renamed to Cerebral Autoregulation Index (CAI) Algorithm. The originally cleared Cerebral Adaptive Index is in effect an index of cerebral autoregulation, and the renaming results in a labeling change. The evidence to support the proposed labeling change for the Cerebral Autoregulation Index algorithm demonstrates the capability of CAI to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired, as expressed by the level of coherence or lack thereof between MAP (as a surrogate of cerebral perfusion pressure) and cerebral StO2 (as a surrogate of cerebral blood flow) of the patient.
The Cerebral Autoregulation Index (CAI) Algorithm is a derived parameter that quantifies the dynamic relationship between two existing hemodynamic parameters, Mean Arterial Pressure (MAP) and the Absolute Levels of Blood Oxygenation Saturation (StO2) in the cerebral tissue. CAI is intended to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired as expressed by the level of coherence between MAP and cerebral StO2. The output will be represented as an index value in a trend plot.
MAP is acquired from the HemoSphere Pressure Cable (initially cleared in K180881 on November 16, 2018). StO2 used for computing CAI is acquired from the ForeSight Oximeter Cable (cleared in K201446 on October 1, 2020).
CAI will be continuously displayed at 20-second rate. The parameter will not have any alarm ranges and will be represented as a number with a range between 0 to 100. A high CAI value (CAI ≥45) means that MAP and StO2 have a greater coherence and informs the clinician that alterations in MAP may result in concomitant changes in cerebral oxygen saturation because cerebral autoregulation is likely impaired. Whereas a low CAI value (CAI < 45) means there is lesser coherence between the two parameters, and therefore alterations in MAP may not result in concomitant changes in cerebral oxygen saturation because cerebral autoregulation is likely intact.
Here’s a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:
Device Name: Cerebral Autoregulation Index (CAI) Algorithm
The document describes a 510(k) submission for a name change (and re-clarification of its meaning) of an existing device (Cerebral Adaptive Index (CAI) Algorithm) to Cerebral Autoregulation Index (CAI) Algorithm. The core algorithm and its function remain the same. The performance data presented appears to be the original validation data for the algorithm, supporting the claim that the renamed device retains its safety and effectiveness.
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Performance Goals) | Reported Device Performance (Overall N=50) |
|---|---|
| Sensitivity ≥ 80% at the CAI threshold of 45 | 82% [95% CI: 75, 88] |
| Specificity ≥ 80% at the CAI threshold of 45 | 94% [95% CI: 91, 96] |
| ROC AUC (Summarized performance, higher AUC indicates better performance) | 0.92 [95% CI: 0.89, 0.94] |
Study Details
-
Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: 50 subjects.
- Data Provenance: Retrospectively obtained from 3 clinical sites:
- Northwestern University, Chicago, USA
- UC Davis, Sacramento, USA
- Amsterdam UMC, Amsterdam, The Netherlands
- Patient Characteristics: Adult surgical patients (cardiac and general surgery) over 18 years of age.
-
Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts:
- The document does not specify the number of experts used to establish the ground truth or their qualifications. The ground truth was established algorithmically based on physiological measurements.
-
Adjudication Method:
- Not applicable/Not mentioned. The ground truth was established via a polynomial fit of CBFV-MAP data to determine LLA and ULA, and then a rule-based classification (Intact or Impaired) was applied. There's no indication of human adjudication of this ground truth.
-
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No MRMC study was done, as this algorithm is not intended for human interpretation or direct assistance in a diagnostic image reading scenario. Its output is an index value representing a physiological state.
-
Standalone Performance:
- Yes, a standalone performance evaluation was conducted. The study assessed the algorithm's ability to discriminate between "Intact" and "Impaired" cerebral autoregulation conditions based on its calculated CAI value, against a ground truth derived from physiological measurements (CBFV-MAP).
-
Type of Ground Truth Used:
- Physiological Ground Truth: The ground truth for cerebral autoregulation status (Intact vs. Impaired) was established using a polynomial fit of Cerebral Blood Flow Velocity (CBFV) and Mean Arterial Pressure (MAP) data. Specifically, LLA (Lower Limit of Autoregulation) and ULA (Upper Limit of Autoregulation) were determined from this data, and an autoregulation status was assigned based on MAP's relationship to these limits:
- Impaired: MAP ≤ LLA or MAP ≥ ULA
- Intact: LLA < MAP < ULA
- Physiological Ground Truth: The ground truth for cerebral autoregulation status (Intact vs. Impaired) was established using a polynomial fit of Cerebral Blood Flow Velocity (CBFV) and Mean Arterial Pressure (MAP) data. Specifically, LLA (Lower Limit of Autoregulation) and ULA (Upper Limit of Autoregulation) were determined from this data, and an autoregulation status was assigned based on MAP's relationship to these limits:
-
Sample Size for the Training Set:
- The document does not explicitly state the sample size for a training set. The validation activities described refer to "Algorithm verification testing" and "Validation using animal data" and "Validation using clinical data." It's possible that the "clinical data" refers to the test set described, and if there was a separate training set, its size and characteristics are not provided in this specific section. Given that this is a 510(k) for a renaming of an already cleared algorithm, the focus is on re-demonstrating the performance of the known algorithm.
-
How the Ground Truth for the Training Set Was Established:
- As the training set sample size is not specified, how its ground truth was established is also not detailed in this excerpt. However, it's reasonable to infer that if a training set was used, the ground truth would have been established similarly to the test set, using physiological measurements (CBFV and MAP) to derive autoregulation status.
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October 16, 2024
Image /page/0/Picture/1 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.
Edwards Lifesciences Daphney Germain-Kolawole Director, Regulatory Affairs Program Management One Edwards Way Irvine, California 92614
Re: K240596
Trade/Device Name: Cerebral Autoregulation Index (CAI) Algorithm Regulation Number: 21 CFR 870.2700 Regulation Name: Oximeter Regulatory Class: Class II Product Code: MUD, QEM Dated: September 13, 2024 Received: September 16, 2024
Dear Daphney Germain-Kolawole:
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 (the 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 available 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.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
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Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the OS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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 medical devices and radiation-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,
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FDA Patrick Antkowiak -S
for
Jay Gupta Assistant Director DHT5A: Division of Neurosurgical, Neurointerventional, and Neurodiagnostic Devices OHT5: Office of Neurological and Physical Medicine 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) K240596
Device Name
Cerebral Autoregulation Index (CAI) Algorithm
Indications for Use (Describe)
Cerebral Autoregulation Index (CAI) Algorithm is an informational index intended to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired as expressed by the level of lack thereof between Mean Arterial Pressure (MAP) and the Absolute Levels of Blood Oxygenation Saturation (StO2) in patient's cerebral tissue. MAP is acquired by the HemoSphere pressure cable and StO2 is acquired by the ForeSight oximeter cable. CAI is intended for use in patients over 18 years of age receiving advanced hemodynamic monitoring. CAI is not indicated to be used for treatment of any disease or condition and no therapeutic decisions should be made based solely on the Cerebral Autoregulation Index (CAI) Algorithm.
| 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)
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510(K) SUMMARY
| Cerebral Autoregulation Index (CAI) Algorithm | ||
|---|---|---|
| 510(k)Submitter | Edwards Lifesciences LLCOne Edwards Way, Irvine, CA 92614(949) 250-5466 | |
| ContactPerson | Primary ContactDaphney Germain-KolawoleDirector, RA Program ManagementEdwards Lifesciences LLCOne Edwards Way,Irvine, CA USA, 92614Tel.: (949) 250-5466Email:daphney_germainkolawole@edwards.com | Secondary ContactKaren ClementSenior Director, Regulatory AffairsEdwards Lifesciences LLCOne Edwards Way,Irvine, CA USA, 92614Tel.: (949) 250-4746Email: karen_clement@edwards.com |
| DatePrepared | September 13, 2024 | |
| Trade Name | Cerebral Autoregulation Index (CAI) Algorithm | |
| RegulationNumber /Name | 21 CFR 870.2700 / Oximeter | |
| ProductCode | MUD (21 CFR 870.2700), QEM (21 CFR 870.2700) | |
| RegulationClass | Class II | |
| PredicateDevice | Cerebral Adaptive Index (CAI) Algorithm | |
| DeviceDescription | The Cerebral Adaptive Index (CAI) Algorithm is being renamed to CerebralAutoregulation Index (CAI) Algorithm. The originally cleared Cerebral Adaptive Indexis in effect an index of cerebral autoregulation, and the renaming results in a labelingchange. The evidence to support the proposed labeling change for the CerebralAutoregulation Index algorithm demonstrates the capability of CAI to represent asurrogate measurement of whether cerebral autoregulation is likely intact or is likelyimpaired, as expressed by the level of coherence or lack thereof between MAP (as asurrogate of cerebral perfusion pressure) and cerebral StO2 (as a surrogate of cerebralblood flow) of the patient.The Cerebral Autoregulation Index (CAI) Algorithm is a derived parameter thatquantifies the dynamic relationship between two existing hemodynamic parameters,Mean Arterial Pressure (MAP) and the Absolute Levels of Blood OxygenationSaturation (StO2) in the cerebral tissue. CAI is intended to represent a surrogatemeasurement of whether cerebral autoregulation is likely intact or is likely impaired as | |
| Cerebral Autoregulation Index (CAI) Algorithm | ||
| expressed by the level of coherence between MAP and cerebral StO2. The output willbe represented as an index value in a trend plot.MAP is acquired from the HemoSphere Pressure Cable (initially cleared in K180881on November 16, 2018). StO2 used for computing CAI is acquired from the ForeSightOximeter Cable (cleared in K201446 on October 1, 2020).CAI will be continuously displayed at 20-second rate. The parameter will not have anyalarm ranges and will be represented as a number with a range between 0 to 100. Ahigh CAI value (CAI ≥45) means that MAP and StO2 have a greater coherence andinforms the clinician that alterations in MAP may result in concomitant changes incerebral oxygen saturation because cerebral autoregulation is likely impaired. Whereasa low CAI value (CAI < 45) means there is lesser coherence between the twoparameters, and therefore alterations in MAP may not result in concomitant changes incerebral oxygen saturation because cerebral autoregulation is likely intact. | ||
| Indicationsfor Use | Cerebral Autoregulation Index (CAI) Algorithm is an informational index intended torepresent a surrogate measurement of whether cerebral autoregulation is likely intactor is likely impaired as expressed by the level of coherence or lack thereof betweenMean Arterial Pressure (MAP) and the Absolute Levels of Blood OxygenationSaturation (StO2) in patient's cerebral tissue. MAP is acquired by the HemoSpherepressure cable and StO2 is acquired by the ForeSight oximeter cable. CAI is intended foruse in patients over 18 years of age receiving advanced hemodynamic monitoring. CAIis not indicated to be used for treatment of any disease or condition and no therapeuticdecisions should be made based solely on the Cerebral Autoregulation Index (CAI)Algorithm. | |
| Intended Use | Cerebral Autoregulation Index (CAI) Algorithm is intended to be used by qualifiedpersonnel or trained clinicians in a critical care environment in a hospital setting. Thealgorithm is intended to represent a surrogate measurement of whether cerebralautoregulation is likely intact or is likely impaired as expressed by the level ofcoherence or lack thereof between MAP and cerebral StO2. | |
| ComparativeAnalysis | The subject Cerebral Autoregulation Index (CAI) Algorithm is similar to the predicateCerebral Adaptive Index (CAI) Algorithm in terms of the intended use and indicationsfor use. The technological characteristics are identical (including design and principleof operation). Both the subject and predicate devices use the measurement of absoluteregional hemoglobin oxygen saturation of blood under the sensor in their calculations.When sensors are applied to patient's cerebral region, CAI uses the StO2 signals inconjunction with MAP signals and calculates the coherence between the measuredcerebral StO2 and MAP. Hence, the predicate Cerebral Adaptive Index (CAI)Algorithm is being used to establish substantial equivalence for the subject CerebralAutoregulation Index (CAI) Algorithm.The following table details the comparisons and differences between the subject andpredicate devices. |
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| Parameter | Subject DeviceCerebralAutoregulationIndex (CAI)Algorithm | PredicateDeviceCerebralAdaptive Index(CAI) Algorithm | Comparison | |
|---|---|---|---|---|
| Trade Name | CerebralAutoregulationIndex (CAI)Algorithm | CerebralAdaptive Index(CAI) Algorithm | Same +AutoregulationDevice name hasbeen modified toreference"Autoregulation"to distinguish thismodel from thepredicate version. | |
| 510(k)number | K240596 | K223651 | Not applicable | |
| Manufacturer | EdwardsLifesciences | EdwardsLifesciences | Same | |
| DeviceClassification | Class II | Class II | Same | |
| RegulationNumber | 21 CFR870.2700 | 21 CFR870.2700 | Same | |
| Product Code– DeviceClassificationName | MUD –Oximeter,TissueSaturationQEM -CerebralOximeter | MUD –Oximeter, TissueSaturationQEM – CerebralOximeter | Same | |
| Intended Use | CerebralAutoregulationIndex (CAI)Algorithm isintended to beused byqualifiedpersonnel ortrainedclinicians in acritical careenvironment ina hospital | CerebralAdaptive Index(CAI) Algorithmis intended to beused by qualifiedpersonnel ortrained cliniciansin a critical careenvironment in ahospital setting.The algorithm isintended to showthe level of | Same +AutoregulationDevice name hasbeen modified toreference“Autoregulation”.The CerebralAdaptive Index isin effect an indexof cerebral | |
| Cerebral Autoregulation Index (CAI) Algorithm | ||||
| setting. CAI isintended torepresent asurrogatemeasurement ofwhethercerebralautoregulationis likely intactor is likelyimpaired asexpressed bythe level ofcoherence orlack thereofbetween MAPand cerebralStO2. | coherencebetween MAPand cerebralStO2. | autoregulation.The evidence tosupport theproposed labelingchange for theCerebralAutoregulationIndex algorithmdemonstrates thecapability of CAIto represent asurrogatemeasurement ofwhether cerebralautoregulation islikely intact or islikely impaired asexpressed by thelevel ofcoherence or lackthereof betweenMAP andCerebral StO2 ofthe patient. | ||
| Indicationsfor Use | CerebralAutoregulationIndex (CAI)Algorithm is aninformationalindex intendedto represent asurrogatemeasurement ofwhethercerebralautoregulationis likely intactor is likelyimpaired asexpressed bythe level ofcoherence orlack | CerebralAdaptive Index(CAI) Algorithmis aninformationalindex to helpassess the levelof coherence orlack thereofbetween MeanArterial Pressure(MAP) and theAbsolute Levelsof BloodOxygenationSaturation (StO2)in patient'scerebral tissue.MAP is acquiredby the | Similarindications.Device name hasbeen modified toreference"Autoregulation".The CerebralAdaptive Index isin effect an indexof cerebralautoregulation,which results in alabeling change.The evidence tosupport theproposed labelingchange for theCerebral | |
| Cerebral Autoregulation Index (CAI) Algorithm | ||||
| thereof betweenMean ArterialPressure (MAP)and theAbsolute Levelsof BloodOxygenationSaturation(StO2) inpatient'scerebral tissue.MAP isacquired by theHemoSpherepressure cableand StO2 isacquired by theForeSightoximeter cable.CAI is intendedfor use inpatients over 18years of agereceivingadvancedhemodynamicmonitoring.CAI is notindicated tobe used fortreatment of anydisease orcondition andno therapeuticdecisionsshould be madebased solely onthe CerebralAutoregulationIndex (CAI)Algorithm. | HemoSpherepressure cableand StO2 isacquired by theForeSightoximeter cable.CAI is intendedfor use inpatients over 18years of agereceivingadvancedhemodynamicmonitoring. CAIis not indicatedto be used fortreatment of anydisease orcondition and notherapeuticdecisions shouldbe made basedsolely on theCerebralAdaptive Index(CAI) Algorithm. | AutoregulationIndex algorithmdemonstrates thecapability of CAIto represent asurrogatemeasurement ofwhether cerebralautoregulation islikely intact or islikely impaired asexpressed by thelevel ofcoherence or lackthereof betweenMAP andCerebral StO2 ofthe patient. | ||
| Parameters | StO2MAP | StO2MAP | Same | |
| Cerebral Autoregulation Index (CAI) Algorithm | ||||
| CAI | CAI | Same | ||
| Method ofOperation | The CAIalgorithmcalculates thelevel ofcoherencebetweenobtained StO2measurementfromNIRSwaveforms andobtained MAPmeasurementfrom thepressurewaveform. TheCAI value isdisplayed to theuser. | The CAIalgorithmcalculates thelevel ofcoherencebetweenobtained StO2measurementfromNIRSwaveforms andobtained MAPmeasurementfrom thepressurewaveform. TheCAI value isdisplayed to theuser. | Same | |
| PerformanceData (Benchand/orClinical) | The following verification activities were performed in support of a substantialequivalence determination for the subject Cerebral Autoregulation Index (CAI)Algorithm and Cerebral Adaptive Index (CAI) Algorithm and to ensure the safety andeffectiveness of the Cerebral Autoregulation Index (CAI) Algorithm.Software VerificationThe Cerebral Autoregulation Index (CAI) Algorithm was tested at the algorithm levelto verify the performance of the device. Algorithm verification testing was performedon the CAI algorithm in accordance with IEC 62304:2006/A1:2016 Medical devicesoftware - Software life cycle processes and FDA's Guidance for Industry and Foodand Drug Administration Staff, the Content of Premarket Submissions for DeviceSoftware Contained in Medical Devices Functions. (issued June 14, 2023). Thevalidation of the CAI Algorithm was performed as follows:1. Validation using animal data2. Validation using clinical dataThe algorithm passed all testing. | |||
| Clinical Performance DataThe following clinical performance data was submitted to support the indications foruse of the subject device: |
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Cerebral Autoregulation Index (CAI) Algorithm
Demographics
The demographics of CAI Algorithm validation dataset are captured in Table 1-1 below.
Patient Baseline Characteristics
The validation dataset had no inclusion/exclusion criteria related to patient baseline characteristics. In general, adult surgical patients (cardiac and general surgery) whose StO2 and MAP were being monitored respectively via Foresight Sensors and Flotrac Sensors and whose cerebral blood flow velocity (CBFV) was being monitored via transcranial doppler ultrasound were randomly selected for the retrospective analysis.
Enrollment
The validation dataset was retrospectively obtained from 3 different clinical sites (Northwestern University, Chicago, US; UC Davis, Sacramento, US; Amsterdam UMC, Amsterdam, The Netherlands). A total of 50 subjects aged 18 or older were randomly selected for inclusion in the CAI Algorithm K240596 validation study. Table 1-1 provides the number of patients enrolled from each site as well as the patient demographics and the surgery types from all three sites.
Table 1-1 Summary of patient demographic information for the 3 sites used in the clinical data performance analysis. Data for Age, Height and Weight are Mean ± 1std and full range [min, max]
| Site | Number of Patients | Age (years) | Gender | Height (cm) | Weight (kg) | Surgery Type |
|---|---|---|---|---|---|---|
| Northwestern University, Chicago, USA | 18 | $66 \pm 10$[46, 84] | 4 Females14 Males | $173 \pm 13$[155, 201] | $89 \pm 30$[53, 163] | Cardiac surgery (N = 12)General surgery (N = 6) |
| UC Davis, Sacramento, USA | 9 | $61 \pm 17$[32, 77] | 4 Females5 Males | $169 \pm 9$[158, 180] | $79 \pm 20$[50, 111] | General surgery (N=9) |
| Amsterdam UMC, Amsterdam, The Netherlands | 23 | $58 \pm 16$[20, 81] | 7 Females16 Males | $180 \pm 11$[157, 200] | $83 \pm 15$[56, 122] | Cardiac surgery (N = 16)General surgery (N =7) |
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Cerebral Autoregulation Index (CAI) Algorithm
General Summarv The following is a summary of the validation procedure performed: MAP, StO2 and CBFV time-series data obtained from adult (18 years and older) patients were used for the validation testing. To validate and assess the performance of CAI, individual patients' Lower Limit of Autoregulation (LLA) and Upper Limit of Autoregulation (ULA) were determined using a polynomial fit of the CBFV-MAP data. A ground-truth cerebral autoregulation status assessment, either Intact or Impaired, was then made based on the identified LLA and ULA according to the following general rule: MAP ≤ LLA, autoregulation status = Impaired ● ● MAP ≥ ULA, autoregulation status = Impaired LLA < MAP < ULA, autoregulation status = Intact ● A Receiver Operating Characteristic (ROC) analysis was then performed to assess the performance of CAI to discriminate Intact vs Impaired cerebral autoregulation. Performance Metrics Using this data, the following performance metrics were calculated: · Sensitivity: The true positive rate; ratio of true positives to total number of positive events; TP/P=TP/(TP+FN), where True Positives (TP) are defined as Impaired cerebral autoregulation data points with a corresponding CAI value greater than or equal to a given threshold, and False Negatives (FN) are defined as Impaired cerebral autoregulation data points with a corresponding CAI value less than a given threshold. • Specificity: The true negative rate: ratio of true negatives to total number of negative events; TN/N=TN/(TN+FP), where True Negatives (TN) are defined as Intact cerebral autoregulation data points with a corresponding CAI value less than a given threshold, and False Positives (FP) are defined as Intact cerebral autoregulation data points with a corresponding CAI value greater than or equal to a given threshold. · ROC AUC: the area under the ROC curve (AUC) summarizes the performance as a single number (0.5 to 1) with a higher AUC associated with a better performing algorithm. Performance Goals The performance goals for CAI algorithm are defined as follows: Sensitivity and Specificity ≥ 80 % at the CAI threshold of 45.
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Cerebral Autoregulation Index (CAI) Algorithm
Results of Clinical Performance Testing
The performances of CAI for the chosen threshold of 45 on the 50 subjects enrolled are reported in Table 1-2 below.
Table 1-2 ROC analysis results for clinical data (N=50)
| ROC AUC | Sensitivity (%) | Specificity (%) | CAI Threshold |
|---|---|---|---|
| [95% confidenceinterval] | [95% confidenceinterval] | [95% confidenceinterval] | |
| 0.92 [0.89, 0.94] | 82 [75, 88] | 94 [91, 96] | 45 |
Table 1-3 provides the confusion matrix that was used to calculate sensitivity/specificity for CAI threshold of 45.
| Cerebral Autoregulation | |||
|---|---|---|---|
| Positive(Impaired Autoregulation) | Negative(Intact Autoregulation) | ||
| CAI | Positive(CAI ≥ 45) | 1812 (TP) | 493 (FP) |
| Negative(CAI < 45) | 392 (FN) | 7851 (TN) |
As shown in Table 1-2, at the chosen threshold of 45, CAI can accurately discriminate conditions of impaired cerebral autoregulation from conditions of intact autoregulation.
In order to evaluate potential site effects on CAI performance, the ROC analysis was also repeated for each site individually. The results are summarized in Table 1-4,1-5, and 1-6 below. The results demonstrate that CAI performance is consistent across different sites, as shown by the almost identical AUCs. The confidence intervals of AUCs and the sensitivity and specificity vary across sites due to different number of patients enrolled in different sites, and different number of positive events and/or negative events in these patients.
| Table 1-4 ROC analysis results for UC Davis clinical data (N=9) | |
|---|---|
| ----------------------------------------------------------------- | -- |
| CAIThreshold | Sensitivity (%)[95% confidenceinterval] | Specificity (%)[95% confidenceinterval] | ROC AUC[95% confidenceinterval] |
|---|---|---|---|
| 45 | 82[66, 93] | 89[67, 98] | 0.90[0.77, 0.96] |
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| Cerebral Autoregulation Index (CAI) Algorithm | |||
|---|---|---|---|
| Table 1-5 ROC analysis results for Northwestern University clinical data (N=18) | |||
| CAI Threshold | Sensitivity (%)[95% confidenceinterval] | Specificity (%)[95% confidenceinterval] | ROC AUC[95% confidenceinterval] |
| 45 | 74[61, 87] | 93[89, 98] | 0.87[0.79, 0.95] |
| Table 1-6 ROC analysis results for Amsterdam UMC clinical data (N=23) | |||
| CAI Threshold | Sensitivity (%)[95% confidenceinterval] | Specificity (%)[95% confidenceinterval] | ROC AUC[95% confidenceinterval] |
| 45 | 84[74, 89] | 96[94, 97] | 0.93[0.89, 0.96] |
| Conclusion | The Cerebral Autoregulation Index (CAI) Algorithm has successfully passedfunctional and performance testing, including software verification and validation,bench, and clinical analysis. Completion of all performance verification and validationactivities demonstrated that the subject device meets its predetermined design andperformance specifications. Verification activities performed confirmed that thedifferences in the features and design did not adversely affect the safety andeffectiveness of the subject device. Note that the lower bound CI performance goal wasnot pre-specified, but the observed results demonstrate safety and effectiveness.The testing performed demonstrates that the Cerebral Autoregulation Index (CAI)Algorithm is substantially equivalent to its legally marketed predicate. |
§ 870.2700 Oximeter.
(a)
Identification. An oximeter is a device used to transmit radiation at a known wavelength(s) through blood and to measure the blood oxygen saturation based on the amount of reflected or scattered radiation. It may be used alone or in conjunction with a fiberoptic oximeter catheter.(b)
Classification. Class II (performance standards).