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The Salem Sump™ Silicone 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 proposed Salem Sump™ Silicone Dual Lumen Stomach Tube with ENFit™ Connection is a dual lumen gastrointestinal enteral access tube made of medical grade silicone. The dual lumen design allows for decompression and administration of fluids within the larger (main) lumen while simultaneously allowing air to enter the secondary (vent) lumen during suctioning. This prevents invagination of the stomach wall into the tube eyelets during gastric decompression. During the period that decompression is needed, delivery of nutritional fluids such as formula, hydration or medication may be delivered through the main catheter lumen. The Salem Sump Silicone Dual Lumen Stomach Tube with ENFit Connection contains an ISO 80369-3 compliant connector tethered to the Y-Shaft of the device. When nutritional fluid delivery is required, the male ENFit connector is inserted into the main lumen. The ENFit connector contains a female cap which helps the connector act as a lumen capping system when feeding or decompression is no longer required. Capping the lumen ends with the ENFit connector and the vent lumen cap helps aid in the prevention of gastric content leakage.

This document pertains to a 510(k) premarket notification for a medical device: the "Salem Sump™ Silicone Dual Lumen Stomach Tube with ENFit™ Connection." It does not describe an AI/ML medical device or any study that proves a device meets acceptance criteria related to AI/ML performance metrics (such as sensitivity, specificity, or human reader improvement with AI assistance).

The document is a submission to the FDA for a physical medical device, specifically a gastrointestinal tube. The acceptance criteria and "study" described are for non-clinical performance testing of this physical device, not for the performance of an algorithm or AI system.

Therefore, I cannot provide the information requested in your prompt because it is designed for an AI/ML device, and this document does not contain that type of information.

To elaborate on why the requested information cannot be found:

• Acceptance Criteria/Reported Performance (Table): The document lists various non-clinical tests (e.g., Functional Verification, Occlusion Verification, Tensile Strength, Biocompatibility). It states that the "results of the testing demonstrate that the proposed device continues to meet the requirements of the product specifications" but does not provide specific numerical acceptance criteria or reported performance values in a table format.
• Sample Size/Data Provenance/Experts/Adjudication/MRMC/Standalone Performance/Ground Truth/Training Set Details: These questions are entirely relevant to AI/ML device studies. This document explicitly states: "Clinical evaluations were not relied upon for evidence of safety of effectiveness, or for a determination of substantial equivalence." This means there was no clinical study, human reader study, or AI algorithm involved that would require the establishment of ground truth by experts, adjudication, or training/test sets as understood in the context of AI/ML.

The "study" referenced in this document is a series of laboratory tests on the physical properties and performance of the gastrointestinal tube.

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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 Stomach Tube is intended for gastric decompression. It is used to drain undesirable contents from the stomach, or decompress the stomach. The device is available in sizes 6Fr to 22Fr for use in adults only.

The Stomach Tube is a sterile, single-use tube manufactured in various sizes from medical grade PVC. The Stomach Tube is intended for gastric decompression. It is used to drain undesirable contents from the stomach, or decompress the stomach. The tube is inserted into a patient's stomach through the patient's nose or mouth.

The Stomach Tube is supplied in French size ranging from 6 to 22, consists of main tube and connector. The stomach tube connector connects to suction device for suctioning, The tube is available in open tip and closed tip form. It is composed of biologically safe materials and supplied sterile and intended for single use only.

The Stomach Tube device, K162340, is a non-AI device. The provided text does not contain information about acceptance criteria and performances related to AI/ML technology. Therefore, the questions related to AI/ML technology (sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, ground truth type, training set sample size, how ground truth for training set was established) are not applicable.

Here's the information regarding the device's acceptance criteria and the study proving it meets them:

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

The provided text states that "The Stomach Tube meets all the pre-determined testing and acceptance criteria" but does not explicitly list the specific acceptance criteria and detailed performance results for each test. Instead, it broadly lists the types of tests conducted.

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

Not applicable as this is not an AI/ML device. The performance testing refers to physical product testing. The document does not specify the sample size used for each physical test or the origin of the test data (e.g., specific country for collecting samples).

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

Not applicable as this is a non-AI/ML device. Ground truth is not established by human experts in this context; performance is determined by established engineering and biological testing methods.

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

Not applicable as this is a non-AI/ML device. Adjudication methods are typically relevant for human expert review in diagnostic studies, not for physical performance testing of a medical device like a stomach tube.

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 as this is a non-AI/ML device.

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

Not applicable as this is a non-AI/ML device.

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

For the non-clinical performance testing, the "ground truth" is based on established engineering standards and biological testing protocols. For instance:

• General performance testing (Dimensions, Leakage, Flow Rate, Tensile, Suction Tubing Collapse): The ground truth is determined by the specifications and tolerances defined in relevant engineering standards or internal company specifications for the device's physical properties and functional performance. It is measured objectively using instruments and procedures.
• Biocompatibility testing (Cytotoxicity, Irritation, Sensitization): The ground truth is established by the results of biological assays performed according to ISO 10993 standards, which assess the material's interaction with biological systems. The "truth" is whether the material elicits an adverse biological response according to the defined criteria of these standards.

8. The sample size for the training set

Not applicable as this is a non-AI/ML device.

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

Not applicable as this is a non-AI/ML device.

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Intended for gastric decompression and delivery of fluids, including irrigation, nutritional supplements, and medication during the time period that gastric decompression is required. The device is intended for patients with age of two-year and older.

The product is a double lumen sump tube available in 5 sizes, 10Fr – 18Fr, and lengths of 36 – 48 inches. The device is equipped with a Multi-functional port to allow alternating use for gastric decompression (via a suction connector) or delivery of fluids, including irrigation, nutritional supplements, and medication via a syringe or feeding set equipped with a female ENFit connector.

The provided text is a 510(k) Summary for a medical device (Salem Sump™ Dual Lumen Stomach Tube with Multi-functional Port). It focuses on demonstrating substantial equivalence to a predicate device, primarily through non-clinical testing. This type of document typically does not include the detailed information requested in the prompt regarding acceptance criteria, study methodologies for performance evaluation, or clinical effectiveness studies in the way an AI/ML device submission would.

Therefore, for almost all categories, the answer will be that the information is not provided in this document.

However, I can extract what is present related to non-clinical testing and general acceptance.

Here's a breakdown based on the provided text:

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

The document does not explicitly present a table of acceptance criteria with corresponding reported performance for a specific clinical or diagnostic metric in the way an AI/ML device would. Instead, it describes various non-clinical tests performed to ensure the device maintains safety and effectiveness equivalent to the predicate device, especially with the addition of the new ENFit connector.

Non-Clinical Tests Mentioned for the ENFit Connector (Implied Acceptance):

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: Not specified. The document refers to non-clinical tests on the device components, not a test set of patient data.
• Data Provenance: Not applicable, as no patient data or clinical study data is referenced for evaluation. The tests are non-clinical, likely conducted in a lab environment.

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

Not applicable. The ground truth, in this context, would be established by engineering specifications and standards for device performance, not expert review of medical images or patient outcomes.

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

Not applicable, as no expert adjudication of a test set is mentioned.

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 not an AI/ML device, and no MRMC study was conducted.

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

Not applicable. This is not an AI/ML device.

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

For the non-clinical tests, the "ground truth" is defined by the established engineering standards, regulatory requirements (e.g., ISO 10993-1:2009, AAMI/CN3:2014 (PS) Part 3), and internal design specifications for device performance and safety (e.g., for fluid leakage, tensile strength, biocompatibility).

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no training set in that context.

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

Not applicable. As there is no training set for an AI/ML algorithm, this question doesn't apply.

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