Search Results

The SURGIMESH®XB is intended to be used for the reinforcement of tissues during surgical repair.

The SURGIMESH®XB is indicated for use in: the reconstruction of hernias and soft tissue deficiencies and for the temporary bridging of fascial defects. The silicone layer minimizes the tissue attachment to the mesh in the case of direct contact with the viscera.

The SURGIMESH®XB surgical mesh is a non-absorbable synthetic mesh, made of nonknitted, non-woven fibers of polypropylene, one surface of which is coated with silicone. The SURGIMESH®XB mesh is supplied sterile and is available in anatomic forms in order to meet the individual patient's surgical needs. The use of SURGIMESH®XB mesh provides reinforcement of soft tissues. On the opposite side, the silicone layer minimizes tissue attachment to the mesh in case of direct contact with the viscera.

This 510(k) summary is for a medical device (SURGIMESH®XB surgical mesh) and primarily focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a study with specific acceptance criteria and performance metrics in the way a diagnostic AI device submission would.

Therefore, many of the requested categories are not applicable or cannot be extracted from this type of regulatory document.

Here's an attempt to address the points based on the provided text, indicating "Not Applicable" or "Not Provided" where the information is not present:

Acceptance Criteria and Study for SURGIMESH®XB

The submission for SURGIMESH®XB is a 510(k) premarket notification, which establishes substantial equivalence to legally marketed predicate devices. This type of submission relies on demonstrating that the new device has the same intended use, similar technological characteristics, and that any differences do not raise new questions of safety or effectiveness. It does not typically involve defining specific performance acceptance criteria (e.g., accuracy, sensitivity, specificity) in the same way an AI diagnostic algorithm would, nor does it present a clinical trial with a test set, ground truth experts, or MRMC studies.

Therefore, the "acceptance criteria" for a device like SURGIMESH®XB are implicitly tied to demonstrating that its mechanical, material, and biocompatibility characteristics are "substantially equivalent" to predicate devices, which are themselves deemed safe and effective.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not Applicable. This submission does not describe a clinical "test set" in the context of diagnostic performance. The evaluation is based on material testing and comparison to predicates.
• Data Provenance: Not Applicable. No patient data or clinical study dataset is described.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

• Number of Experts: Not Applicable. No ground truth establishment by experts is described for this type of device submission.
• Qualifications of Experts: Not Applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not Applicable. No test set requiring expert adjudication 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

• MRMC Study: No. This is a surgical mesh, not an AI diagnostic device for human readers.
• Effect Size: Not Applicable.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Standalone Performance: Not Applicable. This is a surgical mesh, not an algorithm.

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

• Type of Ground Truth: Not Applicable. The "ground truth" concept for a surgical mesh revolves around proven safety and effectiveness of similar devices and the demonstration of equivalent physical, mechanical, and biological properties. It's not based on case-level diagnoses or outcomes in a study, but rather on material science and biocompatibility testing.

8. The Sample Size for the Training Set

• Sample Size: Not Applicable. This is a surgical mesh, not an AI device that uses a training set.

9. How the Ground Truth for the Training Set was Established

• Ground Truth Establishment: Not Applicable.

Ask a specific question about this device

The CMB Antimicrobial Dressing is indicated for professional use as an antimicrobial barrier for partial and full-thickness wounds such as: pressure ulcers, venous ulcers, diabetic ulcers, burns and donor and recipient graft sites.

The CMB Antimicrobial dressing is a single layer dressing consisting of a woven adsorbent polyester containing elemental silver and zinc. In the presence of exudate, the dressing can be used with an appropriate secondary barrier to help maintain a moist wound healing environment.

The provided text describes the CMB Antimicrobial Dressing, a device primarily for wound care. There is very limited information about specific acceptance criteria or details of a study that proves the device meets particular criteria. The document is a 510(k) Summary, which focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance against predefined acceptance criteria for a novel device.

However, based on the limited information provided, here's an attempt to answer your questions:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state numerical acceptance criteria with corresponding performance results. It only mentions types of tests performed.

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 specify sample sizes for any of the in vitro or biocompatibility tests. It also does not mention the country of origin of the data or whether the studies were retrospective or prospective.

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 is not applicable to the information provided. The studies mentioned (antimicrobial performance, biocompatibility) are laboratory tests, not clinical studies requiring expert interpretation of results to establish a "ground truth" in the way it's described for image analysis or diagnoses.

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

Not applicable. Laboratory tests typically involve established protocols and readouts, not adjudications of subjective interpretations.

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

No such study was mentioned. The device is a wound dressing, not an AI-powered diagnostic tool that human readers would use.

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

This question is not applicable as the device is a physical wound dressing, not an algorithm. The "antimicrobial performance" was tested in vitro, which can be considered a standalone test for the device's inherent property.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

For the in vitro antimicrobial performance, the ground truth would be established by standard microbiological methods, such as colony counts or zone of inhibition measurements, which quantify bacterial reduction or inhibition. For biocompatibility tests, the ground truth is established by standard toxicology and biological evaluation methods (e.g., cell viability assays for cytotoxicity, skin reaction scores for irritation/sensitization). These are objective measurements against established scientific standards, not expert consensus or pathology in the clinical sense.

8. The sample size for the training set

Not applicable. The CMB Antimicrobial Dressing is a physical device, not an AI model that requires a training set.

9. How the ground truth for the training set was established

Not applicable, as there is no training set for this type of device.

Ask a specific question about this device