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The RenovaRP® Centesis Pump is intended to be used in conjunction with the RenovaRP Tube Set and the RenovaRP Fluid Drainage Bags to remove ascitic fluid from the abdominal cavity for paracentesis, and remove pleural effusion from the thoracic cavity for thoracentesis.

The Renova RP Centesis Pump is intended to be used by trained healthcare professionals knowledgeable about paracentesis and thoracentesis.

The RenovaRP® Centesis Pump is intended to be used in conjunction with the RenovaRP® Tube Set and RenovaRP® Fluid Drainage Bags (provided separately from the pump) to remove fluid from the abdominal cavity for paracentesis, and pleural effusion from the thoracic cavity for thoracentesis.

This document is a 510(k) premarket notification for the RenovaRP® Centesis Pump System. It aims to demonstrate substantial equivalence to a predicate device, the RenovaRP® Paracentesis Pump (K970186), for an expanded indication of use to include thoracentesis in addition to paracentesis.

Here's an analysis of the acceptance criteria and supporting studies based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not contain specific acceptance criteria for a new device's performance in terms of clinical outcomes (e.g., success rate of fluid removal, complication rates). Instead, it relies on demonstrating substantial equivalence to a previously cleared predicate device for the expanded indication.

The table below summarizes the technical specifications and aspects of the device that are compared to the predicate, demonstrating their "performance" in terms of equivalence.

2. Sample Size Used for the Test Set and Data Provenance

The document explicitly states that no performance data was needed to evaluate the expansion of indications for use to include thoracentesis. The justification for this is that the subject device's fundamental design, operational, and technological characteristics remain identical to the predicate device.

Therefore, there is no "test set" in the sense of a clinical or simulated diagnostic performance dataset with a specified sample size. This submission is based on the substantial equivalence of the physical device and its existing (previously cleared) performance for a very similar procedure (paracentesis vs. thoracentesis).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

Since no clinical or diagnostic performance test set was used, there were no experts relied upon to establish ground truth for such a dataset. The clearance is based on the technical equivalence and existing safety and effectiveness profile of the predicate device for a related procedure.

4. Adjudication Method for the Test Set

As no test set requiring clinical interpretation or outcome assessment was used, there was no adjudication method applied.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No MRMC comparative effectiveness study was done. The submission seeks clearance based on substantial equivalence of a physical medical device, not an AI or diagnostic algorithm that would typically be evaluated in an MRMC study.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No standalone performance study of an algorithm was done. The device in question is a physical pump, not a diagnostic algorithm.

7. The Type of Ground Truth Used

Given that no new clinical performance data was explicitly required for the expanded indication, there was no new ground truth established in this submission related to clinical outcomes. The "ground truth" for the device's safety and effectiveness for fluid removal relies on the prior clearance of the predicate device (K970186) and general engineering and safety standards.

8. The Sample Size for the Training Set

This submission is for a physical medical device (a pump), not an AI algorithm requiring a training set. Therefore, there is no training set sample size.

9. How the Ground Truth for the Training Set Was Established

As there is no training set for an AI algorithm, this question is not applicable.

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EverLift™ Submucosal Lifting Agent is indicated for use in gastrointestinal endoscopic procedures for submucosal lift of polyps, adenomas, early-stage cancers, or other gastrointestinal lesions prior to excision with a snare or other appropriate endoscopic device.

The GI Supply EverLift™ Submucosal Lifting Agent (10mL) is a prefilled plastic syringe with attached plunger rod containing 10mL of lifting agent. The syringe has a luer lock connection capable of interfacing with a standard, commercially available endoscopic injection needle.

EverLift™ Submucosal Lifting Agent is an injectable liguid composition for use as a submucosal injection agent during endoscopic mucosal resection (EMR), endoscopic mucosal dissection (ESD), and polypectomy procedures in the gastrointestinal tract. The device is intended for use in endoscopic resection procedures in the upper and the lower gastrointestinal tract, including the esophagus, the stomach, the small intestine, the sigmoid colon, and the rectum, as a submucosal injectable agent during the removal of polyps, adenomas, early-stage cancers, and other pathological lesions by EMR, ESD, or polypectomy.

EverLift™ Submucosal Lifting Agent is injected into the submucosal layer by means of a standard, commercially available endoscopic injection needle, which is inserted into the working channel of the endoscope. The composition, when injected, creates a cushion in situ by lifting the gastrointestinal mucosa from the submucosal layer, allowing the endoscopist to perform an easy and safe resection procedure (EMR, ESD, or polypectomy).

This document focuses on the EverLift™ Submucosal Lifting Agent (10mL) and its substantial equivalence to a predicate device, the EverLift™ Submucosal Lifting Agent (5mL). This is a medical device, not an AI/ML algorithm, therefore most of the requested information regarding AI/ML studies (such as MRMC studies, standalone performance, training set details, or ground truth establishment methods for AI) is not applicable.

The acceptance criteria and device performance are established through a series of non-clinical performance tests designed to show that the 10mL device is as safe and effective as the previously cleared 5mL predicate device.

Here's the relevant information extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document describes several non-clinical performance tests. For each test, the conclusion is that the subject device (10mL) performed equivalently or met the acceptance criteria used for the predicate device (5mL). The specific numerical acceptance criteria for each test are not explicitly detailed in quantifiable values, but rather referred to as "the same method and acceptance criteria as the predicate device" or conforming to specific ISO/USP standards.

2. Sample Size Used for the Test Set and Data Provenance

The document does not explicitly state the sample sizes used for each individual non-clinical performance test. It refers to "the subject device" and "the predicate device" implying that samples of each were tested.

The data provenance is from non-clinical performance testing conducted by the manufacturer, GI Supply. This is typically laboratory or bench testing. There is no mention of human subject data, retrospective, or prospective studies in a clinical setting.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

This question is not applicable as this is a medical device performance study, not a study evaluating an AI/ML algorithm requiring expert ground truth for interpretation of images or other data. The "ground truth" for these tests is defined by the technical specifications of the device and relevant international standards (e.g., ISO, USP, ASTM).

4. Adjudication Method for the Test Set

Not applicable. This is not an AI/ML study requiring adjudication of expert interpretations. The evaluation is based on objective measurements against predefined technical specifications and standards.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done

No. An MRMC comparative effectiveness study is not mentioned as this is not an AI/ML device.

6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done

No. This device is a submucosal lifting agent, a physical medical product, not an algorithm.

7. The Type of Ground Truth Used

The "ground truth" (or basis for acceptance) for these non-clinical performance tests consists of:

• Technical specifications of the device (implying equivalence to the predicate device).
• International standards such as ISO 7886-1:2017, ISO 17665-1, USP , USP , ASTM D7386-16, and ASTM F1980-16.
• The performance of the legally marketed predicate device (K191923) as a benchmark for equivalence.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device that requires a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable. As this is not an AI/ML device, there is no training set or medical "ground truth" established in this context.

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EverLift™ Submucosal Lifting Agent is indicated for use in gastrointestinal endoscopic procedures for submucosal lift of polyps, adenomas, early-stage cancers, or other gastrointestinal lesions prior to excision with a snare or other appropriate endoscopic device.

The GI Supply EverLift™ Submucosal Lifting Agent is a prefilled plastic syringe with attached plunger rod containing 5mL of lifting agent. The syringe has a luer lock connection capable of interfacing with a standard, commercially available, endoscopic injection needle.

The EverLift™ Submucosal Lifting Agent is an injectable liquid composition for use as a submucosal injection agent during endoscopic mucosal resection (EMR), endoscopic mucosal dissection (ESD) and polypectomy procedures in the gastrointestinal tract. The device is intended for use in endoscopic resection procedures in the upper and the lower gastrointestinal tract, including the esophagus, the stomach, the small intestine, the sigmoid colon, and the rectum, as a submucosal injectable agent during the removal of polyps, adenomas, early-stage cancers and other pathological lesions by EMR, ESD or polypectomy.

EverLift™ Submucosal Lifting Agent is injected into the submucosal layer by means of a standard, commercially available, endoscopic injection needle, which is inserted into the working channel of the endoscope. The composition, when injected, creates a cushion in situ by lifting the gastrointestinal mucosa from the submucosal laver, allowing the endoscopist to perform an easy and safe resection procedure (EMR, ESD or polypectomy).

The provided document is a 510(k) premarket notification for the EverLift Submucosal Lifting Agent, describing its substantial equivalence to a predicate device. It details non-clinical performance testing but does not include information about AI/ML device performance or clinical studies involving human readers or AI assistance. Therefore, I cannot fulfill all parts of your request related to AI/ML device acceptance criteria and studies.

Based on the provided text, here's what can be extracted and what cannot:

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

The document speaks to "functional and performance requirements" and various "functional performance tests" but does not explicitly list quantified acceptance criteria with corresponding performance metrics in a clear table format that would be typical for an AI/ML device. Instead, it states that tests were conducted to "demonstrate substantial equivalence."

Acceptance Criteria and Reported Device Performance (as inferred and specified in the document):

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: The document mentions "a series of functional performance tests, animal studies, biocompatibility tests, and sterility tests" but does not provide specific sample sizes (e.g., number of devices tested, number of animals in the preclinical study).
• Data Provenance: The document does not specify the country of origin for the data or whether the studies were retrospective or prospective. Given it's a non-AI/ML device based on physical/chemical properties and animal studies, "retrospective/prospective" in the context of clinical data isn't directly applicable here.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not applicable and not provided as this is a medical device for submucosal lifting, not an AI/ML diagnostic or image analysis device requiring expert ground truth for image interpretation. The ground truth for this device's performance is based on physical/chemical measurements and in-vivo effects in animal models.

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

This information is not applicable and not provided as this relates to expert review and consensus for imaging or diagnostic studies, which is not relevant to this device's testing.

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

This information is not applicable and not provided. The device is not an AI/ML algorithm that assists human readers. It is a physical agent used in endoscopic procedures.

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

This information is not applicable and not provided. The device is not an AI algorithm.

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

The "ground truth" for this device's performance is established through:

• Direct physical and chemical measurements (e.g., pH, viscosity, osmolality, density, flow rate).
• Direct observation of physical effects and safety in an in vitro (container integrity) and ex vivo / in vivo (porcine model for lift duration and performance) setting.
• Results from standardized biocompatibility, sterility, and aging tests.
  This is not based on expert consensus, pathology, or outcomes data in the typical sense of AI/ML diagnostic evaluation.

8. The sample size for the training set

This information is not applicable and not provided as this is not an AI/ML device that requires a training set.

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

This information is not applicable and not provided as this is not an AI/ML device that requires a training set.

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The GI Supply Biliary Stent is a disposable single-use device intended for use to temporarily by-pass obstructions in the biliary tree and allow drainage into the duodenum.

The GI Supply Biliary Stent is a disposable single-use device.

The provided FDA document is a 510(k) clearance letter for the GI Supply Biliary Stent. This type of document does not typically contain detailed information about the acceptance criteria, study design, or performance metrics that would be associated with a diagnostic AI/ML device.

The 510(k) process for a device like a biliary stent primarily focuses on demonstrating substantial equivalence to a legally marketed predicate device, often through bench testing (physical and mechanical properties), biocompatibility, and sometimes limited animal or human clinical data to assess safety and performance in a non-inferiority context. It does not involve AI model development or the detailed validation studies you've asked about for AI-driven diagnostics.

Therefore, I cannot extract the requested information from the provided text. The document confirms that the device is a biliary stent, intended for temporarily bypassing obstructions in the biliary tree and allowing drainage into the duodenum. There is no mention of AI, machine learning, image analysis, or diagnostic functions within this document.

If you have a document pertaining to an AI/ML diagnostic device, please provide that, and I would be happy to analyze it for the requested details.

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HP-ONE is for in-vitro diagnostic use only. It is intended to detect the urease enzyme of Helicobacter pylori and provide a presumptive diagnosis of H. pylori gastritis.

HP-ONE detects the urease enzyme for the presumptive identification of Helicobacter pylori in gastric mucosal biopsies. It is intended for in-vitro diagnostic use only. A gastric mucosal endoscopic biopsy is placed in the HP-ONE tray well and a reagent containing urea, hydrogen peroxide, a pH dye indicator, and an acidic buffer is placed over the biopsy specimen. A bubbling reaction occurs as catalase breaks down the peroxide. If H. pylori is present, the urease in H. pylori converts the urea to ammonia which raises the pH and changes the color of the reagent, indicating a positive test.

This document describes the HP-ONE device, its intended use, and performance characteristics. However, it does not explicitly state "acceptance criteria" as a separate predefined standard. Instead, the "acceptance criteria" are implicitly met by the reported performance characteristics that were considered sufficient for substantial equivalence to a predicate device.

Here's the information requested, organized based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: 117 patients
• Data Provenance: The text does not specify the country of origin of the data. It states, "In the clinical study of 117 patients with possible peptic ulcer disease..." This suggests the data was from a clinical study, but whether it was retrospective or prospective is not explicitly stated. Given it's a study for regulatory submission, it is typically a prospective or carefully selected retrospective cohort.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

The ground truth was established by histological criteria (presence of H. pylori organisms upon staining). The text does not specify the number or qualifications of the experts (e.g., pathologists) who performed the histological assessments.

4. Adjudication Method for the Test Set

The text does not describe an adjudication method for the test set. The ground truth was based on histological diagnosis.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. The document explicitly states, "HP-ONE agreed with the positive histological diagnosis in 60 cases (92.3%) and agreed with the negative diagnosis in all 52 (100%) of the cases." This indicates a standalone performance evaluation against a reference standard, not a comparative effectiveness study involving human readers with and without AI assistance.

6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop Performance)

Yes. The study presented is a standalone performance evaluation of the HP-ONE device against histological diagnosis as the ground truth. HP-ONE itself is a diagnostic test kit that produces a result; it's not an "algorithm" in the typical sense of AI, but rather a chemical reaction-based diagnostic tool. The performance metrics (92.3% sensitivity, 100% specificity) reflect the device's inherent capability.

7. Type of Ground Truth Used

The ground truth used was histological criteria (presence of H. pylori organisms upon staining).

8. Sample Size for the Training Set

The document does not describe a separate "training set." The clinical study of 117 patients appears to be the primary dataset reported for performance evaluation. For a chemical diagnostic test like HP-ONE, the "training" typically refers to the R&D and optimization process for the reagent formulation, not an algorithmic training process with a distinct dataset.

9. How the Ground Truth for the Training Set Was Established

Since no separate training set is described in the provided text, this question is not applicable. The device's formulation would have been developed and optimized based on scientific principles and internal testing, but without a formally described "training set" with established ground truth in the context of this 510(k) summary.

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Ask a specific question about this device