Evidence map›Paper›PMID 37193162›Full record

ArticleAmerican journal of translational research2023

Evaluation of dietary quality of patients with severe cerebrovascular disease by diet balance index-16.

Siwei Yu, Qiong Song, Wei Gu

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% 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

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 2 institutions in 1 country.

Siwei YuDepartment of Critical Care Medicine, Shanghai Electric Power Hospital Shanghai 200050, China.
Qiong SongDepartment of Critical Care Medicine, Shanghai Pudong New Area Gongli Hospital Shanghai 200050, China.
Wei GuNutriology Department, Shanghai Pudong New Area Gongli Hospital Shanghai 200050, China.
Second Military Medical University · CNShanghai University of Electric Power · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the dietary quality of patients with severe cerebrovascular disease using Diet Balance Index-16 (DBI-16) and to provide scientific evidence for the establishment of targeted dietary intervention and related dietary nutritional education for patients.

methodsThe general information of 214 hospitalized patients with severe cerebrovascular disease, including gender and age etc., were investigated by a self-made questionnaire on health risk factors, and the dietary quality conditions of patients was evaluated by DBI-16 scoring method.

resultsThe dietary quality of patients with severe cerebrovascular disease had low levels of imbalanced conditions, accompanied with low levels of inadequate intake and excessive intake. The degree of excessive intake in female patients was clearly less than that in male patients. The degree of inadequate intake and total scores in patients younger than 55 years old was lower than those in the other two groups. The intake of vegetables, fruits, milk and soybeans in most of patients did not reach the recommended nutrient intake and the animal product amount was insufficient. In addition, the intake of low quality food and condiments such as oil and salt were excessive in patients with severe cerebrovascular disease. Dietary pattern A was the main model.

conclusionsThe overall diet structure of patients with severe cerebrovascular disease is not rational. It is recommended to appropriately balance the intake of grains and animal products, increase the intake of milk, soybeans, vegetables and fruits, and strictly control the amount of oil and salt.

Indexed as

Dietary balance indexdietary qualitysevere cerebrovascular disease

Identifiers

PMID37193162
PMCPMC10182525
OpenAlexW4376870947

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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.