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The WishBone Medical Plate and Screw System is indicated for pediatric and adult patients of the clavice, scapula, humerus, ulna, radius, metacarpals, pelvis acetabulum, femur, fibula, tibia, metatarsals and middle foot bones, and treatment of the calcaneus, and fixation of bones that have been surgically prepared (osteotomy) for correction of deformity or arthrodesis.

The system includes Femoral Locking Plates and Screws, which are in infant, child, and adolescent pediatric subgroups and small stature adult patients.

The WishBone Medical Femoral Locking Plate System was designed to address deformity correction in the proximal and distal femur where plating is an option for correction. It is intended to be used for temporary stable internal fixation of femoral osteotomies and fractures in pediatric patients. The system consists of two plate sizes, 3.5mm and 4.5mm, which align with the corresponding screw sizes, and are offered in varying lengths based on the quantity of screw holes needed. Plates have three screw holes in the "head" of each plate, plus 3, 4, 6, 8, or 10 screw holes in the shaft of the plates, based on plate configuration. Plates are also offered in varying angles ranging from 85° to 140°, with differing offsets and flares. These variations allow surgeons to best match the presenting patient's anatomy. New 3.5mm and 4.5mm locking and non-locking cortical screws are being added to the system for use with these new plates.

The subject Femoral Locking Plate System implants are composed of 316- Stainless Steel material (ASTM F138-19) and are supplied in one of two single-use sterile packaging configurations based on plate size: sterile packed Tyvek-covered trays or Nylon pouches, each with a double sterile barrier.

The Femoral Locking Plate System is a line extension of the WishBone Medical Plate and Screw System (K180736 & K213498).

The provided regulatory submission for the WishBone Medical Plate and Screw System (K230527) does not include acceptance criteria or the study data that typically demonstrates medical device performance against such criteria in the context of diagnostic or AI-driven devices.

This submission is for a mechanical orthopedic implant (plates and screws), and the "acceptance criteria" discussed are primarily related to ensuring the new device (Femoral Locking Plate System) is substantially equivalent to previously cleared predicate devices based on design, materials, manufacturing processes, and mechanical performance.

Here's why the requested information regarding acceptance criteria and performance studies in the context of an AI/diagnostic device is not present:

• Device Type: This is a Class II orthopedic implant (metallic bone fixation appliances). The clearance process for such devices heavily relies on demonstrating mechanical equivalence, biocompatibility, and sterilization validation compared to existing, legally marketed predicate devices. It is not an AI/diagnostic device that would typically have performance metrics like sensitivity, specificity, or AUC based on analyzing clinical data.
• "Acceptance Criteria" for this device: For this type of device, "acceptance criteria" are implied through the non-clinical performance testing. These are typically engineering specifications and thresholds (e.g., specific torque values for screw torsion, load limits for bend tests) that the device must meet to ensure its mechanical integrity and safety. These are not explicitly laid out in a table in the provided public summary.
• "Study that proves the device meets the acceptance criteria": This refers to the non-clinical performance testing mentioned.

Therefore, many of the specific questions (like sample size for test set, data provenance, ground truth, MRMC studies, AI performance, etc.) are not applicable to this type of medical device submission.

However, I can extract the relevant information that is present in the document regarding the justification for substantial equivalence.

Summary of Acceptance Criteria and Performance (Based on Device Type and Available Information)

Given that this is a mechanical orthopedic implant, "acceptance criteria" are implied by successful performance in biomechanical and material tests. The document states that engineering analyses and testing were conducted to reaffirm substantial equivalence, meaning the device met the established performance standards of the predicate devices.

Detailed Breakdown for AI/Diagnostic Device Questions (Not Applicable or Information Not Provided Herein):

1. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective): Not Applicable. This is a mechanical device, not a diagnostic or AI device that uses clinical data for performance evaluation in this context. The "test set" here refers to the physical devices subjected to mechanical and material testing, not a dataset of patient images or readings.
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. Ground truth, in the context of clinical data interpretation, is not relevant for this mechanical device. The "ground truth" for mechanical testing would be the accepted engineering standards and specifications.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not Applicable. Adjudication methods are used for resolving disagreements in expert interpretations of clinical data, which is not part of this submission type.
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: Not Applicable. This is not an AI-assisted diagnostic or interpretation device.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not Applicable. This is not an algorithm.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not Applicable. For mechanical performance, the "ground truth" is adherence to established ASTM standards and comparable performance to predicate devices.
7. The sample size for the training set: Not Applicable. There is no "training set" in the AI sense for this device.
8. How the ground truth for the training set was established: Not Applicable.

Conclusion:

The provided document details a 510(k) submission for a mechanical bone plate and screw system. The "acceptance criteria" and "studies" are related to mechanical engineering tests, material science, and sterilization validation to demonstrate substantial equivalence to predicate devices, rather than the performance metrics typically associated with AI or diagnostic clinical performance studies.

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The WishBone Medical Plate and Screw System is used for pediatric and adult patients as indicated for pelvic, small and long bone fracture fixation of bones that have been surgically prepared (osteotomy) for correction of deformity or arthrodesis.

Indications for use include fractures of the clavicle, scapula, humerus, ulna, radius, middle hand, metacarpals, pelvis acetabulum. femur. fibula. tibia. metatarsals and middle foot bones. and treatment of the calcaneus.

Specifically, the Straight Fibula Plates are in infant, child, and adolescent pediatric subgroups and adult patients.

The WishBone Medical 7-Hole Straight Fibula Plate and WishBone Medical 3.0mm Cortical Screws and Locking Screws are wrought titanium alloy plate and screws (per ASTM F136) that are being added to the existing WishBone Medical Plate and Screw System as a line extension.

The provided document is a 510(k) premarket notification for a medical device (WishBone Medical Plate and Screw System: 3.0mm Screws and 7-Hole Straight Fibula Plate). This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving the device meets specific acceptance criteria through a full-scale clinical trial or an AI algorithm's performance study.

Therefore, the document does NOT contain information relevant to the following points of your request:

• 1. A table of acceptance criteria and the reported device performance: This document does not establish performance criteria in terms of accuracy, sensitivity, or specificity for an AI algorithm.
• 2. Sample sized used for the test set and the data provenance: There is no "test set" in the context of an AI algorithm's performance study described here. The "testing" refers to mechanical and engineering analyses.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Ground truth establishment by experts is relevant for AI model training and validation, which is not discussed here.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for this type of device submission.
• 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: This is relevant for AI-assisted diagnostic devices, which this is not.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: No AI algorithm is described.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable for the type of testing described (mechanical/engineering analyses).
• 8. The sample size for the training set: There is no AI model or training set discussed.
• 9. How the ground truth for the training set was established: Not applicable, as there is no AI model or training set.

What the document does describe regarding "acceptance criteria" and "proof":

The "acceptance criteria" for a 510(k) submission generally revolve around demonstrating substantial equivalence to a predicate device. The "proof" is provided through non-clinical (engineering) testing and analysis.

Here's a breakdown of the relevant information provided in the document:

Acceptance Criteria (Implied by Substantial Equivalence Framework):

The device is considered "accepted" if it is demonstrated to be substantially equivalent to a predicate device, meaning:

• Same intended use: Yes, stated multiple times ("The subject device and predicate systems have the same intended use").
• Same indications for use: Yes, stated multiple times ("The subject device and predicate systems have the same intended use" and specific indications for use are listed and align with the predicate's general category).
• Same materials: Yes, "The subject device is manufactured from the same materials." (wrought titanium alloy per ASTM F136).
• Similar design features: Yes, "The subject device design is similar to the predicates."
• Same sterilization method and dose: Yes, "The subject and predicate devices have the same sterilization method and dose."
• No new or increased risks identified: This is the overarching goal of the performance data.

Study Proving Device Meets Acceptance Criteria (Non-Clinical Testing):

The "study" in this context refers to engineering analyses and non-clinical testing.

• Type of Testing: Engineering analyses were conducted to demonstrate substantial equivalence with the predicate device.

  • Axial Pullout Strength (per FDA Guidance "Orthopedic Non-Spinal Metallic Bone Screws and Washers - Performance Criteria for Safety and Performance Based Pathway" issued December 11, 2020).
  • Engineering analysis for Screw Torsion (per ASTM F543) - no new worst case.
  • Engineering analysis for Bending Fatigue (per ASTM F382) - no new worst case.
  • Engineering analysis for Insertion and Removal - no new worst case.
  • Engineering analysis for Pull-through Strength - no new worst case.
  • Engineering analysis for Fretting and Corrosion (per ASTM F897) - no new worst case.
  • Engineering analysis for Biocompatibility Risk Assessment (per ISO 10993-1 and FDA Guidance "Use of International Standard ISO 10993-1, "Biological evaluation of medical devices - Part 1: Evaluation and testing within a risk management process" issued September 2020).

• Reported Device Performance (Results of Non-Clinical Testing):

  • "The devices performed within the intended use."
  • "No new questions of safety or efficacy were raised."
  • "The devices were found to be substantially equivalent to predicate devices."

• Sample Size: Not specified for each mechanical test, but implies sufficient samples were tested to conduct the engineering analyses.

• Data Provenance: The testing is laboratory-based engineering analysis, not patient data.

• Clinical Testing: "Clinical testing was not deemed necessary to demonstrate substantial equivalence."

In summary, this document is a regulatory submission for a traditional medical device (bone plate and screws), not an AI/software as a medical device. Therefore, the questions related to AI algorithm performance are not applicable. The device's "acceptance criteria" are met by demonstrating substantial equivalence through a series of specific engineering tests and analyses, indicating no new safety or effectiveness concerns compared to already approved devices.

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The WishBone Bone Plate and Screw System is used for pediatric and adult patients as indicated for pelvic, small and long bone fracture fixation and fixation of bones that have been surgically prepared (osteotion of deformity or arthrodesis.

Indications for use include fractures of the clavicle, scapula, humerus, ulna, radius, middle hand, metacarpals, pelvis acetabulum, femur, fibula, tibia, metatarsals and middle foot bones, and treatment of the calcaneus.

The purpose of this subject 510(k) is to introduce 4.0mm diameter cannulated screws and washers to the bone plate and screw system cleared under K180736.

This document describes a 510(k) premarket notification for the WishBone Medical Plate and Screw System. It is a submission for an orthopedic device, specifically bone plates and screws.

Here's an analysis of the provided information regarding acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance

The submission refers to acceptance criteria, but doesn't explicitly state a table with quantitative values for each criterion and the device's performance against them. Instead, it indicates that the device met certain standards.

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

• Test Set Sample Size: Not explicitly stated in terms of number of screws or plates tested. The document mentions "Engineering analysis and mechanical testing," but does not provide specific sample numbers for these tests.
• Data Provenance: The studies were non-clinical engineering and mechanical tests performed to demonstrate compliance with standards (ASTM F543-17) and FDA guidance documents. This indicates the testing was likely conducted in a controlled lab environment. There is no information regarding country of origin for the data, nor whether it was retrospective or prospective, as these terms typically apply to clinical studies.

3. Number of Experts Used to Establish Ground Truth and Their Qualifications

This information is not applicable as the studies were non-clinical mechanical tests, not clinical studies involving human patients or expert interpretation of medical data (like imaging). Therefore, no "ground truth" derived from expert consensus was required for this particular submission.

4. Adjudication Method for the Test Set

This information is not applicable as the studies were non-clinical mechanical tests. Adjudication methods (like 2+1, 3+1) are relevant for clinical studies where multiple experts evaluate cases and discrepancies need to be resolved.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI/radiology devices where human readers' performance with and without AI assistance is evaluated. The WishBone Medical Plate and Screw System is a physical orthopedic implant, not an AI diagnostic or assistive device.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No, a standalone study (in the context of an algorithm's performance without human interaction) was not done. This is because the device in question is a physical medical implant, not an algorithm or AI software.

7. Type of Ground Truth Used

The "ground truth" for the non-clinical tests was established by industry standards (ASTM F543-17) and performance criteria defined within FDA guidance documents for metallic bone screws and washers. These define the expected mechanical properties and failure limits.

8. Sample Size for the Training Set

This information is not applicable. The device is a physical implant, not an AI/machine learning model that requires a training set.

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

This information is not applicable for the same reason as point 8.

Ask a specific question about this device

The WishBone Medical Plate and Screw System is used for pediatric and adult patients as indicated for pelvic, small and long bone fracture fixation and fixation of bones that have been surgically prepared (osteotomy) for correction of deformity or arthrodesis.

Indications for use include fractures of the clavicle, scapula, humerus, ulna, radius, middle hand, metacarpals, pelvis acetabulum, femur, fibula, tibia, metatarsals and middle foot bones, and treatment of the calcaneus.

Not Found

The provided text is a 510(k) premarket notification letter and the "Indications for Use" for the WishBone Medical Plate and Screw System. It is a regulatory document concerning a bone fixation device, not a study report for an AI/algorithm-driven medical device. Therefore, it does not contain information on acceptance criteria, device performance metrics, sample sizes for test/training sets, expert qualifications, adjudication methods, or comparative effectiveness studies typically associated with AI device evaluations.

The document primarily states that the FDA has determined the device to be "substantially equivalent" to legally marketed predicate devices.

Missing Information:

The document lacks all the requested details regarding acceptance criteria and the study proving the device meets them because it is not a study report for an AI/algorithm device. Specifically, it does not include:

1. A table of acceptance criteria and reported device performance.
2. Sample sizes for test sets or data provenance.
3. Number of experts or their qualifications.
4. Adjudication method.
5. Information on multi-reader multi-case (MRMC) comparative effectiveness studies.
6. Information on standalone (algorithm-only) performance studies.
7. Type of ground truth used.
8. Sample size for the training set.
9. How ground truth for the training set was established.

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