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510(k) Data Aggregation
(43 days)
DISPOSABLE RE-NEW FORCEPS
Cutting, Grasping, and Dissecting Various Abdominal Tissue during Endoscopic (inclusive of laparoscopic) Surgical Procedures.
The Disposable Re-New Forceps Laparoscopic Surgical Tips are an extension of the Re-New Forceps Laparoscopic Instruments product line used to cut, grasp, and dissect various abdominal tissue during Endoscopic (inclusive of laparoscopic) surgical procedures. The Disposable Re-New Forceps Laparoscopic Surgical Tips consist of a series disposable tip configurations. Tip configurations include: Grasper, Fenestreded Forceps, "Dolphin Nose" Dissector, "Babcock", and "Maryland" Dissector.
The provided text is a 510(k) Summary and related FDA correspondence for the "Disposable Re-New Forceps Laparoscopic Surgical Tips." This document primarily focuses on establishing substantial equivalence to a predicate device and gaining market clearance. It does not contain information about acceptance criteria or specific studies proving the device meets particular performance metrics.
The device in question is a manual surgical instrument, not an AI/ML-driven medical device. Therefore, many of the requested fields related to AI/ML device evaluation (like MRMC studies, training set details, or ground truth for AI) are not applicable.
Here's a breakdown based on the provided text, highlighting the absence of the requested information:
Acceptance Criteria and Device Performance Study
As this device is a manual surgical instrument and the documentation is for 510(k) premarket notification, it focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting detailed performance studies against specific acceptance criteria. The document states:
- "The technical characteristics of the Disposable Re-New Forceps Laparoscopic Surgical Tips are identical to those of the Microline Re-New Forceps (K974066)."
- "Differences that exist between these devices relating to technical specifications, materials, and physical appearance do not affect the relative safety or effectiveness of the Disposable Re-New Forceps relative to its predicate."
This indicates that the acceptance criteria are implicitly met by demonstrating sameness or non-inferiority in safety and effectiveness compared to the predicate device. Specific quantitative performance metrics and acceptance thresholds are not detailed in this summary.
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Implicit) | Reported Device Performance |
---|---|
Substantial equivalence in safety and effectiveness to predicate device (Microline Re-New Forceps, K974066) for indicated uses. | Technical characteristics are identical; differences in specs, materials, and physical appearance do not affect relative safety or effectiveness compared to the predicate. |
2. Sample size used for the test set and the data provenance
Not applicable. The 510(k) summary does not describe a "test set" in the context of an AI/ML or diagnostic device validation. The evaluation is based on a comparison of device characteristics to a predicate, not on clinical performance data from a specific test set.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. No "ground truth" or expert consensus is described for device validation in this 510(k) summary.
4. Adjudication method for the test set
Not applicable. No test set or adjudication method is described.
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 manual surgical instrument, not an AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This device is a manual instrument, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable. No ground truth is described. The evaluation relies on demonstrating substantial equivalence to a predicate device based on technical characteristics, materials, and intended use.
8. The sample size for the training set
Not applicable. This is not an AI/ML device, so there is no training set mentioned.
9. How the ground truth for the training set was established
Not applicable. As there's no training set, there's no ground truth establishment for it.
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