K Number
K081229
Date Cleared
2008-07-21

(82 days)

Product Code
Regulation Number
862.1675
Panel
CH
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Saf-T Closed Blood Collection System® device is attached to a peripheral IV catheter at the time of IV catheter placement for use as a direct blood draw device into a vacuum tube or to allow a syringe blood draw and transfer to fill vacuum tubes.

The Saf-T Closed Blood Collection System® device is intended for use as a direct blood draw device into a vacuum tube or to allow a syringe blood draw and transfer to fill vacuum tubes.

Device Description

The Saf-T Closed Blood Collection System® device is a venous blood drawing device that is currently used as syringe draw and transfer device to fill vacuum tubes. This submission expands the indications to allow a direct blood draw into a vacuum tube. A syringe draw and transfer remains as an option - the Clinician can choose the method depending upon patient status. The use of this device involves minimal Luer manipulations, which minimizes the risk of sample contamination. This submission also increases the holder length to be equal to similar devices, the longer length will aid in vacuum tube alignment into the holder.

AI/ML Overview

The provided text describes a 510(k) summary for the "Saf-T Closed Blood Collection System®" device. However, it does not contain information about acceptance criteria or a study designed to prove the device meets specific performance metrics in the way typically required for a novel AI/software medical device.

Instead, this submission is for a traditional medical device (venous blood collection device) seeking a 510(k) clearance based on substantial equivalence to predicate devices. The study mentioned is "Bench testing," which confirmed similar performance specifications between the proposed and predicate devices. This type of testing is generally mechanical or functional and doesn't involve clinical performance metrics like sensitivity, specificity, or reader studies.

Therefore, many of the requested items (acceptance criteria, device performance, sample size for test sets, data provenance, expert ground truth, adjudication method, MRMC studies, standalone performance, training set details) are not applicable or not present in this document because it describes a traditional device clearance, not an AI/software device.

Here's an attempt to answer the questions based only on the provided text, highlighting where information is absent:


Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Not Explicitly Stated)Reported Device Performance
Implied: Similar performance specifications to predicate device.Bench testing confirms that the proposed device and the predicate device have similar performance specifications.
Implied: Safety and Effectiveness for intended use.Bench testing conducted demonstrates that the proposed device is safe and effective and is substantially equivalent to the predicate device.

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

  • Sample Size: Not specified in the document. The term "bench testing" typically implies testing of manufacturing samples, but the exact number is not provided.
  • Data Provenance: Not specified. "Bench testing" usually occurs in a laboratory or manufacturing setting. No information on country of origin or retrospective/prospective nature is given.

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

  • Not applicable / Not specified. As this is a physical device and the study is "bench testing," there is no indication of expert involvement in establishing a "ground truth" in the diagnostic sense. The performance is likely measured against predefined engineering specifications.

4. Adjudication Method for the Test Set

  • Not applicable / Not specified. Adjudication methods (like 2+1) are typically used for expert review of images or clinical cases to establish ground truth. This is not mentioned in the context of bench testing for a physical device.

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. An MRMC study was not done. This type of study is relevant for AI/software devices that assist human readers in diagnosis or interpretation, which is not the function of this blood collection system.

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

  • Not applicable. This device is a physical venous blood collection system, not an algorithm. Therefore, a standalone algorithm performance study is not relevant.

7. The Type of Ground Truth Used

  • Implicitly, engineering specifications/design requirements. For bench testing of a physical device, the "ground truth" would be the device's adherence to its design specifications, functional requirements (e.g., blood flow, luer connection integrity, vacuum tube alignment), and safety standards. No pathology or outcomes data is mentioned for ground truth.

8. The Sample Size for the Training Set

  • Not applicable / Not specified. This document describes a physical medical device, not an AI/machine learning algorithm, so there is no concept of a "training set" in this context.

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

  • Not applicable. As there is no training set for an AI algorithm, this question is not relevant.

Summary regarding AI/Software Device Context:

The provided text is for a 510(k) submission of a traditional, physical medical device. The "Non-Clinical Data" section explicitly states "Bench testing confirms that the proposed device and the predicate device have similar performance specifications" and "Clinical Data: Not Required." This indicates that the regulatory pathway relied on engineering and functional testing to demonstrate substantial equivalence, rather than clinical trials or performance assessments relevant to AI/software diagnostic devices. Therefore, most of the detailed questions about acceptance criteria for AI performance, clinical study design, and AI model evaluation are not addressed in this document.

§ 862.1675 Blood specimen collection device.

(a)
Identification. A blood specimen collection device is a device intended for medical purposes to collect and to handle blood specimens and to separate serum from nonserum (cellular) components prior to further testing. This generic type device may include blood collection tubes, vials, systems, serum separators, blood collection trays, or vacuum sample tubes.(b)
Classification. Class II.