Evidence map›Paper›PMID 25848699›Full record

ArticleCardiovascular diabetology2015

Awareness, treatment and control of cardiometabolic disorders in Chinese adults with diabetes: a national representative population study.

Tiange Wang, Yu Xu, Min Xu, Weiqing Wang, Yufang Bi, Jieli Lu, Meng Dai, Di Zhang, Lin Ding, Baihui Xu and 9 more

3 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 23% 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.

NCT04053959 phase4completednot on this mapstarted 2019, after this paper: background citation

A Study to Assess the Effect and Safety of Artificial Intelligence Assisted Insulin Titration System on Glucose Control in Type 2 Diabetes Mellitus Patients: A Single-center, Open-labeled, Parallel, Randomized Controlled Trial

TypeinterventionalSponsorShanghai Zhongshan HospitalRan2019 to 2020Enrolled46ConditionsType 2 DiabetesArmsAI assisted insulin system, Physician based insulin regime
NCT04517201 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Study to Assess Artificial Intelligence-Assisted Insulin Titration System on Inpatients Glucose Control

TypeinterventionalSponsorShanghai Zhongshan HospitalRan2020 to 2021Enrolled120ConditionsType 2 DiabetesArmsiNCDSS based insulin regime, Physician based insulin regime
NCT04642378 nacompletednot on this mapstarted 2021, after this paper: background citation

Study to Assess the Efficacy and Safety of iNCDSS Assisted Insulin Dosage Titration System on Glucose Control in Type 2 Diabetes Mellitus Patients : a Muticenter, Single-blind, Randomized Controlled Study

TypeinterventionalSponsorShanghai Zhongshan HospitalRan2021 to 2022Enrolled149ConditionsType 2 DiabetesArmsiNCDSS based insulin regime, routine insulin treatment regime
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
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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

19 authors at 3 institutions in 2 countries.

Tiange Wang
Yu Xu
Min Xu
Weiqing Wang
Yufang Bi
Jieli Lu
Meng Dai
Di Zhang
Lin Ding
Baihui Xu
Jichao Sun
Wenhua Zhao
Yong Jiang
Limin Wang
Yichong Li
Mei Zhang
Shenghan Lai
Linhong Wang
Guang Ning
Shanghai Jiao Tong University · CNNational Center for Chronic and Noncommunicable Disease Control and Prevention · CNJohns Hopkins University · US

Funding

Research Training in Gene-Environment Interaction in ChinaD43TW009107 · FIC · TULANE UNIVERSITY OF LOUISIANA · PI GU, DONGFENG, HE, JIANG · 2012 to 2016
$1.1M
FIC NIH HHS D43 TW009107FIC NIH HHS D43TW009107
6 · The paper itself

Abstract

backgroundThe diagnosis of diabetes has important clinic implications for the prevention and management of cardiometabolic disorders. We aimed to investigate the awareness, treatment and control of hypertension and dyslipidemia in previously-diagnosed and newly-diagnosed diabetes in Chinese adult population.

methodsWe conducted a cross-sectional survey in a nationally representative sample of 98658 Chinese adults aged 18 years or older in 2010, using a complex, multistage, probability sampling design. Glycemic status were defined according to the 2010 American Diabetes Association criteria. Hypertension was diagnosed by the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Dyslipidemia was diagnosed by the 2004 National Cholesterol Education Program Adult Treatment Panel III.

resultsThe weighted prevalence of hypertension and dyslipidemia gradually increased in adults with normal glucose regulation, prediabetes, newly-diagnosed diabetes and previously-diagnosed diabetes. Compared to newly-diagnosed diabetes patients, previously-diagnosed diabetes patients were more likely to be aware of hypertension (weighted percentage [95% confidence interval]: 55.2% [52.9%-57.5%] vs 37.6% [35.9%-39.3%]) and dyslipidemia (33.9% [31.8%-36.1%] vs 12.8% [11.7%-13.9%]), to receive blood pressure-lowing (43.7% [41.5%-46.0%] vs 27.5% [26.0%-29.0%]) and lipid-lowering (18.9% [17.2%-20.7%] vs 5.4% [4.6%-6.2%]) therapies, and to have controlled blood pressure (4.7% [3.5%-6.2%] vs 3.5% [2.6%-4.8%]) and lipid (15.9% [12.3%-20.3%] vs 9.5% [6.4%-13.8%]) levels.

conclusionsDetection and control of hypertension and dyslipidemia is far from optimal in Chinese adults, especially in newly-diagnosed diabetes. Improved screening for diabetes is required to promote a better prevention, treatment and control of hypertension and dyslipidemia in China.

Indexed as

Asian PeoplePopulation SurveillanceAdultAwarenessCardiovascular DiseasesCross-Sectional StudiesDiabetes MellitusFemaleHumansMaleMiddle AgedTreatment Outcome

Identifiers

PMID25848699
PMCPMC4356058
OpenAlexW2142930342

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.