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510(k) Data Aggregation
(90 days)
The NTERO HOTROD™ System is intended to coagulate tissue during surgical procedures.
Not Found
The provided text describes a 510(k) submission for the NTERO HOTROD™ System, an electrosurgical device. It outlines the intended use, classification, equivalent devices, and summary of the substantial equivalence determination by the FDA. However, the document does not contain the specific information required to answer your questions about acceptance criteria and a study proving those criteria are met for an AI/device performance study.
Here's why and what information is missing:
- No Acceptance Criteria or Stated Performance: The document states "Results of animal testing demonstrate that the NTERO HOTROD™ System is safe and effective for its intended function," but it does not specify any quantitative acceptance criteria (e.g., specific coagulation depth, time to achieve hemostasis, or a quantifiable measure of "effectiveness" or "safety") or report numerical device performance against such criteria.
- No AI Component: The NTERO HOTROD™ System is an electrosurgical device for tissue coagulation, not an AI-powered diagnostic or therapeutic device. Therefore, questions related to AI performance, such as sample sizes for test/training sets, data provenance, ground truth establishment by experts, adjudication methods, MRMC studies, or standalone algorithm performance, are not applicable to this device description.
- Study Details are Limited: The study mentioned is "animal testing" for safety and effectiveness and "biocompatibility" testing for materials. No detailed methodology, sample sizes, or specific results are provided beyond the general statement of safety and effectiveness.
Based on the provided text, I cannot complete the table or answer the specific questions related to acceptance criteria and an AI-related study. The document is a regulatory filing for a traditional medical device, not an AI-driven one, and lacks the detailed performance metrics you've requested.
However, I can extract and state what is available based on your prompt's structure:
Acceptance Criteria and Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Safety and effectiveness for intended function (coagulation of tissue during surgical procedures) | Demonstrated through animal testing. |
| Biocompatibility of materials in direct tissue and blood contact | Materials have been shown to be biocompatible. |
Detailed Study Information (Based on available text):
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Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not specified. The document only mentions "animal testing."
- Data Provenance: Animal testing. No country of origin is specified. The study type is effectively "prospective experimental" as it involved conducting tests on animals.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This was animal testing for a non-AI device. Ground truth establishment by experts in the context of diagnostic image interpretation, for example, is not relevant here. The "ground truth" would be direct physiological outcomes in the animals.
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Adjudication method for the test set: Not applicable. This was animal testing for a non-AI device.
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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. The NTERO HOTROD™ System is an electrosurgical device, not a diagnostic AI system with human readers.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. The NTERO HOTROD™ System is an electrosurgical device, not an algorithm.
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The type of ground truth used: Direct physiological and histological observation in animal models and material property testing for biocompatibility.
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The sample size for the training set: Not applicable. No "training set" in the context of machine learning, as this is not an AI device.
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How the ground truth for the training set was established: Not applicable.
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(88 days)
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(53 days)
The NTERO RF Sleeve is intended for use during laparoscopic surgery to maintain a port of entry and to coagulate tissue.
Not Found
The provided text describes a 510(k) submission for the NTERO RF Sleeve, a Class II electrosurgical device. The submission focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria for a new type of device.
Therefore, much of the requested information regarding acceptance criteria, specific test results, ground truth, and expert involvement is not present in the provided document. The device's safety and effectiveness were primarily established through comparison to legally marketed predicate devices.
Here's a breakdown of the available information:
1. Table of Acceptance Criteria and Reported Device Performance
Note: The provided document does not list specific numerical acceptance criteria. The "Reported Device Performance" is a general statement of positive test results and biocompatibility.
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Performance: Results of in vitro and in vivo testing demonstrate that the NTERO RF Sleeve is safe and effective for its intended function. | |
| Biocompatibility: The materials used in the NTERO Probe have been shown to be biocompatible. |
2. Sample Size Used for the Test Set and Data Provenance
The document states "Results of in vitro and in vivo testing" but does not specify the sample sizes for these tests.
Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
Not applicable. The document describes performance testing, but there is no mention of an expert panel establishing a "ground truth" for diagnostic or analytical performance, as would be typical for image analysis or AI devices. The evaluation focuses on the functional performance and safety of the surgical device.
4. Adjudication Method for the Test Set
Not applicable. As there's no mention of expert-established ground truth, there's no adjudication method described.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
Not applicable. The device is a surgical instrument, not an AI diagnostic tool that would typically involve a MRMC study to assess reader improvement with AI assistance.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
Not applicable. This device is a manual surgical tool and does not involve an algorithm with standalone performance.
7. Type of Ground Truth Used
Not applicable/Not specified in the context of diagnostic "ground truth." The testing focused on functional performance and biocompatibility through in vitro and in vivo methods, rather than establishing a diagnostic ground truth against which an algorithm would be measured. The "ground truth" for a surgical device would be its ability to perform its intended function safely and effectively within biological systems, observed during these tests.
8. Sample Size for the Training Set
Not applicable. This device is hardware (a surgical sleeve) and does not involve a "training set" in the context of machine learning or AI models.
9. How the Ground Truth for the Training Set Was Established
Not applicable. As there is no training set, this query is irrelevant for this device.
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