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The Next Generation Salem Sump is intended for gastric decompression and delivery of fluids, including irrigation, nutritional supplements, and medication, during the time period that gastric decompression is required.

The Next Generation Salem Sump is a dual lumen Naso Gastric tube with a multiport connector/valve to facilitate switching among the various function of the device.

The provided text is a 510(k) summary for the "Next Generation Salem Sump," which is a medical device. This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving performance against specific acceptance criteria through extensive clinical studies as one might find for a novel, higher-risk device.

Therefore, the information typically requested in your prompt (e.g., sample size for test set, number of experts for ground truth, MRMC studies, standalone performance, training set details) is not applicable or not available in this type of document because the device is a re-engineered version of an existing device and the "studies" are primarily non-clinical comparisons to predicate devices and industry standards.

Here's a breakdown based on the provided text, addressing your points where possible, and indicating where information is not present:

Acceptance Criteria and Device Performance Study for Next Generation Salem Sump (K040388)

This submission is a 510(k) Premarket Notification for a Class II medical device (Gastrointestinal tube and accessories). The device, the "Next Generation Salem Sump," is intended for gastric decompression and fluid delivery. The primary method of demonstrating its suitability for market clearance is by proving substantial equivalence to legally marketed predicate devices, rather than through extensive clinical efficacy trials against pre-defined acceptance criteria for performance. The "study" here refers to non-clinical testing to demonstrate equivalence or adherence to industry standards.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size (Test Set): Not specified. The document refers to "Nonclinical Testing" which likely involves specific device prototypes or components, but the number of units tested is not detailed in this summary.
• Data Provenance: Not specified, but given it's non-clinical testing performed by the manufacturer (The Kendall Company / Tyco Healthcare Group), it would be proprietary testing. Contextually, such testing is generally performed in a controlled laboratory setting, not with patient data.

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

• Not Applicable. For a device like a nasogastric tube undergoing non-clinical testing for substantial equivalence, "ground truth" and "experts" in the context of clinical interpretation (e.g., radiologists interpreting images) are not relevant. The "ground truth" here would be adherence to engineering specifications and performance standards as determined by test methods.

4. Adjudication method for the test set

• Not Applicable. No human interpretation or adjudication in the clinical sense is described. Non-clinical testing follows predefined protocols and acceptance criteria based on engineering and material science principles.

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 is a physical medical device (nasogastric tube), not an AI/software-as-a-medical-device (SaMD) or imaging device that would involve human readers or AI assistance.

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

• Not Applicable. See point 5.

7. The type of ground truth used

• Not Applicable / Engineering Specifications and Standards. For this type of submission, "ground truth" refers to the established engineering specifications for the device components and performance metrics derived from industry standards (EN1615:2000) or direct comparison to the predicate devices. It is not clinical data like pathology reports, expert consensus of images, or patient outcomes.

8. The sample size for the training set

• Not Applicable. There is no "training set" as this is not a machine learning or AI-driven device.

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

• Not Applicable. See point 8.

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