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The CELL-DYN Ruby System is a multiparameter, automated hematology analyzer designed for in vitro diagnostic use in clinical laboratories and physician office laboratories.
The CELL-DYN Ruby System is designed to analyze EDTA-anticoagulated blood and report the following hematological parameters:
White Blood Cell Parameters: WBC - White Blood Cell Concentration, NEU - Neutrophil Absolute Concentration, %N - Neutrophil Percentage of WBC, LYM - Lymphocyte Absolute Concentration, %L - Lymphocyte Percentage of WBC, MONO - Monocyte Absolute Concentration, %M - Monocyte Percentage of WBC, EOS - Eosinophil Absolute Concentration, %E - Eosinophil Percentage of WBC, BASO - Basophil Absolute Concentration, %B - Basophil Percentage of WBC
Red Blood Cell Parameters: RBC - Red Blood Cell Concentration, HCT - Hematocrit, MCV - Mean Cell Volume, RDW - Red Cell Distribution Width, %R - Reticulocyte Percent, RETC - Reticulocyte Absolute Concentration
Hemoglobin Parameters: HGB - Hemoglobin Concentration, MCH - Mean Cell Hemoglobin, MCHC - Mean Cell Hemoglobin Concentration
Platelet Parameters: PLT - Platelet Concentration, MPV - Mean Platelet Volume

The CELL-DYN Ruby System is a tabletop analyzer consisting of the main analyzer, data module, flat panel display station, and printer. The main analyzer and data module are housed in a single chassis. The display station and printer are stand-alone modules. The CELL-DYN Ruby is equipped with a Sample Loader that provides continuous automated closed sampling for up to 50 closed tube samples at a time. The instrument's utilizes the CELL-DYN MAPSST™ technology, laser flow cytometry and a Microsoft® Windows® Operating System, USB connectivity on the data module to allow the interface of a wide variety of printer types and a standard hand-held bar code reader to help expedite patient specimen identification.

The provided text describes the CELL-DYN Ruby™ System, an automated hematology analyzer, and its substantial equivalence to a predicate device, the CELL-DYN® 3200 System. However, the text does not explicitly state specific acceptance criteria in a quantitative manner or provide a detailed study report that proves the device meets such criteria.

The "Equivalency Data" section generally states: "Data on file at Abbott Laboratories consisting of background, carryover, imprecision (reproducibility), analytical measurement range (linearity), and sensitivity and specificity information shows performance to the manufacturer's specifications." This implies that internal studies were conducted to confirm performance against pre-defined specifications, but these specifications themselves are not detailed in the provided document.

Therefore, many of the requested items cannot be definitively answered from the given text.

Here's a breakdown of what can and cannot be extracted:

1. A table of acceptance criteria and the reported device performance

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size: Not specified.
• Data Provenance: Not specified, other than "Data on file at Abbott Laboratories." It's common for such studies to be conducted internally or with clinical partners, potentially in the US (where Abbott Laboratories is based), but this is not confirmed. The document does not specify if the data was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable/Not specified. This device is an automated hematology analyzer, meaning it generates quantitative results for blood parameters. The "ground truth" for its performance would typically involve comparison to reference methods or validated manual counts, not expert consensus on image interpretation.

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

• Not applicable/Not specified. Adjudication methods are typically relevant for subjective assessments, particularly in imaging or pathology. For an automated analyzer, performance is assessed quantitatively against reference methods.

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 an automated hematology analyzer, not an AI-assisted diagnostic tool that aids human readers in interpreting images or data. It performs the analysis itself.

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

• Yes, implicitly. The entire basis of an automated hematology analyzer is its standalone algorithmic performance in quantifying blood parameters. The studies mentioned (background, carryover, imprecision, linearity, sensitivity, specificity) would inherently be conducted on the device's standalone performance.

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

• While not explicitly stated, for an automated hematology analyzer, the "ground truth" or reference method for determining accuracy would likely involve:
  • Reference laboratory methods: Using established, highly accurate laboratory techniques for specific parameters.
  • Validated manual microscopic differentials: For WBC differential, manual counting by highly skilled laboratorians is often considered a gold standard.
  • Calibrator materials: Using materials with known parameter values.

8. The sample size for the training set

• Not applicable/Not specified. This document describes a device (hardware and software) that performs measurements. While the software algorithms within the device might have been developed and refined using data, the document does not refer to "training sets" in the context of machine learning, which is typically where that term applies. The testing described is for performance validation, not algorithm training.

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

• Not applicable/Not specified for the reasons mentioned in point 8.

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