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The Procedure mask/Surgical mask/Face mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids, and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single-use, disposable device, provided non-sterile.

The subject device is a three-layer, single-use, flat-pleated mask. The inner and outer layers of the mask are made of polypropylene nonwoven, and the middle layer is made of polypropylene melt-blown nonwoven. The subject device is available in one type, ear loop. The ear loops are made of polyester and spandex. The ear loops model is held in place over the users' mouth and nose by two elastic ear loops welded to the mask. The nose clip is made of Iron and polypropylene. Users can adjust the nose clip according to the shape of the bridge of the nose, and fix the mask on the bridge of the nose to prevent the mask from falling off. The ear loop masks are available in two size, 17.5 × 9.5 cm and 14.5 × 9.5 cm. And the colors for the ear loop mask are yellow, blue and white. The ear loop masks are available in level 1, level 2 and level 3 masks based on ASTM F2100-23. This is a single-use, disposable device, provided non-sterile.

The provided document is a 510(k) Clearance Letter for a medical device: Procedure mask/Surgical mask/Face mask. This type of document, specifically the "Summary of Non-Clinical Test" section, details the performance characteristics required for the device to meet regulatory standards.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Important Note: The provided document is for a medical mask, not an AI-powered diagnostic device. Therefore, many of the typical questions regarding AI/software performance studies (e.g., sample size for test set, number of experts, adjudication, MRMC studies, training set details, ground truth for AI) are not applicable to this submission. The "study" here refers to physical and biological performance testing of the mask material itself.

Acceptance Criteria and Reported Device Performance

The acceptance criteria are based on established standards like ASTM F2100-23, ASTM F1862/F1862M-24, ASTM F2101-23, EN 14683:2019+AC:2019, 16 CFR Part 1610, and ISO 10993 series. The table below summarizes these criteria and the reported performance:

Table 1: Acceptance Criteria and Reported Device Performance

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For Prescription Use: Under the supervision of a healthcare professional, Antibacterial Gel Wound Dressing is indicated for the management of first and superficial second degree burns, wounds such as stasis ulcers, pressure ulcers, diabetic ulcers, lacerations, abrasions, skin tears, surgical incision sites, device insertion site wounds, graft sites, and donor sites.

For Over-the-Counter Use: Antibacterial Gel Wound Dressing is intended for the management of minor abrasions, cuts, lacerations and scalds.

The subject device, Antibacterial Gel Wound Dressing, is a non-sterile, repeated-use moist amorphous gel. The hydrogel consists of amorphous cellulose-based gel complex, silver ions and Benzalkonium Chloride (BZK). The silver ions and Benzalkonium Chloride (BZK) act as a preservative to inhibit the growth of microorganisms in the gel during shelf storage. The hydroxyethyl cellulose is used as thickener to modify the viscosity of the wound gel, resulting in a moist amorphous gel with the function of moisture donation and moisture absorption. The combination of allantoin and propylene glycol are used as moisturizer to prevent gel water release. The gel possesses both moisture donating and moisture sequestering action depending on the moisture level in the wound. The hydrogel helps to maintain a moist wound environment. The hydrogel is supplied in collapsible blind ended heat sealed HDPE tubes fitted with screw caps.

The provided text describes a 510(k) premarket notification for an "Antibacterial Gel Wound Dressing," asserting its substantial equivalence to a predicate device. However, this document does not describe a study involving the use of artificial intelligence (AI) or an algorithm-only performance assessment.

Therefore, I cannot provide information on acceptance criteria for an AI device, sample sizes for test sets in an AI study, expert ground truth establishment for AI, adjudication methods for AI, MRMC comparative effectiveness studies with AI, or standalone AI performance.

The document focuses on the safety and effectiveness of a medical device (wound dressing) through physical performance testing, biocompatibility studies, and an animal study, in comparison to a predicate device.

If you have a document describing an AI medical device, I would be happy to analyze it according to your requested criteria.

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Prescription Use:
Skin and Wound Cleanser for prescription use is intended for use under the supervision of healthcare professionals for cleansing, moistening, debriding, and removal of foreign material including microorganisms and debris from wounds, including acute and chronic dermal lesions, such as Stage I-IV pressure ulcers, leg ulcers, diabetic foot ulcers, post-surgical wounds, first and second degree burns, grafted and donor sites. It is also intended for moistening absorbent wound dressings and cleaning minor cuts, minor burns, superficial abrasions and minor irritations of the skin.

OTC Use:
Skin and Wound Cleanser for over-the-counter use is intended for cleansing wounds and moistening absorbent wound dressings for the management of minor cuts, minor abrasions, minor lacerations and minor burns.

The proposed devices, Skin and Wound Cleanser, is a clear, colorless solution that is intended for wound management including cleansing, irrigating, and debriding dermal wounds in addition to moistening and lubricating absorbent wound dressings (e.g. gauze).The solution of Skin and Wound Cleanser contains purified water, PHMB, undecylenamidopropyl betaine, and trace ingredients (allantoin, citric acid). During the application of product, fluid moving across the wound aids in the removal of foreign objects such as dirt and debris. Skin and Wound Cleanser solution contains PHMB, a known antimicrobial preservative, which is shown to inhibit the growth of microorganisms such as Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Candida albicans, Aspergillus niger, Methicillinresistant Staphylococcus aureus (MRSA), Vancomycin-resistant Enterocccus faecalis (VRE) to maintain quality of the product during storage of the wound cleansing solution.

The provided document is an FDA 510(k) summary for a medical device called "Skin and Wound Cleanser." It outlines the regulatory submission, identity of the device, identification of predicate devices, device description, intended use, and non-clinical test conclusions.

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

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes non-clinical tests performed to ensure the device meets design specifications and is substantially equivalent to predicate devices. The acceptance criteria are implicitly tied to compliance with the standards listed and the successful demonstration of the specified performance.

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: The document does not specify the exact sample sizes (e.g., number of replicates, number of animals, etc.) used for each non-clinical test. It only states that "Non clinical tests were conducted to verify that the proposed device met all design specifications."
• Data Provenance: Not explicitly stated in terms of country of origin but refers to established international (ISO) and US (USP) standards. The tests are presented as being conducted by the applicant, Winner Medical Co., Ltd. The study appears to be a prospective non-clinical study specifically conducted for this submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

• This information is not applicable (N/A) as the tests conducted are non-clinical, laboratory-based analyses (biological evaluation and antimicrobial effectiveness), rather than studies requiring human expert interpretation or a "ground truth" derived from expert consensus. The "ground truth", in this context, is the quantitative or qualitative outcome specified by the respective ISO or USP standard, assessed by laboratory personnel.

4. Adjudication Method for the Test Set:

• This information is N/A for the same reasons as point 3. The non-clinical tests are evaluated against predefined criteria in the standards, not through adjudication by multiple experts.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical study is included in this submission." This type of study is typically for image-based diagnostic or prognostic devices involving human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:

• This question is N/A as the device is a "Skin and Wound Cleanser," which is a physical solution, not a software algorithm or an AI device.

7. The type of ground truth used:

• The "ground truth" for the non-clinical tests is derived from established scientific standards and methodologies. For example:
  • Biocompatibility: The "ground truth" is determined by observing cellular responses (cytotoxicity), tissue reactions (local effects, irritation), and systemic effects in laboratory models, as per the guidelines and endpoints defined in the ISO 10993 series.
  • Antimicrobial Effectiveness: The "ground truth" is measured by the reduction in microbial population over time, in comparison to specified log reductions or absence of growth criteria as defined by USP for various microorganisms.

8. The Sample Size for the Training Set:

• This question is N/A as the device is a physical wound cleanser and does not involve a "training set" in the context of machine learning or AI. The non-clinical tests are performed on the device itself.

9. How the Ground Truth for the Training Set was Established:

• This question is N/A for the same reasons as point 8.

In summary, the K231564 submission relies on non-clinical, laboratory-based testing to demonstrate conformance to recognized standards for biocompatibility and antimicrobial effectiveness, establishing substantial equivalence to predicate devices, rather than clinical studies or AI algorithm performance evaluations.

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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

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.

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.

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Antibacterial bandage is to be applied topically to the skin for management of minor cuts, minor scrapes and minor burns.

The subject device. Antibacterial bandage, is to be applied topically to the skin for the management of minor cuts, minor scrapes and minor burns. The subject devices are available sterile in three models. All of devices contain three layers: (1) adhesive backing layer (fabric or plastic); (2) exactly same antibacterial non-stick absorbent pad layer (composed of Polyester fiber, viscose fiber, PE mesh, Benzalkonium chloride); (3) release liner. Each model is available in different sizes with identical materials, chemicals and physical properties, therefore, size of the device will not affect the function and performance of products. All models of subject device, Antibacterial bandage, are for single use only and sterilized by Ethylene Oxide using conditions validated following ISO 11135:2014.

The provided text describes a 510(k) premarket notification for an "Antibacterial Bandage" (K221311) and compares it to a predicate device (K113583) and a reference device (K200821). The submission aims to demonstrate substantial equivalence, not to prove that the device meets specific acceptance criteria through a clinical study. Therefore, a direct answer to the request regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of device performance metrics often expected for AI or diagnostic devices (e.g., accuracy, sensitivity, specificity, MRMC studies) cannot be fully provided from the given document.

However, I can extract the non-clinical test conclusions which serve as the basis for demonstrating substantial equivalence based on performance and biocompatibility. These tests implicitly define "acceptance criteria" through their methodologies and the successful comparison to the predicate device.

Here's a breakdown of the information that can be extracted, framed as closely as possible to the request:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly list numerical "acceptance criteria" with corresponding "reported device performance" in a typical clinical study outcome format like sensitivity or specificity. Instead, the "acceptance criteria" are implied by the successful completion of specified performance and biocompatibility tests, demonstrating equivalence to the predicate device or compliance with standards.

For Antibacterial Effectiveness, a specific quantitative measure is mentioned for both the subject and predicate devices:

For other performance tests and biocompatibility, the reported "performance" is that the device "met the requirement" or "complied with the corresponding standards," or "was not different" from the control.

Here's how the other "acceptance criteria" and "reported performance" can be inferred from the non-clinical tests:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Non-Clinical Performance Tests & Biocompatibility Tests: The document does not specify sample sizes (e.g., number of bandages tested for peel strength) or the data provenance for these lab-based tests. These are typically performed in a controlled laboratory setting.
• Animal Study: A "porcine wound healing study" was carried out, indicating an animal model. The sample size for this study is not specified, nor is the country of origin of the animal data. It would be considered prospective for the animal subjects involved.

3. 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)

This question is not applicable to the provided document. The device is an antibacterial bandage, not an AI or diagnostic device that requires expert review for ground truth establishment for a diagnostic test set. The ground truth for the non-clinical and animal studies is based on objective laboratory measurements and biological observations, not expert consensus on interpretations of images or signals.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This question is not applicable. Adjudication methods like 2+1 are typically used for establishing ground truth in clinical studies involving human interpretation (e.g., radiologists reviewing images). The studies described here are non-clinical and animal studies.

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

No MRMC study was done. This type of study is relevant for AI-powered diagnostic devices, which is not the case for an antibacterial bandage.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This question is not applicable. The device is not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Non-Clinical Performance Tests: Ground truth is established by the specified test methods and standards (e.g., EN 13726-1:2002, ASTM D3330/D3330M). The "truth" is the measured physical or chemical property of the bandage.
• Biocompatibility Tests: Ground truth is defined by the biological response observed according to the specific ISO standards (e.g., presence/absence of cytotoxicity, sensitization).
• Animal Study: Ground truth is based on observed wound healing performance characteristics and local tolerance in the porcine model.

8. The sample size for the training set

This question is not applicable. The device (antibacterial bandage) does not involve machine learning or AI, and therefore does not have a "training set" in that context.

9. How the ground truth for the training set was established

This question is not applicable, as there is no training set for this device.

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The Procedure mask/Surgical mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids, and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single-use, disposable device, provided non-sterile.

The proposed device is a three-layer, single-use, flat- pleated mask. The inner and outer layers of the mask are made of polypropylene nonwoven, and the middle layer is made of polypropylene melt-blown nonwoven. The proposed devices are available in two types, ear loop and tie-on. The ear loops are made of polyester and spandex, and the ties are made of polypropylene nonwoven. The ear loops/ties are used to secure the mask over the users' mouth and face. The nose clip is made of Iron and polypropylene. Users can adjust the nose piece according to the shape of the nose, and fix the mask on the bridge of the nose to prevent the mask from falling off. The ear loop masks are available in two size, 17.5×9.5 cm and 14.5×9 cm; the tie-on mask is available in one size, 17.5×9.5 cm. And the colors for the ear loop mask are blue and black; the color for the tie-on mask is blue. Both the ear loop and tie-on masks are available in level 3 masks based on ASTM F2100-19 due to the difference in gram weight of the mask body. The proposed device is provided in non-sterile.

This document is a 510(k) Summary for a medical device (Procedure mask/Surgical mask/Face mask). The information provided demonstrates that the device meets the acceptance criteria through non-clinical testing.

Here's the breakdown of your requested information:

1. A table of acceptance criteria and the reported device performance

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Prescription Use: PHMB Wound Dressings are indicated for use in the management of post-surgical incisions, pressure sores, venous stasis ulcers, diabetic ulcers, donor sites, abrasions, first and superficial second degree burns, dermatologic disorders, other wounds inflicted by trauma and, as a secondary dressing or cover dressing for packed wounds. OTC Use: For Over-the-Counter Use, PHMB Wound Dressing is used for minor abrasions, minor lacerations, minor cuts, minor scalds, and minor burns.

The proposed device PHMB Wound Dressing is a sterile wound dressing. It is used as a primary or secondary dressing to absorb wound exudates. Based on in vitro testing, the antibacterial agent PHMB in dressing helps to resist bacterial colonization within the dressing for up to 7 days. The proposed device is available in two configurations, The first one, PHMB Island Wound Dressing with acrylic adhesive, consists of a polyester viscose non-woven backing layer coated with acrylic adhesive as the top layer, a center soft absorbent pad which is made of non-woven fabric containing 0.2 % PHMB and it is laminated with the PET film, and a release liner covers on the top adhesive layer border part. The second one, PHMB Pad Wound Dressing, only consists of a soft absorbent pad containing 0.2 % PHMB and the non-woven absorbent pad is laminated with the PET film.

The provided text describes a 510(k) premarket notification for a PHMB Wound Dressing, indicating that it is a medical device. However, it does not detail acceptance criteria or a study proving that an "AI device" meets acceptance criteria. The document is primarily focused on demonstrating substantial equivalence to predicate devices for regulatory clearance.

Therefore, I cannot fulfill your request for information regarding an AI device's acceptance criteria and related study details based on the provided text. The document refers to a PHMB Wound Dressing, which is a physical medical device, not an AI or software-based device.

The "Non-Clinical Test Conclusion" section (page 5) does mention in vitro testing demonstrating antibacterial effectiveness, but this testing is for the wound dressing's physical properties and not related to AI performance.

If you have a document describing an AI device, please provide that for analysis.

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The Silicone Ag Foam Dressing (OTC) /Silicone Ag Foam Dressing with Border (OTC)/ Ag Foam Dressing Non-adhesive (OTC) and Ag Foam Dressing Adhesive (OTC) are indicated to cover and protect, absorb wound exudate, and maintain moisture balance of minor cuts, minor abrasions, minor lacerations, and minor burns.

It is a sterile, single-use dressing, the foam layer contain about 0.25-0.35mg/cm2 silver. The dressing absorbs wound exudate and releases silver ions within the dressing in the presence of wound fluid to help reduce bacterial colonization of the dressing. It also assists in maintaining a moist environment for optimal wound healing, and allows intact removal. The devices are available in four configurations: Ag Foam Dressing Non-adhesive, Ag Foam Dressing Adhesive, Silicone Ag Foam Dressing, and Silicone Ag Foam dressing with Border. The dressing has light yellow or light brown appearance and is available in the form of pad and in different sizes packaged in pouches. All dressings can absorb exudates, maintains a moist wound healing environment and has good antibacterial properties. It has been shown that antibacterial effectiveness within the dressing for up to 7 days, as demonstrated in vitro.

Here's a breakdown of the acceptance criteria and study information for the Ag Foam Dressing, based on the provided document:

This document pertains to the 510(k) clearance of Ag Foam Dressings and does not describe acceptance criteria for an AI/ML powered device. Instead, it details the substantial equivalence of the proposed medical device to existing predicate devices. The "acceptance criteria" in this context refer to the demonstration that the new device is as safe and effective as the predicate devices, primarily through non-clinical testing and comparison of characteristics.

Since this is a filing for a wound dressing and not an AI/ML device, many of the requested fields (like "AI vs without AI assistance," "standalone algorithm performance," "training set size," "ground truth for training set") are not applicable and will be marked as such.

Acceptance Criteria and Device Performance for Ag Foam Dressings

1. Table of Acceptance Criteria (Non-Clinical Standards) and Reported Device Performance

For medical devices like wound dressings, "acceptance criteria" are typically met by demonstrating compliance with established international standards for safety and performance (biocompatibility, sterility, absorbency, etc.) and by showing substantial equivalence to legally marketed predicate devices.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify exact sample sizes for each non-clinical test (e.g., number of units tested for absorbency, or number of biological replicates for cytotoxicity). It states that "Non clinical tests were conducted to verify that the proposed device met all design specifications."

• Sample Size: Not explicitly stated for individual tests. The phrasing implies sufficient samples were used to meet the requirements of the standards cited (e.g., ISO, ASTM, USP).
• Data Provenance: The tests were conducted internally by Winner Medical Co., Ltd. or by contract labs following international standards. The provenance is therefore laboratory-based, for the purpose of demonstrating device performance and safety. It is not patient or country-specific data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

Not applicable. This is a medical device submission for wound dressings, not an AI/ML device where expert ground truth for interpretation would be relevant. The "ground truth" here is compliance with established engineering and biocompatibility standards.

4. Adjudication Method for the Test Set

Not applicable. This is a medical device submission for wound dressings, not an AI/ML device requiring adjudication of diagnostic interpretations. The "adjudication" is compliance with documented test protocols and standards.

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 device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done

Not applicable. This is not an AI/ML algorithm.

7. The Type of Ground Truth Used

The "ground truth" for this medical device clearance is based on:

• Compliance with International Standards: The device's physical, chemical, and biological properties were evaluated against recognized standards (ISO 10993, ISO 11135, ISO 11137, ASTM F88/F88M-15, ASTM F1929-15, USP ).
• Substantial Equivalence: The device's characteristics (intended use, mechanism, material, sterilization, biocompatibility, antibacterial duration, single use) were compared to legally marketed predicate devices, with detailed comparisons provided in Table 1 (pages 8-9).

8. The Sample Size for the Training Set

Not applicable. This is a medical device, not an AI/ML device that requires a training set.

9. How the Ground Truth for the Training Set was Established

Not applicable. This is a medical device, not an AI/ML device that requires a training set and its associated ground truth establishment.

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Antimicrobial gauze sponge dressing, antimicrobial super sponge dressing, and antimicrobial non-woven sponge dressing are indicated to cover and protect, absorb wound exudate, and maintain moisture balance of minor abrasions, minor lacerations, and minor burns.

The devices are available in three configurations, which are Antimicrobial gauze sponge dressing, Antimicrobial super sponge dressing and Antimicrobial non-woven sponge dressing. All of them consist of (1) a dressing (base material) and (2) anti-microbial agent. For each configuration, it is available in several models, which are different in size and quantity of anti-microbial agent.

Based on in vitro testing, the product can achieve board spectrum antimicrobial effect within the dressing for Gram+ and Gram- Bacteria and Fungi. It has been shown to have 4 log bacterial reduction in vitro against the following test organisms: Staphylococcus aureus (ATCC 6538), Escherlchia coli (ATCC 25922), Candida albicans (ATCC 10231), Pseudomona aeruginosa (ATCC 9027) and Bacillus subtilis (ATCC 6633), Streptococcus pyogenes (ATCC 19615), Serratia marcescens (ATCC 31026), Aspergillus niger (ATCC 16404). The effective inhibition of bacteria is 7 days.

This document is a 510(k) summary for antimicrobial sponge dressings and does not involve AI/ML technology. Therefore, it does not contain the information requested in your prompt regarding acceptance criteria, study details for AI/ML device performance, sample sizes, expert ground truth establishment, MRMC studies, or standalone algorithm performance.

The document focuses on demonstrating substantial equivalence of the proposed antimicrobial dressings to previously cleared predicate devices, primarily by showing similar intended use, technological characteristics (materials, antimicrobial agents, sterilization), and a reliance on non-clinical testing (biocompatibility, antimicrobial effectiveness, absorbency). It explicitly states that "No clinical study is included in this submission." Consequently, there are no acceptance criteria or study details regarding human or AI performance to report.

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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.

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.

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