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PLEXUR P is intended for use in filling bony voids or gaps of the skeletal system (i.e., spine, pelvis and extremities) that are not intrinsic to the stability of the bony structure. These defects may be surgically created osseous defects or osseous defects resulting from traumatic injury to the bone. Plexur P may also be used as a bone graft extender in the spine. PLEXUR P is resorbed/remodeled and is replaced by host bone during the healing process.

PLEXUR P is bone void filler that contains as its principal constituents processed human allograft bone tissue and a resorbable polymer. PLEXUR P is produced in various physical forms/shapes/geometries and may be further shaped or cut by the surgeon to meet the particular needs and preferences of the surgeon. PLEXUR P is intended for use as bone void filler in bony voids or gaps of the skeletal system (i.e., spine, pelvis, and extremities) not intrinsic to the stability of the bony structure. Plexur P mav also be used as a bone graft extender in the spine. PLEXUR P is provided in ready-to-use form in various package sizes by volume or dimension and is intended for single patient use.

The provided text describes the 510(k) summary for the PLEXUR P bone void filler. It indicates that the device has been found substantially equivalent to predicate devices based on certain performance data. However, the document does not include specific acceptance criteria, nor does it detail a study with quantitative results that definitively "proves" the device meets such criteria in the way a clinical trial or a statistically powered non-inferiority study would.

Here's an analysis based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or provide a table of performance metrics. The core of the performance evaluation is based on a comparative, rather than absolute, standard against predicate devices.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: The document states "studies in animal" but does not specify the number of animals or the overall sample size used in these studies.
• Data Provenance: The studies were conducted "in animal." No country of origin is mentioned, and it is implied to be prospective animal studies, not retrospective human data.

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 provided. The animal studies would likely involve veterinary pathologists or researchers assessing bone healing, but no details are given.

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

This information is not provided in the document.

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 conducted. This device is a bone void filler, not an AI-powered diagnostic tool, so an MRMC study comparing human readers with and without AI assistance is not applicable.

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

This is not applicable as the device is a medical implant, not an algorithm.

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

The ground truth for the animal studies would have been based on biological and histological assessments of bone in-growth and new bone formation, likely through techniques such as histology, histomorphometry, and potentially imaging of the bone healing process. This would fall under pathology/biological outcomes in animal models.

8. The sample size for the training set

This is not applicable as the device is an implant and does not involve machine learning or a training set in the typical sense.

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

This is not applicable as the device is an implant and does not involve machine learning or a training set.

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PLEXUR P is intended for use in filling bony voids or gaps of the skeletal system (i.e., extremities, pelvis) that are not intrinsic to the stability of the bony structure. These defects may be surgically created osseous defects or osseous defects resulting from traumatic injury to the bone. PLEXUR P is resorbed/remodeled and is replaced by host bone during the healing process.

PLEXUR P is a bone void filler that contains as its principal constituents processed human allograft bone tissue and a resorbable polymer. PLEXUR P is produced in various physical forms/shapes/geometries and may be further shaped or cut by the surgeon to meet the particular needs and preferences of the surgeon. PLEXUR P is intended for use as a bone void filler in bony voids or gaps of the skeletal system (i.e., extremities, pelvis) not intrinsic to the stability of the bony structure. PLEXUR P is provided in ready-to-use form in various package sizes by volume or dimension and is intended for single patient use.

The provided text describes a 510(k) summary for the PLEXUR P bone void filler. This document is related to a medical device's regulatory approval process and includes performance data from animal studies. However, it does not describe an AI/ML device and therefore does not contain information typically associated with studies proving device performance against acceptance criteria for AI/ML models.

Based on the provided text, I can only extract the following relevant information:

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

The provided text does not contain any explicit acceptance criteria in the format typically used for AI/ML device performance (e.g., sensitivity, specificity, AUC thresholds). Instead, for this non-AI bone void filler, the performance is described in terms of its biological function.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

• Sample size for test set: The text mentions "studies in animals" but does not specify the number of animals or the sample size used.
• Data provenance: "studies in animals" are mentioned, but no country of origin or whether the studies were retrospective or prospective is specified.

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)

Not applicable, as this is not an AI/ML device involving expert labeling for ground truth.

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

Not applicable, as this is not an AI/ML device requiring adjudication of expert labels.

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, as this is not an AI/ML device.

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

Not applicable, as this is not an AI/ML device.

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

The "ground truth" for the device's function was observed through biological outcomes in animal studies, specifically "bone ingrowth and new bone formation." This could be considered a form of outcome data or histological observation in the context of biological research.

8. The sample size for the training set

Not applicable, as this is not an AI/ML device.

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

Not applicable, as this is not an AI/ML device.

Ask a specific question about this device