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The Salem Sump™ Dual Lumen Stomach Tube with ENFit™ Connection is intended for gastric decompression and administration of nutrition, fluids and medication. The device is intended for patients with age of two and older.

The Salem Sump™ Dual Lumen Stomach Tube with ENFit™ Connection is a double-lumen tube made of PVC used for naso/orogastric drainage and feeding. The larger (main) lumen is for feeding and drainage, while the smaller lumen draws in outside air to moderate the amount of suction at the drainage eyes. The device contains an ISO 80369-3 compliant ENFit connector which is inserted into the main lumen after decompression is no longer required to administer enteral fluids, including enteral nutrition, hydration and medication. It is a single use device which is provided sterilized via EO sterilization.

The provided document is a 510(k) premarket notification for a medical device: the Salem Sump™ Dual Lumen Stomach Tube with ENFit™ Connection. This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets novel clinical acceptance criteria for an AI/CAD system or a diagnostic tool that requires robust clinical performance studies.

Therefore, the information requested in your prompt regarding acceptance criteria for an AI study, sample sizes, expert ground truth adjudication, MRMC studies, standalone algorithm performance, or training set details cannot be found in this document. The requirements you listed are typically applicable to software as a medical device (SaMD) or devices that rely heavily on algorithmic or diagnostic performance for their intended use.

This 510(k) summary focuses on the physical and functional characteristics of a physical device (a stomach tube) and its safety and efficacy as compared to a previously cleared device. The "acceptance criteria" here would be largely non-clinical performance benchmarks and adherence to established standards for medical tubing and connectors.

Here's how to interpret the document in the context of what is provided:

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

The document doesn't present a formal table of acceptance criteria with quantitative results in the way you might expect for an AI study. Instead, it lists the non-clinical performance data (testing) performed and broadly states that the results "show that the modified device continues to meet the requirements of the product specifications and supports the determination of substantial equivalence."

The "acceptance criteria" are implied by the standards and the successful completion of the listed tests:

The "reported device performance" for each of these is broadly summarized as "met requirements" or "complies," demonstrating "substantial equivalence."

Regarding points 2-9 of your prompt:

These points are not applicable to this 510(k) submission because it is for a physical medical device (Salem Sump™ Dual Lumen Stomach Tube with ENFit™ Connection), not an AI/CAD system or a diagnostic device.

• 2. Sample sized used for the test set and the data provenance: Not applicable. Testing was likely done on a sample of manufactured devices, but not on "data" in the sense of patient images or clinical records.
• 3. Number of experts used to establish the ground truth... and qualifications: Not applicable. Ground truth for a physical tube involves manufacturing specifications and physical testing, not expert clinical interpretation.
• 4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 5. If a multi reader multi case (MRMC) comparative effectiveness study was done...: Not applicable. This is for an AI/CAD system.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for this device is based on engineering specifications, material properties, and performance standards for medical tubing and connectors (e.g., ISO, EN standards).
• 8. The sample size for the training set: Not applicable. This is not an AI/ML device.
• 9. How the ground truth for the training set was established: Not applicable.

In summary, this document is a regulatory submission for a physical medical device, not a software or AI-based diagnostic tool. The "acceptance criteria" and "study" described align with the physical and functional performance testing required for a Class II device like a stomach tube.

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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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