The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Bolus Calculators
Open accessAbstract
Matching meal insulin to carbohydrate intake, blood glucose, and activity level is recommended in type 1 diabetes management. Calculating an appropriate insulin bolus size several times per day is, however, challenging and resource demanding. Accordingly, there is a need for bolus calculators to support patients in insulin treatment decisions. Currently, bolus calculators are available integrated in insulin pumps, as stand-alone devices and in the form of software applications that can be downloaded to, for example, smartphones. Functionality and complexity of bolus calculators vary greatly, and the few handfuls of published bolus calculator studies are heterogeneous with regard to study design, intervention, duration, and outcome measures. Furthermore, many factors unrelated to the specific device affect outcomes from bolus calculator use and therefore bolus calculator study comparisons should be conducted cautiously. Despite these reservations, there seems to be increasing evidence that bolus calculators may improve glycemic control and treatment satisfaction in patients who use the devices actively and as intended.
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In the citing paper
“Insulin stacking (overlap of bolus doses) is estimated to occur in 60% of insulin bolus doses putting the individual at risk for hypoglycemia.22”
From Shining the Spotlight on Multiple Daily Insulin Therapy: Real-World Evidence of the InPen Smart Insulin Pen (2024) · cites this paper as [22]
In the citing paper
“two meals containing the same amount of carbohydrate can elicit different glycemic responses because of differences in food structure, processing, starch fractions (rapidly available vs. slowly available), and the effect of non-carbohydrate components (fat, protein, fiber) on gastric emptying and intestinal digestion [4,5,6,7].”
From Does Resistant Starch Formed by Cooling Pasta Decrease the Postprandial Glycemic Response in Type 1 Diabetes? A Randomized Single-Blind Crossover Study (2026) · cites this paper as [7]
In the citing paper
“In addition, bolus calculators integrated into medical products or software/apps can reduce wrong bolus calculations by the user and subsequently the risk of hypoglycemic events [35].”
From Self-Monitoring of Blood Glucose as an Integral Part in the Management of People with Type 2 Diabetes Mellitus (2022) · cites this paper as [35]
Citations
Cites
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Research works printed but not linked: 2
- Walsh PA, 2006, Pumping Insulin
- Schmidt S, 2014, Diabetes Technol Ther, 15, A-1
Cited by
Sorted by citations
Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment
Cappon, G., Acciaroli, G., Vettoretti, M., Facchinetti, A., & Sparacino, G. (2017) · Electronics · doi:10.3390/electronics6030065 · Cited by 247
ISPAD Clinical Practice Consensus Guidelines 2018: diabetes technologies
Sherr, J. L., Tauschmann, M., Battelino, T., de Bock, M., Forlenza, G., Roman, R., Hood, K. K., & Maahs, D. M. (2018) · Pediatric Diabetes · doi:10.1111/pedi.12731 · Cited by 197
Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors
Vettoretti, M., Cappon, G., Facchinetti, A., & Sparacino, G. (2020) · Sensors · doi:10.3390/s20143870 · Cited by 176
Reinforcement learning application in diabetes blood glucose control: A systematic review
Tejedor, M., Woldaregay, A. Z., & Godtliebsen, F. (2020) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2020.101836 · Cited by 173
Preventing undesirable behavior of intelligent machines
Thomas, P. S., da Silva, B. C., Barto, A. G., Giguere, S., Brun, Y., & Brunskill, E. (2019) · Science · doi:10.1126/science.aag3311 · Cited by 156
Metadata
- Authors
- Schmidt, S., & Nørgaard, K.
- Affiliations
- Hvidovre Hospital (DK)
- Corresponding author
- Schmidt, Signe
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2014-05-19
- Volume
- 8
- Issue
- 5
- Pages
- 1035-1041
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC4455388
- OpenAlex
- W4241093605
- Cited by
- 170
- References
- 36
- Citations by year
- 2026: 12 · 2025: 22 · 2024: 17 · 2023: 22 · 2022: 10 · 2021: 12 · 2020: 18 · 2019: 16 · 2018: 14 · 2017: 12 · 2016: 8 · 2015: 7
- FWCI
- 1.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- bolus calculator, type 1 diabetes, insulin pump, mobile application, glycemic control, treatment satisfaction, patient decision support
- MeSH terms
- Blood Glucose, Diabetes Mellitus, Type 1, Humans, Hypoglycemic Agents, Insulin, Drug Dosage Calculations
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