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510(k) Data Aggregation
(57 days)
NAVIGATOR URETERAL ACCESS SHEATH SET
Indicated for use in endoscopic procedures to facilitate the passage of endoscopes, urological instruments and for the injection of fluids into the urinary tract via antegrade and/or retrograde access.
The UASS II is designed to create a conduit for urological procedural instruments. This set consists of two components: an inner tapered semi-rigid dilator and an outer more flexible sheath. The outer flexible sheath fits over the semi-rigid inner dilator and it may be locked into place. These components are radiopaque and have a lubricous hydrophilic coating. The device is offered in two French sizes, 11/13 Fr, and 13/15 Fr. in lengths up to 46cm. The UASS II may be placed retrograde and/or antegrade. To guide the access sheath into the body orifice the dilator is advanced over up to a .038" guidewire. The device can be visualized under x-ray (fluoroscopy) during placement to confirm location. The proposed device can accept other urological instrumentation with OD's compatible with the sheath's working channel of 11 and 13 Fr, respectively. The proposed device is provided sterile single use. The packaging materials used for the proposed UASS are commonly used materials for packaging medical devices and similar to the predicate device. The device will be packaged in a labeled, single polyfilm/tyvek peel pouch double sealed, which will be placed in a labeled, paperboard shelf carton.
The provided document is a 510(k) premarket notification for a medical device called the "Ureteral Access Sheath Set II" (UASS II). This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing extensive clinical study data with acceptance criteria for device performance as would be found in a PMA (Premarket Approval) application.
Therefore, the document does not contain the detailed clinical study information typically provided for AI/ML-based devices, such as a table of acceptance criteria, sample sizes for test and training sets, expert qualifications, adjudication methods, or MRMC studies. The device in question is a physical medical instrument, not an AI/ML algorithm.
However, based on the information provided, here's what can be extracted and inferred:
1. A table of acceptance criteria and the reported device performance:
The document doesn't provide specific quantitative acceptance criteria or detailed performance results in a table format as would be seen for an AI/ML diagnostic device (e.g., sensitivity, specificity, AUC). Instead, it relies on demonstrating substantial equivalence to a predicate device.
The "performance data" mentioned focuses on physical comparison and functional testing to support this equivalence. The reported "performance" is that the device is determined to be substantially equivalent to the predicate.
| Acceptance Criteria Type (Inferred) | Reported Device Performance |
|---|---|
| Design Equivalence to Predicate | The UASS II is "substantially equivalent in design" to previously cleared devices. Description highlights two components (inner tapered semi-rigid dilator, outer more flexible sheath), radiopacity, and lubricious hydrophilic coating, which are characteristic of existing ureteral access sheaths. |
| Materials Equivalence to Predicate | The UASS II is "substantially equivalent in... materials" to previously cleared devices. Mention of packaging materials being "commonly used materials for packaging medical devices and similar to the predicate device." |
| Intended Use Equivalence | The UASS II has the same "intended use" as the predicate: "to facilitate the passage of endoscopes, urological instruments and for the injection of fluids into the urinary tract via antegrade and/or retrograde access." |
| Principle of Operation Equivalence | The UASS II is "substantially equivalent to devices previously cleared... in terms of... principles of operation." It functions by creating a conduit and is advanced over a guidewire, visualized under fluoroscopy, similar to predicate devices. |
| Functional Testing (Implied) | "Results of physical comparison and functional testing support a determination of substantial equivalence..." Specific parameters or metrics of this functional testing are not detailed in this summary. These would likely include aspects like dimensional accuracy, guidewire compatibility, coating integrity, and mechanical strength. |
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 describe a "test set" in the context of clinical data for an AI/ML algorithm. For a physical device like this, "testing" would refer to engineering and bench testing. The sample sizes for these tests are not provided in this summary. Data provenance (country of origin, retrospective/prospective) is not applicable here as it's not a clinical data study.
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. "Ground truth" in this context typically refers to clinical diagnoses or outcomes for AI/ML evaluation. For a physical device, testing involves engineering standards and functional verification, not expert interpretation of clinical cases for ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable, as there's no clinical test set requiring expert adjudication 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. MRMC studies are specific to evaluating human performance with and without AI assistance, which is not relevant for a physical ureteral access sheath.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
Not applicable. This device is a physical instrument, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
Not applicable. The "ground truth" for a physical device is its adherence to design specifications, material properties, and functional performance as determined by engineering tests and manufacturing standards, not clinical diagnostic outcomes.
8. The sample size for the training set:
Not applicable. "Training set" refers to data used to train an AI/ML model, which this device is not.
9. How the ground truth for the training set was established:
Not applicable.
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