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Replens is a personal lubricant for 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 and synthetic (polyurethane and polyisoprene) condoms.

Replens Vaginal Moisturizer is a non-sterile, water-based, white to off-white, non-irritating, non-greasy, non-staining vaginal gel delivered in single-use, pre-filled applicators as a long-lasting moisturizer for vaginal dryness. The use of prefilled applicators provides less mess in application. Replens Vaginal Moisturizer is intended for ongoing use, not exclusively for use during intimate sexual activity.

The provided document is a 510(k) Summary for Replens Long-Lasting Vaginal Moisturizer (in pre-filled applicators). It primarily focuses on demonstrating substantial equivalence to a predicate device for regulatory clearance rather than establishing a new device's performance against explicit acceptance criteria in a typical clinical study format for novel devices.

Therefore, the requested information, particularly regarding specific acceptance criteria, comprehensive effect sizes, and detailed ground truth establishment methods for a standalone AI algorithm, is largely not applicable or not explicitly stated in this type of regulatory submission. The document outlines safety and performance data in relation to its intended use and comparison to a predicate device.

However, I can extract and infer some information based on what is provided:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) for a personal lubricant, the "acceptance criteria" are generally tied to demonstrating safety, intended use (moisturizing and lubrication), and compatibility with condoms, rather than a quantifiable performance metric (like accuracy or sensitivity) typically seen in AI or diagnostic devices. The acceptance is implied by successfully passing various tests.

2. Sample Sizes and Data Provenance for Test Set (Clinical Studies)

The "test set" in this context refers to the clinical studies used to support the safety and efficacy of the Replens device.

• Whitehead (1991): 32 patients enrolled (Replens group)
• Nachtigall (1994): 15 patients enrolled
• Gelfand and Wendman (1994): 25 patients enrolled
• Bachmann et al. (1991): 89 patients enrolled (Replens group)
• Bachmann et al. (1992): 54 patients enrolled
• Zinny and Lee (1991): 26 patients enrolled
• Young et al. (1991): 30 patients enrolled
• Nakamura (1991): 10 patients enrolled

Data Provenance: The document does not explicitly state the country of origin for each study. However, authors like Bachmann, Nachtigall, Gelfand, and Wendman are typically associated with studies conducted in North America (primarily the US). Retrospective or Prospective: The study designs (double-blind, cross-over, open, parallel) indicate these were prospective clinical trials.

3. Number of Experts and Qualifications for Ground Truth

This information is not provided in the summary. For a medical device like Replens, "ground truth" would be established through patient-reported outcomes, clinical assessments (e.g., pH measurements, vaginal dryness index assessment by a clinician), and potentially histological examination (as mentioned for subacute vaginal irritation). The specific number and qualifications of experts involved in these assessments are not detailed.

4. Adjudication Method for the Test Set

This information is not provided. Clinical studies typically have methods for assessing patient outcomes and safety events, but a specific "adjudication method" in the context of diagnostic agreement (like for imaging AI) is not relevant or described here.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, an MRMC comparative effectiveness study was not performed as this device is a personal lubricant, not an AI diagnostic tool. The concept of "human readers improving with AI vs. without AI assistance" is not applicable here.

6. Standalone Performance Study

Yes, the clinical studies listed (Bachmann et al., Nachtigall, Gelfand and Wendman, Zinny and Lee, Young et al., Nakamura) represent standalone performance studies for the Replens device. They assess its effects, safety, and patient-reported outcomes without "human-in-the-loop" interaction in the sense of an AI algorithm enhancing human decision-making.

7. Type of Ground Truth Used

The ground truth used in the clinical studies for Replens appears to be a combination of:

• Clinical Assessments: Vaginal pH determination, vaginal mucosa observations, vaginal dryness index.
• Patient-Reported Outcomes: Relief of patient's symptoms (vaginal dryness), completion of diary cards.
• Pathology: Histological examination (for subacute vaginal irritation testing).
• Safety Data: Adverse event reporting and tolerability assessments.

8. Sample Size for the Training Set

This information is not applicable. Replens is a medical device (personal lubricant), not an AI algorithm. Therefore, there is no "training set" in the context of machine learning. The clinical studies mentioned serve as the evidence base for its safety and efficacy.

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

This information is not applicable as there is no training set for an AI algorithm.

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Replens is a personal lubricant for 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 and synthetic (polyurethane and polyisoprene) condoms.

Replens Vaqinal Moisturizer is a non-sterile, water-based, white to off-white, non-irritating, non-greasy, non-staining vaginal gel delivered in a tube with a reusable applicator as a long-lasting moisturizer for vaginal dryness. The use of the reusable applicator provides less mess in application. Replens Vaginal Moisturizer is intended for ongoing use, not exclusively for use during intimate sexual activity.

Replens Vaginal Moisturizer contains ingredients commonly used in other products for vaginal use sold as medical devices and cosmetics. All ingredients are either NF, USP, or are considered "generally recognized as safe for their intended use". The quantitative formulation is considered confidential commercial information.

The Replens Vaginal Moisturizer, a personal lubricant for vaginal application, underwent various tests and clinical studies to demonstrate its safety and effectiveness. The acceptance criteria and performance data are summarized below.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document refers to a series of eight clinical studies as the "test set" for Replens Long-Lasting Vaginal Moisturizer.

• Sample Sizes: The number of patients enrolled in the Replens arm across these studies varied:
  • Bachmann et al (1991): 89 patients
  • Bachmann et al (1992): 54 patients
  • Zinny and Lee (1991): 26 patients
  • Young et al (1991): 30 patients
  • Nakamura (1991): 10 patients
  • Whitehead (1991): 32 patients
  • Nachtigall (1994): 15 patients
  • Gelfand and Wendman (1994): 25 patients
• Data Provenance: The provenance of the data is not explicitly stated in terms of country of origin but is indicated by the publication of several studies in peer-reviewed journals (e.g., Clinical Practice in Sexuality, Today's Therapeutic Trends, Fertility and Sterility, J. Women's Health). Some studies were "Unpublished." The studies appear to be prospective clinical trials given their design (e.g., double-blind, cross-over, open-label) and specific dosage regimens and durations.

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

The concept of "ground truth" established by experts, as typically understood in the context of AI/ML device performance evaluation, is not directly applicable to this submission. This is a 510(k) for a medical device (vaginal moisturizer), not an AI/ML algorithm.

The "ground truth" for the clinical efficacy and safety was established:

• Clinically by the direct observation, assessment (e.g., vaginal pH, vaginal dryness index), and reported symptoms of the patients participating in the clinical trials.
• Statistically by the analysis of these clinical outcomes by the researchers who conducted and published these studies.
• Biologically through the results of the various biocompatibility tests.

The "experts" involved would be the clinical investigators (physicians, researchers) who designed and executed these studies, interpreted the data, and published the findings. Their qualifications are not explicitly detailed but are implied by their authorship in scientific papers.

4. Adjudication Method for the Test Set

Adjudication methods (like 2+1, 3+1) are typically used in AI/ML studies to resolve discrepancies in expert labeling or diagnoses. This concept is not applicable to this 510(k) submission as it is not for an AI/ML device. The clinical studies followed standard trial protocols for data collection and analysis, which inherently include methods for managing and interpreting patient data and outcomes. For double-blind studies, the blinding helps ensure impartial assessment.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was mentioned. This type of study comparing human readers with and without AI assistance is specific to AI/ML devices and is not relevant to this product submission.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No standalone (algorithm only) performance study was conducted or is relevant. This device is a topical moisturizer, not an AI algorithm.

7. Type of Ground Truth Used

The "ground truth" for this device's performance was based on:

• Clinical Endpoints: Patient-reported symptoms (e.g., relief of vaginal dryness), objective clinical measurements (e.g., vaginal pH, vaginal dryness index), and physician assessments of the vaginal mucosa.
• Biocompatibility Standards: Pre-defined safety standards for cytotoxicity, irritation, sensitization, and toxicity.
• Physical/Chemical Testing: Laboratory assessments for stability, preservative effectiveness, and condom compatibility.

8. Sample Size for the Training Set

The concept of a "training set" is specific to AI/ML models. This device is a traditional medical product (vaginal moisturizer), not an AI/ML algorithm. Therefore, there is no training set in the AI/ML sense. The product development and testing relied on chemical formulation, manufacturing best practices, and the clinical and non-clinical studies summarized.

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

As there is no training set for an AI/ML algorithm, this question is not applicable.

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The device is for the treatment of external hemorrhoids by applying cold therapy (cryotherapy) directly to swollen hemorrhoidal veins. By applying the device to the tissue, the inflammation is reduced. The direct application of cold provides prompt relief of/extinguishes itching, burning, pain, and swelling. In addition, the device is beneficial for the treatment of perianal fissures due to the vasoconstriction and analgesia properties of the device.

The Cryostat Cold Therapy Pack device consists of a combination of water and chemicals in an anatomically designed sealed plastic bag, enclosed in a cloth outer wrapper for comfort. Six Cold Therapy Packs are packaged in one carton. An individual cold pack is 95mm long and 25mm wide and 26mm in depth. A cold pack consists of a series of inner plastic containers, one of which contains water and FDA food grade dye (to distinguish it from the other fluid), inside a second container which contains a secondary fluid, consisting of water, USP Food grade Kosher propylene glycol as well as a different color FDA food grade dye. The freezing temperature of the first fluid is higher than that of the second fluid. This allows a time released cooling process which delivers high performance cold therapy because of conduction and convection following the phase change of the primary fluid from solid to liquid. The containers are made of formable film common in the food and medical packaging industry. The film is a multi-layer extrusion with one layer being Nylon to add strength and act as a vapor barrier. Visual inspection is performed to verify seal integrity and the dye in the fluids facilitates quality control. Since the intended use of the device is to treat a specific ailment which requires comfort, the miniature cold pack is then wrapped in a heat sealable fabric for comfort to the affected area. The material chosen is white, so that the device, once used can be seen as soiled and therefore is disposed of.

The provided text is a 510(k) Premarket Notification Submission for the Lil' Drug Store Products, Inc. Cryostat™, a device for treating external hemorrhoids with cold therapy. This document focuses on demonstrating substantial equivalence to a predicate device, not on conducting a study with specific acceptance criteria related to a new device performance metric for diagnosis or treatment effectiveness that would involve clinical trials, expert adjudication, or AI.

Therefore, many of the requested elements for describing "acceptance criteria and the study that proves the device meets the acceptance criteria" are not applicable in this context. The "study" here refers to a battery of technical tests, not a clinical study involving human participants in the way the questions imply.

Here's an analysis based on the provided text, addressing the applicable points and explaining why others are not present:

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

   The document does not explicitly state "acceptance criteria" in the format of specific thresholds for clinical performance metrics (like sensitivity, specificity, accuracy). Instead, it lists technical tests performed to demonstrate safety and effectiveness, and implicitly, the device "met" these tests for the FDA to issue a substantial equivalence determination.

   Test Performed	Reported Device Performance (Implicitly Met for Substantial Equivalence)
   Temperature longevity	Demonstrated adequate duration of cold therapy.
   Flammability	Met safety standards for flammability.
   Burst strength	Met safety standards for burst strength.
   Tensile strength	Met safety standards for tensile strength.
   Tear strength	Met safety standards for tear strength.
   Safety/toxicological	Demonstrated safety regarding materials and potential toxicity.
   Irritation	Demonstrated no or acceptable irritation.
   Sensitization	Demonstrated no or acceptable sensitization.
   Cytotoxicity	Demonstrated no cytotoxicity.

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

   Not applicable. The document describes engineering and materials testing, not a clinical test set with human subjects. The "tests performed" (temperature longevity, flammability, etc.) would be conducted on samples of the device itself. Specific sample sizes for these engineering tests are not mentioned in this summary. Data provenance is not relevant in this context.

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)

   Not applicable. This is not a study requiring expert ground truth for diagnostic or clinical evaluation. The "ground truth" for the engineering tests would be established by standard engineering and safety protocols and measurements.

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

   Not applicable. This is not a study requiring expert adjudication of clinical outcomes or interpretations.

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 document pertains to a physical medical device (cold therapy pack), not an AI algorithm or a diagnostic tool that involves human readers/interpreters.

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 technical tests (flammability, burst strength, etc.), the "ground truth" is defined by established engineering standards, material science properties, and safety thresholds. For example, flammability testing would have a pass/fail criterion based on material burning characteristics. For the toxicological assessment, it would be based on established toxicology protocols.

8. The sample size for the training set

   Not applicable. There is no "training set" in the context of this device and its regulatory submission. This is not an AI/machine learning device.

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

   Not applicable. There is no "training set."

Summary of the Device's "Study" and Basis for Acceptance:

The "study" described in this 510(k) submission is a "rigorous risk assessment and performance test regimen" designed to demonstrate the safety and effectiveness of the Cryostat device. The submission’s primary goal is to prove substantial equivalence to a previously legally marketed predicate device (Hemor-Rite Cryotherapy, K042564).

The tests performed were:

• Temperature longevity
• Flammability
• Burst strength
• Tensile strength
• Tear strength
• Safety/toxicological assessment
• Irritation
• Sensitization
• Cytotoxicity

The device "met" these performance criteria implicitly, as "The FDA finding of substantial equivalence of your device... permits your device to proceed to the market." The detailed results or specific thresholds for these tests are not provided in this summary but would have been part of the full 510(k) submission reviewed by the FDA. The "acceptance criteria" here are inherent to meeting relevant safety and performance standards for a medical device of this type, allowing the FDA to determine it is "safe and effective for its proposed indications" and "substantially equivalent" to predicate devices.

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