Evidence map›Paper›PMID 38799141›Full record

ArticleJournal of clinical biochemistry and nutrition2024

Effect of high-amylose rice "Hoshinishiki" on postprandial glucose levels measured by continuous glucose monitoring in patients with diabetes.

Jia Li, Koutatsu Maruyama, Satoshi Minakuchi, Kumiko Toshimitu, Ryoichi Kawamura, Yasunori Takata, Haruhiko Osawa

Abstract read
In one paragraph

Article in Journal of clinical biochemistry and nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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.

Jia LiThe United Graduate School of Agricultural Sciences, Ehime University, 3-5-7 Tarumi, Matsuyama, Ehime 790-8566, Japan.
Koutatsu MaruyamaThe United Graduate School of Agricultural Sciences, Ehime University, 3-5-7 Tarumi, Matsuyama, Ehime 790-8566, Japan.
Satoshi MinakuchiEhime Research Institute of Agriculture, Forestry and Fisheries, 311 Kaminamba, Matsuyama, Ehime 799-2405, Japan.
Kumiko ToshimituEhime University Hospital, Shitsukawa, Toon, Ehime 791-0295, Japan.
Ryoichi KawamuraDepartment of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295, Japan.
Yasunori TakataDepartment of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295, Japan.
Haruhiko OsawaDepartment of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We examined the effect of consuming Hoshinishiki, a type of high-amylose rice, on postprandial glucose as measured by continuous glucose monitoring in diabetes patients. A single-blinded clinical trial involving 11 hospitalized patients diagnosed with type 1 or type 2 diabetes was performed. The patients consumed high-amylose rice for 2 days (days 2 and 4 of the study) and control rice for 2 days (days 1 and 3 of the study). Linear mixed models were used to test the effects on the 24-h mean glucose levels, time in range (TIR), incremental area under the curve of glucose levels at 2 h after meals, the average glucose levels at 1, 2, and 3 h after meals, and the maximum glucose levels within 3 h. The results showed that the consumption of high-amylose rice led to significantly lower 24-h mean glucose levels, levels at 2 and 3 h after a meal, and postprandial glucose peak levels within 3 h, as well as significantly higher TIR. A similar trend was observed when the analysis was restricted to patients with type 2 diabetes. These results suggest that high-amylose rice may be a more beneficial staple food for glycemic control than regular rice.

Indexed as

continuous glucose monitoringdiabetesglucosehigh-amylose rice

Identifiers

PMID38799141
PMCPMC11111464

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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.