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510(k) Data Aggregation
(77 days)
KAWASUMI LABORATORIES PHILEBOTOMY SET
A CONDUIT FOR BLOOD REMOVAL FROM A PATIENT TO A VACUUM BOTTLE TO AID IN THE TREATMENT OF A DISEASE OR OTHER CONDITION.
A STERILE, SINGLE USE DEVICE FOR WITHDRAWING BLOOD. BASIC CONCEPT: A CONDUIT USED FOR WITHDRAWING BLOOD FROM THE PATIENT'S VEIN TO A VACUUM BOTTLE RESERVOIR
This document describes a 510(k) submission for a medical device (Kawasumi Laboratories Phlebotomy Set) and, as such, focuses on demonstrating substantial equivalence to a predicate device rather than comprehensive performance studies with detailed acceptance criteria typically found in AI/ML device submissions.
Therefore, many of the requested elements (e.g., sample sizes for test sets, number of experts, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable or available in this type of regulatory submission. The device is a relatively simple, sterile, single-use blood collection set, and the focus is on its basic function and safety.
Here's a breakdown of the available information based on your request:
1. Table of Acceptance Criteria and the Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Biocompatibility: Device materials contacting body fluids must be suitable for intended use. | Kawasumi Laboratories conducted biocompatibility tests on body fluid-contacting material portions. The data is believed to show the device is suitable for its intended use. (Implied acceptance: No adverse biocompatibility reactions or material toxicity.) |
| Pyrogenicity: Device must be non-pyrogenic. | The device meets all pyrogenicity test requirements. (Implied acceptance: Absence of fever-inducing substances.) |
| Performance: Device effectively removes blood from a patient into a vacuum bottle, performing as well as the predicate device. | The device's basic concept is "A conduit used for withdrawing blood from the patient's vein to a vacuum bottle reservoir." The submission states, "There are no significant performance characteristics of this device compared to substantially equivalent devices marketed for sale... The device is used to remove blood from a patient into a vacuum bottle." Conclusion: The device "performs as well as the predicate device." |
| Safety: Device is as safe as the predicate device. | Conclusion: "Therefore, it is as safe as the predicate device and performs as well as the predicate device." |
2. Sample size used for the test set and the data provenance
- Not applicable/Available. This submission focuses on demonstrating substantial equivalence through design and material characteristics, along with standard biocompatibility and pyrogenicity testing, rather than a clinical "test set" in the context of AI/ML or diagnostic performance.
- Data Provenance: Not specified, but standard regulatory tests (biocompatibility, pyrogenicity) are typically performed in certified laboratories.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable/Available. There is no "ground truth" establishment in the sense of expert review of data for a diagnostic or AI/ML algorithm. Safety and performance are assessed via specified tests and comparison to a predicate.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable/Available. No such adjudication method is mentioned or relevant for this type of device submission.
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. This is a basic medical device (phlebotomy set), not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No. This is a basic medical device, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable. The "ground truth" for this device's performance and safety is based on validated laboratory testing methods (e.g., ISO standards for biocompatibility and pyrogenicity) and the established performance of the predicate device.
8. The sample size for the training set
- Not applicable/Available. There is no "training set" in the context of an AI/ML algorithm.
9. How the ground truth for the training set was established
- Not applicable/Available. No training set exists for this device.
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