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Help prevent edema and leg discomfort and help prevent deep vein thrombosis for long distance travelers
Help prevent edema and leg discomfort, and help prevent deep vein thrombosis in individuals subjected to immobility.

Therafirm Trouser Socks and their substantial equivalents are knit on circular knit machines. These products are made with nylon and spandex; however some Therafirm Trouser Socks contain Coolmax/Lycra for the wearer's comfort. Therafirm Trouser Socks and their substantial equivalents provide similar compression at the ankle, are sized based on ankle and calf circumferences, and include shoe sizes as a helpful reference.

The provided text is a 510(k) summary for medical support stockings and does not contain the kind of detailed information requested for acceptance criteria and a study proving device performance in the context of an AI/algorithm-based medical device.

**This document describes: **

• Device: Therafirm Men's Trouser Socks and Women's Trouser Socks (compression stockings).
• Indication for Use: Help prevent edema and leg discomfort, and help prevent deep vein thrombosis for long distance travelers.
• Classification: Medical Support Stocking (Class II medical device, Product Code DWL).
• Substantial Equivalence: Claimed equivalence to Jobst Travel Socks (K032325) and SSL Americas Flight Sock (K040353).
• Testing: Mentions "nonclinical testing that demonstrates that the device is safe, effective, and performs in comparison to predicate devices" in a section on "Performance Testing - Bench and Exhibits on pages 40 - 43". However, these pages are not provided in the input.

Therefore, I cannot provide the requested information because the input does not contain a study about an AI/algorithm device, nor specific acceptance criteria and performance data in that context.

The questions in the prompt (sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, type of ground truth, training set sample size, how training set ground truth was established) are all highly relevant to the evaluation of AI/machine learning medical devices, but are not applicable to the documentation provided for compression socks, which primarily relies on substantial equivalence to existing products and bench testing for physical characteristics like compression.

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