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The Brand Name 1-Step Pregnancy Test is an at-home pregnancy test marketed over-the-counter (OTC) to lay consumers. The Brand Name 1-Step Pregnancy Test detects the presence of hCG in the urine as an aid in the early diagnosis of pregnancy. The test, which can be used anytime of the day, can detect hCG as early as the first day of the missed menses.

The Brand Name 1-Step Pregnancy Test is a Class II in vitro diagnostic medical device product that functions by way of a double antibody immunochromatographic assay in detecting the presence of hCG in the urine as an aid in the early diagnosis of pregnancy. It consists of a plastic stick, which contains an absorbent tip that protrudes from the end of the device and collects and delivers urine to reagents on a chromatographic strip contained within the device. The test is performed by placing the absorbent tip of the device in the urine stream for 5 seconds or by immersing the absorbent tip into a container of urine for 5 seconds. The absorbent section of the strip allows the urine sample to move chromatographically along the reagent strip reconstituting the diffusible reagents placed strategically along the strip and delivering them to the appropriate capture zones for visualization of the test results. The detection of hCG (pregnant) in the urine sample is indicated by the appearance of two pink lines in the test window. If there is no hCG (not-pregnant) in the urine, one pink line will appear.

Here's an analysis of the provided 510(k) summary regarding the acceptance criteria and supporting studies for the "Brand Name 1-Step Pregnancy Test":

1. Acceptance Criteria and Reported Device Performance

The provided document details various performance studies but does not explicitly state numerical acceptance criteria for sensitivity, specificity, or agreement. Instead, it describes general objectives and outcomes. However, it implicitly demonstrates that the device met the criteria for substantial equivalence to the predicate device.

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

The document does not specify the exact sample sizes for the test sets in any of the described studies (laboratory accuracy, sensitivity, or consumer use).

Regarding data provenance, the studies are described as "laboratory studies" and "studies" evaluating consumer ability. Given the context of a 510(k) submission for a new product, these would almost certainly be prospective studies conducted specifically for this submission. The document does not mention the country of origin of the data, but
given the submitter is Carter-Wallace in Cranbury, New Jersey, it is highly probable the
studies were conducted in the United States.

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

The document does not specify the number of experts used or their qualifications for establishing ground truth in the laboratory studies. For a hCG test, the ground truth for positive/negative results would typically be established by:

• Quantitative laboratory assays: Using a highly accurate reference method to measure hCG levels.
• Clinical assessment: In some cases, confirming pregnancy status through other clinical means (though less common for in vitro diagnostic ground truth).

For the consumer studies, the "ground truth" for the interpretation ability would be derived from comparison to the device's actual performance (i.e., whether the consumer's interpretation matched the correct result as determined by the laboratory).

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1, none) for the test sets. For IVD devices like pregnancy tests, adjudication among human readers or experts is less common for establishing the analytical ground truth (presence or absence of hCG) as the results are typically objectively measured by quantitative methods. However, for the consumer interpretation studies, it's possible internal protocols were used to resolve discrepancies if consumers disagreed on the interpretation of a test result, but this is not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. The document describes laboratory studies comparing the new device to a predicate device, and consumer studies to assess user interpretation. These are not MRMC studies designed to assess the improvement of human readers with AI assistance, as this is a standalone diagnostic test, not an AI-assisted diagnostic tool.

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

Yes, a form of standalone performance was assessed. The "Brand Name 1-Step Pregnancy Test" is an in vitro diagnostic device, not an algorithm. Its "standalone" performance refers to its ability to detect hCG accurately on its own. The laboratory studies ("evaluation of the laboratory accuracy" and "evaluate and confirm the sensitivity") directly assess this standalone performance – how well the device itself, without human interpretation of ambiguous signals, determines the presence or absence of hCG. The consumer studies then assess the "human-in-the-loop" aspect: whether lay users can correctly interpret the device's output.

7. The Type of Ground Truth Used

The ground truth for the analytical performance studies (laboratory accuracy and sensitivity) would be based on quantitative biochemical assays for human chorionic gonadotropin (hCG) levels in urine samples. This would be the definitive measure of hCG concentration, allowing for the determination of true positive and true negative samples.

For the consumer interpretation studies, the ground truth for correct interpretation would be established by comparing the consumer's visual reading of the test lines against the known analytical result (positive or negative for hCG) of the sample used.

8. The Sample Size for the Training Set

The concept of a "training set" is typically associated with machine learning or artificial intelligence models. As the "Brand Name 1-Step Pregnancy Test" is an immunochromatographic device and not an AI algorithm, there is no training set in the conventional sense. The device's characteristics are inherent to its design and chemical reagents, not learned from data.

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

Since there is no training set for this type of device, this question is not applicable.

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The Brand Name 1-Step Pregnancy Test is a simple-to-use at-home pregnancy test marketed over-the-counter (OTC) to lay consumers. The test device product is intended for the detection of human chorionic gonadotropin (hCG) in urine as an aid in the detection of early pregnancy.

The Brand Name 1 -Step Pregnancy Test is a Class II in vitro diagnostic medical device product that functions by way of an immunochemical chromatographic-chromogenic method in detecting the presence of hCG in the urine as an aid in the early diagnosis of pregnancy. It consists of a plastic stick, housing an absorbent pad that collects and delivers urine to reagents on a chromatographic strip contained within the device. The test is performed by placing the absorbent pad of the device in the urine stream for 5 seconds or by dipping the device into a container of urine for 5 seconds. The absorbent section of the strip allows the urine sample to move chromatographically along the reagent strip reconstituting the diffusible reagents placed strategically along the strip and delivering them to the appropriate capture zones for visualization of the test results. The detection of hCG in the urine sample (pregnant) is indicated by the appearance of two pink lines in the test window. If there is no hCG (not-pregnant) in the urine, one pink line will appear.

This document is a 510(k) summary for a pregnancy test, not an AI/ML medical device. Therefore, many of the requested fields (e.g., sample sizes for test and training sets, expert qualifications, MRMC studies, ground truth establishment for AI) are not applicable.

Here's the information that can be extracted and a clear indication of what is not applicable to this type of device:

1. Table of Acceptance Criteria and Reported Device Performance

Study Details (as applicable for this device type):

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

• Sample Size (Clinical Study): 78 pregnant and 58 non-pregnant subjects (Total = 136 subjects)
• Data Provenance: Not explicitly stated, but clinical studies are generally prospective. The text implies a real-world setting with "lay consumers."

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

• Not Applicable. For a pregnancy test, the ground truth (pregnancy status) is established by other definitive clinical methods (e.g., physician-confirmed pregnancy via other assays or ultrasound), not typically by expert review of the test device's output. The "Expert" column in the table refers to the expert reading of the brand-name device and predicate device, likely by trained laboratory personnel or clinicians, not experts establishing the true pregnancy status.

4. Adjudication method for the test set:

• Adjudication Method: Not explicitly stated. For the clinical study table, results were compared between the Brand Name device, the predicate device, and "Expert" readings of both. It's unclear if there was an adjudication process for discordant results between the expert readings and the clinical predicate, or if "Expert" refers to the confirmed pregnancy status. Given the nature of a pregnancy test, the "ground truth" would be established by independent clinical means.

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-powered device. The study involved lay users and expert readers for the device itself, but not in the context of an AI-assisted workflow.

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

• Not Applicable. This is a diagnostic medical device that provides a visual readout. Its performance is its standalone performance, and ultimately relies on human interpretation (either lay users or experts). There is no "algorithm only" component separate from the physical test strip.

7. The type of ground truth used:

• Type of Ground Truth: The ground truth for pregnancy status was established by independent clinical confirmation (likely via a combination of physician diagnosis, other laboratory tests for hCG, etc.), as indicated by the comparison with "Clinically Confirmed Pregnant" and "Clinically Confirmed Not Pregnant" categories in the lay user study description. For the clinical study, the expert reading of the predicate device and the new device were compared.

8. The sample size for the training set:

• Not Applicable. This device does not use machine learning or AI, and therefore does not have a "training set" in that context. The device's design and manufacturing process are established through traditional engineering and quality control, not data-driven model training.

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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