(20 days)
QuikClot® Brand Hemostatic Agent is intended for emergency use only as an external temporary traumatic wound treatment to achieve hemostasis for moderate to severe bleeding.
The new bead form of QuikClot® Brand Hemostatic Agent, also called "Advanced Beaded Formulation", is intended for emergency use as an external temporary traumatic wound treatment to achieve hemostasis and prevent blood loss. The beads consist of a synthetic molecular sieve (zeolite) that accelerates the body's natural clotting processes by increasing the concentration of platelets and clotting factors at the wound site. Individual sieve particles of the hemostatic agent adsorb water molecules. As the water is removed from the blood, the platelets and clotting factors are concentrated. The platelets have been activated by the normal response to injury. This adsorption process is exothermic. The resultant increase in temperature at the site of application increases the rate of the clotting reactions and platelet aggregation and adhesion. Both of the mechanisms described above, concentration of clotting factors and the increase in rates of platelet aggregation/adhesion, work together to increase the clotting rate. This would be consistent with what is known about the effects of temperature and concentration on coagulation enzyme activity and platelet function. The product is designed and packaged to be easily packed, carried and applied using only one hand. It is well suited for moderate to large eviscerating wounds, to create hemostasis by coagulation. Used in conjunction with direct pressure, QuikClot® Brand Hemostatic Agent, Advanced Beaded Formulation reduces blood loss dramatically, and significantly increases survivability of high volume catastrophic wounds.
The provided document is a 510(k) premarket notification for a medical device (QuikClot® Brand Hemostatic Agent, Advanced Beaded Formulation). It describes the device, its intended use, and claims substantial equivalence to a predicate device.
However, the document does not contain the acceptance criteria and study details as typically understood for AI/ML device performance evaluation studies. The information present pertains to the regulatory clearance process for a physical hemostatic agent, not an AI/ML algorithm.
Therefore, many of the requested items (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, training set size, ground truth for training) are not applicable or cannot be extracted from this document as these are specific to AI/ML device evaluations.
Here's a breakdown of what can be extracted and what cannot:
1. A table of acceptance criteria and the reported device performance
- Acceptance Criteria: Not explicitly stated as pass/fail metrics within a table in this document. The document relies on equivalence to a predicate device.
- Reported Device Performance:
- Claimed Performance: "performs at least as well as the current granular product in the swine femoral artery model."
- Mechanism of Action: Accelerates the body's natural clotting processes by increasing the concentration of platelets and clotting factors at the wound site, and the exothermic adsorption process increases temperature, which increases clotting rates and platelet aggregation/adhesion.
- Clinical Goal: "reduces blood loss dramatically, and significantly increases survivability of high volume catastrophic wounds."
2. Sample sized used for the test set and the data provenance
- Sample Size: "In-Vivo testing on swine was performed". No specific number of subjects (swine) is given in this summary.
- Data Provenance:
- Country of Origin: Performed at the Portsmouth Naval Hospital in Virginia (USA).
- Retrospective or Prospective: Implied to be prospective in-vivo testing as it was "performed" for this submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not Applicable. This is for an in-vivo animal study of a physical device, not an AI/ML algorithm requiring expert interpretation of data.
4. Adjudication method for the test set
- Not Applicable. See point 3.
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 for a physical medical device, not an AI/ML algorithm.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not Applicable. This is for a physical medical device.
7. The type of ground truth used
- Ground Truth: The "ground truth" in this context would likely be direct physiological measurements of hemostasis and blood loss in the swine model, assessed by animal researchers/veterinarians. No specific methodology for ground truth establishment (e.g., pathology, outcomes data) is detailed beyond "In-Vivo testing on swine."
8. The sample size for the training set
- Not Applicable. This refers to a physical device, not an AI/ML algorithm that requires a "training set."
9. How the ground truth for the training set was established
- Not Applicable. See point 8.
Summary of what is present:
- Device: QuikClot® Brand Hemostatic Agent, Advanced Beaded Formulation (a physical hemostatic product).
- Indication: Emergency use only as an external temporary traumatic wound treatment to achieve hemostasis for moderate to severe bleeding.
- Study Type: In-Vivo testing on swine.
- Outcome Claim: Performs at least as well as the predicate (granular) product in the swine femoral artery model.
- Basis of Clearance: Substantial equivalence to a legally marketed predicate device (QuikClot® Brand Hemostatic Granules, K013390).
- Additional Tests (for biocompatibility, likely related to the predicate): Agar Overlay Cytotoxicity Test, Water Adsorption Rate, Skin Sensitization, Skin Irritation, Intracutaneous Test, Muscle Implant, Long-Term Muscle Implant.
To reiterate, the provided text is a 510(k) summary for a physical hemostatic agent and does not contain the detailed performance study information typically requested for AI/ML devices.
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