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The Accu-Chek Guide Solo diabetes manager blood glucose monitoring system is comprised of the Accu-Chek Guide Solo diabetes manager blood glucose meter, Accu-Chek Bolus Advisor and the Accu-Chek Guide test strips.

The Accu-Chek Guide Solo diabetes manager blood glucose monitoring system is intended to quantitatively measure glucose in fresh capillary whole blood from the fingertip. The Accu-Chek Guide Solo diabetes manager blood glucose monitoring system is intended for self-testing outside the body (in vitro diagnostic use), by individuals with diabetes at home as an aid in monitoring the effectiveness of glucose control.

The Accu-Chek Guide Solo diabetes manager blood glucose monitoring system is intended to be used by a single person and should not be shared.

This Accu-Chek Guide Solo diabetes manager blood glucose monitoring system is not for use in diagnosis or screening of diabetes mellitus, nor for neonatal use.

The Accu-Chek Bolus Advisor, as a component of the Accu-Chek Guide Solo diabetes manager, is indicated for the management of diabetes by calculating an insulin dose or carbohydrate intake based on user-entered data. Before its use, a physician or healthcare professional must activate the bolus calculator and provide the patient-specific target blood glucose, insulin-to-carbohydrate ratio, and insulin sensitivity parameters to be programmed into the software. The Accu-Chek bolus advisor is intended for home use.

The Accu-Chek Guide Solo diabetes manager steers the Accu-Chek Solo micropump.

The Accu-Chek Guide Solo diabetes manager blood glucose monitoring system consists of the following components:

• Accu-Chek Guide Solo diabetes manager
• Accu-Chek Bolus Advisor
• Accu-Chek Guide Test Strips

The Accu-Chek Guide Solo diabetes manager blood glucose monitoring system is a handheld device that incorporates features to aid in self-monitoring of blood glucose. The blood glucose results are displayed on the screen and stored in the meter's memory, and may also be transmitted via USB wireless communication. Our blood glucose monitoring system creates a glucose result from an amperometric reaction. Capillary whole blood from the user's fingertip reacts with the chemicals in the test strip to create a harmless electrical current in the test strip. The blood glucose meter reads the current and gives a blood glucose result.

The Accu-Chek Guide Solo diabetes manager is a remote control for the Accu-Chek Solo micropump.

This document describes the acceptance criteria and the study proving the device, Accu-Chek Guide Solo diabetes manager blood glucose monitoring system, meets those criteria.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for accuracy are based on comparison to a laboratory reference method (Roche/Hitachi cobas c 501 PCA-HK) for fresh capillary whole blood samples. While explicit acceptance criteria (e.g., "must be X% within Y% of laboratory reference") are not directly stated as a separate table, the reported clinical performance data demonstrates the device's accuracy against recognized standards. The ISO 15197:2013 standard often serves as a benchmark for blood glucose monitoring systems, requiring at least 95% of results to fall within ±15 mg/dL for glucose concentrations 0.99) | All Lots: 0.998 |
| Interference | No significant interference from common interfering substances at relevant concentrations. | Met acceptance criteria, with specific limitations for abnormally high concentrations (>5 mg/dL) of ascorbic acid and xylose. Labeling reflects these limitations. |
| Robustness (Flex Studies) | System operates within specified ranges under stress conditions and detects errors correctly. | Passed mechanical vibration and shock, operating conditions (temperature/humidity), altitude effects, and stability testing. Handled samples outside measuring range, short sample detection, sample perturbation, intermittent sampling, and used strips by operating within ranges or displaying errors. |
| Electromagnetic Interference (EMC) & Electrical Safety | Compliance with relevant national and international standards. | Passed IEC 61010-1, IEC 60601-1-2, IEC 61000-4-2, IEC 61000-4-3, IEC 61000-4-6, IEC 61000-4-8, and FCC 47 CFR 15 Part B. |

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

• Sample Size for Clinical Performance Test Set: 350 individual results (implied by "348 of 350 results," "343 of 350 results," etc.).
• Data Provenance: The clinical study was conducted in the United States and involved non-professional, inexperienced lay persons as intended users. The study explicitly states it uses "fresh capillary whole blood from the fingertip," indicating a prospective collection of data for this study. The precision and linearity studies used venous blood samples and linearity solutions respectively, which would typically be controlled, prospective experiments.

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

The ground truth for the clinical performance study was established by a "Roche/Hitachi cobas c 501 PCA-HK reference method" and "blood glucose readings obtained by trained technicians." The document does not specify the number of trained technicians or their specific qualifications (e.g., years of experience), but "trained technicians" implies expert personnel skilled in laboratory reference methods.

4. Adjudication Method for the Test Set

Not applicable. For a quantitative measurement device like a blood glucose meter, ground truth is established by a highly accurate laboratory reference instrument, not by expert adjudication of discrete classifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, with Effect Size

Not applicable. This device is a quantitative blood glucose monitoring system, not an AI-assisted diagnostic imaging device requiring MRMC studies. The human "readers" here are the lay users, and the study assesses their ability to obtain accurate readings with the device (standalone) compared to a lab reference, rather than comparing human interpretation with and without AI assistance.

6. If a Standalone Performance Study was done

Yes, a standalone performance study was done. The "Clinical Performance" section directly evaluates the accuracy of the Accu-Chek Guide Solo diabetes manager Blood Glucose monitoring system "compared to the Roche/Hitachi cobas c 501 PCA-HK reference method" when used by lay persons. This is a direct assessment of the device's performance in the hands of its intended user, without comparison to a human interpretation as an alternative, but rather against a gold standard biochemical measurement.

7. The Type of Ground Truth Used

The primary ground truth for the clinical accuracy study was laboratory reference method results, specifically from the "Roche/Hitachi cobas c 501 PCA-HK." This is a gold standard in laboratory glucose measurement. For precision and linearity, the ground truth was established by prepared blood samples (for precision) and linearity solutions (for linearity), with their precise glucose concentrations determined by highly accurate laboratory methods.

8. The Sample Size for the Training Set

The document does not specify the sample size for the training set (if any specific "training" was done in an AI/ML context, which is not directly indicated for this type of device, but rather for its software components). The precision and linearity studies used specific sample sizes:

• Within-Run Precision: Ten replicate assays on ten meters using three strip lots at eight concentration levels.
• Intermediate Precision: Ten replicate assays on ten meters using three strip lots at six concentration levels.
• Linearity: Blood samples prepared to a hematocrit range of 36-52% and run on 36 meters using strips from three lots at eleven blood glucose concentration levels.

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

Given that this is a blood glucose meter (a measurement device relying on electrochemical principles, not primarily AI/ML for its core glucose measurement), "training set" and "ground truth for training set" in the context of typical AI/ML development are not directly applicable for the glucose measurement component. The "training" for such a device is in its chemical and electrical calibration during manufacturing and design, which is validated through the precision, linearity, and accuracy studies using known concentration materials and reference methods.

For the "Accu-Chek Bolus Advisor" software component, which is new, the document states: "Before its use, a physician or healthcare professional must activate the bolus calculator and provide the patient-specific target blood glucose, insulin-to-carbohydrate ratio, and insulin sensitivity parameters to be programmed into the software." This implies that the 'ground truth' or calibration for this specific software functionality is based on individual patient parameters set by a healthcare professional, rather than a general training dataset. The software "testing and documentation for Major level of concern software was completed," indicating standard software validation processes, which would include testing against defined functional requirements and potentially simulated or real patient input/output scenarios based on established medical algorithms. However, no specifics about data used for training this software are provided in the context of the main glucose measurement device.

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The Accu-Chek Solo micropump system with interoperable technology is intended for the subcutaneous delivery of insulin, at set and variable rates, for the management of diabetes mellitus in persons requiring insulin. The Accu-Chek Solo micropump system is able to communicate with compatible, digitally connected devices, including automated insulin dosing software, to receive, execute, and confirm commands from these devices. The Accu-Chek Solo micropump system is intended for single patient, home use and requires a prescription. The Accu-Chek Solo micropump system is indicated for use in individuals 2 years of age and greater.

The Accu-Chek Solo micropump is a portable programmable insulin pump, which adheres to the patient's skin. The patch is comprised of two connected parts: a disposable reservoir, in which the insulin is stored and a reusable pump, which includes the pumping mechanism and electronic components. The patch is controlled via a connected Device. The Accu-Chek Solo micropump is designed to deliver basal and bolus insulin doses at various rates, volumes and patterns, as prescribed by the user's physician.

I am sorry, but the provided text does not contain the information required to describe the acceptance criteria and the study that proves the device meets the acceptance criteria, as per your detailed request.

The document is a 510(k) premarket notification summary for the Accu-Chek Solo micropump system. It primarily focuses on demonstrating substantial equivalence to a predicate device (Omnipod DASH Insulin Management System). While it lists various non-clinical tests performed (e.g., human factors, biocompatibility, sterility, electrical safety, software, cybersecurity, interoperability, and system reliability/safety testing), it does not provide specific acceptance criteria or detailed results that quantify device performance against those criteria.

Specifically, it lacks the following information crucial for your request:

• A table of acceptance criteria and reported device performance: The document mentions "The Performance testing of the Accu-Chek Solo micropump System demonstrated that the device met all device specifications," but it does not specify what those specifications are beyond broad categories like "Accuracy of Insulin Delivery" with some general percentages (e.g., "±18% or better at 0.1 U/h" for basal rates). It doesn't present a clear table linking acceptance criteria to actual measured performance for various functionalities.
• Sample sizes used for the test set and data provenance: Details on the number of samples/devices tested for the various non-clinical tests are not provided. There is no mention of a "test set" in the context of an AI/ML device or data provenance (e.g., country of origin, retrospective/prospective).
• Number of experts used to establish ground truth & qualifications: This information is completely absent, as the document doesn't describe a study involving expert assessment or ground truth labeling in the context of AI/ML performance.
• Adjudication method for the test set: Not applicable based on the document's content.
• MRMC comparative effectiveness study: The document does not describe any multi-reader multi-case study, nor does it discuss human reader improvement with or without AI assistance. This device is an insulin pump, not an AI-assisted diagnostic tool.
• Standalone (algorithm only) performance: Not applicable, as this is a physical medical device (insulin pump) with software, not a standalone AI algorithm being evaluated for diagnostic or predictive performance.
• Type of ground truth used: Given the device type, ground truth would relate to physiological parameters (e.g., actual insulin delivered, occlusion detection). While some performance metrics are mentioned (e.g., accuracy of insulin delivery, occlusion detection time), the specific "ground truth" methodology for establishing these values in testing is not detailed in the way one would describe for an AI/ML model (e.g., pathology, outcomes data).
• Sample size for the training set: Not applicable. The document discusses software verification and validation testing, but it does not refer to a "training set" in the context of machine learning model development.
• How ground truth for the training set was established: Not applicable.

The document primarily focuses on:

• Substantial equivalence comparison to a predicate device.
• Confirmation of various engineering and regulatory compliance tests (e.g., electrical safety, EMC, software V&V, cybersecurity, human factors, biocompatibility, sterility, insulin compatibility) without providing specific quantitative results for most acceptance criteria.
• A brief mention of a "clinical study" for the insertion process of the cannula, stating its aim was to prove safety, robustness, and pain-freeness, but it does not provide study details (e.g., sample size, specific outcomes, or quantitative results against acceptance criteria).

Therefore, I cannot fulfill your request based on the provided text, as it describes a clearance for an insulin pump, not an AI/ML device requiring the typical performance evaluation metrics you've outlined.

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