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The Nonlinear Taper Lag Screw is intended for the fixation of long and small bone fractures.

The Nonlinear Taper Lag Screw is a cancellous lag screw with a nonlinear tapered shank for optimal strength-to-diameter properties. Screws are available in a range of sizes.

The provided text describes a 510(k) submission for a medical device called the "Nonlinear Taper Lag Screw." This is a bone fixation screw, and the information primarily focuses on its regulatory approval process, intended use, and substantial equivalence to a predicate device, rather than a study evaluating its performance against specific acceptance criteria in a clinical setting in the way an AI/ML device would be.

Therefore, many of the requested items (e.g., sample size for test set, number of experts for ground truth, MRMC study, training set details) are not applicable to this type of device and submission. This is a traditional medical device, not an AI/ML device.

However, I can extract the relevant performance data and address the applicable points based on the provided text.

Acceptance Criteria and Device Performance for Nonlinear Taper Lag Screw

Given that the "Nonlinear Taper Lag Screw" is a traditional medical device (bone fixation screw) and not an AI/ML-based device, the concept of "acceptance criteria" and "device performance" in the context of the provided document primarily refers to the non-clinical engineering and mechanical properties required for FDA 510(k) clearance, rather than clinical performance metrics typically associated with AI/ML systems.

The FDA's 510(k) clearance process for such a device relies on demonstrating "substantial equivalence" to a legally marketed predicate device (Aesculap Titanium Alloy Bone Screws, K970549) based on similar intended use and technological characteristics, including, where appropriate, performance data.

Here's an interpretation based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

- Stiffness
- Strength
- Fatigue Life | "Properties of stiffness, strength, and fatigue life were characterized." |

| Overall Performance:
- Adequate for fixation of long and small bone fractures
- Comparable to predicate device (K970549) | Cleared as substantially equivalent for the intended use. |

Note: The document does not explicitly state numerical acceptance thresholds or detailed performance values. These are implied to have met the necessary standards for substantial equivalence to the predicate device as demonstrated in the non-clinical testing.

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

• Sample Size: Not specified in the provided text. This typically refers to the number of screws or test specimens used in the non-clinical mechanical testing.
• Data Provenance: Non-clinical (laboratory) testing was performed. The country of origin for the data is not specified, but the company (Theken Surgical) is based in Barberton, Ohio, USA, suggesting testing was likely conducted in the US or a facility compliant with US regulatory standards. The testing was retrospective in the sense that the data was generated prior to the 510(k) submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• N/A. This question is relevant for AI/ML performance evaluation where human experts determine the ground truth for image or data interpretation. For a mechanical device, ground truth is established by objective physical measurements and engineering standards (e.g., ASTM standards for mechanical properties). The "experts" would be the engineers and technicians conducting the mechanical tests and interpreting the results against established engineering specifications.

4. Adjudication Method for the Test Set

• N/A. Adjudication methods (e.g., 2+1, 3+1 consensus) are used for resolving disagreements among human experts in AI/ML performance studies. For mechanical testing, the "adjudication" is typically through adherence to standardized testing protocols and quality control measures.

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

• No. An MRMC study is not applicable as this is not an AI/ML diagnostic or interpretive device.

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

• Yes, but not an "algorithm." The "Performance Data" section describes "Non-clinical: Static and fatigue cantilever beam testing" which was performed on the device itself. This is a standalone performance evaluation of the physical device's mechanical properties without human intervention impacting its intrinsic material or structural performance.

7. Type of Ground Truth Used

• Mechanical Measurement Standards. The "ground truth" for the non-clinical testing would be derived from established engineering standards and specifications for stiffness, strength, and fatigue life of bone fixation screws, often defined by organizations like ASTM or ISO. The tests measure objective physical properties of the screw.

8. Sample Size for the Training Set

• N/A. This concept is for AI/ML models. For a physical device, there is a design and manufacturing process, but not a "training set" in the AI sense.

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

• N/A. (See point 8).

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