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SixFix™ Hexapod Fixator and Deformity Analysis and Correction Software (DACS) is intended to be used for posttraumatic joint contracture which has resulted in loss of range of motion; fractures and disease which generally may result in joint contractures or loss of range of motion and fractures requiring distraction; open and closed fracture fixation; pseudo-arthrosis of long bones; limb lengthening by epiphyseal or metaphyseal distraction; correction of bony or soft tissue deformities; correction of bony or soft tissue defects; joint arthrodesis; infected fractures or nonunions.

The SixFix™ web application for the DACS software can be used with the SixFix™ Hexapod fixator. Use of the software is optional for clinicians using the SixFix™ Hexapod fixator.

The SixFix™ Deformity Analysis and Correction Software (DACS) can be used with the SixFix™ Hexapod fixator (K190069), otherwise known as a spatial frame external fixator. Use of the software is optional for clinicians using the SixFix™ Hexapod, which is a circular external fixator based on Illizarov principles. The software utilizes radiographs, along with surgeon inputs, to develop a patient prescription to correct the deformity.

The provided FDA 510(k) clearance letter and summary for the SixFix™ Hexapod Fixator and Deformity Analysis and Correction Software (DACS) contain details about the device's intended use, description, and comparison to a predicate device. However, it does not provide the specific quantitative acceptance criteria or detailed study results typically found in a comprehensive study report for software performance.

The document states:

• "Functional testing used the same approach as testing for the predicate device and included 43 test cases representing a range of clinical scenarios to ensure the device performed as intended."
• "Test results demonstrate that the device is as safe, as effective, and performs as well as or better than the legally marketed device predicates."

This indicates that testing was performed, but the precise acceptance criteria, the reported device performance against those criteria, or the detailed methodology (sample size for test set, data provenance, expert involvement, ground truth establishment, MRMC study, etc.) are not included in this summary.

Therefore, many of your requested details cannot be extracted from the provided text. I will provide a table and describe what information is available and what is missing based on the provided document.

Acceptance Criteria and Device Performance (Based on provided document)

Since the document does not explicitly state quantitative acceptance criteria or detailed performance metrics, the "acceptance criteria" can be inferred as successful completion of the functional tests and demonstrating equivalence to the predicate. The "reported device performance" is a general statement of successful testing.

Detailed Study Information (Based on provided document)

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

   • Sample Size for Test Set: The document states "43 test cases representing a range of clinical scenarios." It does not specify if these "test cases" refer to patient datasets or defined functional tests. Assuming "test cases" are distinct clinical scenarios/data points used to validate the software, the sample size for the test set is 43.
   • Data Provenance: Not specified. It does not mention the country of origin of the data or whether it was retrospective or prospective.

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

   • Not specified. The document broadly mentions "surgeon inputs" but does not detail how ground truth for the test set was established or the number/qualifications of experts involved in that process.

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

   • Not specified. This detail is not provided in the document.

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:

   • No MRMC study is mentioned. The document focuses on the software itself and its equivalence to a predicate, not on human-in-the-loop performance improvement. The "Use of the software is optional for clinicians using the SixFix™ Hexapod fixator" suggests it's a tool, but its impact on human reader performance is not discussed.

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

   • Yes, implicitly. The "Functional testing" involving 43 test cases likely refers to standalone software performance. The software "utilizes radiographs, along with surgeon inputs, to develop a patient prescription to correct the deformity." The testing would have evaluated the accuracy of these generated prescriptions based on input data.

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

   • Not explicitly stated for the test set. Given the nature of the software (deformity analysis and correction), the ground truth for the test cases would likely involve pre-defined, clinically correct "prescriptions" or measurements established by expert opinion or theoretical calculations validated by experts. It's not pathology or outcomes data in this context.

7. The sample size for the training set:

   • Not specified. The document mentions testing and validation but provides no information about a training set size, implying either it's not a machine learning model that requires a distinct, labeled training set of this type, or the information is simply not included in this summary. Given it's a "Deformity Analysis and Correction Software" and not explicitly termed an AI/ML device in the modern sense (though it performs "analysis"), it might be a rules-based or algorithmic system that doesn't rely on a separate training dataset in the same way a deep learning model would.

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

   • Not applicable/Not specified, as no training set information is provided.

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The SixFix™ Hexapod and Deformity Analysis and Correction Software (DACS) are intended to be used for posttraumatic joint contracture which has resulted in loss of range of motion; fractures and disease which generally may result in joint contractures or loss of range of motion and fractures requiring distraction; open and closed fracture fixation; pseudo-arthrosis of long bones; limb lengthening by epiphyseal or metaphyseal distraction; correction of bony or soft tissue deformities; correction of bony or soft tissue defects; joint arthrodesis; infected fractures or nonunions.

The SixFix™ Hexapod Fixator is a multilateral circular external fixation system. The system includes the following external fixator elements: rings, footplates, arches, struts, threaded rods, wires, external fixation accessories, and software. All of the elements are provided non-sterile and are for single use only.

The system is designed such that gradually adjusting the lengths of the struts in relation to one another alters the orientation of the rings and, consequently, the bone segments connected to the rings by half-pins and wires during the treatment period in order to achieve the patient's treatment goals.

The Deformity Analysis and Correction Software is an optional software component and is used to assist the physician in calculating the lengths of the struts connecting the rings to manipulate the bone fragments. The software receives inputs from the physician and allows the physician to visualize the moving bone position. The program computes the strut lengths necessary to implement any desired translation and/or rotation required by the surgeon.

The provided text describes the SixFix™ Hexapod Fixator and Deformity Analysis and Correction Software (DACS) but does not detail specific acceptance criteria or a study that rigorously proves the device meets those criteria with quantitative performance metrics.

Instead, the document highlights:

• Substantial Equivalence: The primary assertion is that the SixFix™ Hexapod Fixator and DACS are "substantially equivalent" to predicate devices (Taylor Spatial Frame, Deformity Analysis and Correction Software (DASC), and Ilizarov External Fixation Wires). This means it performs as well as or better than legally marketed predicate devices without raising new questions of safety or effectiveness.
• Performance Data Overview: It mentions that "Static and dynamic mechanical testing were performed" and "Software verification and validation testing were conducted." However, it does not provide the results of these tests in terms of specific acceptance criteria.

Therefore, an answer using the requested format would mostly consist of "Not Provided" or "N/A" for many fields, as the document does not contain the level of detail asked for in the prompt regarding a specific study proving quantifiable acceptance criteria.

Here's an attempt to answer based on the given text, with the understanding that much information is missing:

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

2. Sample sized used for the test set and the data provenance
Not provided in the document. The text refers to "static and dynamic mechanical testing" and "software verification and validation testing" but does not specify sample sizes for these tests or the provenance of any data used (e.g., country of origin, retrospective/prospective).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable/Not provided. The document focuses on substantial equivalence based on mechanical and software testing, not on clinical performance evaluated against expert ground truth for interpretation or diagnosis.

4. Adjudication method for the test set
Not applicable/Not provided. No clinical test set or expert adjudication process is described in the provided text.

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/Not provided. This document does not describe an MRMC study. The DACS is software to assist the physician in calculating strut lengths and visualizing bone position, not for diagnostic interpretation by human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
While the DACS is a standalone software component in terms of its execution, the performance demonstration focuses on its functional equivalence to a predicate software and its role in assisting a physician. No specific "standalone performance" study (e.g., accuracy of calculations compared to a gold standard without human input as part of the evaluation) is detailed with quantifiable results. The text states, "The DACS matches the functions performed by the predicate DACS."

7. The type of ground truth used
For the mechanical testing, the ground truth would likely be established engineering standards or validated predicate device performance data.
For the software testing, the ground truth would be the expected output or behavior according to the software requirements specification and comparison to the predicate software's known functionality.
Specific details are not provided.

8. The sample size for the training set
Not applicable/Not provided. The document describes software verification and validation, not a machine learning model that would require a "training set" in the conventional sense.

9. How the ground truth for the training set was established
Not applicable/Not provided. As no training set for a machine learning model is mentioned, this information is not relevant to the provided text.

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