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The Revogene® instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. Revogene is capable of automated lysis and dilution of samples originating from various clinical specimen types. Revogene performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

The Revogene® instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. Revogene is capable of automated lysis and dilution of samples originating from various clinical specimen types. Revogene performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

The provided document is an FDA 510(k) Substantial Equivalence Determination Decision Summary for the Revogene instrument.
Crucially, this submission (K222779) is a "Special 510(k)" for a firmware modification only, specifically to add a cooling sequence before lid opening in the event of a run interruption.

Therefore, the document does not contain information about a study to prove the device's diagnostic performance against acceptance criteria in the typical sense of analytical or clinical performance (e.g., sensitivity, specificity for detecting a disease). Instead, the performance demonstrated here relates to the safety feature implemented by the firmware update.

Based on the provided text, here's an analysis of the acceptance criteria and study that address the firmware modification:

1. Table of Acceptance Criteria and Reported Device Performance:

The document implicitly defines the acceptance criteria for this specific modification: the firmware update must successfully implement a cooling sequence before lid opening when a run is interrupted, to prevent access to hot parts.

2. Sample size used for the test set and the data provenance:

The document does not detail specific sample sizes or data provenance (e.g., country of origin, retrospective/prospective) for testing this firmware modification. This is expected given the nature of a Special 510(k) for a safety-related firmware update. The FDA's decision to clear the device implies they were satisfied with the internal validation conducted by the manufacturer to demonstrate the successful implementation of this safety feature. No clinical data or large-scale analytical testing is typically required for such minor safety updates.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not applicable for this type of firmware modification. The ground truth here is a functional safety requirement (i.e., "are hot parts accessible when a run is aborted after the update?"). This would be verified through engineering testing and safety assessments, not typically by expert consensus of clinical or radiological images.

4. Adjudication method for the test set:

Not applicable. This is not a study assessing diagnostic performance where adjudication of ambiguous results would be necessary.

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:

Not applicable. This device is an instrument for molecular diagnostics (nucleic acid testing), not an AI-assisted diagnostic imaging device.

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

Not directly applicable in the typical sense (e.g., for an AI algorithm). The device itself operates "standalone" in its function of automated lysis, amplification, and detection, but the "performance" discussed here is a safety feature of its firmware, not its diagnostic accuracy.

7. The type of ground truth used:

The ground truth for this specific firmware modification is a functional safety performance objective. The "truth" is whether the cooling sequence activates as intended upon run interruption and whether it effectively prevents access to hot parts, thereby improving user safety. This would be established through engineering functional testing and safety verification protocols.

8. The sample size for the training set:

Not applicable. This is a firmware modification for a safety feature, not a machine learning algorithm that requires a "training set."

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

Not applicable. As above, no training set for a machine learning model is involved.

Summary of the document's relevance to your request:

The provided document is an FDA clearance letter for a firmware upgrade to an existing medical device, the Revogene instrument. This is a very specific type of submission (Special 510(k)) that focuses on demonstrating that a minor change does not adversely affect the device's safety or effectiveness, or alter its fundamental scientific technology.

Therefore, the typical metrics and study designs used for evaluating the diagnostic performance of new AI/ML-based devices (e.g., sensitivity, specificity, MRMC studies, ground truth established by expert consensus or pathology) are not present or applicable here. The "acceptance criteria" and "study" are focused solely on verifying the successful and safe implementation of the firmware's added cooling sequence upon run interruption.

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