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The BOLD ® SCREW is indicated for fixing the elective osteotomics of the mid-foot bones and the metatarsal and phalanges of the foot only. Examples include:

• · Mono or Bi-cortical osteotomies in the forefoot
• · Distal or proximal metatarsal osteotomics
• · Weil osteotomy
• · Fusion of the first metatarsophalangeal joint and interphalangeal joint.
• · Fixation of osteotomies for Hallux Valgus treatment (such as Scarf, Chevron, ... etc.)
• · Akin type ostcotomy
• · Arthrodesis base first metatarsal cunciform joint to reposition and stabilize metatarsus varus primus

The BOLD® SCREW is a cannulated screw made of a Titanium alloy. Its design includes a non-threaded shaft and a screw tip. Screws come in lengths of 10-34 mm.

The document provided is a 510(k) summary for a medical device (BOLD® SCREW) seeking substantial equivalence to predicate devices, not a study report detailing acceptance criteria and performance data for an AI/ML device. Therefore, it does not contain the information requested in points 1 through 9, which are typically found in studies for AI/ML device evaluations.

The document primarily focuses on:

• Sponsor and contact information
• Device identification (name, classification, codes)
• Description of device components and material
• Intended use and indications for use
• Predicate devices for comparison
• Comparison of technological characteristics to predicate devices
• A brief mention of a mechanical study (rupture torque)
• FDA's substantial equivalence determination letter

Regarding the mechanical study mentioned:

A study on the rupture torque of the BOLD® SCREW was performed.

• Acceptance Criteria: The device needed to comply with the French Standard Nº NF-F-90-414 for resistance to torsion.
• Reported Device Performance: The BOLD® SCREW was "found to have a resistance to torsion in compliance with the selected Standard."

However, this is a mechanical performance study of a bone screw, not a study of an AI/ML device, and thus doesn't include the detailed "acceptance criteria and study that proves the device meets the acceptance criteria" in the context of AI/ML performance metrics (such as sensitivity, specificity, AUC, etc., or details about ground truth, expert consensus, sample sizes for training/test sets, or MRMC studies).

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