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Each of the four models within the Series 9100+ PLUS (i.e., Model 9120, Model 9118, Model 9110, and Model 9100 Rx) is intended for use as a fully automated hematology cell counter for the in vitro diagnostic testing of whole blood specimens. The Series 9100+ PLUS also is intended to flag or identify specimens containing abnormal blood cells.

The Series 9100+ PLUS is comprised of four models of hematology analyzers: Models 9120, 9118, 9110, and 9100 Rx. The most advanced hematology analyzer of the four models (i.e., the model with the greatest number of testing parameters) is the Model 9120, testing a total of 20 parameters. The other models in the Series 9100+ PLUS (i.e., Models 9118, 9110, and 9100 Rx) have exactly the same technological design and electronics as the Model 9120, except that each of these three models lacks one or more of the testing parameters and/or features offered by the Model 9120. This downgrading is achieved in models other than the Model 9120 simply by suppressing or eliminating the software functions that would otherwise allow each of those analyzers to test all of the possible parameters.

Three of the four models in the Series 9100+ PLUS (i.e., Models 9120, 9118, and 9100 Rx) contain a built-in 5-, 3-. or 1-Part Differential software package (respectively) that has the ability to perform interpretive 5-part and quantitative 3or 1-part white cell histogram differentials.

The interpretive report for the Model 9120 and the quantitative reports for the Model 9118 and the Model 9100Rx removes subjectivity and provides possible suggestions of interpretation of the white cell, and platelet histograms based on a computer comparison of the histogram pattern with a multiplicity of pre-set limits. The interpretive report for the Model 9120 does not provide positive identification of cell types, but it alerts the user to the possible presence of abnormally high or low concentrations of normal cell types, abnormal cell types, and abnormally small or large sizes of normal cell types. Both the interpretive and the quantitative reports also provide one or more messages that categorize suspected abnormalities.

The rate of determination for each model in the Series 9100+ PLUS is approximately one sample per 1.33 minutes. This rate includes the time from introduction of the whole blood sample to sample analysis, along with the display and printing of the test results. The system is totally automated with an internal dilution system.

Each model in the Series 9100+ PLUS has a cap piercer module that permits sampling of the blood specimens without removing the stopper from the blood vacuum collection tube. An "AutoSampler" module (denoted by the term "Ax") is optional and allows for the automatic mixing and sampling of multiple EDTAanticoagulated blood specimens from a batch of closed 5 mL vacuum tubes. The AutoSampler also has a Bar Code Scanner option which enables the automatic identification entry of tubes labeled with a standard bar code. Additionally, a manual Bar Code Scanner is available which functions independently of the the AutoSampler, and the user may add the Bar Code Scanner option to each model of the Series 9100+ PLUS without adding the AutoSampler module.

A blood sample can be introduced to the hematology analyzer by one of five methods: (1) the whole blood mode (through the sample probe); (2) the prediluted (fingerstick) sample mode; (3) the platelet-rich plasma mode; (4) the cap piercer mode; or (5) the "Ax" option. Each model of hematology analyzer within the Series 9100+ PLUS uses the same methods to measure the given parameters. The Series 9100+ PLUS makes use of several reagents and supplies.

This document describes the Serono Diagnostics, Inc.'s System 9100+ PLUS Automated Hematology Analyzers. However, the provided text does not contain acceptance criteria or the specific results of a study designed to prove the device meets said criteria.

The document discusses analytical performance testing but does not present the acceptance criteria for those tests or the detailed results in a format that directly addresses the prompt's request for a table of acceptance criteria and reported performance. It simply states that the device "functioned as intended."

Therefore, I cannot fulfill all parts of your request. I can, however, extract information about the types of studies performed, but without the acceptance criteria and detailed performance values, a table as requested is not possible.

Here's a breakdown of what can be extracted based on the provided text, and what cannot:

Information that CANNOT be provided from the text:

• A table of acceptance criteria and the reported device performance: This critical information is absent. The document mentions types of performance testing but does not provide specific criteria (e.g., "linearity R^2 > 0.99") or the exact numerical results for the device against those (unspecified) criteria.
• Sample sizes used for the test set and the data provenance: While performance testing was done, the sample sizes for these tests are not mentioned, nor is the origin of the data (country, retrospective/prospective).
• Number of experts used to establish the ground truth for the test set and their qualifications: This information is not present.
• Adjudication method for the test set: Not mentioned.
• If a multi reader multi case (MRMC) comparative effectiveness study was done, and its effect size: This type of study is not mentioned. The device is an automated analyzer, not one that typically involves human readers in an MRMC study for its primary validation.
• The type of ground truth used: Not explicitly stated for any of the performance tests.
• The sample size for the training set: The document discusses performance testing but does not mention a "training set" in the context of machine learning, as this device appears to be an automated analyzer based on established measurement principles, not a machine learning model.
• How the ground truth for the training set was established: Not applicable, as no training set is mentioned in the context of the device's validation.

Information that CAN be inferred or extracted about the studies performed (although lacking detailed results):

1. Acceptance criteria and reported device performance:

   • Not provided. The document states: "In all instances, the Series 9100+ PLUS functioned as intended. These test results demonstrated that the Series 9100+ PLUS is both effective for its intended use and functions in a substantially equivalent manner to the predicate devices." This is a general statement, not specific criteria or performance metrics.

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

   • Not provided. The text does not specify sample sizes or data provenance for any of the performance tests.

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

   • Not provided.

4. Adjudication method for the test set:

   • Not provided.

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 device is an automated hematology analyzer, not an AI-assisted diagnostic tool for human readers in the way an MRMC study would typically evaluate.

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

   • Yes, standalone performance testing was done. The listed performance tests (Linearity, Precision, Accuracy, Carryover) evaluate the performance of the automated analyzer itself, without human intervention in the primary measurement.

7. The type of ground truth used:

   • The document implies that "comparisons" were made, especially for accuracy (e.g., "mode-to-mode comparison with sample run in the whole blood mode") and for substantial equivalence ("similar performance specifications and testing results for such analyses as correlation coefficient, linearity, precision... and accuracy" compared to predicate devices). This suggests that the ground truth for these analytical performance studies would typically be established by:
     • Reference methods or highly accurate laboratory instruments: For linearity, precision, and accuracy compared to a known value or a more established method.
     • Comparison to predicate devices: A key part of the substantial equivalence argument, implying that the performance of the new device aligns with that of the established predicate.

8. The sample size for the training set:

   • Not applicable/Not provided. This document describes an automated hematology analyzer, not a device developed using machine learning that would have a distinct "training set." Its operational parameters are likely based on chemical and physical principles, not on learned patterns from a large dataset.

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

   • Not applicable/Not provided. (See point 8).

In summary, while the document categorizes the types of performance tests conducted, it fails to provide the specific acceptance criteria and the detailed quantitative results required to complete the requested table and further analyses. The device's nature as an automated analyzer means certain types of studies (like MRMC or those involving AI-specific training sets) are not relevant to its validation as described.

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