Search Results

The OsseoFit Interfacing Anchor and OsseoFit Bone Tunnel Construct are intended for use in soft tissue to bone fixation for the following indications: Shoulder Rotator Cuff Repair

The Riverpoint Medical Interfacing Anchor is comprised of a pre-deployed all-suture anchor with attached repair sutures and 302 stainless steel needles. The Interfacing Anchor is inserted into either the humerus or into passing slots available in devices intended for total shoulder arthroplasty. The Riverpoint Medical Bone Tunnel Construct is comprised of a double armed Ultra-High Molecular Weight Polyethylene (UHMWPE) suture with a preassembled polypropylene passing loop and 302 stainless steel needles. Suture supplied meet United States Pharmacopeia (USP) requirements for nonabsorbable suture except for diameter. Suture dyes are FDA authorized. The device is sterilized by ethylene oxide gas and is provided sterile for single use. Interfacing Anchor and Bone Tunnel Construct are available in common sizes and lengths with preattached 302 stainless steel needles and will be sold sterile for single use. The device is intended for use in a hospital/clinic/surgical setting.

The provided text is a 510(k) summary for the OsseoFit Interfacing Anchor and OsseoFit Bone Tunnel Construct. This document details the regulatory review process for a medical device and its substantial equivalence to a predicate device.

It does NOT describe an AI/ML-driven medical device, nor does it contain information about diagnostic performance metrics (e.g., sensitivity, specificity, AUC), test set characteristics, expert adjudication processes, or MRMC studies.

The "Performance Data" section of the document refers to non-clinical performance testing for a surgical device (an anchor and tunnel construct), not a diagnostic AI. The tests mentioned are:

• Usability engineering validation with simulated use in cadaveric models (EN62366:2015)
• Endotoxin/pyrogenicity testing (ANSI/AAMI ST72:2019, USP , USP , USP )
• Mechanical testing to verify fixation strength (cyclic and pullout testing)

Therefore, I cannot provide the requested information regarding acceptance criteria and study details for an AI/ML device's performance, as the provided text pertains to a physical surgical device.

To directly answer your prompt based on the provided text, the following cannot be extracted:

• A table of acceptance criteria and reported device performance related to diagnostic accuracy (as it's not a diagnostic device). The acceptance criteria mentioned are for mechanical and usability performance of a surgical implant.
• Sample sizes used for a "test set" in the context of image analysis or diagnostic performance. The "test set" here refers to cadaveric models and mechanical testing samples.
• Data provenance (country of origin, retrospective/prospective) for a diagnostic dataset.
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method for a test set.
• MRMC comparative effectiveness study, including effect size.
• Standalone (algorithm only) performance.
• Type of ground truth (expert consensus, pathology, outcomes data).
• Sample size for a training set.
• How ground truth for the training set was established.

However, based on the provided text, here's what can be inferred or directly stated about the "acceptance criteria" and "study" for this specific device (a surgical implant):

Acceptance Criteria and Device Performance (for a surgical implant):

Study Details (for this surgical implant):

1. Sample sizes used for the test set and data provenance:

   • The "test set" refers to samples for mechanical testing and cadaveric models for usability. Specific numerical sample sizes are not provided in this summary.
   • Data provenance is not described (e.g., where the cadavers came from, or if the mechanical tests were done by a specific lab).
   • The studies were non-clinical ("bench testing" and "simulated use").

2. 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):

   • Not applicable in the context of diagnostic "ground truth." The "ground truth" for a surgical implant's mechanical performance is defined by engineering standards and comparative testing to predicates. Usability testing would involve typical users (surgeons, OR staff), but the number or qualifications are not specified.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable as this is not a diagnostic study requiring human expert consensus/adjudication of results. Performance is measured against physical test standards and engineering specifications.

4. 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:

   • No, a MRMC comparative effectiveness study was not done. This is a physical surgical device, not an AI/ML diagnostic tool.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Not applicable as this is a physical surgical device, not an algorithm.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For mechanical testing: Engineering specifications and comparative performance to a legally marketed predicate device.
   • For usability testing: Performance in simulated use conditions in cadaveric models against predefined usability objectives (derived from EN62366:2015).

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML device with a "training set."

8. How the ground truth for the training set was established:

   • Not applicable.

Ask a specific question about this device