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K Number
K231152
Device Name
Collagen Wound Dressing
Manufacturer
Winner Medical Co., Ltd.
Date Cleared
2023-10-12

(171 days)

Product Code
KGN
Regulation Number
N/A
Type
Traditional
Panel
SU
Reference & Predicate Devices
K060456
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Collagen Wound Dressing is indicated for the management of exuding wounds including: Full thickness and partial thickness wounds Pressure and venous ulcers Ulcers caused by mixed vascular etiologies Diabetic ulcers Partial thickness burns Donor sites and other bleeding surface wounds Abrasions Traumatic wound healing by secondary intention Dehisced surgical incisions

Device Description

Collagen Wound Dressing is an advanced wound care device composed of pure freezedried cross-linked bovine collagen. It is a sterile, absorbent, white, porous, topical wound dressing. As a primary wound dressing, it can be cut to any size or be used in multi-layers to fit wound. It can also be used in combination with either occlusive or semi-occlusive secondary dressing. The product is biodegradable.

AI/ML Overview

The provided text does not describe a study that proves a device meets acceptance criteria for an AI/ML medical device. Instead, it is an FDA 510(k) clearance letter for a Collagen Wound Dressing, which is a physical medical device, not an AI/ML software.

The document discusses non-clinical data, performance tests (e.g., appearance, weight, absorption, pH, heavy metals, sterility, SEM, DSC, FTIR), biocompatibility, sterilization, and shelf-life studies. It explicitly states, "No clinical study is included in this submission."

Therefore, I cannot extract the information for an AI/ML medical device as requested, because the provided text is about a physical wound dressing and does not contain any details related to:

  • Acceptance criteria for an AI/ML algorithm's performance (e.g., sensitivity, specificity, AUC)
  • Sample sizes for test sets used in AI/ML validation
  • Number/qualifications of experts for ground truth establishmen
  • Adjudication methods
  • MRMC studies
  • Standalone algorithm performance
  • Type of ground truth (e.g., pathology, outcomes data) in the context of an AI/ML model
  • Training set details for an AI/ML model

The request's template is specifically designed for AI/ML device evaluations, which is not applicable to the content of this FDA clearance letter.

N/A