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510(k) Data Aggregation
(449 days)
The SecurAcath device is indicated for catheter securement to the access site by means of subcutaneous anchors in:
a) Short or long-term securement of percutaneous indwelling catheters for intravenous use
b) Short or long-term securement of percutaneous indwelling catheters for abscess/general drainage
The SecurAcath device is a standalone subcutaneous anchoring securement system used to secure the catheter to the access site. The securement is achieved by means of a blunt nitinol anchor deployed into the subcutaneous space at the catheter access site, and the clamping of the catheter shaft between the Base Assembly and Cover of the device.
The provided text is a 510(k) Summary for the SecurAcath device. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study report with specific acceptance criteria and performance metrics for a novel AI/ML device.
Therefore, I cannot fully answer your request as it pertains to AI/ML device evaluation criteria. The document describes a medical device for catheter securement and its equivalence to a predicate, not an AI/ML system.
However, I can extract the general type of performance data mentioned and explain why it doesn't fit the AI/ML framework you've outlined:
1. Table of Acceptance Criteria and Reported Device Performance:
The document lists "Performance tests" that were conducted, but it does not provide specific acceptance criteria or quantitative performance metrics for these tests. Instead, it makes a general statement: "Test results demonstrate that the device functions as intended."
| Acceptance Criteria (Not Explicitly Stated for this Device as per AI/ML Framework) | Reported Device Performance (General Statement in Document) |
|---|---|
| Not specified for AI/ML performance | Meets product specifications and is able to secure catheters to access sites. |
| Specific quantitative thresholds for various metrics (e.g., sensitivity, specificity, accuracy, F1-score) based on clinical or technical relevance. | Functions as intended. |
2. Sample Size for Test Set and Data Provenance: Not applicable as this is not an AI/ML study. The document refers to "Performance tests" but does not detail the sample sizes for these tests or the provenance of any data.
3. Number of Experts and Qualifications for Ground Truth: Not applicable as this is not an AI/ML study. The device's performance evaluation would involve engineering and clinical testing, not expert adjudication of AI outputs.
4. Adjudication Method: Not applicable.
5. Multi-Reader, Multi-Case (MRMC) Comparative Effectiveness Study: Not applicable.
6. Standalone (Algorithm Only) Performance: Not applicable as this is a physical medical device, not an algorithm.
7. Type of Ground Truth Used: Not applicable in the AI/ML sense. The "ground truth" for this device would be established through engineering specifications, biomechanical testing outcomes, and clinical observations of catheter securement effectiveness, rather than expert interpretation of data.
8. Sample Size for Training Set: Not applicable as there is no AI/ML training involved for this device.
9. How Ground Truth for Training Set Was Established: Not applicable.
In summary, the provided FDA 510(k) summary is for a physical medical device (catheter securement device) and therefore does not contain the information requested regarding acceptance criteria and studies for an AI/ML device. The document focuses on demonstrating substantial equivalence to a predicate device based on intended use, technological characteristics, and general performance testing (e.g., dimensional verification, functional tests, securement reliability, human factor design validation).
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