Search Results

The DV-XXX aspirator provides a portable, battery-powered medical vacuum source. The DV-XXX can also be powered from a standard wall outlet with the use of an AC power adapter. It is intended for use in the home care or hospital environment.

The DV-XXX is a portable AC/DC high vacuum / high flow suction pump. The DV-XXX can be powered from a standard wall outlet or from a rechargeable battery pack. The DV-XXX creates a negative pressure (vacuum) that draws fluids through tubing and into a collection container where the fluids are trapped for proper disposal. The device is comprised of a maintenance-free pump unit, an AC power adapter with power cord, an on/off switch, a pressure relief valve and pressure adjustment knob, a pressure gauge, an inline filter, intermediate tubing, and a rechargeable battery pack. Optional accessories which may be included with the unit include a collection canister and suction tubing.

The DV-XXX produces a flow rate of up to 20 liters per minute, and has a maximum vacuum pressure of 620 mmHg. Housed in ABS plastic, the DV-XXX has an IP22 ingress protection rating; and, as a Class II (double-insulated) electrical appliance, the unit affords Type BF applied part protection against electric shock.

The DV-XXX must only be used on the order of a physician.

This document is a 510(k) Premarket Notification from the FDA for a medical device called the "Cliq Aspirator DV-XXX (model family)". As such, it is focused on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving the detailed performance metrics of a novel AI/ML-driven device.

Therefore, the information typically requested for acceptance criteria and studies proving the device meets those criteria, particularly for AI/ML devices (e.g., sample size for test/training sets, expert ground truth, adjudication methods, MRMC studies, standalone performance, effect sizes), is largely not present in this document.

This document describes a powered suction pump, a traditional medical device, not an AI/ML diagnostic or therapeutic device. The "performance" discussed refers to physical specifications and compliance with electrical and safety standards, not diagnostic accuracy or effectiveness in an AI context.

Here's how the provided information relates to your request, with an emphasis on what is not applicable or not found in this type of submission:

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

The document doesn't provide specific "acceptance criteria" in the sense of a numerical threshold for clinical performance (like sensitivity/specificity for a diagnostic AI). Instead, it relies on demonstrating compliance with recognized consensus standards and substantial equivalence to a predicate device.

The "performance" metrics for this device are largely physical and electrical characteristics.

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

• Not applicable / Not present. This is for a physical device, and testing involves engineering and safety compliance (e.g., electrical, mechanical, EMC), not a "test set" of clinical data to evaluate an algorithm's performance. The documentation mentions "Non-clinical performance and safety tests" were conducted and "met all predefined criteria," but gives no details on sample size of devices tested for these engineering aspects. Data provenance (country of origin, retrospective/prospective) is irrelevant for this type of device submission.

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

• Not applicable / Not present. Ground truth in the context of AI/machine learning (e.g., for image interpretation) is not relevant for this device. Ground truth for the device's function is established by its physical specifications and meeting engineering standards, measured by calibrated equipment and engineering tests.

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

• Not applicable / Not present. This concept applies to expert consensus on clinical data labels, not to the performance testing of a powered suction pump.

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 present. This document describes a medical device (suction pump), not an AI-assisted diagnostic or therapeutic tool. Therefore, MRMC studies are not relevant.

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

• Not applicable / Not present. There is no algorithm being evaluated in this submission.

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

• Not applicable. The "ground truth" for this device's performance is objective measurements against engineering specifications and international consensus standards (e.g., a pressure gauge measures actual vacuum pressure, electrical tests confirm safety compliance).

8. The sample size for the training set

• Not applicable / Not present. This device does not involve machine learning; therefore, there is no training set.

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

• Not applicable / Not present. As there is no training set, this question is not relevant.

In summary: This FDA 510(k) submission for the "Cliq Aspirator DV-XXX" is typical for a traditional medical device (a powered suction pump). It focuses on demonstrating substantial equivalence to an existing predicate device and compliance with recognized safety and performance standards. The types of acceptance criteria and study designs you've listed (related to AI/ML performance, ground truth establishment, reader studies) are not pertinent to this specific device or its regulatory pathway.

Ask a specific question about this device