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The CAPILLARYS NEONAT Hb kit is designed for the separation of the normal hemoglobins (F and A) in blood samples from human new-borns, and for the major hemoglobin vanants (S, C, E, D and Bart's), by electrophoresis in alkaline buffer (pH 9.4) with the CAPILLARYS 2 System. The CAPILLARYS NEONAT Hb kit is designed for laboratory use.

The CAPILLARYS 2 is an automated analyzer which performs a complete hemoglobin profile for the qualitative analysis of hemoglobins. The assay is performed on the hemolysate of whole blood samples previously collected on filter paper.

For In Vitro Diagnostic Use.

The Hb AF Control is designed:

• for the migration control before starting a new analysis sequence and for the qualitative quality control, for human hemoglobins A and F with the SEBIA CAPILLARYS NEONAT Hb electrophoresis procedure used with the CAPILLARYS 2 system, and,

• for the quantitative quality control for detection of the human hemoglobins A, F and A2 with the SEBIA electrophoresis procedures : HYDRAGEL HEMOGLOBIN(E) used with the HYDRASYS system, CAPILLARYS HEMOGLOBIN(E) used with the CAPILLARYS system and MINICAP HEMOGLOBIN(E) used with the MINICAP system.

The Hb AF Control is designed for laboratory use. It should be used (with its bar code label for the CAPILLARYS and MINICAP procedures) like a normal human blood. The values obtained must fall within the range provided with each batch of Hb AF Control.

For In Vitro Diagnostic Use.

The CAPILLARYS 2 is an automated analyzer which performs a complete hemoglobin profile for the qualitative analysis of hemoglobins. The assay is performed on the hemolysate of whole blood samples previously collected on filter paper.

The provided text is a 510(k) premarket notification decision letter from the FDA regarding a medical device, specifically the CAPILLARYS NEONAT Hb kit and Hb AF CONTROL. This type of document typically focuses on establishing substantial equivalence to a predicate device rather than detailing extensive clinical study results with specific acceptance criteria, sample sizes for training or test sets, or ground truth establishment methods for an AI/algorithm-based device.

Therefore, the information requested in your prompt regarding acceptance criteria, study details, sample sizes, expert qualifications, and AI-specific metrics (MRMC, standalone performance, training set ground truth) is not present in the provided document.

This document confirms that the device is substantially equivalent to legally marketed predicate devices for its stated indications for use, without delving into the detailed experimental design and results that would be expected for a novel AI-driven diagnostic.

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The Saturn 9000 system generates digital X-ray images that can be used for general X-ray system not for Mammography. The Saturn 9000 system can interface to traditional X-ray generator and get digital X-ray image. The Saturn 9000 is intended to be used in same clinical application as traditional film-screen based general radiography system.

The Saturn 9000 Is equipped with a digital detector, X-ray generator interface, and image acquisition workstation. The digital detector is a-Se deposited plat panel detector. The input X-ray photons are absorbed in a-Se layer that creates an electrical charge which is representation of the X-ray input. The charge is read-out by a matrix scan of the array that converts the charges into a modulated electrical signal. X-ray exposure is controlled by switch box, which also controls the acquisition timing of the detector. Saturn 9000 includes acquisition workstation ("AWS") monitor, keyboard and mouse, computer, electronics, and accessory storage. The resultant output signal can be transmitted to remote viewing sites. and/or it can be stored electronically for later viewing. The AWS is used for image acquisition, processing, and display. The AWS can also be used for database management and can send images to archive, review or filming,

The provided 510(k) summary for the New Medical Co., LTD. Saturn 9000 focuses on demonstrating substantial equivalence to a predicate device for general X-ray imaging, excluding mammography. It relies heavily on non-clinical testing and a "concurrence study" but provides very limited detail about the clinical study design or its results in terms of specific performance metrics or acceptance criteria related to a specific product.

Therefore, many of the requested details about acceptance criteria, specific device performance, sample sizes, ground truth establishment, expert qualifications, and MRMC studies are not available in the provided text.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Limitations: The document does not provide specific numerical acceptance criteria (e.g., minimum AUC, sensitivity, specificity) or specific numerical performance results for the Saturn 9000. It relies on a general statement of "compatibility" and "concurrence."

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

• Sample Size for Test Set: Not explicitly stated. The document mentions a "concurrence study" and an "independent clinical trial" but does not specify how many patients or images were included.
• Data Provenance: Not explicitly stated. The context implies the study was conducted to support a submission in the US (FDA), but the country of origin of the actual patient data is not mentioned. It is also not specified whether the data was retrospective or prospective.

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

• This information is not provided in the document. The abstract nature of the clinical study description means there is no detail on who established ground truth or their qualifications.

4. Adjudication Method for the Test Set

• This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

• No, an MRMC comparative effectiveness study involving AI assistance was not done. The device being described is a digital X-ray image capture device (hardware), not an AI algorithm. The study described is a "concurrence study" aimed at showing the device produces images comparable to a predicate device, which is a film-screen system.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• This question is not applicable as the Saturn 9000 is a hardware device (digital X-ray system), not an AI algorithm. Its performance is inherent in its ability to capture images.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• This information is not explicitly stated. Given it's a "concurrence study" comparing a new digital system to a traditional film-screen system, the "ground truth" likely revolved around comparing image quality and diagnostic utility as interpreted by human readers, possibly against the findings on the predicate device's images (e.g., if a lesion was visible on film, was it also visible on the digital image?). However, the specific methodology for establishing this "ground truth" (e.g., expert consensus on specific clinical findings) is not detailed.

8. The Sample Size for the Training Set

• This information is not applicable/not provided. The Saturn 9000 is a hardware device, not an AI model that requires a training set of images in the typical sense. Any "training" would be related to calibrating the hardware itself, not an algorithm's learning.

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

• This information is not applicable/not provided for the same reasons as point 8.

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