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The Radial Medical Compression System is indicated for use in:

• Preventing deep vein thrombosis (DVT)
• Enhancing blood circulation
• Diminishing post-operative pain and swelling
• Reducing wound healing time
• Treatment and assistance in healing: stasis dermatitis; venous stasis ulcers; arterial and diabetic leg ulcers
• Treatment of chronic venous insufficiency
• Reducing edema

The Radial Medical Compression System (RMCS) is a light weight, mobile, sequential compression device (SCD) placed around the lower leg. The device is designed to provide sequential compression to the calf to augment blood flow. The system includes three components: the Cirvo sequential compression device, an inductive charging cradle and a smart device app (i.e. tablet or smartphone). The RMCS records the amount and duration of compression received during a therapy session as well as compliance with the prescribed therapy. Identified patient data, and compiled, de-identified data will be shared with the treating physician to facilitate clinical decision making.
The Cirvo uses a mechanical system to sequentially compress the leg utilizing four tension zones tensioned in series. A circumferential sleeve of polyester material is placed around the calf, held in place using hook and loop straps. During the compression cycle, a reduction in the effective circumference of the sleeve exerts a radially inward force on the calf. The device has a compression cycle time of 6 seconds and a physician-determined dwell time between compression cycles. The range of compression cycle pressures of the Cirvo is 40-60 mmHg.

The provided text describes the Radial Medical Compression System (RMCS) and its clearance via a 510(k) pathway, demonstrating substantial equivalence to a predicate device. However, the information provided does not include the details typically found in a study proving an AI/device meets acceptance criteria using a test set with ground truth established by experts and adjudication methods, nor does it describe a multi-reader multi-case (MRMC) comparative effectiveness study with human readers assisted by AI.

The document outlines performance testing for a medical device (a sequential compression system) for therapeutic purposes, not an AI or diagnostic device that would require the establishment of ground truth for a test set, expert consensus, or specific acceptance criteria around diagnostic performance metrics like sensitivity, specificity, or AUC.

Therefore, I cannot directly answer your prompt's specific requirements regarding acceptance criteria and a study proving an AI device meets those criteria, as the provided text describes a mechanical medical device and its validation for FDA clearance, which focuses on device performance, safety, and substantial equivalence to a predicate.

However, I can extract the closest analogous information from the provided text regarding the device's performance testing and clinical evaluation.

Based on the provided text, here's an attempt to extract relevant details, acknowledging that it's for a mechanical device and not an AI/diagnostic system as implied by the prompt's structure:

The Radial Medical Compression System (RMCS) is a light-weight, mobile, sequential compression device (SCD) designed to provide sequential compression to the calf to augment blood flow. Its clearance was based on demonstrating substantial equivalence to a legally marketed predicate device (Vasculaire Compression System, K122609).

Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" for diagnostic performance (as would be typical for an AI device) but rather functional and safety performance specifications. The "performance" assessment is primarily comparative and related to its intended physiological effect.

Table 1: Key Performance Attributes and Comparison (Extracted from "Summary Comparison to Predicate" and "Clinical Performance Testing")

Study Details (Clinical Performance Testing)

The "Clinical Performance Testing" section describes a feasibility study rather than a full-scale clinical trial used for a new AI diagnostic device to establish standalone or human-in-the-loop performance. This study's purpose was to evaluate venous flow augmentation.

1. Sample Size and Data Provenance:
* Test Set Sample Size: 10 subjects.
* Data Provenance: The study was conducted on recruited subjects. The text mentions "an IRB approved study," suggesting prospective data collection, likely within the US, given the FDA submission context. No explicit country of origin is stated beyond the general context of US regulatory approval.

2. Number of Experts and Qualifications:
* This type of study (measuring physiological parameters like peak venous velocity) typically involves trained medical professionals performing the measurements (e.g., ultrasound technicians, physicians). However, the document does not specify the number or qualifications of experts used for data collection or analysis within this feasibility study. There's no "ground truth" adjudicated by multiple experts in the sense of image interpretation for AI.

3. Adjudication Method:
* Not applicable to this type of study. The measurements (peak venous velocity) are quantitative.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
* No, an MRMC study was not done. This study was a physiological measurement study on a medical device, not an AI diagnostic tool involving multiple readers interpreting cases. Therefore, there's no effect size for human readers improving with AI assistance.

5. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance):
* Not applicable in the typical sense for an AI device. The "performance" described is the device's direct physiological effect (venous flow augmentation) when worn by a subject, which is an "algorithm only" type of assessment in that it evaluates the device's physical function. However, it's not an AI algorithm generating a diagnostic output.

6. Type of Ground Truth Used:
* The "ground truth" in this context is the physiologically measured peak venous velocity (cm/s) at specific anatomical sites (popliteal and femoral veins) using an objective measurement method (implied to be Doppler ultrasound, common for such measurements). This serves as the quantitative outcome data.
* It also compared to a baseline measurement and a commercially available portable intermittent pneumatic compression (IPC) device.

7. Sample Size for Training Set:
* Not applicable. This document describes a medical device, not an AI system that undergoes a separate training phase with a distinct training dataset.

8. How the Ground Truth for the Training Set Was Established:
* Not applicable. As above, there's no AI training set or associated ground truth establishment process described.

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