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IdentEvent® is a software-only product with an algorithm intended to analyze previously acquired, adult (≥18 years) scalp EEG signals and mark events that may correspond to electrographic seizures for the purpose of reviewing prolonged EEG traces. The marked events are reviewed, possibly deleted, and interpreted by qualified clinical practitioners who will exercise professional judgment in using the information.

IdentEvent also includes the display of the quantitative EEG parameters Amplitude Variation and Maximum Frequency, which are intended to help the user analyze the EEG waveform after it has been collected.

IdentEvent requires the use of EEGs recorded with at least a 16-channel scalp montage following the standard 10/20 electrode placement system. IdentEvent does not provide any diagnostic conclusion about the patient's condition to the user.

IdentEvent® is a software-only product with an algorithm intended to analyze previously acquired, adult (≥18 years) scalp EEG signals and mark events that may correspond to electrographic seizures for the purpose of reviewing prolonged EEG traces. The marked events are reviewed, possibly deleted, and interpreted by qualified clinical practitioners who will exercise professional judgment in using the information.

IdentEvent also includes the display of the quantitative EEG parameters Amplitude Variation and Maximum Frequency, which are intended to help the user analyze the EEG waveform after it has been collected.

IdentEvent requires the use of EEGs recorded with at least a 16-channel scalp montage following the standard 10/20 electrode placement system. IdentEvent does not provide any diagnostic conclusion about the patient's condition to the user.

This document is a 510(k) summary for the IdentEvent 2.0A device. However, it does not include detailed information regarding the acceptance criteria, specific study results, sample sizes for test and training sets, expert qualifications, or adjudication methods in the level of detail requested in the prompt.

The document primarily focuses on the FDA's substantial equivalence determination for the device, its indications for use, and regulatory information. It describes the IdentEvent 2.0A as a software-only product with an algorithm intended to analyze previously acquired, adult (≥18 years) scalp EEG signals and mark events that may correspond to electrographic seizures for the purpose of reviewing prolonged EEG traces. It also mentions the display of quantitative EEG parameters (Amplitude Variation and Maximum Frequency).

Therefore, based solely on the provided text, a complete answer as requested is not possible. However, I can infer some information from the "Indications for Use" section and general knowledge of medical device submissions to construct a partial answer and highlight what's missing.

Here's an attempt to answer the questions based on the provided document and common expectations for such submissions, specifying what is not explicitly stated:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state acceptance criteria or provide a table of reported device performance metrics (e.g., sensitivity, specificity, PPV, NPV). These details would typically be found in the more comprehensive 510(k) submission summary or a separate performance study report, which is not included here. The "Indications for Use" section describes the function of the device rather than its performance against specific clinical benchmarks.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided in the document.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided in the document.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

The document does not explicitly state if an MRMC study was done, nor does it provide an effect size for human reader improvement with AI assistance. The device's indication "for the purpose of reviewing prolonged EEG traces" by "qualified clinical practitioners who will exercise professional judgment in using the information" suggests it's an assistive tool, implying human-in-the-loop use. However, a formal comparative effectiveness study where improvement is quantified is not detailed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The document does not explicitly state if a standalone performance study was done. The indication that "The marked events are reviewed, possibly deleted, and interpreted by qualified clinical practitioners" strongly suggests that the device is intended for human-in-the-loop use, rather than a standalone diagnostic tool. Typically, studies for such devices would evaluate the algorithm's marking accuracy, which is a standalone performance aspect, but the actual performance metrics are not given here.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

The document does not explicitly state the type of ground truth used for validation. Given the device targets electrographic seizures, the ground truth would most likely be established by expert consensus of qualified clinical practitioners (e.g., neurologists, epileptologists) reviewing the raw EEG data, potentially combined with clinical outcomes or other diagnostic information if available.

8. The sample size for the training set

This information is not provided in the document.

9. How the ground truth for the training set was established

This information is not provided in the document. It would typically be established by expert review and annotation of the EEG data, similar to the test set ground truth.

Summary of what's provided vs. missing:

• Provided: Device name (IdentEvent 2.0A), Regulation Number (21 CFR 882.1400), Regulation Name (Electroencephalograph), Regulatory Class (Class II), Product Code (OMB, OLT), Indications for Use (analyzes previously acquired adult scalp EEG signals to mark events corresponding to electrographic seizures, displays Amplitude Variation and Maximum Frequency, requires 16-channel scalp montage), Type of Use (Prescription Use).
• Missing from this document: All specific details about acceptance criteria, performance metrics (sensitivity, specificity, accuracy), sample sizes (test and training), data provenance, expert qualifications for ground truth, adjudication methods, MRMC study results, or specific standalone study results. These details are critical for a full understanding of the device's validation.

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IdentEvent ™ is a software-only product with an algorithm intended to analyze previously acquired, adult (≥18 years) scalp EEG signals and mark events that may correspond to electrographic seizures for the purpose of reviewing prolonged EEG traces. The marked events are reviewed, possibly deleted, and interpreted by qualified clinical practitioners who will exercise professional judgment in using the information.

IdentEvent also includes the display of the quantitative EEG parameters Amplitude Variation and Maximum Frequency, which are intended to help the user analyze the EEG waveform after it has been collected.

IdentEvent requires the use of EEGs recorded with at least a 16-channel scalp montage following the standard 10/20 electrode placement system. IdentEvent does not provide any diagnostic conclusion about the patient's condition to the user.

Optima's IdentEvent™ analyzes digital scalp electroencephalograph (EEG) signals recorded from standard recording systems and displays information about brain electrical activity to the user. The application only analyzes and displays information from previously recorded digital EEG files. IdentEvent is designed for post-hoc EEG review of long-term EEG recordings, including the detection of seizure events.

IdentEvent requires previously recorded, digitized scalp EEG recordings with electrodes placed according to the standard 10/20 system. The recording can then be automatically analyzed to detect seizures which are then marked for review by the user. IdentEvent includes the following features (outputs):

• Display of raw & filtered EEG signals for review
• Display of the following quantitative EEG (qEEG) measures:
  • Amplitude Variation
  • Maximum Frequency
• Review (and possible deletion) of detected seizures
• Entry, editing and display of user-entered comments
• Graphical and text reports of detected seizures and comments.

Here's a detailed breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

1. Sample Size and Data Provenance:

   • Test Set Sample Size: A total of 436 EEG segments sampled from 55 long-term scalp EEG recordings. These 55 recordings came from 55 patients.
   • Data Provenance: Retrospective. The patients had medically refractory seizures and were admitted to multiple clinical sites for long-term EEG-video recordings for diagnostic or pre-surgical evaluation. The location of these clinical sites (country of origin) is not explicitly stated.

2. Number and Qualifications of Experts for Ground Truth:

   • Number of Experts: Three independent, blinded EEG experts.
   • Qualifications: All were neurologists/epileptologists. Specific years of experience are not mentioned.

3. Adjudication Method for Test Set:

   • A majority rule (at least 2 out of 3) was applied to determine the "true" electrographic seizure events. This method was chosen due to anticipated inter-rater variability among EEG experts.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No, a MRMC study was not explicitly described in the provided text. The study focused on comparing the algorithm's performance (IdentEvent) against a predicate device's algorithm (Persyst Reveal) and against expert consensus, not on evaluating human reader improvement with or without AI assistance.

5. Standalone (Algorithm Only) Performance Study:

   • Yes, a standalone study was performed. The "IdentEvent" algorithm's performance was evaluated independently against the reference standard established by the expert panel. The reported "Positive % Agreement" and "Negative Disagreement Rate" are standalone performance metrics for the algorithm.

6. Type of Ground Truth Used:

   • Expert Consensus: The ground truth for electrographic seizures was established by a panel of three independent, blinded neurologists/epileptologists using a majority rule.

7. Training Set Sample Size:

   • The document does not explicitly state the sample size for the training set. It only describes the test dataset.

8. How Ground Truth for Training Set Was Established:

   • The document does not describe how the ground truth for any potential training set was established. It only details the establishment of ground truth for the test set used for performance evaluation.

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