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The HALLU® -PLATES are intended to be implanted for fixation of fractures, osteotomies or arthrodesis of the first metatarso-phalangeal joint. Examples include:
-Hallux rigidus
-Severe hallux valgus (IM angle > 20° and HV angle > 40°)
-Deformity from rheumatoid arthritis
-Failed previous surgical procedure
-Traumatic arthritis
-Neuromuscular instability.

The HALLU® -PLATES are available in two different designs :

• the HALLU®-C PLATE -
• the HALLU®-S PLATE -
  The HALLU®-C PLATE and the HALLU® -S PLATE are low profile Titanium plates dedicated to first metatarso-phalangeal arthrodesis. Those implants are pre-bent for optimal anatomical adaptation (10° valgus and 10°dorsiflexion). Their fixation is provided by Titanium SNAP-OFF® screws available in a two diameters: 3.0 and 2.7 mm. They exist in different colors for size identification. The bone contact surface is sand blasted in order to maximize plate stability. The range of HALLU -C PLATE and HALLUS S PLATE include 6 sizes ( 31eft/3right) for optimal anatomic fit. Moreover, the HALLU®-S PLATE has an anatomical design providing optimal bone coverage.

The provided text describes a medical device, the HALLU®-PLATES, and its regulatory clearance based on substantial equivalence to predicate devices, rather than a study proving performance against specific acceptance criteria for a new AI/software device. Therefore, much of the requested information regarding AI/software device studies (e.g., sample sizes for test/training sets, expert adjudication methods, MRMC studies, standalone performance, ground truth for training) is not applicable.

However, I can extract the information related to the device's testing and the standards it met.

1. Table of Acceptance Criteria and Reported Device Performance

Detailed Breakdown of Applicable Information:

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

• Sample Size: Not explicitly stated as this was a physical device test, not a data-driven software evaluation. The document mentions "Test 1" and "Test 2," implying multiple samples of the plate were tested for bending and fatigue.
• Data Provenance: The tests were conducted to comply with French Standard ISO 9585 and ASTM Standard F-382-99. This implies the tests were performed in a controlled laboratory setting, likely in the country of origin of the sponsor (France) or a qualified testing facility. The study type is experimental/bench testing, not retrospective or prospective human data.

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

• This question is not applicable as the "ground truth" for a physical device test like this is defined by established engineering standards (ISO 9585 and ASTM F-382-99) and the physical properties of the materials and design, not by expert human interpretation.

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

• This question is not applicable for a physical device test. The compliance is determined by measurements against predefined standard thresholds.

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, a MRMC comparative effectiveness study was not done. This is a physical bone plate, not an AI or imaging device that would involve human readers.

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

• Yes, a standalone test was done. The device's performance (bending strength, stiffness, fatigue strength) was evaluated independently against established physical standards. This is analogous to a "standalone" test for a physical product.

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

• The ground truth was based on established engineering standards for bone plates: French Standard ISO 9585 and ASTM Standard F-382-99.

8. The sample size for the training set:

• Not applicable. This device underwent physical bench testing, not a machine learning training process.

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

• Not applicable. As above, there was no training set for a machine learning model.

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