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Long-term ventilator for intensive care. For patient requiring tidal volume starting at 50 ml.

Savina is a long term ventilator unit designed for patients with a tidal volume of 50 ml or more and is used in the intensive care areas, recovery rooms, inter and intra hospital transport and subacute care facilities. NIV means Non-Invasive Ventilation and supports the mask application mode. The NIV Option is available for Savina with SW 2.0. The NIV Option for Savina expands the range of available ventilation strategies to include Non-Invasive Ventilation. NIV is not a new ventilation mode but a different format to deliver ventilation to the patient. With the NIV Option activated, the user can switch the ventilator during preparation of the machine into one of two application modes: a) "Tube" application mode, b) "Mask" application mode. The "Tube" application mode corresponds to the reqular behavior of the device if the NIV option is not activated. If the "Mask" application mode is selected, the user gains the option to configure parts of the device integrated monitoring to adapt the specific need of the mask ventilated patient.

The provided text describes the "NIV Option for Savina" device, which is an enhancement to the Savina ventilator to include Non-Invasive Ventilation (NIV) capabilities. However, the document does NOT contain information about specific acceptance criteria or a study that details device performance against such criteria in the manner requested (e.g., accuracy, sensitivity, specificity, or objective metrics typically found in performance studies).

The document is a 510(k) Summary and a clearance letter, primarily focused on establishing substantial equivalence to predicate devices rather than proving specific performance against predefined acceptance criteria through a detailed study with objective metrics.

Therefore, most of the requested information cannot be extracted directly from the provided text.

Here is a summary of what information can be gathered and what is missing:

1. Table of acceptance criteria and reported device performance:

2. Sample size used for the test set and the data provenance:

• Sample size: Not specified.
• Data provenance: Not specified. The document only states that "Design, development and verification of the device was performed in accordance with FDA guidance and company internal standards" and "The testing and analysis of results provide assurance that the device meets its specifications and is safe and effective." This implies testing was done, but details are absent.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable/Not specified. This type of information is typically related to diagnostic or interpretive devices, which this ventilator option is not. Ground truth for a ventilator would generally relate to its physical performance, safety features, and accuracy of delivered parameters, which are usually measured against physical standards or reference devices, not expert human interpretation.

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

• Not applicable/Not specified. (See point 3 above).

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 device is a ventilator option, not an AI-assisted diagnostic or interpretive system involving human readers.

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

• Not applicable. The device is a physical medical device (ventilator option), not an algorithm in the sense of AI or image analysis. Its "performance" would be assessed through engineering and clinical validation rather than standalone algorithm testing.

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

• Not specified directly. For a ventilator, ground truth would typically refer to established engineering standards, physiological models, or direct measurements against calibrated equipment to verify the accuracy of delivered gas volumes, pressures, flow rates, alarm functionality, and safety features. Clinical outcomes might be considered for overall effectiveness but are not usually the "ground truth" for individual performance metrics.

8. The sample size for the training set:

• Not applicable/Not specified. This term is typically used for AI/machine learning models. While the device underwent "design, development, and verification," the concept of a "training set" in the context of machine learning is not relevant here.

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

• Not applicable/Not specified. (See point 8 above).

In summary: The provided document is a regulatory submission for 510(k) clearance, which focuses on demonstrating substantial equivalence to existing devices. It confirms that the device meets specifications and is safe and effective, but it does not provide the detailed performance study data, acceptance criteria, or specific methodologies (like sample sizes, ground truth establishment, or expert involvement) that would be found in a comprehensive clinical or performance validation study report.

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VentView - a PC programm for displaying ventilation parameters and status messages in both graphical and numerical form for the Drager ventilators Savina, Evita 2 dura and Evita 4.

VentView - a PC programm for displaying ventilation parameters and status messages in both graphical and numerical form for the Drager ventilators Savina, Evita 2 dura and Evita 4.

I am sorry, but the provided text only contains an FDA 510(k) clearance letter for the "VentView" device. This letter indicates that the device has received marketing clearance but does not include information about acceptance criteria, specific studies, or performance data to answer your request.

To provide that information, I would need a different document, such as a summary of safety and effectiveness, a clinical study report, or a detailed technical specification for the VentView device.

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The Drager Sola surgical lights (Sola 1000, 700, 500) are intended to locally illuninate an operating or examination area of the patient's body with high intensity light.

The Drager Sola 300 is intended to be used as an examination light or as a satellite light within a surgical lighting system.

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The provided document describes the acceptance criteria and a study demonstrating the Dräger Sola surgical lights meet these criteria.

Here's the breakdown of the information requested:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• Sample Size: Not explicitly stated as a numerical count of devices tested. The report indicates that the "Sola series were tested," implying a representative sample of Dräger Sola 1000, 700, 500, and 300 models.
• Data Provenance: The document is dated December 1998 and refers to "many years of experience in manufacturing lights" and this product being "on the market in Europe for 4 years" (referencing the current and previous product MLxx0) with no registered complaints. This suggests a retrospective analysis of field performance data and compliance testing based on European market experience. The testing against IEC standards is described as having been performed on the devices. The report originates from Germany ("Dräger Medizintechnik GMBH").

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• The report does not mention a specific number of experts or their qualifications for establishing ground truth in the context of a "test set" for performance evaluation, as one might see in a clinical study.
• The evaluation is based on compliance with established international engineering and medical device safety standards (IEC 60601-1, IEC 60601-2-41) and internal engineering calculations and experience. The implication is that the "ground truth" for safety and performance is defined by these standards and the engineering principles applied during development and testing.

4. Adjudication method for the test set:

• No adjudication method (e.g., 2+1, 3+1, none) is described in the context of a typical clinical test set with human readers. The evaluation is focused on compliance testing against objective engineering standards and internal risk assessments, which would not involve such adjudication.

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 document describes a submission for a surgical lamp (Dräger Sola series), which is a physical medical device, not an AI-powered diagnostic or assistive tool. Therefore, an MRMC comparative effectiveness study involving AI assistance for human readers is not applicable and was not performed.

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

• No. As mentioned above, this is a physical medical device (surgical lamp), not an algorithm. Therefore, a standalone algorithm performance study is not applicable.

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

• The "ground truth" for the device's compliance is primarily defined by:
  • International engineering standards and regulations: IEC 60601-1 and IEC 60601-2-41.
  • Engineering calculations and safety factors: E.g., 4x safety factor for mechanical strength and suspended loads.
  • Manufacturing standards and in-house inspection: For components like diffusing lenses.
  • Retrospective field experience: "No complaints have been registered," "No complaints have been received which have necessitated a change in the product."

8. The sample size for the training set:

• Not applicable. As this is a physical medical device and not an AI/machine learning algorithm, there is no concept of a "training set" in the context described. The device's design and manufacturing rely on established engineering principles and standards, not data-driven model training.

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

• Not applicable. There is no training set for this type of device.

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