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510(k) Data Aggregation
(88 days)
PERSYST REVEAL
This software is intended for use by a trained EEG technician or neurologist.
The Persyst Reveal is a software only product. It runs on a personal computer and requires no specialized hardware. It identifies spike and seizure events are then reviewed, possibly deleted, and interpreted by the user. The digitized EEG input is read from a file on the personal computer (or available across the network).
Neither the computer nor the software control the delivery of energy, the administration of parenteral drugs, or another form of life sustaining function to the patient.
No diagnostic or effectiveness claims are made.
The provided text is a 510(k) clearance letter for the Persyst Reveal device, which is a software product that identifies spike and seizure events in EEG data. The clearance is based on substantial equivalence to a predicate device, the Stellate Sensa.
It's important to note that the provided text is a regulatory clearance document, not a detailed technical study report. As such, it does not contain the specific performance metrics, study designs, or detailed data typically found in a clinical study proving device effectiveness against acceptance criteria.
The document explicitly states: "No diagnostic or effectiveness claims are made." This strongly implies that the clearance was based on demonstrating functional equivalence to the predicate and meeting general controls, rather than rigorous performance metric-based studies against pre-defined acceptance criteria for diagnostic efficacy.
Therefore, many of the requested details about acceptance criteria and study particulars cannot be extracted from this document.
Here's what can be inferred and what cannot:
1. A table of acceptance criteria and the reported device performance
Acceptance Criteria | Reported Device Performance |
---|---|
Not explicitly defined in the document for performance metrics. The primary "acceptance criteria" for 510(k) clearance is substantial equivalence (functional and safety equivalence) to a predicate device. | The device identifies spike and seizure events from digitized EEG input. |
No diagnostic or effectiveness claims are made. | No performance metrics (e.g., sensitivity, specificity, accuracy) are reported in this document. |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
- Not available in the document. The document does not describe a performance study with a test set.
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)
- Not available in the document. Since no performance study is described, there's no mention of experts establishing ground truth for a test set. The software is intended for review and interpretation by a "trained EEG technician or neurologist."
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
- Not available in the document. No test set or adjudication method is described.
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
- No, it was not done and is not described in the document. The document states "No diagnostic or effectiveness claims are made," indicating that such a study (which would aim to prove improved effectiveness) was not part of this submission for clearance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not explicitly described as a formal standalone performance study. The device "identifies spike and seizure events are then reviewed, possibly deleted, and interpreted by the user." This implies it's intended as an assistive tool, not for standalone diagnostic use without human-in-the-loop. Given "No diagnostic or effectiveness claims are made," a rigorous standalone performance study against clinical ground truth is highly unlikely to have been conducted for this submission.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Not available in the document. No ground truth definition is provided, as no performance study is detailed.
8. The sample size for the training set
- Not available in the document. The document does not provide details about algorithm training or development.
9. How the ground truth for the training set was established
- Not available in the document. No information regarding training set ground truth is present.
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