Search Results

The intended use for the Aurora MD-30 CO2 Laser is for the vaporization, excision, ablation, or photocaogulation of soft tissue in the surgical specialties of ENT, Gynecology, Laparoscopic Surgery including GYN Laparoscopy, Aesthetic Surgery, Dental and Oral Surgery, Neurosurgery, Orthopedics, General Surgery and Podiatry.

The Aurora MD-30 CO2 Laser is a Carbon Dioxide (CO2) surgical laser system that can deliver up to 30 watts of laser power in the 11.2-micron range in the infrared. The laser can be used in a variety of surgical specialties. The power can be selectively delivered either through an articulated arm or through infrared fibers using an integrated electromechanically controlled optical switch that directs the beam either vertically into the articulated arm or at an angle into the fiber. The laser can operate in either continuous wave, pulsed or super pulse modes. It can deliver laser power down to 1/2 a watt and can operate down to millisecond pulse widths. The system also has a visible aiming beam to indicate where the CO2 laser beam will be delivered.

The laser system has a 12inch highly visible color touchscreen to control the laser. It consists of a small self-contained floor standing, easily moveable console which contains the laser and all associated electronics and delivery systems.

The Aurora MD-30 CO2 Laser has an integrated dual switch adapter that is operated by an electrical linear motor and controlled by the console. The switch allows the user to redirect the laser beam from the articulated arm to the fiber as desired.

The provided text is a 510(k) summary for a medical device (Aurora MD-30 CO2 Laser). It describes the device, its intended use, and compares its technological characteristics to predicate devices. Crucially, it states that "Clinical testing was not required to establish substantial equivalence" and therefore, the document does not contain any information about a study that proves the device meets acceptance criteria related to accuracy or performance in a clinical setting.

The "Non-Clinical Testing Summary" table lists tests against various IEC standards (e.g., IEC 60601-1 for basic safety and essential performance, IEC 60601-2-22 for laser equipment, IEC 60601-1-2 for electromagnetic compatibility). These are engineering and safety tests, not clinical performance tests.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving clinical performance, as the document explicitly states such a study was "NA - Clinical testing was not required to establish substantial equivalence."

To answer your request, if this were an AI/ML device or a device where clinical performance was required for substantial equivalence, the document would contain sections detailing:

1. A table of acceptance criteria and the reported device performance: This would list target metrics (e.g., sensitivity, specificity, accuracy, concordance with experts) and the achieved values from a clinical study.
2. Sample size used for the test set and the data provenance: Details on how many cases were in the test set, where the data came from (e.g., specific hospitals, a registry), and if it was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Information on how many clinicians reviewed the cases, and their credentials.
4. Adjudication method: How disagreements amongst experts were resolved (e.g., primary reads, consensus review, super-reviewer).
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Description of the study design, and effect sizes (e.g., improvement in reader performance with AI assistance).
6. If a standalone performance (algorithm only) was done: The performance metrics (sensitivity, specificity, AUROC, etc.) of the algorithm on its own.
7. The type of ground truth used: Whether it was expert consensus, pathology reports, follow-up data, etc.
8. The sample size for the training set: The number of cases used to train the AI model.
9. How the ground truth for the training set was established: Similar to the test set, but for the data used to teach the model.

Since the provided document pertains to a surgical laser system where substantial equivalence was demonstrated through comparison to predicate devices and engineering/safety non-clinical testing, it does not include the type of clinical performance data you are asking for.

Ask a specific question about this device