K Number
K130043
Date Cleared
2013-02-12

(35 days)

Product Code
Regulation Number
868.5830
Panel
AN
Reference & Predicate Devices
Predicate For
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

AUTOTRANSFUSION

  1. For the collection of autologuous blood from the patient's pleural cavity or mediastinal area for reinfusion purposes in trauma and post-operative situations
    CHEST DRAINAGE
  2. To evacuate air and/or fluid from the chest cavity or mediastinum
  3. To help prevent air and/or fluid from re-accumulating in the chest cavity or mediastinum.
  4. To help re-establish and maintain normal intra-thoracic pressure gradients.
  5. To facilitate complete lung re-expansion to restore normal breathing dynamics.

The Pleur-evac® Autotransfusion Bag is indicated as a sterile, single use device used for collection and reinfusion of autologous blood from the thoracic cavity when attached to a Pleur-evac® System. The fluid path is non-pyrogenic.

Device Description

The Pleur-evac Sahara® Plus Continuous Reinfusion Autotransfusion System is provided as a sterile unit intended for single patient use. The fluid path is non-pyrogenic. The Pleur-evac Sahara Plus System is used for the collection and continuous reinfusion of autologous blood. By attaching the Pleur-evac Sahara Autotransfusion Bag, the Pleurevac Sahara Plus System serves as a bag reinfusion system. When autotransfusion is completed, the Pleur-evac Sahara Plus System can serve as a chest drainage collection unit.

AI/ML Overview

Here's an analysis of the provided text regarding the acceptance criteria and the study that proves the device meets them, structured to address your specific points:

The provided document describes a 510(k) submission for the Pleur-evac Sahara® Plus Continuous Reinfusion Autotransfusion System. This is a medical device, and the submission aims to demonstrate substantial equivalence to a predicate device, rather than proving efficacy in a clinical setting in the way an AI-powered diagnostic device might. Therefore, many of the questions related to AI-specific study design (like MRMC studies, AI assistance, ground truth for training sets, number of experts for ground truth, etc.) are not applicable to this type of device and submission.

The "study" described here is primarily bench testing to verify performance characteristics of a material change.

  1. A table of acceptance criteria and the reported device performance
Acceptance Criteria (Test Specification)Reported Device Performance (Result)
Pressure Equalization RatePASS (All values tested allowed the pressure in a full collection chamber to rise from 17 cm H2O vacuum to 2 cm H2O vacuum between 1 second and 22 seconds.)
Filter Position VisualPASS (All covers tested contacted the filter material on the entire cover retaining surface.)
Filter VisualPASS (All Pleur-evac units tested contained a filter in the HNRV assembly.)
ASTM F1608-00(2009) (Bacterial Filter Efficacy)PASS (All Pleur-evac units tested had an LRV > 4. This standard typically refers to the retention of bacteria/viruses, establishing sterility or barrier efficacy.)
  1. Sample sizes used for the test set and the data provenance

    • Sample Size: The document does not explicitly state the exact numerical sample size for each test ("All values tested," "All covers tested," "All Pleur-evac units tested"). However, it consistently refers to "All" units tested for each criterion, implying that every unit subjected to that specific test passed. In a 510(k), particularly for bench testing, this often means a statistically valid number of samples were tested to demonstrate consistent performance within a lot or production run, though the exact number isn't quantified in this summary.
    • Data Provenance: The data is from bench testing conducted by the manufacturer, Teleflex Medical, Inc. The location of the testing is not specified, but the manufacturer's address is in Research Triangle Park, NC, USA. The data is prospective in the sense that the tests were performed specifically to validate the material change and support the 510(k) submission.
  2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    • N/A. As this is bench testing of physical device performance based on established engineering and material standards, expert clinical judgment for "ground truth" (as in image interpretation) is not applicable. The "ground truth" here is determined by objective measurements and visual inspections against predefined engineering specifications.
  3. Adjudication method for the test set

    • N/A. Adjudication methods (like 2+1 or 3+1) are typically used for subjectively assessed data, such as medical image interpretations, to establish a consensus ground truth. For objective bench tests, results are directly measured or visually verified against clear PASS/FAIL criteria, so an adjudication process is not relevant.
  4. 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 not an AI-powered diagnostic device. It's an autotransfusion system with a material change. Therefore, MRMC studies and AI assistance metrics are not applicable.
  5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    • N/A. This is not an algorithm or software-based device. It's a hardware medical device.
  6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

    • The "ground truth" for this device's performance validation is based on engineering specifications and established test methods (e.g., pressure equalization rate, visual inspection criteria, and the ASTM F1608-00(2009) standard which relates to bacterial filtration efficacy). It's objective, measurable performance against physical and material requirements, rather than clinical outcomes or interpretations.
  7. The sample size for the training set

    • N/A. There is no "training set" as this is not a machine learning/AI device.
  8. How the ground truth for the training set was established

    • N/A. There is no training set or associated ground truth establishment for this type of device validation.

§ 868.5830 Autotransfusion apparatus.

(a)
Identification. An autotransfusion apparatus is a device used to collect and reinfuse the blood lost by a patient due to surgery or trauma.(b)
Classification. Class II (performance standards).