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The Endoflip™ 300 System is indicated for use in a clinical setting to measure pressure and dimensions in the esophagus, pylorus, and anal sphincters in adults and to measure pressure and dimensions in the esoplagus, in patients from five years of age. It is intended to be used as an adjunct to other diagnostic methods as part of a comprehensive evaluation of patients with symptoms consistent with gastrointestinal motility disorders.

The subject Endoflip™ 300 System is equivalent to the predicate Endoflip™ 300 System (K223705) except for an update to the Endoflip™ 300 System software to remove the analysis episode feature of the predicate device. Other software updates include minor feature enhancements and bug fixes. Changes to device labeling rrom the software updates and other minor changes for clarification purposes were also addressed.

The Endoflip™ 300 System software is supplied pre-installed in the Endoflip™ 300 Display System. It is also the software used for the Endoflip™ 300 Reader in reader mode only. There is no change to the display system hardware or to how the reader is supplied (USB stick).

No changes were made to any of the other components that comprise the Endoflip™ 300 System when compared to the predicate.

The provided text describes a 510(k) premarket notification for the Endoflip™ 300 System, which involves software updates to an existing device. This entire document is a 510(k) submission meant to demonstrate substantial equivalence to a predicate device, not a study specifically designed to establish acceptance criteria for a new device.

Therefore, many of the requested details regarding a standalone study, multi-reader multi-case study, and detailed ground truth methodologies for a specific study proving acceptance criteria are not present in this type of regulatory document.

However, based on the information provided, here's what can be extracted:

Acceptance Criteria and Device Performance:

The document's primary objective is to demonstrate substantial equivalence to the predicate device (Endoflip™ 300 System K223705) after software updates. Therefore, the "acceptance criteria" are implicitly that the updated device performs equivalently to the predicate device and does not introduce new safety or effectiveness concerns.

Specific numerical acceptance criteria and reported device performance from a clinical trial or performance study are not explicitly provided in terms of metrics like sensitivity, specificity, or error rates. Instead, the performance is evaluated through software verification.

Table of Acceptance Criteria and Reported Device Performance:

Since explicit quantitative acceptance criteria for a new device's performance are not given (as this is a 510(k) for an updated software version of an existing device), we can infer the acceptance criteria for the software updates.

Study Details:

The document describes software verification testing as the primary study type to establish substantial equivalence for the software updates.

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

   • Test Set Sample Size: Not specified. Software verification typically involves testing against a range of inputs and scenarios, but a "sample size" in the context of clinical data for performance metrics is not applicable here as no clinical performance data is presented.
   • Data Provenance: Not specified, as it's software verification, not a clinical data study.

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

   • Not applicable. This was software verification, not a study requiring expert-established ground truth on clinical data. The "ground truth" for software testing would be the expected behavior of the software according to its design specifications.

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

   • Not applicable. This was software verification.

4. 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, a multi-reader multi-case comparative effectiveness study was not done. The device (Endoflip™ 300 System) is a "Gastrointestinal Motility Monitoring System" that measures pressure and dimensions; it's not described as an AI-powered diagnostic tool for interpretation, but rather a direct measurement device with software for processing and displaying those measurements. The updates were minor software enhancements and bug fixes.

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

   • Yes, in a sense. The "study" was software verification, which inherently evaluates the algorithm's performance on its own against specifications, without human interpretation in the loop for diagnostic accuracy. The device itself is standalone in its measurement function, providing data to clinicians for their interpretation.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For software verification, the "ground truth" would be the software's design specifications and requirements. Each test case has an expected output or behavior based on these specifications, and the software's actual output is compared against this expected behavior. This is not clinical ground truth like pathology or expert consensus.

7. The sample size for the training set:

   • Not applicable. This was software verification testing for an updated version of an existing medical device, not a machine learning model involving a training set.

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

   • Not applicable for the same reason as above.

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