Evidence map›Paper›PMID 38245731›Full record

ArticleCardiovascular diabetology2024

Circulating palmitoyl sphingomyelin levels predict the 10-year increased risk of cardiovascular disease death in Chinese adults: findings from the Da Qing Diabetes Study.

Xin Qian, Hongmei Jia, Jinping Wang, Siyao He, Meng Yu, Xinxing Feng, Qiuhong Gong, Yali An, Xuan Wang, Na Shi and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 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
2.1field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

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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

14 authors at 2 institutions in 1 country.

Xin Qian *Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0003-2961-3380
Hongmei Jia *Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jinping WangDepartment of Cardiology, Da Qing First Hospital, Da Qing, China.
Siyao HeEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Meng YuInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xinxing FengEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Qiuhong GongEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yali AnEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xuan WangEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Na ShiEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hui LiDepartment of Cardiology, Da Qing First Hospital, Da Qing, China.
Zhongmei ZouInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. zmzou@implad.ac.cn.
Guangwei LiDepartment of Endocrinology, China-Japan Friendship Hospital, Beijing, China. guangwei_li45@126.com.ORCID 0000-0003-1061-7293
Yanyan ChenEndocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. dryanyanchen@126.com.ORCID 0000-0002-4697-149X
Chinese Academy of Medical Sciences & Peking Union Medical College · CNChina-Japan Friendship Hospital · CN

Funding

ACL HHS U19GH000636CGH CDC HHS U19 GH000636
6 · The paper itself

Abstract

backgroundHigher levels of palmitoyl sphingomyelin (PSM, synonymous with sphingomyelin 16:0) are associated with an increased risk of cardiovascular disease (CVD) in people with diabetes. Whether circulating PSM levels can practically predict the long-term risk of CVD and all-cause death remains unclear. This study aimed to investigate whether circulating PSM is a real predictor of CVD death in Chinese adults with or without diabetes.

methodsA total of 286 and 219 individuals with and without diabetes, respectively, from the original Da Qing Diabetes Study were enrolled. Blood samples collected in 2009 were used as a baseline to assess circulating PSM levels. The outcomes of CVD and all-cause death were followed up from 2009 to 2020, and 178 participants died, including 87 deaths due to CVD. Cox proportional hazards regression was used to estimate HRs and their 95% CIs for the outcomes.

resultsFractional polynomial regression analysis showed a linear association between baseline circulating PSM concentration (log-2 transformed) and the risk of all-cause and CVD death (p < 0.001), but not non-CVD death (p > 0.05), in all participants after adjustment for confounders. When the participants were stratified by PSM-tertile, the highest tertile, regardless of diabetes, had a higher incidence of CVD death (41.5 vs. 14.7 and 22.2 vs. 2.9 per 1000 person-years in patients with and without diabetes, respectively, all log-rank p < 0.01). Individuals with diabetes in the highest tertile group had a higher risk of CVD death than those in the lowest tertile (HR = 2.73; 95%CI, 1.20-6.22).

conclusionsElevated PSM levels are significantly associated with a higher 10-year risk of CVD death, but not non-CVD death, in Chinese adults with diabetes. These findings suggest that PSM is a potentially useful long-term predictor of CVD death in individuals with diabetes.

Indexed as

Cardiovascular DiseasesDiabetes MellitusAdultChinaFollow-Up StudiesHumansRisk FactorsSphingomyelinsSphingomyelinsAll-cause deathCVD deathPredictorPSM

Identifiers

PMID38245731
PMCPMC10800040
OpenAlexW4391057631

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.