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Carex Hybrid Personal Lubricant is a personal lubricant. for penile and/or vaginal application, intended to moisturize and lubricate, to enhance the ease and comfort of intimate sexual activity and supplement the body's natural lubrication. This product is compatible with natural rubber latex, and polyisoprene condoms. This product is not compatible with polyurethane condoms

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This document is not about an AI/ML device but rather a 510(k) clearance for a personal lubricant. It does not contain information on acceptance criteria for an AI device, performance studies, sample sizes, expert ground truth, or MRMC studies. Therefore, I cannot fulfill your request based on the provided text.

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Karex's water based personal lubricant with flavors is a personal lubricant, for penile and/or vaginal application, intended to moisturize and lubricate, to enhance the ease and comfort of intimate sexual activity and supplement the body's natural lubrication. This product is compatible with natural rubber latex condoms. This product is not compatible with polyisoprene and polyurethane condoms.

Water Based Personal Lubricant with Flavors

• Vanilla
• Aloe Vera
• Strawberry
• Banana
• Peppermint
• Chocolate

This document is a 510(k) premarket notification decision letter from the FDA to Karex Industries Sdn. Bhd. for a "Water Based Personal Lubricant with Flavors." The letter states that the device is substantially equivalent to legally marketed predicate devices.

Crucially, this document pertains to a medical device approval for a lubricant, not a study evaluating an AI-powered diagnostic device. As such, the information requested for acceptance criteria and study details (e.g., test set, training set, expert consensus, MRMC studies) is not present in this document. The document primarily discusses regulatory compliance and the FDA's substantial equivalence determination for a physical product.

Therefore, I cannot provide the requested information based on the provided text. The document does not contain data or information about:

1. A table of acceptance criteria and reported device performance for an AI/diagnostic device.
2. Sample sizes, data provenance, ground truth establishment for test or training sets.
3. Number and qualifications of experts.
4. Adjudication methods.
5. MRMC studies or effect sizes for human readers.
6. Standalone algorithm performance.
7. Type of ground truth used (e.g., pathology, outcomes data).

The text is about the regulatory approval of a personal lubricant.

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Natural Rubber Latex Male Condoms [Parallel Sided, Smooth, Lubricated or Non-lubricated]
a) Parallel Sided Smooth, 53mm Condoms
b) Parallel Sided Smooth, 53mm Condoms - Ultra Thin
c) Parallel Sided Smooth, 53mm Condoms - Super Thin
d) Parallel Sided Smooth, 56mm Condoms
e) Parallel Sided Smooth, 56mm Condoms - Ultra Thin
The Karex condom is used for contraceptive and for prophylactic purposes (to help prevent pregnancy and the transmission of sexually transmitted infections).

Natural Rubber Latex Male Condoms [Parallel Sided, Smooth, Lubricated or Non-lubricated]

This document is a 510(k) premarket notification decision letter from the FDA regarding Natural Rubber Latex Male Condoms manufactured by Karex Industries Sdn. Bhd. It is not a study proving a device meets acceptance criteria.

The document states that the FDA has reviewed the submission and determined the device is "substantially equivalent" to legally marketed predicate devices. This means the device is considered as safe and effective as a device already on the market, but it does not provide details on specific performance acceptance criteria or the studies conducted by the manufacturer to demonstrate those criteria were met for this particular condom.

Therefore, I cannot provide the requested information based on the provided text. The document does not contain:

• A table of acceptance criteria and reported device performance.
• Sample sizes used for test sets or data provenance.
• Information on experts used to establish ground truth or their qualifications.
• Adjudication methods.
• Details of a multireader multicase (MRMC) comparative effectiveness study.
• Evidence of a standalone algorithm performance study (as this is a physical medical device, not an AI algorithm).
• Type of ground truth used.
• Sample size for training sets.
• How ground truth for training data was established.

This document is an FDA approval letter, not a scientific study report. To get the requested information, you would need to access the technical submission documents provided by Karex Industries Sdn. Bhd. to the FDA, which are not included here.

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Black Colored Condoms [Parallel Sided or Contoured or Flared or Non-textured, Lubricated or Non-lubricated]

a) Parallel sided smooth, 53mm Black colored condom

b) Parallel sided dotted, 53mm Black colored condom

c} Parallel sided ribbed, 53mm Black colored condom

d) Parallel sided smooth, 56mm Black colored condom

e) Contoured studded, 53mm Black colored condom

f) Contoured ribbed & studded, 53mm Black colored condom

g) Contoured ribbed, 52mm Black colored condom

h) Flared smooth, 56mm Black colored condom

The Karex condom is used for contraceptive and for prophylactic purposes (to help prevent pregnancy and the transmission of sexually transmitted diseases).

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The provided text is related to the FDA's acceptance of "Black Colored Condoms" by Karex Industries Sdn. Bhd. for marketing. It is a 510(k) premarket notification, which establishes substantial equivalence to a legally marketed predicate device.

This document is not a study report for a medical device that uses algorithms or AI, so many of the requested criteria are not applicable. This document is for a physical product (condoms), not a software-based medical device.

Therefore, I cannot provide information for most of the requested points, as they pertain to the evaluation of AI/algorithm-based medical devices. However, I can extract the relevant information from the provided text.

Here's the information that can be extracted or deduced:

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

Based on the document, the "acceptance criteria" are not explicitly stated in a quantitative performance table like one would expect for an AI/algorithm. Instead, the acceptance is based on meeting regulatory requirements and demonstrating "substantial equivalence" to a predicate device. The performance is implied by the generic indications for use of condoms.

For the following points (2-9), the information is not present in the provided document because it describes the regulatory clearance of a physical consumer product (condoms), not an AI/algorithm medical device study.

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

   • N/A. This document does not describe a study involving a test set of data for an AI/algorithm.

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)

   • N/A. This document does not describe a study involving experts establishing ground truth for an AI/algorithm.

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

   • N/A. This document does not describe a study involving adjudication for an AI/algorithm.

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

   • N/A. This is not an AI/algorithm device.

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

   • N/A. This is not an AI/algorithm device.

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

   • N/A. This document does not describe a study involving ground truth for an AI/algorithm. For condoms, performance is typically assessed through physical testing methods (e.g., burst tests, water leak tests) and clinical studies for efficacy. These details are not in this 510(k) letter.

8. The sample size for the training set

   • N/A. This document does not describe an AI/algorithm device with a training set.

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

   • N/A. This document does not describe an AI/algorithm device with a training set.

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The Karex condom is used for contraceptive and for prophylactic purposes (to help prevent pregnancy and the transmission of sexually transmitted diseases).

Orange colored condoms with orange scents

The provided document is a 510(k) premarket notification letter from the FDA regarding a condom, specifically "Orange colored condoms with orange scents." This document does not contain information about a medical device that utilizes AI, machine learning, or complex imaging. Therefore, it does not include the details typically found in an acceptance criteria and study report for such devices.

The request asks for specific information related to the performance evaluation of a device, including:

1. A table of acceptance criteria and reported device performance.
2. Sample size and data provenance.
3. Number and qualifications of experts for ground truth.
4. Adjudication method.
5. MRMC study details and effect size.
6. Standalone performance.
7. Type of ground truth.
8. Training set sample size.
9. Ground truth establishment for training set.

None of this information is available in the provided FDA 510(k) clearance letter for the condom.

To fulfill the request, one would need a performance study report for an AI/ML medical device, which is not what has been provided.

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The Karex Large and Extra Large condom is used for contraceptive and for . prophylactic purposes (to help prevent pregnancy and the transmission of sexually transmitted diseases).

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This document is an FDA 510(k) clearance letter for "Large and Extra Large Condoms" manufactured by Karex Industries Sdn. Bhd. It does not contain information about acceptance criteria or a study proving device performance as typically expected for medical imaging or AI-based diagnostic devices.

The document states that the device is "substantially equivalent" to legally marketed predicate devices, which is the basis for 510(k) clearance. This means that the FDA reviewed documentation demonstrating that the new device is as safe and effective as a legally marketed device. For condoms, this typically involves manufacturing quality control and performance testing against established standards (e.g., ISO or ASTM standards) for burst strength, freedom from holes, dimensions, etc., rather than clinical studies with human subjects in the same way an AI diagnostic would be evaluated.

Therefore, I cannot provide the requested information about acceptance criteria, study details, sample sizes, expert qualifications, or ground truth, as this type of information is not present in the provided document because it is a clearance letter for a medical device that gained approval via substantial equivalency, not a clinical study report for an AI/diagnostic device.

If you have a document describing a clinical study or performance evaluation for an AI-based device, I can analyze that.

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The Karex condom is used for contraceptive and for Prophylactic purposes (to help prevent pregnancy and the transmission of sexually transmitted diseases).

This condom is made of a natural rubber latex sheath, which completely covers the penis with a closely fitted membrane. This condom is straight sided or contoured , textured or non textured ,with a reservoir tip; nominal length 180mm, nominal width 53mm, and nominal thickness 0.07mm. It is nonlubricated or lubricated with silicone and cornstarch is used as a dressing material. The condom is either colored or non colored, flavored or non flavored, and designed to conform to established national and international voluntary standards including ASTM D3492 and ISO 4074.

The provided text describes a 510(k) premarket notification for a Male Natural Rubber Latex Condom, not a device that utilizes AI or requires complex studies with ground truth or expert adjudication to establish performance. The document focuses on demonstrating substantial equivalence to pre-existing predicate devices.

Therefore, many of the requested categories (such as sample size for test/training sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth types) are not applicable to this type of regulatory submission. The performance criteria for a condom are physical and biological, verified through laboratory testing and material analysis, rather than clinical or AI-based assessments.

Here's how the information that is applicable can be extracted and presented, with explanations for the non-applicable sections:

Acceptance Criteria and Device Performance for Male Latex Condom

The acceptance criteria for this male latex condom are based on conformance to established national and international voluntary standards, specifically ASTM D3492 and ISO 4074, for its physical properties and biocompatibility. The performance is demonstrated by stating compliance with these standards and by establishing substantial equivalence to predicate devices that have already met these standards.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample Size: Not explicitly stated in the provided text. For physical and biocompatibility testing of condoms, various sample sizes would be used for each specific test (e.g., burst tests, tensile strength, cytotoxicity). These are typically defined by the standards (ASTM D3492, ISO 4074) themselves.
• Data Provenance: The device manufacturer, Karex Industries Sdn. Bhd., is based in Johor, Malaysia. The testing would have been conducted by or for this company, likely in Malaysia or accredited labs adhering to international standards. The evaluation of color pigments and flavorings is noted to have occurred "as part of the Predicate Device formulations," implying reliance on prior data or testing reports for those components.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. For a male latex condom, "ground truth" is established through standardized laboratory testing against international specifications (ASTM, ISO), rather than expert consensus on clinical or imaging data. The experts involved would be engineers, chemists, and quality assurance specialists performing the tests according to the established protocols.

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

Not applicable. Adjudication methods like 2+1 or 3+1 typically apply to interpretation of complex data (e.g., medical images) by multiple human readers. For condom testing, results are objective measurements (e.g., burst pressure, elongation, presence/absence of cytotoxic effects) that either meet or fail the specified criteria.

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 a medical device (condom) and not an AI-powered diagnostic or assistive tool. MRMC studies are irrelevant here.

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

Not applicable. There is no algorithm involved in the performance of a latex condom.

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

The "ground truth" for this device is based on objective measurements from physical, chemical, and biological laboratory tests against the specific requirements and thresholds defined by international and national standards (ASTM D3492, ISO 4074, ISO 10993). This is analogous to a standard for a material property, rather than an interpretation of complex data.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device; therefore, there is no "training set."

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

Not applicable. As there is no training set for an AI model, this question is not relevant.

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The Karex condom is used for contraceptive and for prophylactic purposes ( to help prevent pregnancy and the transmission of sexually transmitted diseases).

This condom is made of a natural rubber latex sheath, which completely covers the penis with a closely fitted membrane. This condom is straight walled, contoured or flared with a reservoir tip; nominal length 180mm, nominal width 53mm, and nominal thickness 0.06mm. It is lubricated with silicone and cornstarch is used as a dressing material. The condom is colored and flavored, and designed to conform to established national and international voluntary standards including ASTM D3492 and ISO 4074.

The provided text describes a 510(k) summary for a male latex condom. It does not present a study with acceptance criteria and device performance results in the way a typical AI/software device would.

Instead, it focuses on demonstrating substantial equivalence to a predicate device by comparing technological characteristics and adherence to established standards for safety and performance of condoms.

Therefore, many of the requested categories for AI/software devices (like sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance) are not applicable to this type of medical device submission.

However, I can extract the relevant information regarding acceptance criteria and the methods used to show compliance for this specific device.

Acceptance Criteria and Reported Device Performance

For this male latex condom, the "acceptance criteria" are compliance with established national and international voluntary standards, and the reported "device performance" is its demonstration of conforming to these standards. The device is also evaluated for biocompatibility and oral toxicity of its components.

As this is a physical medical device (condom) and not an AI/software device, the following points are largely not applicable or cannot be extracted from the provided text.

2. Sample size used for the test set and the data provenance:

• Not applicable in the context of AI/software testing. For physical devices like condoms, testing involves batch sampling and physical/chemical tests. The specific sample sizes for material conformance or performance tests (e.g., burst tests) are not detailed in this summary but would be part of the underlying design control documentation. The data provenance would be from manufacturing and testing facilities.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. Ground truth for a physical product's performance against industry standards is established through standardized testing methodologies, not expert consensus on interpretations.

4. Adjudication method for the test set:

• Not applicable. Standardized tests yield objective results (e.g., a burst pressure, a chemical concentration), not subjective interpretations requiring adjudication.

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 type of study is specific to AI-assisted human interpretation in diagnostic or screening tasks.

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

• Not applicable. There is no algorithm or software component described that would operate in a standalone manner.

7. The type of ground truth used:

• The "ground truth" here is compliance with established national and international voluntary standards (ASTM D3492, ISO 4074) for condom performance and biocompatibility and toxicity requirements (ISO 10993) for materials. This is based on objective measurements and established thresholds derived from scientific understanding and extensive testing in the field.

8. The sample size for the training set:

• Not applicable. There is no AI/machine learning component requiring a training set.

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

• Not applicable. There is no AI/machine learning component.

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