Evidence map›Paper›PMID 36793281›Full record

ArticleFrontiers in endocrinology2023

In-silico evaluation of an artificial pancreas achieving automatic glycemic control in patients with type 1 diabetes.

Wenping Liu, Ting Chen, Bingjin Liang, Yanran Wang, Haoyu Jin

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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. Review
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

5 authors.

Wenping LiuInstitute of Medical Devices, Guangdong Food and Drug Vocational College, Guangzhou, China.
Ting ChenInstitute of Medical Devices, Guangdong Food and Drug Vocational College, Guangzhou, China.
Bingjin LiangInstitute of Medical Devices, Guangdong Food and Drug Vocational College, Guangzhou, China.
Yanran WangInstitute of Medical Devices, Guangdong Food and Drug Vocational College, Guangzhou, China.
Haoyu JinInstitute of Medical Devices, Guangdong Food and Drug Vocational College, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial pancreas (AP) is a useful tool for maintaining the blood glucose (BG) of patients with type 1 diabetes (T1D) within the euglycemic range. An intelligent controller has been developed based on general predictive control (GPC) for AP. This controller exhibits good performance with the UVA/Padova T1D mellitus simulator approved by the US Food and Drug Administration. In this work, the GPC controller was further evaluated under strict conditions, including a pump with noise and error, a CGM sensor with noise and error, a high carbohydrate intake, and a large population of 100 in-silico subjects. Test results showed that the subjects are in high risk for hypoglycemia. Thus, an insulin on board (IOB) calculator, as well as an adaptive control weighting parameter (AW) strategy, was introduced. The percentage of time spent in euglycemic range of the in-silico subjects was 86.0% ± 5.8%, and the patient group had a low risk of hypoglycemia with the GPC+IOB+AW controller. Moreover, the proposed AW strategy is more effective in hypoglycemia prevention and does not require any personalized data compared with the IOB calculator. Thus, the proposed controller realized an automatic control of the BG of patients with T1D without meal announcements and complex user interaction.

Indexed as

Diabetes Mellitus, Type 1HypoglycemiaPancreas, ArtificialAlgorithmsBlood GlucoseGlycemic ControlHumansHypoglycemic AgentsInsulinBlood GlucoseHypoglycemic AgentsInsulinadaptive control weighting parameterautomated artificial pancreaseffective and safe glycemic controlgeneral predictive controlhypoglycemia prevention

Identifiers

PMID36793281
PMCPMC9922739

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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.