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The Surg Tech GENOLL™ system is intended to reduce or relieve pain and restore function and motion to the knee joint. Total knee replacement is indicated for patients with severe knee pain and disability due to rheumatoid arthritis, osteoarthritis, primary and secondary traumatic arthritis, collagen disorders, avascular necrosis of the femoral condyle or pseudogout, posttraumatic loss of joint configuration, particularly when there is patellofemoral erosion, dysfunction or prior patellectomy, moderate valgus, varus, or flexion deformities. This device may also be indicated in the salvage of previously failed surgical attempts if the knee can be satisfactorily balanced and stabilized at the time of surgery. This device is intended for cemented use only.

The SurgTech GENOLL"Total Knee System is used for total knee arthroplasty in skeletally mature individuals. The system consists of a CoCr alloy Posterior Stabilized (PS) femoral component (10 sizes, Left and Right), a CoCr alloy tibial baseplate (10 sizes), a conventional polyethylene PS tibial bearing insert (5 sizes with 5 thicknesses each) and a conventional polyethylene patella (3 sizes). Instrumentation necessary for proper implantation is also included.

The provided text is related to an FDA 510(k) premarket notification for a medical device called the "SurgTech GENOLL™ Total Knee System." This document is a clearance letter, not a description of an AI/ML-based device or its performance study.

Therefore, none of the requested information regarding acceptance criteria, device performance, sample sizes, expert qualifications, ground truth establishment, or clinical study methods can be found in the provided text.

The document explicitly states under section (b)(2) "Clinical testing:" that "Clinical testing was not required to demonstrate substantial equivalence in this premarket notification." This indicates that the clearance was based on demonstrating equivalence to predicate devices through similarities in intended use, design, materials, packaging, sterilization, and mechanical performance, rather than through
clinical or AI/ML performance studies.

The acceptance criteria listed in the document are for non-clinical testing of the physical components (e.g., Baseplate Fatigue, Constraint, Contact Area, PS Post Fatigue, Tibial Insert/Baseplate Disassembly, Bacterial endotoxins), not for an AI/ML system's diagnostic or predictive performance.

In summary, the provided text does not contain the information needed to answer your request about acceptance criteria and study data for an AI/ML device.

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The SurgTech Bipolar Head system is intended for use for cases of:
• Non-inflammatory degenerative joint disease such as osteoarthritis, avascular necrosis, ankylosis, protrusio acetabuli and painful hip dysplasia.

• · Inflammatory degenerative joint disease such as rheumatoid arthritis.
• Correction of function deformity.
• · Revision procedures where other treatments or devices have failed.
  · Treatment of nonunion femoral neck and trochanteric fractures of the proximal femur with head involvement that are unmanageable using other techniques.

The SurgTech Bipolar Head System is used for hip hemiarthroplasty in skeletally mature individuals. The system consists of a CoCr alloy shell (38-58mm outer diameters), a polyethylene bearing insert (22mm and 28mm inner diameters) and retaining ring, and CoCr alloy femoral heads (22mm and 28mm) in various offsets. Instrumentation necessary for proper implantation is also included.

The provided text is a 510(k) premarket notification for a medical device, the SurgTech Bipolar Head System. This type of regulatory submission in the US focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving novel safety and effectiveness through extensive clinical trials.

As such, the document does not describe acceptance criteria for a study or a study proving the device meets those criteria in the way one would expect for an AI algorithm or a device requiring new clinical efficacy data.

Here's an analysis based on the information provided, explaining why certain sections of your request cannot be fulfilled:

Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are implicitly tied to demonstrating substantial equivalence to predicate devices. This is achieved primarily through non-clinical testing comparing physical and mechanical characteristics. The document does not list specific numerical acceptance criteria (e.g., minimum accuracy score, sensitivity thresholds) because it's not a performance study of that nature.

Table of Acceptance Criteria and Reported Device Performance:

Explanation of Missing Information for an AI/Clinical Efficacy Study:

The following points cannot be addressed from the provided text because this is a 510(k) submission for a physical orthopedic implant, not an AI or diagnostic device that typically undergoes such efficacy studies.

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. Clinical testing was not required or performed for this 510(k). The "test set" here refers to physical devices undergoing mechanical tests.
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 for a physical implant's mechanical properties is typically established through standardized testing procedures, not expert consensus on medical images or diagnoses.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 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.): For the non-clinical testing, the "ground truth" is adherence to established engineering standards and test methods (e.g., ASTM, ISO) for mechanical properties and biocompatibility.
7. The sample size for the training set: Not applicable. This device does not use a "training set" in the context of machine learning.
8. How the ground truth for the training set was established: Not applicable.

Summary from the Document:

• Non-clinical testing: The device underwent non-clinical testing for "Femoral Head/Bipolar Liner Pull Out/Lever Out," "Femoral Head/Femoral Stem Pull Off," "Range of Motion," and "Bacterial Endotoxins." These tests are typical for orthopedic implants to demonstrate mechanical integrity and biocompatibility.
• Clinical testing: "Clinical testing was not required to demonstrate substantial equivalence in this premarket notification." This explicitly states that no human clinical trials were conducted for this submission.
• Basis for Substantial Equivalence: The manufacturer believes the device is substantially equivalent based on "similarities in intended use, design, materials, packaging, sterilization and mechanical performance" to the identified predicate devices. The technological characteristics "do not raise any new questions of safety and efficacy."

In conclusion, the document describes a regulatory submission for a physical medical device (hip prosthesis) where substantial equivalence is demonstrated through non-clinical performance testing against predicate devices and adherence to established material and mechanical standards, not through clinical efficacy studies involving human subjects or AI-specific validation.

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The SurgTech MALUC™ System is intended for use for cases of severely painful and/or disabled joint from osteoarthritis, traumatic arthritis, rheumatoid arthritis or congenital hip dysplasia, avascular necrosis of the femoral head, acute traumatic fracture of the femoral head or neck, failed previous hip surgery (including joint reconstruction, internal fixation, arthrodesis, hemiarthroplasty and/or total arthroplasty), and certain cases of ankylosis.

The MALUC™ Total Hip Arthroplasty System is used for primary total hip replacement in skeletally mature individuals. The system consists of monolithic cemented and press-fit femoral stems, modular CoCr and BIOLOX® delta femoral heads in various sizes and offsets, uncemented acetabular shells and conventional polyethylene liners. Accessory components include distal centralizers, cancellous bone screws and cement restrictors. Instrumentation necessary for proper implantation is also included.

This document is a 510(k) premarket notification for the MALUC™ Total Hip Arthroplasty System. It focuses on demonstrating substantial equivalence to predicate devices rather than proving a device meets specific clinical performance acceptance criteria in a study. Therefore, much of the requested information regarding acceptance criteria, device performance, and study design for clinical effectiveness is not present in this submission.

Here's a breakdown of what information can be extracted and what cannot:

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

The submission states that non-clinical mechanical testing was performed in accordance with several ISO and ASTM standards, and the device "met all predetermined acceptance criteria." It also mentions bacterial endotoxin testing which "met the predetermined acceptance criteria." However, the specific numerical acceptance criteria and the reported device performance values are not provided in this public summary.

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

This information is not applicable as no clinical test set or data provenance is mentioned for device performance. The submission explicitly states: "(b)(2) Clinical testing: Clinical testing was not required to demonstrate substantial equivalence in this premarket notification." The tests performed are non-clinical (mechanical and endotoxin).

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 applicable as no clinical study involving human interpretation or ground truth establishment is described.

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

This information is not applicable as no clinical test set requiring 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

This information is not applicable as this is a hip arthroplasty system, not an AI-assisted diagnostic device, and no MRMC study was conducted or is relevant to this submission.

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

This information is not applicable as this is a medical implant, not a standalone algorithm.

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

This information is not applicable as no clinical ground truth was established for device performance in this submission. The "ground truth" for the non-clinical tests would be the established standards and specifications (e.g., ISO 21535, ASTM F2996, USP ), and the device's ability to meet those.

8. The sample size for the training set

This information is not applicable. This is a physical medical device, not an AI model requiring a training set.

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

This information is not applicable. As above, this is not an AI model.

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The SurgTech Thoracolumbosacral (TLS) Posterior Fixation System is intended to provide pedicle and non-pedicle immobilization and stabilization of the posterior non-cervical spine (T1-S2/Ilium) in skeletally mature patients as an adjunct to fusion in the treatment of the following acute and chronic instabilities or deformities: degenerative disc disease (defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies), spondylolisthesis, trauma (i.e., fracture or dislocation), spinal stenosis, curvatures (i.e., scoliosis, kyphosis and/or lordosis), tumor, pseudarthrosis, and/or failed previous fusion.

The SurgTech Thoracolumbosacral (TLS) Posterior Fixation System consists of longitudinal members (rods), anchors (hooks and screws), interconnections (cross connector) and fasteners in a variety of sizes to accommodate differing anatomic requirements.

This document describes a 510(k) premarket notification for the "SurgTech Thoracolumbosacral (TLS) Posterior Fixation System," a spinal implant, not an AI/ML powered device.

Therefore, the requested information about acceptance criteria and study design relevant to AI/ML device performance (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set details) is not applicable and cannot be found within the provided text.

The document focuses on demonstrating substantial equivalence to predicate devices through mechanical testing and comparison of technological characteristics.

Here’s the information that is present regarding the device's performance and testing:

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

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

• Not Applicable. The testing performed was mechanical testing of the device itself, not a clinical study on human subjects in the context of an AI/ML model's performance. The "test set" here refers to the device constructs subjected to mechanical stress. The number of constructs tested is not specified, but it's stated they were "worst-case" constructs.
• Provenance: Not specified beyond the tests being conducted on physical device constructs.

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

• Not Applicable. This is not an AI/ML diagnostic or predictive device requiring expert ground truth for its performance evaluation in that context. The "ground truth" for mechanical testing is based on established engineering standards (ASTM F1717) and the ability to withstand specified loads without failure, usually validated by engineers.

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

• Not Applicable. Adjudication methods are relevant for clinical assessments, particularly in AI studies where expert consensus on image interpretation or diagnoses is needed. This was mechanical testing.

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. This device is a spine implant, not an AI-assisted diagnostic tool. No MRMC study was performed.

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

• Not Applicable. This device is a physical implant, not an algorithm.

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

• For mechanical testing, the "ground truth" is defined by the acceptance criteria specified in the ASTM F1717 standard (mechanical performance thresholds and failure modes). The device's performance was compared to that of legally marketed predicate devices, implying that their performance under the same standard serves as a comparative benchmark.

8. The sample size for the training set:

• Not Applicable. There is no AI/ML model, hence no training set.

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

• Not Applicable. There is no AI/ML model, hence no training set ground truth.

In summary, the provided document describes a medical device (spinal fixation system) that received 510(k) clearance based on substantial equivalence demonstrated through mechanical testing against established standards and comparison to predicate devices, not through performance evaluation of an AI-powered diagnostic or therapeutic algorithm.

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The SurgTech Trauma System plates and screws are intended to be used for internal bone fixation for bone fractures, fusions, osteotomies and non-unions appropriate for the size and design of the device.
The large plate set components are indicated for the use including the femur and tibia. The small plate set is indicated for use in various bones including the clavicle, scapula, humerus, radius, ulna, pelvis, tibia and fibula. The mini plate set is indicated for use in various small bones including the metacsals, phalanges, calcaneus and those of the ankle.
In addition, the SurgTech Trauma System cancellous, cannulated lag, headless compression and non-locking cortical screws are indicated for use in bone reconstruction, arthrodesis, joint fusion, fracture repair and fracture fixation, appropriate for the size of the device.

The SurgTech Trauma System is a plate and screw fixation system. Plates are offered in "mini," "small" and "large" set sizes in a variety of shapes based upon the anatomical fixation required. Screws are also offered in "mini" "small" and "large" sets and, in addition, in locking cortical, non-locking cortical, cancellous and headless versions. Screws can also be used for fixation without the plates.

The provided text describes a 510(k) premarket notification for the "SurgTech Trauma System," which consists of bone plates and screws. This document is a regulatory submission to the FDA demonstrating substantial equivalence to existing legally marketed devices.

Crucially, the provided text DOES NOT contain information about an AI/ML-based medical device study.

Instead, the "Performance Data" section explicitly states that the device's performance was evaluated through mechanical testing of the plates and screws according to ASTM standards (ASTM F382 for bending, and other standards for torsion, insertion/removal, and pullout for screws).

Therefore, I cannot fulfill your request for information related to AI/ML acceptance criteria or a study proving its performance, as this document pertains to a traditional orthopedic implant, not an AI-powered diagnostic or therapeutic device.

To reiterate, the document details:

• Device: SurgTech Trauma System (bone plates and screws)
• Purpose of Submission: 510(k) premarket notification for substantial equivalence.
• Performance Evaluation Method: Mechanical testing (e.g., static and dynamic bending, torsion, insertion/removal, pullout) against ASTM standards.

It does not mention any AI/ML components, ground truth establishment by experts, MRMC studies, or any other elements relevant to AI/ML device performance evaluation.

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The SurgTech Interbody System is indicated for use with autogenous bone graft in skeletally mature patients with degenerative disc disease (DDD) at one or two contiguous levels from L2 to S1. DDD is defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies. These patients should have had six months of non-operative treatment. These patients may have had a previous non-fusion spinal surgery and may also have up to Grade 1 spondylolisthesis or retrolisthesis at the involved spinal level(s). These devices are intended to be used with supplemental fixation which has been cleared for use in the lumbar spine.

The SurgTech Interbody System is a system of intervertebral body fusion devices. The Posterior Lumbar device is a structural column in a generally rectangular shape having a rounded nose. Teeth are integral to the inferior and superior surfaces and there is a central cavity to be filled with autograft. The implants are available in an assortment of footprint, height and angulation combinations to accommodate a variety of anatomic requirements.

The provided text describes a 510(k) premarket notification for a medical device called the "SurgTech Interbody System." This document is focused on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific clinical acceptance criteria through a study with performance metrics.

Therefore, many of the requested details about acceptance criteria, study sample sizes, expert ground truth, adjudication methods, and MRMC studies are not applicable or available within this type of regulatory submission.

However, I can extract information regarding the performance testing that was conducted:

1. Table of acceptance criteria and reported device performance:
   The document does not specify quantitative acceptance criteria. Instead, it states that the device's performance was compared to predicate devices.

   Acceptance Criteria (Quantitative)	Reported Device Performance (Quantitative)
   Not specified (Qualitative: Substantially equivalent to predicate)	Not specified (Qualitative: Demonstrated substantial equivalence to predicate)

   Performance Testing Details Provided:

   • Mechanical Testing: Performed on the "worst case" SurgTech Interbody System device according to ASTM F2077. This included static and dynamic compression.
   • Subsidence Testing: Performed on the "worst case" SIS PL device according to ASTM F2267.
   • Conclusion: "The mechanical test results demonstrate that the SurgTech Interbody System performance is substantially equivalent to the predicate devices."

2. Sample size used for the test set and the data provenance: Not applicable. This was mechanical testing, not a clinical study on a patient test set. The provenance is internal testing by SurgTech Inc.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This was mechanical engineering testing, not clinical evaluation requiring expert ground truth.

4. Adjudication method for the test set: Not applicable.

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. This is not an AI-enabled device and no MRMC study was performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI-enabled device.

7. The type of ground truth used: For the mechanical tests, the "ground truth" was established by adherence to and successful completion of specified ASTM standards (ASTM F2077 for static/dynamic compression and ASTM F2267 for subsidence). The "substantial equivalence" claim is relative to the performance of predicate devices under similar testing.

8. The sample size for the training set: Not applicable. There is no mention of a training set as this is not an AI/ML device. The testing was physical mechanical testing.

9. How the ground truth for the training set was established: Not applicable.

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