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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

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

Study Details

1. 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.

2. 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.

3. 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.

4. 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.

5. 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).

6. 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

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