K Number
K090812
Date Cleared
2009-07-30

(127 days)

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

TheraForm™ Standard / Sheet is intended for the management of wounds including:

  • Partial and full-thickness wounds .
  • Pressure ulcers
  • Venous ulcers
  • Diabetic ulcers
  • Chronic ulcers
  • Tunneled / undermined wounds
  • Surgical wounds (donor sites / grafts, post-moh's surgery, post-laser surgery, podiatric, wound dehiscence)
  • Trauma wounds (abrasions, lacerations, second-degree burns, and skin tears)
  • Draining wounds
Device Description

TheraForm™ Standard / Sheet Absorbable Collagen Membrane is a sterile, pliable porous wound dressing made of highly purified collagen derived from porcine. TheraForm™ Standard / Sheet is completely absorbable and highly biocompatible.

AI/ML Overview

This document, K090812, is a 510(k) premarket notification for a wound dressing called TheraForm™ Standard / Sheet.

Here's an analysis of the provided information concerning acceptance criteria and studies:

Acceptance Criteria and Reported Device Performance

Acceptance CriteriaReported Device Performance
Biocompatibility"TheraForm™ Standard / Sheet was subjected to a panel of tests to assess biocompatibility and it passed the requirements of all tests."

Study Information

This 510(k) summary document describes a biocompatibility study. It is not a study that directly proves device performance in terms of clinical effectiveness or comparison to a predicate device in a comparative effectiveness study in the way typically seen for diagnostic or AI-driven devices. Instead, it focuses on ensuring the safety of the materials.

  1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
    The document does not specify the sample size used for the "panel of tests" for biocompatibility. There is no information regarding the provenance of any data used for these tests (e.g., country of origin, retrospective or prospective).

  2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):
    Not applicable. For biocompatibility testing, ground truth is established through standardized laboratory assays and regulatory guidelines rather than expert consensus on clinical outcomes.

  3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
    Not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies when interpreting ambiguous results or establishing a "ground truth" through expert consensus for diagnostic or prognostic devices. This is not relevant for biocompatibility testing.

  4. 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:
    No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed, nor would it be relevant for this type of device (a wound dressing). This device is not an AI-driven or diagnostic device that requires human interpretation. The 510(k) focuses on substantial equivalence to a predicate device based primarily on design, materials, indications, and manufacturing, along with biocompatibility testing.

  5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
    No, a standalone algorithm performance study was not done, as this is not an AI-driven device.

  6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
    For the biocompatibility tests, the "ground truth" would be established by the compliance of the test results with international standards and regulatory guidelines for biocompatibility (e.g., ISO 10993 series). This is not expert consensus, pathology, or outcomes data in the clinical sense, but rather a determination based on chemical and biological assay results.

  7. The sample size for the training set:
    Not applicable. There is no "training set" as this is not a machine learning or AI-driven device.

  8. How the ground truth for the training set was established:
    Not applicable. There is no training set for this device.

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