Search Results
Found 3 results
510(k) Data Aggregation
(721 days)
GLYTEC, LLC
The Glucommander System is a glycemic management tool intended to evaluate current as well as cumulative patient blood glucose values coupled with patient information including age, weight and height, and, based on the aggregate of these measurement parameters, whether one or many, recommend an IV dosage of insulin, glucose or saline or a subcutaneous basal and bolus insulin dosing recommendation to adjust and maintain the blood glucose level towards a configurable physician-determined target range.
The Glucommander System is indicated for use in adult and pediatric (ages 2 - 17 years) patients.
The G+ System logic is not a substitute for, but rather an adjunct to clinical reasoning. The measurements and calculations generated are intended to be used by qualified and trained medical personnel in evaluating patient conditions in conjunction with clinical history, symptoms, and other diagnostic measurements, as well as the medical professional's clinical judgment. No medical decision should be based solely on the recommended quidance provided by this software program.
The indications for use are identical to the predicate device.
The Glucommander System is a software algorithm device intended to evaluate the current as well as cumulative patient blood glucose values and, based on the aggregate of those measurements, whether one or many, recommend a dosage of insulin, glucose, or saline in order to direct the blood glucose level towards a predetermined target range. Once that target blood glucose range has been reached, the system's function is to recommend a titration of insulin, glucose, and saline for the purpose of maintaining the patient's blood glucose level in that target range. The system is programmed to provide intravenous dosing of glucose, saline, and insulin, as well as subcutaneous dosing of insulin for both pediatric (ages 2-17 years) and adult patients.
This document is a 510(k) summary for the Glytec Glucommander device. It details the device's description, indications for use, and a comparison to a predicate device to establish substantial equivalence.
Based on the provided text, the device "Glytec Glucommander" functions as a software algorithm that recommends insulin, glucose, or saline dosages based on patient blood glucose values and other patient information. The 510(k) submission primarily focuses on demonstrating substantial equivalence to a predicate device and does not involve the type of study that would typically establish quantitative acceptance criteria for performance metrics (e.g., sensitivity, specificity, or dose accuracy compared to a ground truth) and then empirically prove the device meets those criteria through a structured test set evaluation, as is common for AI/ML-based diagnostic devices.
Instead, the submission for Glytec Glucommander focuses on demonstrating that new functionalities (Continuous Tube Feeding Module, Ambulatory Care Module, Subcutaneous Module) "do not raise different questions of safety or effectiveness" compared to the predicate device. The performance data section explicitly states: "The 510k submission included software, cybersecurity, and human factors documentation to demonstrate the performance of the device is substantially equivalent to the predicate."
Therefore, I cannot provide a table of acceptance criteria and reported device performance in the way typically seen for standalone performance claims (e.g., accuracy against a medical ground truth). The acceptance criteria, in this context, relate more to regulatory and engineering standards (e.g., software validation, cybersecurity, human factors) and the demonstration of substantial equivalence rather than a medical performance metric.
Given the information provided, here's an analysis of what can be inferred or explicitly stated regarding the acceptance criteria and the "study" that proves the device meets them:
1. A table of acceptance criteria and the reported device performance
As explained above, the document does not present quantitative performance acceptance criteria (e.g., a specific percentage of cases where the device must be accurate in its recommendations) compared to a medical ground truth. Instead, the "acceptance criteria" are implied by the regulatory standard of "substantial equivalence" and the types of documentation provided.
| Acceptance Criterion (Implied) | Reported Device Performance/Evidence |
|---|---|
| New functionality does not raise different safety/effectiveness questions. (Regulatory/Clinical) | "These features do not raise different questions of safety or effectiveness." Supported by non-clinical performance data comparing to the predicate. |
| Device is substantially equivalent to predicate device (K113853). (Regulatory) | "Information presented supports substantial equivalence of the Glucommander System to the predicate device." "The proposed enhancements have the same indications for use, are similar in design, have the same fundamental scientific technology, and are tested the same way as the predicate device." |
| Software functionality and integrity. (Engineering/Software) | "The 510k submission included software... documentation to demonstrate the performance of the device is substantially equivalent to the predicate." Implies compliance with software development lifecycle standards and verification/validation. |
| Cybersecurity. (Engineering/Security) | "...cybersecurity... documentation to demonstrate the performance of the device is substantially equivalent to the predicate." Implies measures to protect data and system integrity. |
| Human factors. (Usability/Safety) | "...human factors documentation to demonstrate the performance of the device is substantially equivalent to the predicate." Implies usability testing and design to minimize user error. |
| Compliance with general controls. (Regulatory) | Stated in the FDA letter: "You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting... good manufacturing practice... etc." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document explicitly states that "Non-clinical performance data was used to demonstrate that the device is substantially equivalent to the predicate device." This suggests that the "testing" involved software, cybersecurity, and human factors validation rather than a clinical study with a patient data test set. Therefore, there is no stated sample size for a patient-based test set, nor information on data provenance (country, retrospective/prospective). This submission relies on engineering and software validation and comparison to a predicate, not clinical performance data from a patient cohort.
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)
Given that "Non-clinical performance data" was used and no clinical test set for algorithmic performance against a medical ground truth is described, there is no information provided regarding experts establishing ground truth for a clinical test set.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable, as no clinical test set with human adjudication is described.
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 such study is mentioned or implied. The device is a "drug dose calculator" that recommends dosages, and is an "adjunct to clinical reasoning," not typically a diagnostic AI. The submission focuses on substantial equivalence through non-clinical data.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
The "performance data" provided are non-clinical (software, cybersecurity, human factors). The device provides "recommendations," implying human-in-the-loop operation, but no standalone performance data for the algorithm's medical accuracy (e.g., how often its recommendations are correct/optimal compared to a gold standard) is detailed for a specific test set. The claim relies on the new modules being "similar in design" and "tested the same way as the predicate device," which itself would have had to meet performance criteria.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable, as no clinical test set requiring a medical ground truth (e.g., for diagnostic accuracy or treatment efficacy) is described in this 510(k) summary. The ground truth, implicitly, would be the established performance and safety of the predicate device, against which the new functionalities are compared through non-clinical means.
8. The sample size for the training set
The document does not describe the development or training of an AI/ML model in a manner that would typically involve a "training set" of patient data. The Glucommander is described as a "software algorithm device," which could imply rule-based logic or a different type of computational model not necessarily relying on a large data training set in the way modern deep learning AI does. Therefore, there is no information on a training set sample size.
9. How the ground truth for the training set was established
Not applicable, as no training set is described. If the algorithm is rule-based, its "ground truth" would be established by clinical guidelines and expert medical knowledge encoded into the software rather than data-driven training.
Ask a specific question about this device
(131 days)
GLYTEC, LLC
The Glucommander System is a glycemic management tool intended to evaluate current and cumulative patient blood glucose values and coupled with patient information including age, weight and height, and, based on the aggregate of these measurement parameters, whether one or many, recommend an IV dosage of insulin, glucose or saline or a subcutaneous basal and bolus insulin dosing recommendation to adjust and maintain the blood glucose level towards a configurable clinician determined target range.
The Glucommander System is indicated for use in adult and pediatric (ages 2 - 17 years) patients.
The Glucommander System logic is not a substitute for, but rather an adjunct to clinical reasoning. The measurements and calculations generated are intended to be used by qualified and trained medical personnel in evaluating patient conditions in conjunction with clinical history, symptoms, and other diagnostic measurements, as well as the medical professional's clinical judgment. No medical decision should be based solely on the recommended guidance provided by this software program.
The Glytec, LLC Glucommander System is a software device used to evaluate current and cumulative patient blood glucose values, and, based on the aggregate of those measurements, whether one or many, recommend an IV dosage of insulin, glucose or saline to direct the blood glucose level towards a predetermined target range. Once that target blood glucose range has been reached, the system's function is to recommend a titration of insulin, glucose, and saline for the purpose of maintaining the patient's blood glucose level in that target range. The system is programmed to provide intravenous dosing of glucose, saline, and insulin, as well as subcutaneous dosing of insulin for both pediatric (ages 2 - 17 years) and adult patients.
Acceptance Criteria and Study for Glytec LLC, Glucommander™ System (K113853)
This 510(k) submission (K113853) is for a modification to an existing device, the GlyTec, LLC G+ System (K101344). The modification is the addition of a pediatric protocol that considers the weight of the patient. As such, the submission focuses on the performance of the modified software and its substantial equivalence to the predicate device, rather than establishing new acceptance criteria or conducting a comprehensive clinical study to prove general device performance.
Based on the provided document, the following can be inferred regarding acceptance criteria and supporting studies:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly state specific quantitative acceptance criteria or performance metrics for the modified Glucommander™ System (K113853) in a table format.
Instead, the submission relies on demonstrating substantial equivalence to the predicate device (K101344) and emphasizes that the modifications introduced (pediatric protocol) do not raise new safety or effectiveness concerns.
The reported "performance" is qualitative, focusing on functional aspects:
| Acceptance Criterion (Inferred) | Reported Device Performance |
|---|---|
| Functional Equivalence to predicate device (K101344) for adult patients | "Other user screen labeling such as the function of screen buttons, the ability to add additional patient data and user information, the ability to password protect information and other similar security features, data handling performance, user controlled automatic system shutdown and software update notifications are unchanged." |
| Correct Calculation of Initial Multiplier for pediatric patients based on weight | "An additional input validation on the date of birth field identifies pediatric patients and calculates the patient's initial multiplier based on the patient's weight..." |
| Appropriate User Interface Design for adult/pediatric identification | "Initial starting parameters and the user interface design were modified to allow for the easy identification and calculation of initial multiplier based on a pediatric patient's weight that clearly indicate the order set as either adult or pediatric." |
| Software Functionality as intended | "The results of usability testing of representative users of the device, software testing and performance testing of the device demonstrate the device functions as intended." |
| No New Safety or Effectiveness Concerns compared to predicate device | "Glytec, Inc. believes no differences exist between this system and the predicate system that raise any new safety.or effectiveness concerns." |
2. Sample Size for the Test Set and Data Provenance
The document mentions "usability testing of representative users of the device, software testing and performance testing of the device." However, it does not specify the sample size used for these tests or the data provenance (e.g., country of origin, retrospective/prospective nature of data).
Given the nature of the submission (modification to an existing device for substantial equivalence), it's likely these tests were focused on verifying the correct implementation of the new pediatric protocol and ensuring no regressions in existing functionalities, rather than a large-scale clinical validation study.
3. Number of Experts and Qualifications for Ground Truth
The document does not mention the use of experts to establish a "ground truth" for a test set. The evaluation appears to be based on internal testing (usability, software, performance) to confirm the new features work as designed and that overall functionality remains equivalent to the predicate.
4. Adjudication Method for the Test Set
Since there is no mention of external experts establishing ground truth for a test set, there is no information on an adjudication method.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC comparative effectiveness study was done or reported. The submission focuses on substantial equivalence based on technical modifications rather than a comparative study of human reader performance with and without AI assistance.
6. Standalone Performance Study
A standalone performance study focused on the algorithm only (without human-in-the-loop performance) was implicitly done through "software testing and performance testing of the device." These tests would assess the internal logic and calculations of the Glucommander™ System, including the new pediatric protocol's ability to correctly calculate the initial multiplier. However, the specific metrics and results of such a standalone study are not detailed.
7. Type of Ground Truth Used
For the "software testing and performance testing," the ground truth would likely be based on:
- Engineering specifications and design documents: Verifying that the software calculations and logic conform to the intended design, especially for the new pediatric weight-based multiplier.
- Predetermined correct outputs: For specific test cases, the expected correct IV dosage recommendations or multiplier calculations would be known and used to validate the device's output.
- Clinical rationale: The pediatric protocol's design would be based on clinical understanding of pediatric glycemic management.
The document does not explicitly state that pathology, outcomes data, or expert consensus (external to the development process) were used as "ground truth" in a formal sense for this specific submission.
8. Sample Size for the Training Set
The document does not provide information on the sample size for a training set. As this is a software device for recommending insulin dosages based on blood glucose values and patient parameters, it's likely built on established algorithms and clinical guidelines, rather than relying on a large "training set" in the context of machine learning for image classification, for example. If any machine learning elements were involved, details are not provided.
9. How the Ground Truth for the Training Set Was Established
Given the lack of information on a training set, the method for establishing its ground truth is also not described.
Ask a specific question about this device
(46 days)
GLYTEC, LLC (FORMALLY KNOWN AS GLUCOTEC, INC.)
The G+ System is intended to evaluate the current as well as cumulative patient blood glucose values, and, based on the aggregate of those measurements, whether one or many, regulate the infusion of I.V. fluids, through and I.V. infusion pump, and drive the blood glucose level towards a predetermined target range. Once that target blood glucose range has been reached, the system's function is to recommend a titration of insulin, glucose, and saline for the purpose of maintaining the patient's blood glucose level in that target range. The system is provide intravenous dosing of glucose, saline, and insulin, as well as subcutaneous dosing of glucose and insulin.
The G+ System logic is not a substitute for, but rather an assist to clinical reasoning. The measurements and calculations generated are intended to be used by qualified and trained medical personnel in evaluating patient conditions in conjunction with clinical history, symptoms, and other diagnostic measurements, as well as the medical professional's clinical judgment. No medical decision should be based solely on the recommended guidance provided by this software program.
The Glytec, LLC G+ System is a software device intended to evaluate the current as well as cumulative patient blood glucose values, and, based on the aggregate of those measurements, whether one or many, regulate the infusion of I.V. fluids, through an I.V. infusion pump, and direct the blood glucose level towards a predetermined target range. Once that target blood glucose range has been reached, the system's function is to recommend a titration of insulin, glucose, and saline for the purpose of maintaining the patient's blood glucose level in that target range. The system is provide intravenous dosing of glucose, saline, and insulin, as well as subcutaneous dosing of glucose and insulin.
The device is available in a Standard Edition or server based Enterprise Edition.
This 510(k) summary does not contain the detailed information required to fill out all the sections of your request regarding acceptance criteria and a study proving those criteria are met. This document primarily focuses on demonstrating substantial equivalence to a predicate device, rather than providing a new, comprehensive performance study that establishes and validates new acceptance criteria.
Here's what can be inferred and what is missing:
1. A table of acceptance criteria and the reported device performance:
This document does not provide explicit acceptance criteria or detailed performance metrics. The core of this 510(k) is a declaration of substantial equivalence to a predicate device (CollaborativeMed, LLC, Glucommander Plus #K061110). Studies demonstrating new performance would have been required for a device that wasn't substantially equivalent to a predicate.
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):
No information is provided regarding a test set sample size or data provenance for a performance study. Since this is a Special 510(k) and focuses on substantial equivalence, it's likely they are relying on the predicate device's established performance without conducting new, extensive performance trials.
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):
No information is provided regarding experts or ground truth establishment for a test set. This would be relevant if a new performance study were conducted.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
No information is provided on an adjudication method, as there's no mention of a performance study with a 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 information is provided about an MRMC study or the effect size of human improvement with AI assistance. This document describes a software device for dose calculation, not an AI for image interpretation or diagnosis where MRMC studies are common.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
The device description explicitly states: "The G+ System logic is not a substitute for, but rather an assist to clinical reasoning... No medical decision should be based solely on the recommended guidance provided by this software program." This indicates it's designed for use with human-in-the-loop. Therefore, a standalone performance study in the sense of a fully autonomous algorithm acting without human oversight would contradict its intended use. However, no specific standalone performance study results are provided.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
No information is provided regarding the type of ground truth used, as there's no mention of a new performance study requiring ground truth establishment.
8. The sample size for the training set:
No information is provided regarding a training set sample size. This document focuses on a "Special 510(k)" for modifications to an existing predicate device, implying that the core algorithms and their validation likely happened with the original device and are not being re-evaluated with a new training set.
9. How the ground truth for the training set was established:
No information is provided on how ground truth was established for a training set.
In summary:
This document is a Special 510(k), which is typically used for modifications to an existing device where the changes do not significantly affect the safety or effectiveness. The primary claim for regulatory clearance is substantial equivalence to the predicate device (CollaborativeMed, LLC, Glucommander Plus #K061110) based on an analysis of "overall performance characteristics." This type of submission generally does not require a new, comprehensive clinical or performance study with new acceptance criteria and detailed data as would be found in a Traditional 510(k) for a novel device or a device with significant changes in technology or indications. The assumption is that the predicate device already demonstrated adequate performance.
Ask a specific question about this device
Page 1 of 1