(191 days)
Prescription Use: Under the supervision of a healthcare professional. Extra Silver Gelling Fiber Dressing may be used for the management of moderate to heavily exuding chronic and acute wounds as follow: Partial thickness (second degree) burns; Pressure ulcers (partial and full thickness); Leg ulcers (venous stasis ulcers, arterial ulcers and leg ulcers of mixed etiology); Diabetic foot ulcers; Surgical wounds that heal by primary intent such as dermatological and surgical incisions; Surgical wounds left to heal by secondary intention such as dehisced surgical incisions and donor sites; Traumatic wounds. OTC Use: Extra Silver Gelling Fiber Dressing may be used for the management of: Minor Abrasions, Minor Lacerations, Minor cuts, Minor scalds and burns.
Extra Silver Gelling Fiber Dressing is a soft, sterile, non-woven pad or ribbon dressing composed of sodium carboxymethylcellulose (CMC) fibers, strengthening fibers and 1.2% ionic silver. This dressing absorbs wound fluid and creates a soft gel that conforms to the wound surface, maintains a moist environment. A moist wound environment supports the body's healing process. The silver antimicrobial may help reduce bacterial colonization within the dressing for up to 7 days. The dressings are supplied sterile in a range of sizes, ranging in area from 25cm2 to 600cm². All dressings have the exactly the same material, chemical, and physical properties and are different only in size. All dressings are sterilized and sold after sterilization by gamma radiation using conditions validated following ISO 11137-2:2013.
This document is an FDA 510(k) summary for a medical device called "Extra Silver Gelling Fiber Dressing". It describes the device and compares it to a previously cleared predicate device.
Here's an analysis of the acceptance criteria and study information provided, structured according to your request:
1. Table of Acceptance Criteria and Reported Device Performance
The FDA 510(k) summary for this type of device (wound dressing) typically relies on demonstrating substantial equivalence to a predicate device rather than strict quantitative performance acceptance criteria for clinical efficacy in the same way a diagnostic AI device might. However, it does specify acceptance criteria for non-clinical tests.
| Acceptance Criteria (Non-Clinical Standard) | Reported Device Performance (Summary) |
|---|---|
| ISO 10993-5:2009 (Cytotoxicity) | Complies with standard |
| ISO 10993-10:2010 (Irritation & Sensitization) | Complies with standard |
| ISO 10993-11:2017 (Systemic Toxicity) | Complies with standard |
| ASTM F88/F88M-15 (Seal Strength) | Complies with standard |
| ASTM F1929-15 (Detecting Seal Leaks) | Complies with standard |
| USP (Bacterial Endotoxins) | Complies with standard |
| AATCC 100-2012 (Antibacterial Finishes) | Demonstrates > 4 log-reduction against 4 gram-positive bacteria and 4 gram-negative bacteria within 7 days. |
| Biocompatibility (ISO 10993-1) | Test results meet requirements for breached or compromised surfaces with prolonged contact (>24h to 30d). |
| Absorbency Performance | Equivalent to the predicate device. |
| Tensile Strength Performance | Superior to the predicate device due to strengthening fibers. |
2. Sample Size Used for the Test Set and Data Provenance
This document describes non-clinical laboratory testing and equivalence comparisons. It does not involve a "test set" in the context of clinical data for an AI algorithm.
- Sample Size for Test Set: Not applicable in the context of clinical data for AI; non-clinical tests typically use replicate samples of the device itself.
- Data Provenance: Not applicable for clinical data; non-clinical lab tests are performed according to recognized standards.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
Not applicable. This device is a wound dressing, not an AI diagnostic system requiring expert-established ground truth for a clinical test set.
4. Adjudication Method for the Test Set
Not applicable. This document pertains to non-clinical testing and substantial equivalence for a physical medical device, not a diagnostic AI system with an adjudication process for a test set.
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. This is not an AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
For the non-clinical tests, the "ground truth" is defined by the specific parameters and methods outlined in the referenced ISO, ASTM, USP, and AATCC standards. For example, for cytotoxicity, the "ground truth" is the observation of cell viability against negative/positive controls as per ISO 10993-5. For antibacterial effectiveness, it's the measured log-reduction of bacterial colonies as per AATCC 100-2012.
8. The sample size for the training set
Not applicable. This is not an AI algorithm requiring a training set.
9. How the ground truth for the training set was established
Not applicable. This is not an AI algorithm.
N/A