Evidence map›Paper›PMID 26839477›Full record

ArticleJournal of Korean medical science2016

In-Silico Trials for Glucose Control in Hospitalized Patients with Type 2 Diabetes.

Karam Choi, Tae Jung Oh, Jung Chan Lee, Myungjoon Kim, Hee Chan Kim, Young Min Cho, Sungwan Kim

Open access · goldAbstract read
In one paragraph

Article in Journal of Korean medical science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 37% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Karam ChoiInterdisciplinary Program for Bioengineering, Graduate School, Seoul National University, Seoul, Korea.ORCID 0000-0001-6781-7435
Tae Jung OhDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.; Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.ORCID 0000-0002-5078-6123
Jung Chan LeeInstitute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea.; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea.; Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-4546-0962
Myungjoon KimInterdisciplinary Program for Bioengineering, Graduate School, Seoul National University, Seoul, Korea.ORCID 0000-0002-4176-546X
Hee Chan KimInstitute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea.; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea.; Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-2112-426X
Young Min ChoDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.; Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-2331-6126
Sungwan KimInstitute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea.; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea.; Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-9318-849X
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although various basal-bolus insulin therapy (BBIT) protocols have been used in the clinical environment, safer and more effective BBIT protocols are required for glucose control in hospitalized patients with type 2 diabetes (T2D). Modeling approaches could provide an evaluation environment for developing the optimal BBIT protocol prior to clinical trials at low cost and without risk of danger. In this study, an in-silico model was proposed to evaluate subcutaneous BBIT protocols in hospitalized patients with T2D. The proposed model was validated by comparing the BBIT protocol and sliding-scale insulin therapy (SSIT) protocol. The model was utilized for in-silico trials to compare the protocols of adjusting basal-insulin dose (BBIT1) versus adjusting total-daily-insulin dose (BBIT2). The model was also used to evaluate two different initial total-daily-insulin doses for various levels of renal function. The BBIT outcomes were superior to those of SSIT, which is consistent with earlier studies. BBIT2 also outperformed BBIT1, producing a decreased daily mean glucose level and longer time-in-target-range. Moreover, with a standard dose, the overall daily mean glucose levels reached the target range faster than with a reduced-dose for all degrees of renal function. The in-silico studies demonstrated several significant findings, including that the adjustment of total-daily-insulin dose is more effective than changes to basal-insulin dose alone. This research represents a first step toward the eventual development of an advanced model for evaluating various BBIT protocols.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 2HospitalizationHumansHypoglycemic AgentsInsulinModels, TheoreticalBlood GlucoseHypoglycemic AgentsInsulinBiomedical EngineeringBlood GlucoseComputer SimulationDiabetes Mellitus, Type 2InsulinModels, Theoretical

Identifiers

PMID26839477
PMCPMC4729503
OpenAlexW2266399480

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.