Trial reportJournal of diabetes science and technology2012
Inpatient studies of a Kalman-filter-based predictive pump shutoff algorithm.
Trial report in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 57 citations in OpenAlex.
- Predictive hyperglycemia and hypoglycemia minimization: In-home double-blind randomized controlled evaluation in children and young adolescents.Pediatric diabetes · 2018Trial
- In-home nighttime predictive low glucose suspend experience in children and adults with type 1 diabetes.Pediatric diabetes · 2017Trial
- Predictive Hyperglycemia and Hypoglycemia Minimization: In-Home Evaluation of Safety, Feasibility, and Efficacy in Overnight Glucose Control in Type 1 Diabetes.Diabetes care · 2017Trial
- Hypoglycemia Detection and Carbohydrate Suggestion in an Artificial Pancreas.Journal of diabetes science and technology · 2016Trial
- Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis.Diabetes care · 2015Trial
- The impact of accelerometer use in exercise-associated hypoglycemia prevention in type 1 diabetes.Journal of diabetes science and technology · 2015Trial
- A randomized trial of a home system to reduce nocturnal hypoglycemia in type 1 diabetes.Diabetes care · 2014Trial
- Outpatient safety assessment of an in-home predictive low-glucose suspend system with type 1 diabetes subjects at elevated risk of nocturnal hypoglycemia.Diabetes technology & therapeutics · 2013Trial
- Artificial Intelligence in Diabetes Care: Applications, Challenges, and Opportunities Ahead.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2025Review
- Assessment of Seasonal Stochastic Local Models for Glucose Prediction without Meal Size Information under Free-Living Conditions.Sensors (Basel, Switzerland) · 2022Article
- Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.Journal of diabetes science and technology · 2021Article
- Improved Low-Glucose Predictive Alerts Based on Sustained Hypoglycemia: Model Development and Validation Study.JMIR diabetes · 2021Article
- Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only.Sensors (Basel, Switzerland) · 2021Article
- Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.Sensors (Basel, Switzerland) · 2020Review
- Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications.Diabetes & metabolism journal · 2019Review
- Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review.Biomedical engineering online · 2019Review
- Continuous Glucose Monitoring Sensors: Past, Present and Future Algorithmic Challenges.Sensors (Basel, Switzerland) · 2016Review
- Hypo- and Hyperglycemic Alarms: Devices and Algorithms.Journal of diabetes science and technology · 2015Review
- A novel method to detect pressure-induced sensor attenuations (PISA) in an artificial pancreas.Journal of diabetes science and technology · 2014Article
- Accuracy evaluation of blood glucose monitoring systems in children on overnight closed-loop control.Journal of diabetes science and technology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundAn insulin pump shutoff system can prevent nocturnal hypoglycemia and is a first step on the pathway toward a closed-loop artificial pancreas. In previous pump shutoff studies using a voting algorithm and a 1 min continuous glucose monitor (CGM), 80% of induced hypoglycemic events were prevented.
methodsThe pump shutoff algorithm used in previous studies was revised to a single Kalman filter to reduce complexity, incorporate CGMs with different sample times, handle sensor signal dropouts, and enforce safety constraints on the allowable pump shutoff time.
resultsRetrospective testing of the new algorithm on previous clinical data sets indicated that, for the four cases where the previous algorithm failed (minimum reference glucose less than 60 mg/dl), the mean suspension start time was 30 min earlier than the previous algorithm. Inpatient studies of the new algorithm have been conducted on 16 subjects. The algorithm prevented hypoglycemia in 73% of subjects. Suspension-induced hyperglycemia is not assessed, because this study forced excessive basal insulin infusion rates.
conclusionsThe new algorithm functioned well and is flexible enough to handle variable sensor sample times and sensor dropouts. It also provides a framework for handling sensor signal attenuations, which can be challenging, particularly when they occur overnight.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.