(381 days)
BIOPATCH* Antimicrobial Dressing containing Chlorhexidine gluconate is intended for use as a hydrophilic wound dressing that is used to absorb exudate and to cover a wound caused by the use of vascular and non-vascular percutaneous medical devices such as: Vascular Devices IV Catheters Central Venous Lines Arterial Catheters Dialysis Catheters Peripherally Inserted Coronary Catheters Mid-Line Catheters Non-vascular percutaneous devices Drains Chest Tubes Externally Placed Orthopedic Pins Epidural Catheters It is also intended to reduce local infections, catheter related blood stream infections (CRBSI), and skin colonization of microorganisms commonly related to CRBSI, in patients with central venous or arterial catheters.
BIOPATCH* Antimicrobial Dressing is an absorptive foam with chlorhexidine gluconate, a well-known antiseptic agent with broad spectrum antimicrobial and antifungal activity.
The BIOPATCH* Antimicrobial Dressing is an absorptive foam with chlorhexidine gluconate, intended as a hydrophilic wound dressing to absorb exudate and cover wounds caused by vascular and non-vascular percutaneous medical devices. It is also intended to reduce local infections, catheter-related bloodstream infections (CRBSI), and skin colonization of microorganisms commonly related to CRBSI in patients with central venous or arterial catheters.
Here's the breakdown of the acceptance criteria and the study that proves the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance:
Acceptance Criteria (Intended Effect) | Reported Device Performance |
---|---|
Reduction in the incidence of local infection | Resulted in a statistically significant 44% reduction in the incidence of local infection (p ≤ 0.0001). |
Reduction in the incidence of catheter-related blood stream infections (CRBSI) | Resulted in a statistically significant 60% reduction in the incidence of catheter-related blood stream infections (p = 0.026). |
Reduction in skin colonization of microorganisms commonly related to CRBSI | Resulted in statistically significant reduction in skin colonization of microorganisms commonly associated with CRBSI (p ≤ 0.05). |
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: The clinical trial consisted of 687 subjects with 1699 central venous or arterial catheter insertion sites.
- Data Provenance: The study was a prospective controlled, randomized clinical trial conducted at two centers. The country of origin is not explicitly stated in the provided text.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
- This information is not provided in the summary. The study relied on clinical outcomes (incidence of infection, CRBSI, and skin colonization) rather than expert review of images or specific data points requiring a separate ground truth established by experts.
4. Adjudication Method for the Test Set:
- This information is not provided in the summary. The study design (controlled, randomized clinical trial) implies direct measurement of clinical outcomes.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No, an MRMC comparative effectiveness study was not done. This type of study is typically used for diagnostic devices involving human interpretation of data (e.g., radiologists reading images) to assess the impact of AI assistance on reader performance. The BIOPATCH study focuses on the direct clinical effectiveness of a physical dressing.
6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study:
- No. The BIOPATCH is a physical medical device, not an algorithm. The study directly evaluated the device's performance in a clinical setting with human patients.
7. Type of Ground Truth Used:
- The ground truth used was clinical outcomes data. This includes:
- Incidence of local infection
- Incidence of catheter-related bloodstream infections (CRBSI)
- Measurement of skin colonization of microorganisms
8. Sample Size for the Training Set:
- This information is not applicable as the BIOPATCH Antimicrobial Dressing is a physical device, not an AI/ML algorithm that requires a training set.
9. How the Ground Truth for the Training Set Was Established:
- This information is not applicable for the same reason as above.
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