Evidence map›Paper›PMID 38212811›Full record

ArticleDiabetology & metabolic syndrome2024

Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank.

Jinxia Hu, Xuanyang Wang, Licheng Cheng, Keke Dang, Zhu Ming, Xinmiao Tao, Xiaoqing Xu, Shuvan Kumar Sarker, Ying Li

Open access · goldAbstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
6.1field-weighted citation impact, top 4% 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 1 institution in 1 country.

Jinxia HuDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Xuanyang WangDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Licheng ChengDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Keke DangDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Zhu MingDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Xinmiao TaoDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Xiaoqing XuDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Shuvan Kumar SarkerDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Ying LiDepartment of Nutrition and Food Hygiene, Key Laboratory of Precision Nutrition and Health, School of Public Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China. liying_helen@163.com.
Harbin Medical University · CN

Funding

National Key Research and Development Program of China 2022YFC2010105National Natural Science Foundation of China 82030100
6 · The paper itself

Abstract

backgroundTo explore the relationship between sleep patterns and cardiovascular disease (CVD) incidence and mortality risk in a population with type 2 diabetes through a UK Biobank sample.

methodsA total of 6860 patients with type 2 diabetes were included in this study. Five sleep factors (including Chronotype, sleep duration, insomnia, daytime sleepiness, and snoring) were collected as a questionnaire. The calculation generates a sleep score of 0-5, and then three sleep patterns were defined based on the sleep scores: poor sleep pattern (0-2), Intermediate sleep pattern (3-4), and healthy sleep pattern (5). HRs and 95% confidence intervals were calculated by multivariate COX proportional risk model adjustment. Restricted cubic splines were used to validate linear associations between sleep scores CVD events.

resultsOur results found a reduced risk of CVD events in individuals with healthy sleep patterns compared to participants with poor sleep patterns. CVD Mortality (HR, 0.690; 95% CI 0.519-0.916), ASCVD (Atherosclerosis CVD) (HR, 0.784; 95% CI 0.671-0.915), CAD (Coronary Artery Disease) (HR, 0.737; 95% CI 0.618-0.879), PAD (Peripheral Arterial Disease) (HR, 0.612; 95% CI 0.418-0.896), Heart Failure (HR, 0.653; 95% CI 0.488-0.875). Restricted cubic spline responded to a negative linear correlation between sleep scores and CVD Mortality, ASCVD, CAD, PAD, and Heart Failure.

conclusionsHealthy sleep patterns are significantly associated with a reduced risk of CVD Mortality, ASCVD, CAD, PAD, and Heart Failure in the diabetes population.

Indexed as

Cardiovascular diseasePolygenic risk score (PRS)Sleep patternType 2 diabetes mellitus (T2DM)

Identifiers

PMID38212811
PMCPMC10782582
OpenAlexW4390748179

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.