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Platform OneStep pregnancy test is Syntron Bioresearch. Inc. name for OTC use of solid phase immunoassay in vitro diagnostic test kit for the qualitative determination of human Chorionic Gonadotropin (hCG) in urine.

solid phase immunoassay in vitro diagnostic test kit

This K960117 document is a Premarket Notification [510(k)] for an in vitro diagnostic test kit, specifically a pregnancy test. The provided text does not contain the acceptance criteria or a study proving the device meets acceptance criteria in the way typically expected for a software or AI-driven medical device.

The document focuses on comparing the Platform OneStep Pregnancy Test with an already marketed device (Besure OneStep Immunoassay) to demonstrate substantial equivalence, a requirement for 510(k) clearance. The "performance" mentioned primarily refers to sensitivity (cutoff concentration) rather than complex metrics like accuracy, sensitivity, or specificity derived from a clinical study with a ground truth established by experts.

Therefore, I cannot directly answer your questions as they are formulated for a different type of device evaluation (e.g., AI/software for image analysis or diagnosis). However, I can interpret the provided information to explain what a 510(k) for an in vitro diagnostic would typically include regarding performance, even if it's not explicitly stated in this truncated document.

Here's an attempt to address your prompts given the context of a 510(k) for an in vitro diagnostic, with many sections marked as "Not Applicable," "Not Provided," or making logical assumptions based on typical IVD submissions:

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

For a pregnancy test, the primary performance characteristic is its sensitivity (detection limit) and specificity (lack of cross-reactivity). While explicit "acceptance criteria" are not listed in the provided text, the core claim is that the device detects hCG at a specific cutoff.

Study that Proves the Device Meets Acceptance Criteria:

The provided text states: "Platform OneStep pregnancy test is based on comparative data with Besure OneStep immunoassay, an assay for human Chorionic Gonadotropin currently being marketed." This strongly suggests that the "study" demonstrating equivalence involves comparing the performance of the Platform OneStep test to the predicate Besure OneStep test. For 510(k)s, this often involves:

• Analytical studies: Comparing the ability of both devices to detect known concentrations of hCG in spiked urine samples, and possibly testing for cross-reactivity with interfering substances.
• Clinical studies (often waived or reduced for IVDs demonstrating equivalence to a predicate): Comparing results from both devices using actual patient urine samples, with confirmation by a reference method.

Note: The given text only mentions the comparison as the basis but does not describe the actual study design, results, or statistical analysis that would typically be included in a 510(k) submission to demonstrate substantial equivalence.

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

• Sample Size: Not provided in the given text.
• Data Provenance: Not provided in the given text. For 510(k)s of this type, data typically comes from laboratory studies (analytical) and sometimes small clinical studies. If clinical data were used, the origin and retrospective/prospective nature would be detailed in the full submission.

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 / Not Provided: For a qualitative IVD like a pregnancy test, "ground truth" is typically established by:
  • Known concentrations: For analytical studies, known, manufactured concentrations of hCG in a matrix (e.g., synthetic urine) are used. The "truth" is the presence/absence and concentration of hCG in the prepared sample.
  • Reference method: For clinical studies, the ground truth for patient samples would be established by a highly accurate, quantitative laboratory reference method for hCG (e.g., a laboratory immunoassay with a high level of precision and accuracy), not by human expert interpretation of the test result itself. The test is designed to be read by the lay user.

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

• Not Applicable / Not Provided: Adjudication methods like 2+1 or 3+1 are typically used in clinical studies involving interpretation of complex data (e.g., medical images) by multiple human experts. For a direct-reading qualitative immunoassay like a pregnancy test, the result is either a line or no line. The ground truth (as explained above) would come from known samples or a reference lab test, not from expert adjudication of the stick's line. However, studies might include assessments of "reader variability" among lay users or trained personnel.

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 an in vitro diagnostic test kit, not an AI-driven diagnostic or medical image analysis tool. There is no "AI assistance" for human readers in the context of reading a pregnancy test stick, nor is there typically a complex "case" interpretation that would require MRMC studies.

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

• Not Applicable: This is a physical immunoassay kit, not an algorithm. The "device" is the test stick, which produces a visual result. The human "in the loop" is the person interpreting the line(s) on the test stick. It's a "standalone" test but in the sense of existing as a physical product, not as a software algorithm.

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

• For analytical performance: Known, manufactured concentrations of hCG.
• For clinical performance (if assessed): Results from a qualified, high-accuracy laboratory reference method for quantitative hCG measurement (e.g., a central lab immunoassay).

8. The sample size for the training set

• Not Applicable: This is not an AI/machine learning device that uses a "training set" in that sense. For IVDs, manufacturing processes are validated, and analytical/clinical studies (as described above) are performed using specific sample sizes (which are not provided in the text).

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

• Not Applicable: As above, there is no "training set" in the machine learning context. Ground truth for the evaluation samples (not training) would be established by known concentrations or a reference laboratory method as outlined in point 7.

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