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The Flow-Screw is intended for the fixation of bone fractures and bone reconstructions. When used for these indications, the Flow-Screw can also be used to deliver injectable bone void fillers to a surgical site.

The Flow-Screw is cannulated and available in fully and partially threaded designs in various lengths. The Flow-Screw is fenestrated along its length which allows it to be used as a delivery system for injectable bone void fillers. The Flow-Screw implants are made of titanium alloy (Ti-6Al-4V) conforming to ASTM F136 or stainless steel conforming to ASTM F138 or ASTM F2229.

The provided text describes a medical device called the "Flow-Screw" and its substantial equivalence to predicate devices, but it does not contain any information about acceptance criteria or a study that proves the device meets those criteria in the context of an AI/ML product.

The document is a 510(k) premarket notification decision letter from the FDA for a physical medical device (a bone fixation screw), not an AI/ML algorithm. Therefore, the questions related to AI/ML product evaluation (like sample sizes for test/training sets, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable to this document.

The "Substantial Equivalence" section mentions "Mechanical Performance" and "BVF Delivery" as criteria, stating:

• Mechanical Performance: "Mechanical testing demonstrates the substantial equivalence of the Flow-Screw relative to the identified predicates when subjected to static compression bending loads."
• BVF Delivery System: "The qualification testing (i.e., Injectability Testing, Experimental Void Fill Imaging Studies, Static Extraction Torque, BVF Characterization) was performed with ETEX Beta-bsm and CarriGen (K062630, K072355, K090242, K101557)"

However, these are not quantitative acceptance criteria in the format requested, nor do they detail the specifics of such studies as would be done for an AI/ML device.

Therefore, I cannot provide the requested information because the document describes a physical medical device and not an AI/ML product.

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The Flow-Nail is intended to treat stable and unstable proximal fractures of the femur including pertrochanteric, intertrochanteric, and high subtrochanteric fractures and combinations of these fractures. The Flow-Nail can also be used to deliver injectable bone void fillers to a surgical site.

The Flow-Nail is a dynamic compression trochanteric nail system and includes an intramedullary nail, a sliding fenestrated lag screw, anti-rotation screws, a cap and accompanying surgical instruments. The Flow-Nail components are made of titanium alloy (Ti-6Al-4V) conforming to ASTM F136.

Acceptance Criteria and Study for Flow-Nail (K140601)

The Flow-Nail is an intramedullary fixation rod intended to treat stable and unstable proximal femur fractures and to deliver injectable bone void fillers. The device's substantial equivalence to predicate devices was established through a comparison of various attributes, including mechanical performance.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set

The provided document (K140601 510(k) Summary) does not explicitly detail the sample size or data provenance (e.g., country of origin, retrospective/prospective) for the test set used in the mechanical performance studies. The study primarily relies on a comparative mechanical testing approach rather than clinical trial data.

3. Number of Experts and Qualifications for Ground Truth of Test Set

This type of submission (510(k) for an intramedullary fixation rod) does not typically involve human expert adjudication for a "test set" in the context of clinical outcomes or imaging classification. The evaluation is based on engineering and material science standards and physical testing. Therefore, the concept of "experts establishing ground truth" as it would apply to, for example, image interpretation, is not relevant here. The "experts" would be the engineers and scientists conducting the mechanical tests and comparing the results to established standards and predicate device performance.

4. Adjudication Method for the Test Set

Given the nature of the mechanical performance studies for a medical device like an intramedullary nail, there is no adjudication method described or typically applied in the way it would be for a clinical diagnostic study (e.g., 2+1 or 3+1). The evaluation is based on objective measurements from standardized mechanical tests.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed. This type of study is relevant for evaluating the impact of AI on human readers in diagnostic tasks, which is not applicable to the Flow-Nail's pre-market submission which focuses on substantial equivalence through mechanical and material testing.

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

Not applicable. The Flow-Nail is a physical medical device, not an AI algorithm. Therefore, "standalone performance" in the context of an algorithm without human-in-the-loop is not relevant.

7. Type of Ground Truth Used

The "ground truth" for the Flow-Nail's substantial equivalence is based on engineering standards, material specifications, and the established performance of existing predicate devices through standardized mechanical testing. This includes:

• ASTM F136 for titanium alloy composition.
• Static and dynamic compression bending loads for mechanical performance.
• Qualification testing for BVF delivery (Injectability Testing, Experimental Void Fill Imaging Studies, Static Extraction Torque, BVF Property characterization).

8. Sample Size for the Training Set

Not applicable. The concept of a "training set" is relevant for machine learning algorithms. The Flow-Nail is a physical medical device, and its development and testing do not involve a training set in this context.

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

Not applicable, as there is no "training set" for this physical device.

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Gamma-bsm Moldable Bone Substitute Material is an implantable bone graft that is a synthetic calcium phosphate, poorly crystalline hydroxyapatite material intended for use in filling bone voids or defects of the skeletal system (i.e. the extremities, posterolateral spine and pelvis) that are not intrinsic to the stability of the bony structure. These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone. Gamma-bsm Moldable Bone Substitute Material is a bone graft substitute that resorbs and is replaced with new bone during the healing process.

Gamma-bsm Moldable Bone Substitute Material is a synthetic, biocompatible bone graft substitute material. At the time of use, the powder component is combined with a specified volume of mixing solution and mixed to form a putty. The resulting putty is administered to the treatment site by manual application. The material can be shaped into a desired form in-situ prior to implantation. After the putty is applied to the treatment site, it hardens at body temperature and converts to an apatitic calcium phosphate material. The end product, poorly crystalline hydroxylapatite (PCHA), is of low crystalline order with a similar chemical and crystalline structure to that of natural bone minerals. Gamma-bsm Moldable Bone Substitute Material is an osteoconductive material that is resorbed and replaced by natural bone over time.

The provided text is a 510(k) summary for the Gamma-bsm Moldable Bone Substitute Material. This document focuses on the regulatory submission for a medical device and does not contain information typically found in a study proving a device meets acceptance criteria for an AI/software-as-a-medical-device (SaMD) product.

The request asks for information related to "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of an AI/SaMD, including details like sample sizes for test and training sets, expert qualifications, and adjudication methods. These types of details are not relevant to the physical bone void filler device described in the provided 510(k) summary.

Therefore, I cannot fulfill the request for information on acceptance criteria and a study proving the device meets those criteria, as the provided text relates to a physical medical device (bone void filler) and not a software/AI product. The submission is a "Traditional 510(k) Submission - Bone Void Fillers" and its performance data section refers to "Regression testing consistent with Class II Special Controls Guidance Document: Resorbable Calcium Salt Bone Void Filler Device; Guidance for Industry and FDA Staff (dated June 2, 2003)". This indicates the type of testing performed would be for a physical material's properties (e.g., biocompatibility, mechanical strength, resorption rate) rather than performance characteristics of an AI algorithm.

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