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The Flex-Thread™ Distal Fibula Intramedullary Nail System is intended for use in the fixation of fibula fractures and osteotomies.

The Flex-Thread™ Distal Fibula Intramedullary Nail System is comprised of an intramedullary fixation device with a flexible threaded tip to engage the proximal portion of a fibula and cortical screws to further enhance stability and fixation of the fibula.

The provided text describes a medical device, the "Flex-Thread™ Distal Fibula Intramedullary Nail System," and its 510(k) submission for FDA clearance. However, the document does not contain information related to software or AI performance.

Therefore, I cannot extract acceptance criteria or study details regarding device performance from the provided text in the context of an AI/Software device. The submission focuses on the mechanical and functional equivalence of the intramedullary nail system to a previously cleared predicate device.

Specifically, the "Non-Clinical and/or Clinical Tests Summary & Conclusions" section on page 4 details mechanical testing and a cadaver lab simulation, which are relevant to the physical device's characteristics and use, not software performance.

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The Conventus Orthopaedics Ulna Fixation System is indicated for treatment of distal or proximal ulna fractures when internal fixation is desired, and fracture fragments are not too numerous and/or too small to be stabilized with the use of the device.

The Conventus Orthopaedics Ulna Fixation System is an intramedullary device intended for distal and proximal ulna fractures. The Ulna Fixation System is a self-expanding implant which is deployed into the medullary canal and provides a scaffold to which bone fragments are attached using fragment screws. The implant is made from titanium alloy (Ti-6Al-4V ELI) and Nitinol.

This document is a 510(k) summary for the Conventus Orthopaedics Ulna Fixation System. It does not describe a study involving an AI/CADe/CADx device and human readers. Instead, it describes a medical device for fracture fixation and preclinical testing done to prove substantial equivalence to predicate devices. Therefore, I cannot extract the information requested as it is not present in the provided text.

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The Conventus PRSTM System is indicated for treatment of proximal radial fractures when internal fixation is desired, and fracture fragments are not too numerous and/or too small to be stabilized with the use of the device.

The Conventus PRSTM is an intramedullary device intended for proximal radius fractures. The PRSTM System is a self-expanding implant which is deployed into the medullary canal and provides a scaffold to which bone fragments are attached using fragment screws. The implant is made from titanium alloy (Ti-6Al-4V ELI) and Nitinol.

This document is a 510(k) premarket notification decision letter from the FDA to Conventus Orthopaedics, Inc. It concerns the Conventus PRSTM System, an intramedullary device for proximal radial fractures. The letter confirms substantial equivalence to predicate devices based on pre-clinical testing mentioned in the 510(k) Summary.

Here's an analysis of the provided information, focusing on acceptance criteria and study details:

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

The provided document does not explicitly state specific acceptance criteria (e.g., pass/fail thresholds) for the pre-clinical tests. It lists the types of tests performed and concludes that "The results demonstrate that the PRSTM System is substantially equivalent to the legally marketed predicate devices." This implies that the device performance met the criteria necessary to demonstrate equivalency to the predicate devices, whatever those inherent criteria were for each test.

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 provide specific sample sizes for any of the listed pre-clinical tests. It also does not specify the data provenance in terms of country of origin or whether the studies were retrospective or prospective. Given these are pre-clinical (laboratory and animal) tests, the concept of retrospective/prospective human data provenance does not apply.

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 section is not applicable to the type of pre-clinical studies described. These studies involve material science, mechanical engineering, and animal models, not human diagnostic interpretation requiring expert consensus on ground truth.

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

This section is not applicable as the studies are physical/mechanical/biological tests, not diagnostic interpretations requiring adjudication.

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

An MRMC comparative effectiveness study was not conducted. This is a pre-clinical evaluation of a surgical implant, not an AI-assisted diagnostic tool.

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

This refers to AI algorithm performance and is not applicable to the pre-clinical evaluation of a medical device implant.

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

For these pre-clinical studies, "ground truth" refers to the established scientific and engineering principles, material properties, and biological responses measured by validated test methods. For example:

• Mechanical tests: Ground truth is derived from engineering standards, material specifications, and the established performance characteristics of the predicate devices.
• Corrosion, wear, nickel ion release, surface analysis, Nitinol properties: Ground truth is based on established material science standards and acceptable ranges for medical implant materials.
• Biocompatibility: Ground truth is established by ISO standards and recognized biological response criteria (e.g., cytotoxicity, sensitization, irritation).
• Animal Testing: Ground truth involves histological analysis, imaging, and functional assessment to determine biological response and healing in comparison to expected outcomes or predicate device performance.

8. The sample size for the training set

This refers to AI model training and is not applicable to the pre-clinical evaluation of a medical device implant.

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

This refers to AI model training and is not applicable to the pre-clinical evaluation of a medical device implant.

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The Conventus Orthopaedics PHS™ System is indicated for the fixation of proximal humerus fractures except when there are too many fracture fragments to repair the articular surface.

The Conventus PHS™ is an intramedullary device intended to treat proximal humerus fractures. The PHS™ System is a self-expanding implant which is deployed into the medullary canal and provides a scaffold to which bone fragments are attached using fragment screws. The implant is made from titanium alloy (Ti-6Al-4V ELI) and Nitinol.

The provided text describes a medical device called the Conventus PHS™ System, an intramedullary device for fixing proximal humerus fractures. However, it does not include information about acceptance criteria or a study that proves the device meets those criteria in the context of diagnostic or AI-assisted performance.

The document is a 510(k) premarket notification summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device, primarily through mechanical and biocompatibility testing. It outlines the device's physical properties and mechanical performance, not its diagnostic accuracy or the performance of any AI component.

Therefore, I cannot provide details for most of your requested information as it is not present in the provided text.

Here is what I can extract:

1. A table of acceptance criteria and the reported device performance
The document does not explicitly state acceptance criteria or performance metrics related to diagnostic accuracy or AI performance. The pre-clinical tests performed are mechanical and material characterization tests (e.g., static and cyclic axial/bend testing, screw pullout testing, corrosion testing, wear testing, biocompatibility testing, animal testing). The conclusion is simply that "The results demonstrate that the PHS™ System is substantially equivalent to the legally marketed predicate devices," without providing specific numerical acceptance criteria or performance values for these tests.

2. Sample size used for the test set and the data provenance
Not applicable. There is no "test set" in the context of diagnostic or AI performance evaluation described. The "testing" refers to mechanical and material characterization of the device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. No ground truth establishment for a diagnostic test set is described.

4. Adjudication method for the test set
Not applicable. No test set adjudication method 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
No. An MRMC study or any study involving human readers or AI assistance is not mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
No. There is no mention of an algorithm or AI performance.

7. The type of ground truth used
Not applicable. No ground truth for diagnostic or AI performance is established. The "ground truth" equivalent for the pre-clinical tests would be established engineering standards and material properties, but these are not for diagnostic performance.

8. The sample size for the training set
Not applicable. No training set for an AI or diagnostic algorithm is mentioned.

9. How the ground truth for the training set was established
Not applicable. No training set for an AI or diagnostic algorithm is mentioned.

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The Conventus DRSTM is intended for the fixation of distal radius fractures.

The Conventus DRSTM is an intramedullary device intended to treat distal radius fractures. The DRS is comprised of an Expandable Scaffold, Fragment Screws, and a Proximal Plate. The device remains flexible during placement, but is made rigid at the completion of the surgical implant procedure. The implant is made from titanium alloy (Ti6Al4V) and Nitinol.

The provided text is a 510(k) summary for the Conventus DRS™ (Distal Radius System) device, which is a fracture fixation device. The document describes the device, its intended use, and its substantial equivalence to a previously cleared device. However, it does not contain information about acceptance criteria, device performance metrics, or any studies with AI involvement.

The 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (K102689) based primarily on the device's design, materials (titanium alloy and Nitinol), and intended use for distal radius fractures. The only "testing" mentioned is for "MR Conditional" labeling, which assesses safety in a magnetic resonance environment, not clinical performance for fracture fixation.

Therefore, I cannot populate the table or answer the questions as the required information (acceptance criteria, performance data, details of a study proving criteria, sample sizes, ground truth establishment, AI involvement, etc.) is not present in the provided document.

The document is a regulatory submission for a traditional medical device (fracture fixation) and does not appear to involve any AI/ML components for diagnosis, prediction, or intervention that would require performance studies against specific acceptance criteria in the manner described in your request.

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The Conventus DRS™ is intended for use in the fixation of fractures of the distal radius.

The Conventus DRSTM is an intramedullary device intended to treat distal radius fractures. The device remains flexible during placement, but is made rigid at the completion of the surgical implant procedure. The implant is made from titanium alloy (Ti-6Al-4V) and Nitinol.

The provided document describes a 510(k) premarket notification for the Conventus DRS™ device, which is an intramedullary device for fixing distal radius fractures. The document is a regulatory submission and focuses on demonstrating substantial equivalence to legally marketed predicate devices, rather than a clinical study evaluating the performance of an AI algorithm or diagnostic tool.

Therefore, many of the requested elements are not applicable to this type of submission.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

Note: The document does not explicitly state "acceptance criteria" for radiographic success or DASH scores in quantitative terms (e.g., "X% of subjects must achieve radiographic success"). Instead, it reports the "demonstrated" performance. For adverse events, the reporting of specific numbers implies a monitoring and reporting requirement rather than a pass/fail criterion.

2. Sample size used for the test set and the data provenance:

• Sample Size (Test Set): Not explicitly stated as a separate "test set" from a larger training set. The clinical evaluation refers to "study subjects," implying this cohort serves as the primary evaluation set for substantial equivalence. The exact number of subjects is not provided.
• Data Provenance: Clinical evaluation was conducted "outside the United States in Tier 1 countries."
• Retrospective or Prospective: Not explicitly stated, but the mention of "collection of radiographic outcomes, functional outcomes (DASH), and adverse event information" suggests a prospective clinical trial or observation period following implantation of the device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• This information is not provided in the document. The document refers to "radiographic outcomes" being collected, but it does not specify how these outcomes were interpreted or if expert consensus was used to establish ground truth for the fracture classification or healing assessment.

4. Adjudication method 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, and if so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• An MRMC study was not conducted. This document describes a medical device (intramedullary fixator), not an AI algorithm or diagnostic tool that assists human readers.

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

• A standalone performance assessment was not done. This is a physical medical device, not an algorithm.

7. The type of ground truth used:

• The "ground truth" for the device's performance is implicitly based on clinical outcomes data, including:
  • Radiographic outcomes: Assessment of fracture reduction and healing.
  • Functional outcomes: Measured by the DASH (Disabilities of the Arm, Shoulder and Hand) score.
  • Adverse event information: Documented complications.

8. The sample size for the training set:

• The concept of a "training set" in the context of an AI algorithm is not applicable here. This document describes a physical medical device. The "clinical evaluation" described would be the primary data for demonstrating safety and effectiveness relative to predicates.

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

• As mentioned above, the concept of a "training set" for an AI algorithm is not applicable. The ground truth for the clinical evaluation was established through direct clinical observation, radiographic assessment, and patient-reported outcomes.

In summary:

This 510(k) summary focuses on demonstrating the substantial equivalence of a bone fixation device to existing predicate devices. It relies on a clinical evaluation (implicitly a prospective study) to gather data on radiographic and functional outcomes, as well as adverse events. The submission does not involve AI, diagnostic image interpretation, or the associated methodologies for establishing ground truth for algorithms.

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