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510(k) Data Aggregation
(36 days)
AMECATH DUAL LUMEN IMPLANTED HEMODIALYSIS CATHETER
"Amecath Dual Lumen Implanted Hemodialysis Catheter" is designed for chronic hemodialysis and apheresis. It is a radiopaque polyurethane catheter designed for percutaneous insertion or insertion via cutdown.
Repair Kit is designed to replace worn or damaged extension connector adapters on the all catheter models:
- . PDLC
- . PYDLC
- P2TC
- . PXDLC
Catheters are not intended for pediatric use.
"Amecath Dual Lumen Implanted Hemodialysis Catheter" is a radiopaque polyurethane catheter designed for percutaneous insertion or insertion via cutdown.
This is a 510(k) premarket notification for a medical device (Amecath Dual Lumen Implanted Hemodialysis Catheter and Repair Kit), not a study report or clinical trial. Therefore, the document does not contain the information requested in your prompt regarding acceptance criteria, study details, sample sizes, ground truth establishment, expert qualifications, or MRMC studies.
The provided text is an FDA approval letter, an "Indications for Use" statement, and references to regulatory information. It confirms that the device has been found substantially equivalent to legally marketed predicate devices.
Specifically, the document does not include:
- A table of acceptance criteria and reported device performance.
- Sample sizes for test sets or their data provenance.
- Number or qualifications of experts used for ground truth.
- Adjudication methods.
- Details of a multi-reader, multi-case comparative effectiveness study or its effect size.
- Standalone (algorithm-only) performance data.
- The type of ground truth used in a study.
- Sample size for training sets.
- How ground truth for a training set was established.
This type of FDA letter focuses on regulatory clearance based on substantial equivalence, not on providing detailed study outcomes for a new device's performance against specific acceptance criteria in the manner one would find in a clinical study report or a publication describing AI algorithm performance.
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