(281 days)
The AIROS 6 Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:
- · Lymphedema
- Venous stasis ulcers
- · Venous insufficiency
- · Peripheral edema
The device is safe for both home and hospital use.
The AIROS 6 Sequential Compression Device is a gradient pneumatic compression device. The device is used for treatment and management of venous or lymphatic disorders. The application of gradient sequential compression increases blood flow and encourages extracellular fluid clearance.
The AIROS 6 system consists of the device and 6-chambered garments. The device provides cycles of compressed air and sequentially inflates the garments from distal to proximal.
The provided text is a 510(k) summary for the AIROS 6 Sequential Compression Device. This type of FDA submission is for demonstrating substantial equivalence to a predicate device, primarily through performance testing and adherence to standards, rather than clinical efficacy studies often associated with AI/ML-based devices.
Therefore, the document does not contain specific details regarding:
- Acceptance criteria and reported device performance related to a diagnostic or AI/ML-based task. The performance tests listed are functional and safety tests for a pneumatic compression device, not accuracy metrics for a diagnostic algorithm.
- Sample sizes for a test set or data provenance (e.g., country of origin, retrospective/prospective). The testing described is for engineering validation of the physical device.
- Number of experts and their qualifications for ground truth establishment. Ground truth as defined for diagnostic AI/ML models is not applicable here.
- Adjudication method for a test set. Not applicable.
- Multi-Reader Multi-Case (MRMC) comparative effectiveness study. This type of study is for evaluating human performance with and without AI assistance, which is not relevant to this device.
- Standalone (algorithm-only) performance. The device is a physical pneumatic compression system, not an algorithm.
- Type of ground truth used (expert consensus, pathology, outcomes data, etc.). Not applicable.
- Sample size for the training set or how ground truth for the training set was established. This device does not involve machine learning or a "training set" in the context of AI.
Based on the provided text, here is what can be extracted regarding the "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of this 510(k) submission:
The "acceptance criteria" in this context are the successful completion of various functional and safety performance tests, and compliance with recognized medical device standards, to demonstrate that the AIROS 6 Sequential Compression Device operates as intended and is safe. The "study" refers to the conducted functional performance testing.
1. A table of acceptance criteria and the reported device performance:
The document lists "Functional Performance Testing" that was performed to "ensure that the system meets its specifications." While the specific numerical acceptance criteria (e.g., "pressure accuracy within +/- X mmHg") are not detailed, the implication is that the device met these criteria for each test.
| Acceptance Criterion (Test Description) | Reported Device Performance |
|---|---|
| Alarm Testing | Met (Implied by submission) |
| LED/LCD Testing | Met (Implied by submission) |
| Cycle Time Testing | Met (Implied by submission) |
| Pressure Accuracy Testing | Met (Implied by submission) |
| Therapy Time Testing | Met (Implied by submission) |
| Therapeutic Performance Testing | Met (Implied by submission) |
| Garment Integrity Testing | Met (Implied by submission) |
| Pull Testing | Met (Implied by submission) |
| Transportation Testing | Met (Implied by submission) |
| Garment Printing Testing | Met (Implied by submission) |
| Button Life Testing | Met (Implied by submission) |
| Noise Testing | Met (Implied by submission) |
| Visual Appearance Testing | Met (Implied by submission) |
Notes:
- The phrase "Testing was performed and to ensure that the system meets its specifications" and the conclusion "AIROS Medical, Inc., believes that the AIROS 6 is substantially equivalent to the predicate device" implicitly state that the device met the acceptance criteria for these tests. The specific quantitative results are not in this summary but would be in the more detailed submission.
- Additionally, compliance with the listed consensus standards (IEC 60601-1, ISO 10993, IEC 61000, ANSI/AAMI ES60601-1, CAN/CSA-C22.2 No. 60601-1) also represents a set of acceptance criteria regarding safety and essential performance.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
- This information is not provided in the 510(k) summary. These details would typically be found in the full test reports submitted to the FDA, not in the public summary. For functional performance tests, a "sample size" often refers to the number of devices or components tested. Data provenance (country, retrospective/prospective) is not relevant for this type of mechanical device testing.
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):
- This concept is not applicable to the testing described for this device. Ground truth in the context of diagnostic performance (e.g., image interpretation) is not relevant here. The "ground truth" for these functional tests would be the established engineering specifications and physical measurements.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- This concept is not applicable to the testing described for this device. Adjudication methods are used in diagnostic studies to resolve reader discrepancies.
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:
- No. This type of study is for evaluating AI-assisted diagnostic performance, which is not relevant to this pneumatic compression device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- No. This device is a physical medical device, not an algorithm, so a "standalone" algorithmic performance evaluation is not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- This concept is not applicable in the context of this device's functional and safety testing. The "ground truth" for the performance characteristics (e.g., pressure output, cycle time) is based on engineering specifications and direct physical measurement calibrated against known standards.
8. The sample size for the training set:
- Not applicable. This device does not involve machine learning or a "training set."
9. How the ground truth for the training set was established:
- Not applicable. As there is no training set, there is no ground truth to establish for it in this context.
§ 870.5800 Compressible limb sleeve.
(a)
Identification. A compressible limb sleeve is a device that is used to prevent pooling of blood in a limb by inflating periodically a sleeve around the limb.(b)
Classification. Class II (performance standards).