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• To help prevent Deep Vein Thrombosis (DVT)

The Flowtron Small Calf Garment is a wraparound Calf garment comprising of a bladder and surrounding material intended to apply cyclic compression to calf to improve return venous blood flow to prevent and reduce the risk of Deep Vein Thrombosis (DVT). The Flowtron Small Calf Garment is connected to an ArjoHuntleigh Flowtron pneumatic pump. The pump controls and generated the delivery of air to inflate and deflate the Calf Garment in a cyclic manner. Flowtron Calf Garments are configured with a custom design connector that means that they are only compatible with ArjoHuntleigh Flowtron pneumatic pumps

This document, K172103, is a 510(k) premarket notification for a medical device called the Flowtron DVT5 Small Calf Garment, manufactured by Getinge (Suzhou) Co., Ltd. and ArjoHuntleigh.

Based on the provided text, this K172103 document is not about an AI/ML-driven medical device. Instead, it concerns a physical medical device (a compressible limb sleeve) used to prevent Deep Vein Thrombosis (DVT). The "acceptance criteria" and "study" described in the document relate to the physical and functional performance of this device and its substantial equivalence to a predicate device, not to the performance of an AI algorithm.

Therefore, many of the requested points regarding AI/ML device evaluation criteria (e.g., sample size for test/training sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training ground truth) are not applicable to this specific document as it does not describe an AI medical device.

However, I can extract and structure the relevant "acceptance criteria" and "study" information pertinent to this physical device as described in the document.

Here's the information derived from the provided text, with emphasis on what is available and a clear indication of what is not applicable due to the nature of the device:

Device Name: Flowtron DVT5 Small Calf Garment
Regulation Name: Compressible Limb Sleeve
Regulatory Class: Class II

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

The document doesn't explicitly present a table of quantitative acceptance criteria with numerical performance targets. Instead, it describes various performance tests conducted to demonstrate substantial equivalence to a predicate device (K925717, DVT10(S) Limb Compression Sleeves Calf Garments). The "acceptance criteria" can be inferred as "Passed" for each test, indicating that the device met the required performance for equivalence.

Note: The core "acceptance criteria" here is that the new device (DVT5) is "identical in materials, function and indications for use" to the predicate device (DVT10(S)), with the only difference being size. The testing aims to prove that this size difference does not negatively impact performance or safety, thus maintaining substantial equivalence.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

• Sample Size: Not specified in the provided text. The document refers to "testing to demonstrate equivalence" but does not quantify the number of units tested.
• Data Provenance: Not explicitly stated. The manufacturer is Getinge (Suzhou) Co., Ltd. in China, but the location where the testing was conducted is not specified. The studies appear to be part of the premarket notification, implying they are new studies conducted for this submission (prospective in that sense) rather than retrospective analysis of existing data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

• Not Applicable. This is a physical device, and the "ground truth" for its performance is based on engineering and materials testing, not expert interpretation of diagnostic images or data. No human experts are described as establishing "ground truth" in the way an AI/ML study would require.

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

• Not Applicable. No human adjudication process is described for the performance tests of this physical device.

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. This is not an AI/ML device, and no human reader studies or MRMC studies are described.

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

• Not Applicable. This is not an AI/ML device, and therefore, no algorithm-only performance study was conducted.

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

• The "ground truth" for this device's performance is based on engineering and physical performance specifications (e.g., pressure cycles, durability, environmental stability, biocompatibility, shelf-life, shipping resilience) compared to the predicate device. These are objective measures determined through laboratory testing, not medical consensus or patient outcomes directly.

8. The sample size for the training set

• Not Applicable. This is not an AI/ML device; there is no "training set."

9. How the ground truth for the training set was established

• Not Applicable. As no training set exists for this type of device, this question is irrelevant.

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To help prevent Deep Vein Thrombosis (DVT)

The Flowtron ACS900 is a pneumatic pump that supplies compressed air to inflate compression garments that are attached to patient's limbs. It is designed to work with the ArjoHuntleigh ranges of DVT calf/thigh compression garments, Foot compression garments and Tri Pulse calf/thigh compression garments. The pump automatically senses the type of compression garment connected and adjusts the pressure/time cycle accordingly. Each garment is compressed alternately, applying pressure to the patient's limb to help prevent deen vein thrombosis.

The provided document is a 510(k) summary for the Flowtron ACS900, a pneumatic pump designed to prevent Deep Vein Thrombosis (DVT). The document describes the device, its intended use, and the testing performed to demonstrate its substantial equivalence to a predicate device.

Here's an analysis based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria with corresponding performance metrics in a way typical for diagnostic or AI-driven devices. Instead, it lists various "Testing conducted" with a binary "Result" (Passed or Complies with Standard). The acceptance criteria are implicitly defined by compliance with established medical device standards and the functional validation of the pump's software/hardware.

Here's the information parsed into a table format as requested, interpreting "acceptance criteria" as the tests performed and "reported device performance" as the outcome:

• Garment detection
• Therapy delivery | Passed |
  | Performance testing garments – Pressure cyclic test:
• with Tri Pulse garments
• with Foot garments
• with DVT garments | Passed |
  | Electrical Testing to Standard AAMI / ANSI ES60601-1:2005/(R)2012 and A1:2012 | Complies with Standard |
  | EMC testing to Standard IEC 60601-1-2, 2007 | Complies with Standard |
  | Environmental Stability testing:
• Storage / Distribution Test
• Operational Temperature / Humidity Test | Passed |

2. Sample size used for the test set and the data provenance

The document does not specify sample sizes or data provenance (e.g., country of origin, retrospective/prospective) relating to clinical performance or patient data. The tests described are primarily engineering and hardware/software validation tests, not clinical efficacy trials with patient populations.

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

Not applicable. The tests described are for a physical medical device (a pneumatic pump and its associated garments) and involve engineering validation and standard compliance, not interpretation of clinical data by experts to establish ground truth for a diagnostic output.

4. Adjudication method for the test set

Not applicable. There is no mention of adjudication as the tests performed are primarily objective engineering and performance evaluations against predefined standards or functional specifications.

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. The Flowtron ACS900 is a physical medical device (a pump for DVT prevention), not an AI-driven diagnostic tool that would involve human readers or MRMC studies.

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

Not applicable. This device is not an algorithm, but a hardware product.

7. The type of ground truth used

The "ground truth" for this device's evaluation is defined by:

• Functional specifications: Ensuring the pump correctly detects garments and delivers therapy as designed.
• Performance specifications: Ensuring the compression garments maintain specific pressure cycles.
• Regulatory standards: Compliance with electrical (AAMI / ANSI ES60601-1) and EMC (IEC 60601-1-2) standards.
• Environmental stability requirements: The device's ability to withstand storage, distribution, and operational conditions.

8. The sample size for the training set

Not applicable. There is no mention of a "training set" as this is not an AI/ML device requiring data for model training.

9. How the ground truth for the training set was established

Not applicable, for the same reason as point 8.

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