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The Ethicon Endo-Surgery® Flexible Bipolar Hemostasis Forceps are intended for use in endoscopic procedures where fusion of vessels or tissue bundles is performed. The device can be used on vessels up to 3 mm and bundles as large as will fit in the jaws of the instrument. The Ethicon Endo-Surgery® Flexible Bipolar Hemostasis Forceps are designed for use with an ERBE VIO 300 D Electrosurgical Generator (ESU) System. It is not recommended for use with other manufacturer's generators.

The Ethicon Endo-Surgery® Flexible Bipolar Hemostasis Forceps Device Description is a sterile, single-use device intended for use in endoscopic procedures where fusion of The device can be used on vessels up to 3 mm vessels or tissue bundles is performed. and bundles as large as will fit in the jaws of the instrument. A vessel fusion is created by the application of bipolar electrosurgical RF energy (coagulation) to the vessels placed between the jaws of the instrument. The Ethicon Endo-Surgery Flexible Bipolar Hemostasis Forceps sources RF energy from an electrosurgical generator. Specifically, the Ethicon Endo-Surgery Flexible Bipolar Hemostasis Forceps are designed for use with an ERBE VIO 300 D Electrosurgical Generator (ESU) System. This device passes through endoscopes having a 3.7 mm or larger working channels.

This document describes a 510(k) premarket notification for the "Ethicon Endo-Surgery® Flexible Bipolar Hemostasis Forceps". This is a medical device, not an AI/ML algorithm. Therefore, many of the requested categories in the prompt, such as "multi reader multi case (MRMC) comparative effectiveness study," "standalone (i.e. algorithm only without human-in-the loop performance)," "sample size for the training set," and "how the ground truth for the training set was established," are not applicable to traditional medical device submissions.

However, I can extract information related to performance testing that demonstrates the device meets its intended use.

Here's an analysis based on the provided document:

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

The document lacks a specific table detailing acceptance criteria alongside reported performance for each criterion. It broadly states that "Bench, animal, biocompatibility, and electrical testing was performed to demonstrate that the EES device performs as intended."

Device Performance Claimed:

• Vessel/Tissue Fusion: The device can perform fusion of vessels or tissue bundles.
• Vessel Size: Effective on vessels up to 3 mm.
• Bundle Size: Effective on bundles as large as will fit in the jaws of the instrument.
• Compatibility: Designed for use with an ERBE VIO 300 D Electrosurgical Generator (ESU) System.
• Endoscope Channel: Requires a 3.7 mm or larger working channel.
• Tissue Manipulation: Jaws contain atraumatic "grooves" to grasp and manipulate tissue.

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

The document does not specify sample sizes for the bench, animal, biocompatibility, or electrical testing. It also does not explicitly mention the country of origin of the data or whether the studies were retrospective or prospective.

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 concept of "ground truth established by experts" is not typically applicable to the performance testing of a physical medical device like electrosurgical forceps. The "ground truth" would be objective measurements of device function (e.g., burst pressure of fused vessels, thermal spread, electrical impedance).

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

Not applicable, as this refers to expert consensus for ground truth, which isn't detailed for this type of device.

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 electrosurgical device, not an AI system.

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

Not applicable. This is a physical electrosurgical device, 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 would be derived from objective measurements and observations during typical medical device performance testing, including:

• Bench Testing: Mechanical properties, electrical safety, fusion strength (e.g., burst pressure), thermal effects.
• Animal Testing: In-vivo performance, tissue effect, hemostasis effectiveness, safety.
• Biocompatibility Testing: Assessment of biological response to materials (e.g., cytotoxicity, irritation, sensitization).

8. The sample size for the training set

Not applicable. This is a physical electrosurgical device, not an AI system that requires a "training set."

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

Not applicable. This is a physical electrosurgical device, not an AI system.

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The InScope Multi-Clip Applier is indicated for use with an endoscope to place clips in the gastrointestinal (GI) tract for the purpose of:

• Endoscopic marking, .
• Hemostasis for: ●
  • o Mucosal and submucosal defects

The InScope™ Mult-Clip Applier is a sterile, single patient use, disposable instrument capable of attaching clips to the mucosal lining of the gastrointestinal (GI) tract. The clips are used to create hemostasis and/or tissue approximation. The distal, flexible portion of the applier is designed to work with a flexible endoscope having a minimum working channel diameter of 3.2 mm. Two opposing jaws grasp tissue via a manually activated lever on a proximal handle. Once the closure lever is latched, a firing mechanism is manually activated, which deploys a titanium clip over the target tissue. The device is supplied preloaded with four (4) titanium clips.

The provided text describes the 510(k) summary for the InScope™ Multi-Clip Applier. This is a medical device submission, and the "study" referred to is the pre-clinical and bench testing conducted to demonstrate substantial equivalence to predicate devices, rather than a clinical trial involving human subjects or AI algorithms. As such, many of the typical questions for AI/algorithm performance studies do not apply.

Here's an analysis based on the provided text:

Acceptance Criteria and Device Performance

The "acceptance criteria" for this device are demonstrating substantial equivalence to predicate devices in specific performance aspects. The reported device performance is that it meets these criteria.

Table of Acceptance Criteria and Reported Device Performance

Study Details

1. Sample Size Used for the Test Set and Data Provenance:

   • The document refers to "bench and preclinical testing" and "preclinical data." It does not specify sample sizes for these tests.
   • Data provenance is preclinical/bench testing. No information on country of origin is provided, but typically, these tests are conducted by the manufacturer (Ethicon Endo-Surgery, Inc. in Cincinnati, OH, USA). The data is retrospective in the sense that it refers to testing done before the 510(k) submission.

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

   • This question is not applicable. The "ground truth" for a medical device like this is based on measurable physical properties and biological responses in preclinical models (e.g., tissue viability, clip retention force, hemostasis effectiveness), not on expert interpretations of medical images or patient outcomes in a clinical setting in the way an AI algorithm would be evaluated. These assessments are typically performed by engineers, biologists, or veterinarians specializing in device testing. The document does not specify the number or qualifications of these individuals.

3. Adjudication Method for the Test Set:

   • This question is not applicable. Adjudication methods like 2+1 or 3+1 are used for human reader studies or to resolve discrepancies in expert labeling, which is not relevant here.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

   • No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI algorithms that assist human readers in interpreting medical data (e.g., radiology images). The InScope Multi-Clip Applier is a physical surgical tool; its effectiveness is evaluated through direct performance metrics, not by how it influences human interpretation.

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

   • Not applicable. The InScope Multi-Clip Applier is a physical device used by a clinician, not an algorithm. Its performance is inherently "with human-in-the-loop" as it requires manual operation.

6. The Type of Ground Truth Used:

   • For the preclinical testing, the "ground truth" was based on direct measurements and observations of physical performance and biological responses in laboratory and animal models. This includes:
     • Measured hemostatic effectiveness.
     • Measured clip retention force/durability.
     • Histopathological assessment of tissue viability after clip placement.
     • Observation of outcomes for procedures like perforation closure in preclinical models.

7. The Sample Size for the Training Set:

   • Not applicable. This device does not use an AI algorithm that requires a training set. The "design and development" process would involve iterative testing and refinement, but this is distinct from machine learning training.

8. How the Ground Truth for the Training Set was Established:

   • Not applicable. As there is no AI algorithm or training set, this question does not apply.

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