The SmartBolus Calculator is software intended for the management of diabetes in persons aged 2 and older requiring rapid-acting U-100 insulin. The SmartBolus Calculator calculates a suggested bolus dose based on user-entered carbohydrates, most recent sensor glucose value (or blood glucose reading if using fingerstick), rate of change of the sensor glucose (if applicable), insulin on board (IOB), and programmable correction factor, insulin to carbohydrate ratio, and target glucose value. The SmartBolus Calculator is intended for single patient, home use and requires a prescription.

The SmartBolus Calculator is a software device that is a component of the Omnipod 5 Automated Insulin Delivery System. The SmartBolus Calculator exists on the Omnipod 5 App portion of the Omnipod 5 ACE Pump and relies on the user interface of the App.

The SmartBolus Calculator receives input parameters and settings from other components of the system and calculates a suggested bolus amount of insulin to correct an elevated glucose level (a correction bolus) and/or to cover carbohydrates from a meal (meal bolus). The SmartBolus Calculator allows users to have the option of populating the current estimated glucose value and trend, which is communicated by the connected iCGM. Users may also manually enter the estimated glucose value or a blood glucose (BG) reading from a blood glucose meter. In addition to glucose, the suggested bolus dose is calculated based on the following parameters: user-entered carbohydrates, rate of change of the sensors qlucose (if using a CGM), correction factor, insulin to carbohydrate ratio, target glucose value, and insulin on board (IOB). Once the calculation is complete, the user has the option of delivering the suggested dose of insulin, modifying the amount, or canceling.

The SmartBolus Calculator can be used in the Omnipod 5 Automated Insulin Delivery System with both Manual Mode and Automated Mode.

Here's a summary of the acceptance criteria and study information for the SmartBolus Calculator, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly list specific acceptance criteria in a quantitative manner for the SmartBolus Calculator's performance. Instead, it states that:

• "Verification activities, as required by the risk analysis, demonstrated that the predetermined acceptance criteria were met and the device is safe for use."
• "Through performance testing, the Subject device has been shown to meet the Special Controls and determined to be substantially equivalent to its predicate."
• "There was no impact to clinical performance of the SmartBolus Calculator for the design change discussed in this submission."

This implies that the assessment for this 510(k) submission focused on demonstrating that the new iOS version of the SmartBolus Calculator (subject device) performs identically to the predicate Android version (K222239) and meets the same safety and effectiveness standards, rather than establishing new performance metrics.

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

The document does not specify a sample size for a test set in the context of clinical or performance data for the SmartBolus Calculator itself. The testing mentioned is primarily "software verification and validation testing" and "risk management" activities.

The data provenance is also not explicitly stated as retrospective or prospective clinical data. The testing described appears to be internal software development and validation, rather than a clinical trial.

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

This information is not provided in the document. The testing described is software-centric, and there's no mention of expert-established ground truth for a test set in a medical diagnostic sense.

4. Adjudication method for the test set

This information is not provided in the document, as it doesn't describe a clinical test set requiring adjudication.

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

An MRMC comparative effectiveness study was not mentioned or described. The device is an "Insulin Therapy Adjustment Device," not a diagnostic imaging device where MRMC studies are typically conducted. The document focuses on demonstrating substantial equivalence of a new software implementation (iOS) to an existing one (Android).

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

The SmartBolus Calculator is described as an "Algorithmic software device." Its function is to "calculate a suggested bolus dose." However, it operates as a component of the Omnipod 5 App, and "Once the calculation is complete, the user has the option of delivering the suggested dose of insulin, modifying the amount, or canceling." This indicates it's a human-in-the-loop system, where the user has ultimate control and decision-making power over the suggested dose. Therefore, a purely standalone clinical performance evaluation without human decision-making is not explicitly implied or discussed in this context. The software's calculation itself is standalone, but its application involves a human.

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

The document does not specify a type of ground truth related to clinical outcomes or expert consensus for its performance evaluation for this particular submission. The "verification activities" and "software verification and validation testing" likely used predefined software requirements, simulated data, and mathematical correctness of calculations as their "ground truth" to ensure the algorithms produced the expected outputs given specific inputs according to the established insulin calculation formulas.

8. The sample size for the training set

The document does not describe a training set in the context of machine learning. The SmartBolus Calculator is an algorithm that computes a bolus dose based on programmable factors and user inputs, not a machine learning model that requires a training set.

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

As there's no mention of a machine learning model or a training set, this information is not applicable.

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endo.digital Platform is intended for the management of diabetes by people with diabetes and their healthcare providers in order to report, upload, log, track, share, monitor and review their data using web and mobile applications. endo.digital Platform also enables communication between people with diabetes and their healthcare providers as well as among healthcare providers.

endo.digital Platform enables the healthcare provider to use endo.digital Algorithm for treatment recommendations as described below and prescribe endo.digital Bolus Calculator for patient use.

endo.digital Algorithm is a decision-support software intended for assisting healthcare professionals in the management of their patients with diabetes who monitor their glucose levels using continuous glucose monitor (CGM) and/or Self-Monitoring Blood Glucose (SMBG) meter; and use any of the following insulin types as their therapy to manage glucose levels via subcutaneous injections or continuous sub-cutaneous insulin infusion (CSII; insulin pump) reported either manually or automatically:

• Long acting insulins (for injections only)
• Short acting insulins:
  • Rapid acting analogs (for injections and insulin pump according to manufacturer indications for use)
  • Regular human insulin (for injections only)

endo.digital Algorithm is intended to be used for patients with:

• Type 1 diabetes over the age of 6 using an insulin pump or subcutaneous insulin injections.
• Type 2 diabetes over the age of 10 who use subcutaneous insulin injections.

endo.digital Algorithm is indicated for use by healthcare professionals when analyzing CGM, SMBG and/or insulin delivery data to generate recommendations for optimizing a patient's insulin treatment plan for basal therapy and/or bolus therapy and/or glucose targets, without considering the full clinical status of a particular patient. endo.digital Algorithm does not replace clinical judgement.

endo.digital Bolus Calculator, a component of the DreaMed Diary App, is a diabetes management tool for people with type 1 diabetes above the age of 6 and type 2 diabetes above the age of 10, who use subcutaneous insulin injections therapy (not for pump use). This tool can help calculate their rapid acting analogs for insulin bolus doses based on user-entered blood glucose and/or meal information.

The initial setup of the user's treatment plans, and bolus calculator settings must be performed by a healthcare provider.

endo.digital Platform is a software device that is designed to be a diabetes management platform. It includes endo.digital Algorithm that provides insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 1 diabetes using an insulin pump or multiple daily injections, a continuous glucose monitoring (CGM) system and/or self-management blood glucose meter (SMBG). endo.digital Algorithm also provides insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 2 diabetes on basal-bolus therapy via multiple daily injections (MDI), a continuous glucose monitoring (CGM) system and/or self-management blood glucose meter (SMBG). endo.digital Algorithm gathers and analyzes information inputted through the Diabetes Management Systems (DMS), which collect biological input information from various diabetes devices and data sources including the DreaMed Diary App. Diabetes device information required and used by endo.digital Algorithm includes glucose readings (either CGM sensor readings and/or capillary blood glucose measurements), insulin dosing logs, and meal data during daily routine care. Following data collection and analysis, the endo.digital Algorithm generates results containing summary data and recommendations for adjustments to the patient's insulin therapy parameters, including basal insulin delivery rate(s), insulin to carbohydrate ratio and correction factor (insulin sensitivity) for pump patients, and for MDI patients a daily injection plan including a basal plan and either a sliding scale (which can include Fixed Meal and Meal Estimation plans) or insulin to carbohydrate ratio and correction factor (insulin sensitivity) for bolus injections. endo.digital Algorithm may also advise on personalized diabetes management tips. Results are sent to the Diabetes Management System, which displays results to physicians and a report provided by the algorithm. The physician can approve, reject or change the recommendations and issue the updated treatment plan to the patient. For MDI patients using rapid acting analogs for insulin bolus dose, the healthcare provider may prescribe endo.digital Bolus Calculator which is integrated in the DreaMed Diary App to aid in calculating their bolus injections.

The provided text details the 510(k) premarket notification for the "endo.digital Platform." While it discusses the device's intended use, description, and substantial equivalence to a predicate device, it does not contain specific information about the acceptance criteria or the study that proves the device meets those criteria. The document states that "software performance data demonstrates that endo.digital Platform is as safe and effective as the predicate device" and that "Design validation testing results confirmed that endo.digital Platform performs according to the stated intended use. Software evaluation consisted of functional testing performed pursuant to DreaMed's software test plan. All test results fell within the pre-determined specification parameters and acceptance criteria." However, it does not provide the acceptance criteria themselves, nor the details of the studies conducted to meet them.

Therefore, I cannot fulfill your request for:

1. A table of acceptance criteria and the reported device performance: This information is not present in the document.
2. Sample size used for the test set and the data provenance: This information is not provided.
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, and its effect size: Not mentioned. The device is a "decision-support software intended for assisting healthcare professionals," implying a human-in-the-loop, but no MRMC study details are shared.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not specified.
7. The type of ground truth used: Not specified.
8. The sample size for the training set: Not provided.
9. How the ground truth for the training set was established: Not provided.

The document focuses on the regulatory submission, equivalence to a predicate device ("Advisor Pro Platform, K210561"), and the general statement that "software performance data demonstrates that endo.digital Platform is as safe and effective as the predicate device." It also mentions "functional testing performed pursuant to DreaMed's software test plan" and that "All test results fell within the pre-determined specification parameters and acceptance criteria," but it does not disclose the specifics of these tests or criteria.

To obtain the requested information, one would typically need to review the full 510(k) submission, which often includes detailed validation reports, clinical studies, and software verification and validation documentation. These are usually not fully disclosed in the public 510(k) summary letter.

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The BlueStar® CGM insulin dose calculator is software intended for the management of type 1 or type 2 diabetes in persons aged 18 years and older requiring fast-acting insulin. The BlueStar CGM insulin dose calculator allows patients to calculate a dose of bolus insulin for a given amount of carbohydrates, the most recent CGM glucose reading and rate of change, activity, and, optionally, insulin on board (IOB). The BlueStar CGM insulin dose calculator requires a prescription.

The BlueStar® CGM insulin dose calculator is a software device module existing in the same mobile medical application as BlueStar® Rx (K203434), which is intended for the management of diabetes. When connected to a compatible integrated continuous glucose monitor (iCGM) and under authorization from a qualified healthcare provider, the BlueStar CGM insulin dose calculator allows patients to calculate a dose of bolus insulin for a given amount of carbohydrates, the most recent iCGM glucose reading and its rate of change, activity, and, optionally, insulin on board (IOB). Other patient-specific inputs from BlueStar Rx are used in the calculation of the recommended dose- specifically, duration of insulin to carb ratio, correction factor, and target glucose. In addition to calculating specific dosing recommendations, the BlueStar CGM insulin dose calculator also provides coaching messages to assist the user in maintaining glucose within the target range.

The use of CGM inputs differentiates the BlueStar CGM insulin dose calculator from the insulin dose calculator included in the previously cleared BlueStar Rx, which uses blood glucose (BG) values from a BG meter using a "fingerstick" method. The CGM insulin dose calculator is intended to coexist with the BG insulin calculator function in the BlueStar Rx software application as the BG calculation may be necessary when CGM is unavailable or the CGM estimated blood glucose does not match how the user feels.

Here's the information about the acceptance criteria and the study that proves the device meets them, based on the provided text:

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

The document does not explicitly present a table of acceptance criteria with specific numerical targets. However, the primary clinical endpoint serves as the de facto acceptance criterion for efficacy, while safety measures address other key concerns.

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

• Sample Size for Test Set: 27 adult subjects.
• Data Provenance: The document does not specify the country of origin of the data. The study was prospective as data was "collected for each subject for 30 days while using the BlueStar mobile app with the CGM insulin dose calculator."

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)

The document does not mention the use of experts to establish ground truth for the test set. The ground truth was established by the CGM data itself, as it measured glucose time in range.

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

The document does not describe any adjudication method for the test set.

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 comparative effectiveness study was not done. The study focused on the effectiveness of the device (BlueStar® CGM insulin dose calculator) in improving or maintaining Time in Range compared to baseline, rather than comparing human reader performance with and without AI assistance.

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

Yes, the clinical study assessed the performance of the "BlueStar mobile app with the CGM insulin dose calculator" as used by the subjects. While patients are "human-in-the-loop" by entering carbohydrates, accepting recommendations, and performing activities, the primary performance metric (TIR) evaluates the algorithm's impact on glucose management, implying a standalone assessment of its functional impact when integrated into patient self-management. The device itself is software that calculates a dose, so the clinical study assesses the impact of these calculations on patient outcomes.

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

The ground truth used was outcomes data, specifically CGM glucose time in range (TIR) and time spent in hypoglycemia, measured directly from Continuous Glucose Monitoring (CGM) devices.

8. The sample size for the training set

The document does not provide information about a separate training set or its sample size. The clinical study described appears to be a validation study.

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

Since information about a training set is not provided, how its ground truth was established is also not available in this document.

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The SmartBolus Calculator is software intended for the management of diabetes in persons aged 2 and older requiring rapid-acting U-100 insulin. The SmartBolus Calculator calculates a suggested bolus dose based on user-entered carbohydrates, most recent sensor glucose value (or blood glucose reading if using fingerstick), rate of change of the sensor glucose (if applicable), insulin on board (IOB), and programmable correction factor, insulin to carbohydrate ratio, and target glucose value. The SmartBolus Calculator is intended for single patient, home use and requires a prescription.

The SmartBolus Calculator is a software device that is a component of the Omnipod 5 Automated Insulin Delivery System. The SmartBolus Calculator exists on the Omnipod 5 App portion of the Omnipod 5 ACE Pump and relies on the user interface of the App. The SmartBolus Calculator receives input parameters and settings from the other components of the system and calculates a suggested bolus amount of insulin to correct an elevated glucose level (a correction bolus) and/or to cover carbohydrates from a meal (meal bolus). The SmartBolus Calculator allows users to have the option of populating the current estimated glucose value and trend, which is communicated by the connected iCGM. Users may also manually enter the estimated glucose value or a blood glucose (BG) reading from a blood glucose meter. In addition to glucose, the suggested bolus dose is calculated based on the following parameters: user-entered carbohydrates, rate of change of the sensor glucose (if using a CGM), correction factor, insulin to carbohydrate ratio, target qlucose value, and insulin on board (IOB). Once the calculation is complete, the user has the option of delivering the suggested dose of insulin, modifying the amount, or canceling. The SmartBolus Calculator can be used in the Omnipod 5 Automated Insulin Delivery System with both Manual Mode and Automated Mode.

The information provided focuses on the substantial equivalence of the SmartBolus Calculator to a predicate device, specifically regarding the expansion of its age range of intended users. The document details the clinical study performed to support this expanded indication, rather than a general acceptance criteria study for the device's core functionality.

Here's an analysis of the provided information based on your requested points:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state formal acceptance criteria in a tabular format for the SmartBolus Calculator's overall performance. Instead, the "acceptance criteria" can be inferred from the clinical study's primary objective, which was to evaluate safety based on glucose metrics. The study aimed to show that the use of the SmartBolus Calculator in the expanded age group (2.0-5.9 years) did not significantly worsen these safety metrics compared to manual entry of blood glucose values.

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

• Sample Size: 5 subjects in the preschool cohort (aged 2.0-5.9 years).
• Data Provenance: The study was a "single-arm, multi-center, prospective clinical study" conducted across "2 US clinical sites." Therefore, the data is prospective and from the USA.

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

This document does not provide details on the number or qualifications of experts used to establish ground truth for the test set. The clinical study collected glucose metrics directly from the subjects, which served as the primary data for evaluation.

4. Adjudication Method for the Test Set

The document does not mention an explicit adjudication method for the clinical study's data. Clinical study data, particularly objective metrics like blood glucose levels, typically do not require adjudication in the same way imaging or subjective diagnostic interpretations might. Safety events would be reviewed by the study investigators and reported.

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

No, an MRMC comparative effectiveness study was not done. This study was a clinical trial evaluating the safety and effectiveness of the device in a specific patient population, not a comparative study of human readers with and without AI assistance.

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

This study was a human-in-the-loop study. The SmartBolus Calculator is a software device that recommends a bolus dose, but the user "has the option of delivering the suggested dose of insulin, modifying the amount, or canceling." The clinical study evaluated the device's performance when used by patients/caregivers in Manual Mode.

7. The Type of Ground Truth Used

The ground truth for the clinical study was based on objective clinical outcomes data (glucose metrics and adverse events) directly measured from the study participants during the two phases of the study (Manual Mode with manual BG entry vs. Manual Mode with SmartBolus Calculator use).

8. The Sample Size for the Training Set

The document does not provide information on the sample size for the training set used to develop the SmartBolus Calculator. The submission focuses on the clinical validation of the device's expanded indication, not its initial development.

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

The document does not provide information on how the ground truth for the training set was established.

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The Omnipod 5 SmartBolus Calculator is software intended for the management of diabetes in persons aged 6 and older requiring rapid-acting U-100 insulin. The Omnipod 5 SmartBolus Calculator calculates a suggested bolus dose based on user-entered carbohydrates, most recent sensor glucose reading (or blood glucose reading if using fingerstick), rate of change of the sensor glucose (if applicable), insulin on board (IOB), and programmable correction factor, insulin to carbohydrate ratio, and target glucose value. The Omnipod 5 SmartBolus Calculator is intended for single patient, home use and requires a prescription.

The Omnipod 5 SmartBolus Calculator is a software device that is a component of the Omnipod 5 Automated Insulin Delivery System. The SmartBolus Calculator exists on the Omnipod 5 App portion of the Omnipod 5 ACE Pump and relies on the user interface of the App.

The Omnipod 5 SmartBolus Calculator receives input parameters and settings from the other components of the system and calculates a suggested bolus amount of insulin to correct an elevated glucose level (a correction bolus) and/or to cover carbohydrates from a meal (meal bolus). The Omnipod 5 SmartBolus Calculator allows users to have the option of populating the current estimated glucose value and trend, which is communicated by the connected iCGM. Users may also manually enter the estimated glucose value or a blood glucose (BG) reading from a blood glucose meter. In addition to glucose, the suggested bolus dose is calculated based on the following parameters: user-entered carbohydrates, rate of change of the sensor glucose (if using a CGM), correction factor, insulin to carbohydrate ratio, target glucose value, and insulin on board (IOB). Once the calculation is complete, the user has the option of delivering the suggested dose of insulin, modifying the amount, or canceling.

The Omnipod 5 SmartBolus Calculator can be used in the Omnipod 5 Automated Insulin Delivery System with both Manual Mode and Automated Mode. When the Omnipod 5 SmartBolus Calculator is used with manually-entered BG readings, it suggests a bolus dose based on the same calculations as the currently cleared Omnipod DASH Insulin Management System (K180045, most recently cleared in K192659).

The document describes the Omnipod 5 SmartBolus Calculator, a software device for diabetes management. Here's a breakdown of the acceptance criteria and the study proving it meets these criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied through the statement that the device meets "Insulin Therapy Adjustment Device special controls and to be safe and effective." The clinical study focused on glycemic control within 4 hours of bolusing. While explicit acceptance criteria for these percentages are not given as strict pass/fail thresholds, the performance observed is presented as evidence of safety and effectiveness, particularly regarding hypoglycemia.

*Note: The primary analysis focused on comparing the CGM-informed SmartBolus Calculator with the standard one, and a statistically significant difference was observed for time spent

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The Advisor Pro Platform is intended for the management of diabetes by people with diabetes and their health care providers in order to report, log, track, share, monitor and review their data using the dedicated computer or mobile software. Advisor Pro Platform also enables communication between people with diabetes and their health care providers as well as among health care providers.

The Advisor Pro Platform enables the healthcare provider to use the Advisor Pro Algorithms for treatment recommendations as described below and prescribe the Advisor Pro Bolus Calculator for patient use.

Advisor Pro Algorithm is a decision-support software intended for assisting healthcare professionals in the management of their patients with diabetes who monitor their glucose levels using continuous glucose monitor (CGM) and/or Self-Monitoring Blood Glucose (SMBG) meter; and use any of the following insulin types as their therapy to manage glucose levels via subcutaneous injections or continuous sub-cutaneous insulin infusion (CSII; insulin pump) reported either manually or automatically:

• Long Acting insulins (for injections only)
• Short acting insulins:
  • Rapid acting analogs (for injections and insulin pump according to manufacturer indications for use)
  • Regular human insulin (for injections only)

The Advisor Pro algorithm is intended to be used for patients with:

• Type 1 diabetes over the age of 6 using an insulin pump or subcutaneous insulin injections.
• Type 2 diabetes over the age of 10 who use subcutaneous insulin injections.

Advisor Pro Algorithm is indicated for use by healthcare professionals when analyzing CGM, SMBG and/or insulin delivery data to generate recommendations for optimizing a patient's insulin treatment plan for basal therapy and/or bolus therapy and/or glucose targets; without considering the full clinical status of a particular patient. Advisor Pro Algorithm does not replace clinical judgment.

The Advisor Pro Bolus Calculator, a component of the DreaMed Diary App, is a diabetes management tool for people with type 1 diabetes above the age of 6 and type 2 diabetes above the age of 10, who use subcutaneous insulin injections therapy (not for pump use). This tool can help calculate their rapid acting analogs for insulin bolus doses based on user-entered blood glucose and/or meal information.

The initial setup of the user's treatment plans, and bolus calculator settings must be performed by a healthcare provider.

The Advisor Pro Platform is a software device that is designed to be a diabetes management platform. It includes the Advisor Pro Algorithm that provides insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 1 diabetes using an insulin pump or multiple daily injections, a continuous glucose monitoring (CGM) system and/or self-management blood glucose meter (SMBG). The Advisor Pro Algorithm also provides insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 2 diabetes on basal-bolus therapy via multiple daily injections (MDI), a continuous glucose monitoring (CGM) system and/or self-management blood glucose meter (SMBG).

The Advisor Pro Algorithm gathers and analyzes information inputted through the Diabetes Management Systems (DMS), which collects biological input information from various diabetes devices and data sources including the DreaMed Diary App. Diabetes device information required and used by Advisor Pro Algorithm includes glucose readings (either CGM sensor readings and/or capillary blood glucose measurements), insulin dosing logs, and meal data during daily routine care.

Following data collection and analysis, the Advisor Pro Algorithm generates results containing summary data and recommendations for adjustments to the patient's insulin therapy parameters, including basal insulin delivery rate(s), insulin to carbohydrate ratio and correction factor (insulin sensitivity) for pump patients and for MDI patients a daily injection plan including a basal plan and either a sliding scale or insulin to carbohydrate ratio and correction factor (insulin sensitivity) for bolus injections. Advisor Pro Algorithm may also advise on personalized diabetes management tips. Results are sent to the Diabetes Management System, which displays results to physicians and a report provided by the algorithm. The physician can approve, reject or change the recommendations and issue the updated treatment plan to the patient.

For MDI patients using rapid acting analogs for insulin bolus dose, the healthcare provider may prescribe the Advisor Pro Bolus Calculator which is integrated in the DreaMed Diary App to aid in calculating their bolus injections.

The provided text describes the DreaMed Advisor Pro Platform, a software device intended for diabetes management. It includes two main components: the Advisor Pro Algorithm (a decision-support tool for healthcare professionals) and the Advisor Pro Bolus Calculator (for patient use).

Here's an analysis of the acceptance criteria and the study proving device performance based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria with corresponding performance metrics like sensitivity, specificity, accuracy, or specific thresholds for agreement. Instead, it focuses on demonstrating that the device's recommendations are "as good as" or "similar to" those of experts.

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

• Test Set Sample Size: The clinical study involved a data set of 17 Type 1 patients and 15 Type 2 patients.
• Data Provenance: The document does not specify the country of origin for the data. It indicates the study was "retrospective clinical study."

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

• Number of Experts: A total of 36 experts were involved.
• Qualifications of Experts: The text states these were "healthcare professional who work at leading centers with a wealth of experience in the field of diabetes and who are especially familiar with diabetes technology devices." Specific professional titles (e.g., endocrinologist, specialized diabetes nurse), years of experience, or board certifications are not provided.

4. Adjudication Method for the Test Set

The document states, "Recommendations were compared to examine the level of agreement between one expert to his colleague versus the level of agreement between Advisor Pro Algorithm recommendations and experts." This implies some form of comparison or consensus evaluation, but a specific adjudication method (e.g., 2+1, 3+1) is not explicitly detailed. It seems to be a comparison of agreement levels rather than a formal adjudication process to establish a single ground truth from multiple expert reads for each case.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

While the study involved multiple experts evaluating cases and comparing their recommendations to the algorithm and to each other, the description doesn't explicitly label it as a formal MRMC comparative effectiveness study in the sense of directly measuring human reader improvement with AI assistance vs. without.

The study aimed to show that the AI's recommendations were "as good as" expert recommendations. It compared "the level of agreement between one expert to his colleague versus the level of agreement between Advisor Pro Algorithm recommendations and experts."

Therefore, it was not a direct MRMC study to quantify how much human readers improve with AI assistance. It was designed to show the equivalence/similarity of the algorithm's recommendations to those of experts. No effect size for human reader improvement with AI assistance is reported because that was not the stated purpose of this particular comparison.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, the study described is a standalone performance evaluation of the Advisor Pro Algorithm's recommendations compared to expert recommendations. The algorithm generated recommendations independently, which were then compared to expert decisions.

7. The Type of Ground Truth Used

The ground truth for the clinical study appears to be expert consensus or expert recommendations for insulin therapy adjustments. The algorithm's recommendations were compared against the recommendations of these experts to establish "level of agreement."

8. The Sample Size for the Training Set

The document does not provide information regarding the sample size used for the training set for the Advisor Pro Algorithm. The clinical study described involved a test set.

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

The document does not provide information on how the ground truth for the training set was established. The clinical study described focuses on the evaluation of the algorithm's performance on a test set, not on its training data.

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DreaMed Advisor Pro is a decision-support software intended for assisting healthcare professionals in the management of patients with Type 1 diabetes who:

· use insulin pumps as their insulin delivery therapy;

· monitor their glucose levels using continuous glucose monitoring (CGM) and/or Self-Monitoring Blood Glucose (SMBG) meter;

• are above the age of 6; and

· use rapid acting U-100 insulin analogs in their pump

DreaMed Advisor Pro is indicated for use by healthcare professionals when analyzing CGM, SMBG and pump data to generate recommendations for optimizing a patient's insulin pump settings for basal rate, Carbohydrate Ratio (CR), and Correction Factor (CF); without considering the full clinical status of a particular patient. DreaMed Advisor Pro does not replace clinical judgement.

DreaMed Advisor Pro is a software device that is designed to provide insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 1 diabetes using an insulin pump, a continuous glucose monitoring (CGM) system and self-management blood glucose meter (SMBG).

The DreaMed Advisor Pro gathers and analyzes information inputted through qualified Diabetes Management Systems (DMS), which collects biological input information from various diabetes devices. Diabetes device information required and used by DreaMed Advisor Pro includes glucose readings (either CGM sensor readings and/or capillary blood glucose measurements), insulin dosing logs, and meal data during daily routine care.

Following data collection and analysis, the DreaMed Advisor Pro generates results containing summary data and recommendations for adjustments to the patient's insulin therapy parameters, including basal insulin delivery rate(s), insulin to carbohydrate ratio and correction factor (insulin sensitivity). DreaMed Advisor Pro may also advise behavioral changes. Results are sent to a qualified Diabetes Management Systems, which displays results to physicians and a report provided by DreaMed Diabetes. The physician can approve, reject or change the recommendations and issue the updated treatment plan to the patient.

The provided text is a 510(k) summary for the DreaMed Advisor Pro, which is a software device intended to assist healthcare professionals in managing Type 1 diabetes. It primarily describes the device, its intended use, and argues for its substantial equivalence to a previously cleared version of the same device (K191370).

However, the document does not contain the detailed information requested about acceptance criteria, specific study results, sample sizes for test and training sets, expert qualifications, adjudication methods, or MRMC comparative effectiveness studies. It simply asserts that the updated DreaMed Advisor Pro is "as safe and effective" as the previously cleared one, with the only change being an expansion of the age range to include patients over 65.

Therefore, I cannot populate the table and answer all the questions based on the provided text. I will indicate where the information is missing.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size for test set: Not provided in the document.
• Data provenance: Not provided in the document. No specific study data is presented, so the origin (country, retrospective/prospective) of any potential test data is not mentioned.

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

Not provided in the document. Since no specific test set study is detailed, there's no information on ground truth establishment or expert involvement.

4. Adjudication method for the test set

Not provided in the document.

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 provided in the document. The submission focuses on substantial equivalence to a previous version of the same AI device, not on comparing human readers with and without the AI.

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

The document describes the device as "decision-support software intended for assisting healthcare professionals," and states that "DreaMed Advisor Pro does not replace clinical judgement." This implies human-in-the-loop operation. No standalone (algorithm-only) performance is described or implied to have been studied for this 510(k) submission.

7. The type of ground truth used

Not provided in the document. No specific ground truth methodology is mentioned as a study proving performance is not detailed in this submission.

8. The sample size for the training set

Not provided in the document.

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

Not provided in the document.

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DreaMed Advisor Pro is a decision-support software intended for assisting healthcare professionals in the management of patients with Type 1 diabetes who:
• use insulin pumps as their insulin delivery therapy;
• monitor their glucose levels using CGM and/or self-management blood glucose meter;
• are above the age of 6 and under 65 years old; and
• use rapid acting U-100 insulin analogs in their pump.
DreaMed Advisor Pro is indicated for use by healthcare professionals when analyzing continuous glucose monitoring (CGM), self-monitoring blood glucose (SMBG) and pump data to generate recommendations for optimizing a patient's insulin pump settings for basal rate, carbohydrate ratio (CR), and correction factor (CF); without considering the full clinical status of a particular patient. DreaMed Advisor Pro does not replace clinical judgement.

DreaMed Advisor Pro is a software device that is designed to provide insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 1 diabetes using an insulin pump, a continuous glucose monitoring (CGM) system and self-management blood glucose meter (SMBG).
The DreaMed Advisor Pro gathers and analyzes information inputted through qualified Diabetes Management Systems (DMS), which collects biological input information from various diabetes devices. Diabetes device information required and used by DreaMed Advisor Pro includes glucose readings (either CGM sensor readings and/or capillary blood glucose measurements), insulin dosing logs, and meal data during daily routine care.
Following data collection and analysis, the DreaMed Advisor Pro generates results containing summary data and recommendations for adjustments to the patient's insulin therapy parameters, including basal insulin delivery rate(s), insulin to carbohydrate ratio and correction factor (insulin sensitivity). DreaMed Advisor Pro may also advise behavioral changes. Results are sent to a qualified Diabetes Management Systems, which displays results to physicians and a report provided by DreaMed Diabetes. The physician can approve, reject or change the recommendations and issue the updated treatment plan to the patient.

The DreaMed Advisor Pro is a decision-support software for healthcare professionals managing Type 1 diabetes patients. It generates recommendations for optimizing insulin pump settings based on continuous glucose monitoring (CGM), self-monitoring blood glucose (SMBG), and pump data.

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 state "acceptance criteria" in a quantitative performance table but discusses equivalence to a predicate device and clinical validity compared to expert recommendations.

2. Sample Size and Data Provenance for the Test Set

• Sample Size for Clinical Study: 15 patients.
• Data Provenance: Retrospective clinical study. The document does not explicitly state the country of origin of the data.

3. Number of Experts and Qualifications

• Number of Experts: 17 experts.
• Qualifications of Experts: They are described as "Healthcare Professional who work at leading centers with a wealth of experience in the field of diabetes and who are especially familiar with diabetes technology devices." No specific number of years of experience or physician titles (e.g., radiologist) are provided, as this is for diabetes management.

4. Adjudication Method

• Adjudication Method: The clinical study compared recommendations to examine the "level of agreement between one expert to his colleague (total of 136 pairs) versus the level of agreement between DreaMed Advisor Pro recommendations and experts (total of 17 pairs)." This implies a comparison against individual expert opinions, rather than a formal consensus-based adjudication method like 2+1 or 3+1. Each expert's recommendation was likely treated as a reference point for comparison.

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

• The document describes a comparative study where the device's recommendations were compared against experts. It's a "retrospective clinical study" involving 17 experts reviewing data for 15 patients. While it involves multiple readers (experts) and multiple cases (patients), it focuses on the agreement between the AI and human experts, and experts among themselves, rather than a direct MRMC study to quantify how much human readers improve with AI assistance vs. without AI assistance. The study concluded that the Advisor Pro's recommendations were "significantly as good as the recommendations of expert," implying equivalence, but not necessarily an "improvement effect size" in a human-in-the-loop scenario.

6. Standalone Performance

• Yes, a standalone performance assessment was done. The "Additional retrospective clinical study" evaluated the DreaMed Advisor Pro's recommendations based on SMBG data alone and compared these recommendations directly to those of human experts. This demonstrates the algorithm's performance in generating recommendations without real-time human input or modification.

7. Type of Ground Truth Used

• Ground Truth: Expert consensus (or rather, expert recommendations serving as a reference) was used. The study compared the device's recommendations against the recommendations made by the 17 human experts.

8. Sample Size for the Training Set

• The document does not explicitly state the sample size used for the training set. It focuses on the validation of the device.

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

• The document does not describe how the ground truth for any potential training set was established. The clinical study mentioned is a validation study comparing the device's output to expert recommendations, not a description of the training data or its ground truth establishment.

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DreaMed Advisor Pro is a decision-support software intended for assisting healthcare professionals in the management of patients with Type 1 diabetes who:

• use insulin pumps as their insulin delivery therapy: .
• . monitor their glucose levels using either of the following:
  • CGM, or O
  • CGM and self-management blood glucose meter O
• . are above the age of 6 and under 65 years old; and
• . use rapid acting U-100 insulin analogs in their pump

DreaMed Advisor Pro is indicated for use by healthcare professionals when analyzing continuous glucose monitoring (CGM), self-monitoring blood glucose (SMBG) and pump data to generate recommendations for optimizing a patient's insulin pump settings for basal rate, carbohydrate ratio (CR), and correction factor (CF); without considering the full clinical status of a particular patient. DreaMed Advisor Pro does not replace clinical judgment.

DreaMed Advisor Pro is a software device that is designed to provide insulin therapy adjustment recommendations to physicians to assist in the management of diabetes for patients with Type 1 diabetes using an insulin pump and a continuous glucose monitoring (CGM) system.

The DreaMed Advisor Pro gathers and analyzes information inputted through qualified 3rd party Diabetes Management Systems (DMS), which collects biological input information from various diabetes devices. Diabetes device information required and used by DreaMed Advisor Pro includes glucose readings (CGM sensor readings with the option for capillary blood glucose measurements), insulin dosing logs, and meal data during daily routine care.

Following data collection and analysis, the DreaMed Advisor Pro generates results containing summary data and recommendations for adjustments to the patient's insulin therapy parameters, including: basal insulin delivery rate(s), insulin to carbohydrate ratio, and correction factor (insulin sensitivity)(b) (4) DreaMed Advisor Pro may also advise behavioral changes. Results are sent to a qualified 3th party Diabetes Management Systems, which displays results to physicians and a report provided by DreaMed Diabetes. The physician can approve, reject or change the recommendations and issue the updated treatment plan to the patient.

Acceptance Criteria and Study for DreaMed Advisor Pro

The DreaMed Advisor Pro is a software device that provides insulin therapy adjustment recommendations to physicians for managing Type 1 diabetes in patients using insulin pumps and Continuous Glucose Monitoring (CGM) systems. The device was evaluated for automatic Class III designation.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly present a table of quantitative acceptance criteria and corresponding reported device performance with numerical thresholds for metrics like accuracy, precision, or sensitivity/specificity for the device's recommendations compared to a gold standard. Instead, the "Performance Characteristics" section details two clinical studies that aim to demonstrate clinical validity and safety. The acceptance of the device seems to be based on the safety and a general alignment of its recommendations with expert opinion, rather than meeting specific quantitative performance metrics against a defined ground truth for individual recommendations.

However, based on the findings from the clinical studies described, we can infer the qualitative performance and the safety-focused acceptance:

• Percentage of CGM time within 70-180 mg/dL increased and percentage below 70 mg/dL reduced in Advisor Pro group compared to control group in one study. |
  | Clinical Validity (Alignment with Expert Opinion): Insulin dosing recommendations (basal rate, carb ratio, correction factor) are generally similar to expert physicians. | - Recommendations for basal rate and carbohydrate ratio were "generally similar" to expert physicians.
• Difference noted for correction factor recommendations between DreaMed Advisor Pro and physicians. |
  | Usability and Comprehension: Users (HCPs and patients/caregivers) can understand and appropriately interpret recommendations. | - Human factors testing performed with 48 lay users and 15 HCPs. "The design and results of the study were reviewed and found acceptable." |
  | Mitigation of Risks: Identified risks to health (erroneous recommendations, incorrect interpretation, inappropriate use, data corruption, insecure transmission) are mitigated to an acceptable level. | - Special controls and general controls are deemed sufficient to mitigate identified risks, with the healthcare professional acting as an intermediary. |

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

• Study 1 (Expert Physician Survey):

  • Test Set Sample Size: 15 patients. Each patient's data was presented as an anonymized PDF file.
  • Data Provenance: Retrospective data of 3 weeks of CGM, SMBG, and insulin pump data from children and adolescents with Type 1 Diabetes using an insulin pump. Collected from 3 centers in Germany, Israel, and Slovenia.

• Study 2 (Clinical Intervention Study):

  • Test Set Sample Size:
    • Intervention group (guided by Advisor Pro): 6 subjects.
    • Control group (guided by expert physician): 7 subjects.
  • Data Provenance: Prospective, single-center study conducted at a pediatric hospital in Israel. Subjects used the algorithm for two iterations of treatment recommendations over a 6-week study period, with data collected during this period.

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

• Study 1 (Expert Physician Survey):

  • Number of Experts: 9 experts.
  • Qualifications: "Expert endocrinologists" with "expert physicians" from 3 centers (3 physicians from each center) participated. No specific years of experience or sub-specialty mentioned beyond "expert endocrinologists."

• Study 2 (Clinical Intervention Study):

  • Number of Experts: Unspecified number of "diabetes healthcare professionals" or "expert physician" (singular). The control group was guided by "the expert physician." This implies at least one expert managed the control group.
  • Qualifications: "Diabetes healthcare professionals" or "expert physician." No specific qualifications mentioned.

4. Adjudication Method for the Test Set

• Study 1 (Expert Physician Survey):

  • Each of the 9 experts independently provided proposed recommended changes.
  • The recommendations from these physicians were then compared among themselves and to the Advisor Pro automated recommendations. The document states "The recommendations from the physicians at each site were also compared." This suggests a form of comparison or analysis of agreement/disagreement among experts, but not a formal consensus-based adjudication to establish a single ground truth before comparison to the device. Diversity in opinions was noted ("diversity between experts").

• Study 2 (Clinical Intervention Study):

  • This study compared outcomes between two groups: one guided by Advisor Pro and one guided by a physician. There was no explicit adjudication method described for establishing a single "ground truth" for insulin recommendations within this comparative effectiveness study, as the physician's adjustments in the control group served as the "standard of care" for comparison.

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

An MRMC study was effectively conducted in Study 1 (Expert Physician Survey).

• Study Design: 9 expert endocrinologists (multi-readers) independently reviewed data from 15 patients (multi-cases) and provided recommendations. These recommendations were then compared to the DreaMed Advisor Pro's recommendations.
• Effect Size of Human Readers with AI vs. without AI assistance: The study compared the Advisor Pro recommendations to expert physician recommendations. It did not involve human readers using the AI and then comparing their performance to human readers not using the AI. Therefore, it does not provide an effect size of how much human readers improve with AI assistance. Instead, it suggests a degree of similarity between AI and expert recommendations:
  • "the recommendations of the DreaMed Advisor Pro were generally similar to the recommendations of expert physicians with respect to the basal rate as well as the carbohydrate ratio (CR)."
  • "there was a difference between the physicians compared to DreaMed Advisor Pro and physician recommendations for the correction factor (CF)."
  • It also noted "diversity between experts with regards to recommendations to the same data."

6. Standalone (Algorithm Only) Performance

Yes, a standalone performance assessment was conducted for the DreaMed Advisor Pro implicit in Study 1 (Expert Physician Survey). The study compared the "Advisor Pro automated recommendations" directly against the recommendations of expert physicians. This indicates the algorithm's output was evaluated without human mediation in terms of generating the recommendation itself.

7. Type of Ground Truth Used

• Study 1 (Expert Physician Survey): Expert consensus/comparison. The ground truth for evaluating the DreaMed Advisor Pro's recommendations was the recommendations provided by the panel of 9 expert endocrinologists. However, as noted, there was "diversity between experts," so it wasn't a single "consensus" in a strict sense, but rather a comparison against a spectrum of expert opinions.
• Study 2 (Clinical Intervention Study): Clinical outcomes data (glycemic control metrics from CGM) and expert physician guidance as a control. The "ground truth" here was less about individual recommendation correctness and more about the impact on patient outcomes. The control group, guided by an expert physician, served as the comparative standard of care.

8. Sample Size for the Training Set

The document does not explicitly state the sample size used for the training set of the DreaMed Advisor Pro algorithm. It only describes the evaluation (test) studies.

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

The document does not provide information on how the ground truth for the training set was established. This information would typically be part of the software development and validation process, but it is not detailed in the provided "DECISION SUMMARY."

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