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EndoTool SubQ 2.1 is a software application for use by trained healthcare professionals to calculate and recommend an individual patient's next dose of insulin to be administered subcutaneously to manage blood glucose levels in patients with hyperglycemia including adult and pediatric patients (age 2 years and above and 12 kg or more). The software is designed to recommend the insulin dose(s) and when indicated a carbohydrate dosed on the prescribing healthcare Provider's nutritional regimen, insulin regimen, target glucose range, and patient specific characteristics.

EndoTool SubQ 2.1 logic is not a substitute for clinical reasoning but an aid for trained healthcare professionals based on obtained glucose readings and entered clinical data. Final dose recommendations for a patient must be made only after consideration of the full clinical status of the patient. No medical decision should be made based solely upon the results provided by this software program.

EndoTool SubQ 2.1 is a software application for use by trained healthcare professionals to calculate and recommend an individual patient's next dose of insulin to be administered subcutaneously to manage blood glucose levels in patients with hyperglycemia including adult and pediatric patients (age 2 years and above and 12 kg or more). The software is designed to recommend the insulin dose(s) and when indicated a carbohydrate dose based on the prescribing healthcare Provider's nutritional regimen, insulin regimen, target glucose range, and patient specific characteristics.

The EndoTool® SubQ 2.1 Glucose Management system includes security, software, and technical support features. Each user has an individual User Identification (ID) and Password to access portions of the application. EndoTool SubQ 2.1 is designed to safeguard the confidentiality, integrity, and availability of electronic protected health information of patients according to the Health Insurance Portability and Accountability Act (HIPAA) privacy rules.

EndoTool SubQ 2.1 is packaged in a user friendly, stand-alone program. The application is installed on Windows Server 2008 R2 or newer. The end-user should access the application using a compatible web browser, such as Internet Explorer 9 and higher, or Google Chrome 58 and higher. The application was developed for use on Personal Computers (PCs), network servers, and terminal server environments. As EndoTool SubQ 2.1 data is time sensitive, it is also imperative that all PCs and servers be set with the correct date and time using UTC.

EndoTool SubQ can utilize barcode scanning in Code 39 format (also known as Alpha39, Code 3 of 9, Code 3/9, Type 39, USS Code 39, or USD-3) for patient identification/verification.

The provided text does not contain detailed information about specific acceptance criteria for the output of the EndoTool SubQ 2.1 software or a study demonstrating that the device meets such criteria. Instead, it focuses on demonstrating substantial equivalence to a predicate device through comparison of technological characteristics and general software verification and validation activities.

Here's an analysis of the information that is available and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided text. The document states that "Software verification and validation testing was conducted per IEC 62304 and FDA's software validation guidance to demonstrate the performance of the device is substantially equivalent to the predicate." It then lists types of testing performed (requirements-based, module and integration, data integration, algorithm test cases, static analysis, regression testing), but it does not provide specific quantitative acceptance criteria (e.g., target accuracy, precision, or other performance metrics for insulin dose recommendations) or the reported performance values against these criteria.

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

Not explicitly available. The document mentions "Algorithm test cases (automated and manual)" as part of performance testing, which implies a test set was used. However, the size of this test set, the nature of the data (e.g., patient records, simulated data), and its provenance (country of origin, retrospective or prospective collection) are not specified.

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

Not available. Since the details of the "Algorithm test cases" are not provided, there is no information on how ground truth was established for these cases, nor the number or qualifications of any experts involved.

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

Not available. This information is dependent on the details of how the ground truth was established, which is not provided.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, and its effect size

No, a MRMC comparative effectiveness study was not explicitly mentioned and does not appear to have been performed. The document focuses on the software's performance and its substantial equivalence to a predicate device, not on comparing human reader performance with and without AI assistance. The device is described as "an aid for trained healthcare professionals," not a tool to enhance human reading of medical images or data in a comparative effectiveness study context.

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

Yes, implicitly. The "Algorithm test cases (automated and manual)" would involve evaluating the algorithm's output independently. The device's description as a "software application for use by trained healthcare professionals to calculate and recommend an individual patient's next dose of insulin" implies standalone algorithmic calculations. However, the performance metrics from this standalone evaluation are not provided.

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

Not explicitly available. For "Algorithm test cases," the ground truth would likely be a clinically validated optimal insulin dose or a set of expected outcomes based on established medical protocols for various patient scenarios. However, the specific method of establishing this ground truth is not detailed.

8. The sample size for the training set

Not available. The document describes a software application that calculates insulin doses. While such applications often involve algorithms that might be "trained" or developed based on data, there is no mention of a distinct "training set" or its size in the context of machine learning or AI. The software is described as having an "algorithm" and being "designed to recommend the insulin dose(s)", suggesting it operates based on predefined logic and parameters rather than a continuously learning model with a training phase.

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

Not applicable/Not available. As above, the concept of a "training set" and establishing ground truth for it is not explicitly discussed for this type of software, which appears to be rule-based or algorithmic rather than a machine learning model requiring labeled training data.

In summary: The provided document is a 510(k) summary focused on demonstrating substantial equivalence of EndoTool SubQ 2.1 to a predicate device, EndoTool SubQ (K180366). It outlines general software validation practices and a comparison of features but lacks the specific performance data, acceptance criteria, and details of clinical studies that would typically be described for a diagnostic AI device requiring quantitative performance metrics against a defined ground truth. The device is a "Predictive Pulmonary-Function Value Calculator" (Regulation Name) but its "Indications for Use" clearly state its function is for "calculat[ing] and recommend[ing] an individual patient's next dose of insulin... to manage blood glucose levels." This discrepancy might be a clerical error in the regulatory classification.

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EndoTool SubQ is a software management system for use by trained healthcare professionals to calculate and recommend an individual patient's next dose of insulin to be administered subcutaneously to manage elevated blood glucose levels in both adult and pediatric patients (age 2 and above and 12 kg or more). The software is designed to recommend the insulin dose(s) (and on occasion a carbohydrate dose for the treatment of hypoglycemia) based on the prescribing healthcare provider's insulin regimen, target glucose level range, and nutritional regimen. The software provides an optional insulinon-board (IOB) calculation that estimates the sum of the remaining insulin activity from previously administered subcutaneous insulin(s). This IOB adjustment reduces the prescribed Bolus dose and, if appropriate, recommends a supplemental carbohydrate dose to the trained healthcare professional.

EndoTool SubQ is not a substitute for clinical reasoning, but rather an aid for trained healthcare professionals based on timely, accurately obtained glucose readings and timely, accurately entered clinical data. Final dose recommendations for a patient must be accepted only after consideration of the full clinical status of the patient. No medical decision should be made based solely upon the recommendations provided by this software program.

Monarch Medical Technologies' EndoTool SubQ Glucose Management System is a software application for use by trained healthcare professionals to calculate a hospitalized patient's next dose of insulin (administered subcutaneously) or carbohydrates to manage blood glucose levels in both adult and pediatric patients (age 2 and above and 12kg and above) based on their individual glucose response to previously administered insulin. The subject device, EndoTool SubO with optional Insulin-on-Board (IOB) calculation, and the predicate device, EndoTool SubQ (K142918), both provide an insulin dose recommendation based on the patient's clinical data and the physician's current prescribed dosing regimen.

EndoTool SubQ Glucose Management System is packaged in a user friendly, browser-based program using Microsoft .Net technologies. The application requires Windows. The application was developed for use on Personal Computers (PCs), network servers, and terminal server environments.

EndoTool SubQ Glucose Management System can utilize barcode scanning for patient identification/verification.

Other platform requirements of the system include installation of the following software: SQL Server 2005 or greater, Crystal Reports Basic for Visual Studio 2008, and Adobe Reader.

The medical device is the EndoTool SubQ, a software management system designed to calculate and recommend insulin doses for managing elevated blood glucose levels.

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly present a table of acceptance criteria with corresponding performance metrics. However, it states that "In all testing, the pre-determined acceptance criteria were met."

The non-clinical testing summary lists the following activities, which inherently define the acceptance criteria:

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

The document does not explicitly state the sample size used for the test set in terms of patient data. The non-clinical testing appears to involve software verification and validation using "Automated Algorithm Test Cases" and "Manual verification test cases," rather than a clinical dataset of patients.

The data provenance is not specified as patient data was not used for testing. The testing described focuses on software performance, not clinical outcomes with real patient data.

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

This information is not provided. The ground truth for the software testing would likely be based on expected outputs of the algorithms, rather than expert clinical consensus.

4. Adjudication Method for the Test Set:

This information is not provided. Given that the testing focuses on software verification and automated algorithm tests, an adjudication method for clinical disagreement would not be applicable.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

A multi-reader multi-case (MRMC) comparative effectiveness study was not done. The document describes non-clinical testing focused on software functionality and algorithm verification, not a study comparing human readers with and without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance Study:

A standalone performance study of the algorithm was done, in the sense that the device's algorithms were tested independently of human interaction. The "Automated Algorithm Test Cases for Insulin on Board" and "Automated algorithm test cases for the complete SubQ application" indicate testing of the algorithm's output against expected results. However, this is in the context of software verification, not a clinical trial to assess standalone clinical performance.

7. Type of Ground Truth Used:

The ground truth used for the testing appears to be expected algorithmic outputs and predefined software requirements. For example, "Verification Testing of Insulin on Board SRS Requirements" indicates comparison against system requirements, and "Automated Algorithm Test Cases" suggests comparing output with mathematically or logically expected results. There is no mention of pathology, expert consensus on patient outcomes, or other clinical ground truth types for the testing described.

8. Sample Size for the Training Set:

The document does not specify a sample size for a training set. This suggests that the device, being a "Predictive Pulmonary-Function Value Calculator" (though the device description refers to insulin dosing, which is a discrepancy in the regulation name) and an insulin dosing recommendation system, likely relies on predefined algorithms and logic rather than a machine learning model that requires a training set.

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

As no training set is mentioned or implied for a machine learning model, the method for establishing its ground truth is not applicable/not provided. The device's "Predictive Pulmonary-Function Value Calculator" (regulation name) or "insulin dose recommendation" (device description) functions would be based on established physiological models and drug pharmacokinetics, implemented as algorithms.

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EndoTool SubQ is a software application for use by trained healthcare professionals to calculate and recommend an individual patient's next dose of insulin to be administered subcutaneously to manage blood glucose levels in patients with Diabetes Mellitus in both adult and pediatric patients (age 2 years and above and 12 kg or more). The software is designed to recommend the insulin dose(s) (and when indicated a carbohydrate dose) based on the prescribing healthcare provider's nutritional regimen, insulin regimen, target glucose range, and patient specific characteristics.

The EndoTool SubQ is not a substitute for clinical reasoning, but is an aid for trained healthcare professionals to manage patients. The System is based on obtained glucose readings and clinical data entered by the medical staff. Final dose decisions for a patient must be made only after consideration of the full clinical status of the patient. No medical decision should be made based solely on the recommendations provided by this software program.

Monarch Medical Technology's EndoTool SubQ Glucose Management System is a glucose management software solution for healthcare institutions. This system uses proprietary control technology to provide patient-specific glycemic control across a broad population of adult and pediatric patients using basal/bolus insulin therapy. This system is designed to correctly dose subcutaneous insulin (and amount of carbohydrates if and when indicated to treat hypoglycemia) to achieve patient-specific, sustained control with different nutritional and insulin regimens, selected by the patient's physician responsible for glycemic control.

EndoTool SubQ Glucose Management System is designed to be used following a physician order with physician set optional diet, insulin regimen, basal/bolus distribution, initial total daily dose of insulin, and glucose target range. The primary user of the EndoTool SubQ Glucose Management System is the bedside caregiver (e.g. nurse) who will use the system to enter clinical data (e.g. food intake and scheduled blood glucose readings). With confirmation of previous data entered, the system makes the next dose calculation of subcutaneous insulin and the next time for a scheduled glucose determination.

The provided text is a 510(k) summary for the EndoTool SubQ™ device, a software application designed to recommend insulin doses for managing blood glucose levels in diabetic patients. However, the document does not contain explicit acceptance criteria and a detailed study report that proves the device meets specific performance metrics. It primarily focuses on demonstrating substantial equivalence to predicate devices based on intended use, technological characteristics, and general functionality.

Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor can I detail specific study parameters such as sample size, data provenance, expert qualifications, adjudication methods, or effects of AI assistance. The document refers to "Requirements-based testing for all functionality" and "Automated algorithm test case execution" but does not provide the results or details of these tests.

Specifically, the document states:

• Test Summary: "Testing included the following: 1) Requirements-based testing for all functionality. 2) Requirements-based testing for all risk-related requirements. 3) Integration testing to ensure that data flows correctly into and out of the database. 4) Automated algorithm test case execution. 5) Off The Shelf (OTS) software embedded in the application was included in the technical verification protocols. Each OTS component was tested to ensure that it functioned as intended."
• Test Summary Conclusion: "The performance of the EndoTool SubQ Glucose Management System is substantially equivalent to that of the Glytec Glucommander G+ Enterprise System (K113853) and EndoTool IV Glucose Management System (K132547) and raises no new safety or effectiveness issues and performs as well as the predicate."

This indicates that testing was performed, but the results, acceptance criteria, and detailed methodology are not included in this summary.

Therefore, most of the requested information cannot be extracted from this document.

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