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510(k) Data Aggregation
(279 days)
Transem and EchoGen Embryo Transfer Catheters
The Transem and EchoGen™ are catheters with angled or spherical tips for embryo transfer into the uterine cavity in the treatment of infertility.
The Transem Stylets are intended to assist the insertion of the Transem or EchoGen™ catheters where the passage through the cervix is impeded.
The Transem and EchoGen™ are Embryo Transfer Catheters with various angled or spherical tips and various lengths. The EchoGen™ variants are designed to be visible under ultrasound imaging. Stylets to aid in the insertion of the embryo catheters are also available.
This document describes the safety and effectiveness of the Transem and EchoGen™ Embryo Transfer Catheters through various performance evaluations, without directly referencing an AI/ML algorithm or its performance. Therefore, I cannot provide details related to acceptance criteria or studies proving device performance from an AI/ML perspective.
However, I can extract information related to the device's performance data and criteria described in the document for its physical and biological characteristics:
1. Table of Acceptance Criteria and Reported Device Performance (Non-AI/ML related):
| Aspect | Acceptance Criteria (or Standard) | Reported Device Performance/Conclusion |
|---|---|---|
| Biocompatibility | ||
| Cytotoxicity | ISO 10993-5:2009 | Not cytotoxic |
| Sensitization | ISO 10993-10:2010 | Not sensitizing |
| Vaginal Irritation | ISO 10993-10:2010 | Non-irritant |
| Sterilization | ISO 11137-2:2006 (Validation) | Validated |
| Sterility Assurance Level | SAL 10^-6^ | Achieves SAL 10^-6^ (implied by validation per ISO 11137-2:2006 and parameter testing during shelf-life) |
| Shelf-life | ISO 11607-1:2006 and ASTM F1980-07 (Testing standards) | Shelf-life established through real-time and accelerated testing. |
| Parameters assessed: Air resistance, Tensile strength, Dimensional characteristics, Sterility, Endotoxin, Mouse Embryo Assay, Package integrity (peel strength, visual inspection, label integrity, contamination). No specific values reported, but implies successful establishment. | ||
| Endotoxins | ≤ 1.25 EU/device (General criteria) | Confirmed to meet this requirement (tested during shelf-life and bench testing using Limulus Amebocyte Lysate test per USP). |
| Mouse Embryo Assay (MEA) | ≥80% blastocyst rate at 96 hr (1-cell test) | Confirmed to meet this requirement (tested during shelf-life and bench testing). |
| Bench Testing | (Not explicitly stated, but implied for functional characteristics) | Physical properties (air resistance, tensile strength, dimensional verification) performed. |
| Performance characteristics (sterility, endotoxin, embryotoxicity [MEA]) verified. | ||
| Echogenic marker assessments (mounting accuracy, pull force to remove), flow restriction, ultrasound visibility assessment performed. Implies successful results. |
Regarding the AI/ML-specific questions, based solely on the provided text, there is no information available:
- Sample size used for the test set and the data provenance: Not applicable as no AI/ML study is mentioned.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
- Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
- 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.
- If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.
- The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
- The sample size for the training set: Not applicable.
- How the ground truth for the training set was established: Not applicable.
This document pertains to the 510(k) premarket notification for traditional medical devices (catheters), which typically focus on material biocompatibility, sterility, physical performance, and similarity to predicate devices, rather than AI/ML algorithm performance.
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