Evidence map›Paper›PMID 32826385›Full record

ArticleStroke and vascular neurology2020

China Stroke Statistics 2019: A Report From the National Center for Healthcare Quality Management in Neurological Diseases, China National Clinical Research Center for Neurological Diseases, the Chinese Stroke Association, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention and Institute for Global Neuroscience and Stroke Collaborations.

Yong-Jun Wang, Zi-Xiao Li, Hong-Qiu Gu, Yi Zhai, Yong Jiang, Xing-Quan Zhao, Yi-Long Wang, Xin Yang, Chun-Juan Wang, Xia Meng and 9 more

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

Article in Stroke and vascular neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 282 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
282citing papers in PubMed, 7 pooled it
50.8field-weighted citation impact, top 1% 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.

NCT05706168 naunknown statusnot on this mapstarted 2023, after this paper: background citation

A Study to Investigate the Effects of Aerobic Exercise Training (AET) on the Large Intracranial and Extracranial Cerebral Arteries and the Cognitive and Motor Functions in Post Stroke Patients.

TypeinterventionalSponsorThe Hong Kong Polytechnic UniversityRan2023 to 2024Enrolled120ConditionsStrokeArmstreadmill exercise, Cycle ergometer exercise
NCT06510712 unknown statusnot on this mapstarted 2024, after this paper: background citation

Nutritional Risk and Health Research for Hospitalized Patients With Neurology Disorders in China

TypeobservationalSponsorXuanwu Hospital, BeijingRan2024 to 2026Enrolled10,000ConditionsNeurological Disorder
3 · Its place in the literature

Who cites it

282 citing papers in PubMed, 7 syntheses or guidelines pooled it, 514 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. The role ofExpert review of clinical pharmacology · 2022
    Pooled it
  7. Pooled it
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

222 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 5 institutions in 5 countries.

Yong-Jun Wang *China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China yongjunwang@ncrcnd.org.cn zhaojz205@163.com.ORCID 0000-0002-9976-2341
Zi-Xiao Li *China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-4713-5418
Hong-Qiu Gu *China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-1608-1856
Yi Zhai *China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yong JiangChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xing-Quan ZhaoChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yi-Long WangChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xin YangChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Chun-Juan WangChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xia MengChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Hao LiChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-8591-4105
Li-Ping LiuChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-2943-055X
Jing JingChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Jing WuNational Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
An-Ding XuDepartment of Neurology and Stroke Center, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong, China.ORCID 0000-0003-3154-0985
Qiang DongDepartment of Neurology, Huashan Hospital,Fudan University, Shanghai, China.ORCID 0000-0002-3874-0130
David WangNeurovascular Division, Department of Neurology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA.ORCID 0000-0003-2277-4608
Ji-Zong ZhaoChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China yongjunwang@ncrcnd.org.cn zhaojz205@163.com.
China Stroke Statistics 2019 Writing Committee
Capital Medical University · CNBarrow Neurological Institute · USChinese Center For Disease Control and Prevention · CNFirst Affiliated Hospital of Jinan University · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China faces the greatest challenge from stroke in the world. The death rate for cerebrovascular diseases in China was 149.49 per 100 000, accounting for 1.57 million deaths in 2018. It ranked third among the leading causes of death behind malignant tumours and heart disease. The age-standardised prevalence and incidence of stroke in 2013 were 1114.8 per 100 000 population and 246.8 per 100 000 person-years, respectively. According to the Global Burden of Disease Study 2017, the years of life lost (YLLs) per 100 000 population for stroke increased by 14.6%; YLLs due to stroke rose from third highest among all causes in 1990 to the highest in 2017. The absolute numbers and rates per 100 000 population for all-age disability-adjusted life years (DALYs) for stroke increased substantially between 1990 and 2017, and stroke was the leading cause of all-age DALYs in 2017. The main contributors to cerebrovascular diseases include behavioural risk factors (smoking and alcohol use) and pre-existing conditions (hypertension, diabetes mellitus, dyslipidaemia and atrial fibrillation (AF)). The most prevalent risk factors among stroke survivors were hypertension (63.0%-84.2%) and smoking (31.7%-47.6%). The least prevalent was AF (2.7%-7.4%). The prevalences for major risk factors for stroke are high and most have increased over time. Based on the latest national epidemiological data, 26.6% of adults aged ≥15 years (307.6 million adults) smoked tobacco products. For those aged ≥18 years, age-adjusted prevalence of hypertension was 25.2%; adjusted prevalence of hypercholesterolaemia was 5.8%; and the standardised prevalence of diabetes was 10.9%. For those aged ≥40 years, the standardised prevalence of AF was 2.31%. Data from the Hospital Quality Monitoring System showed that 3 010 204 inpatients with stroke were admitted to 1853 tertiary care hospitals during 2018. Of those, 2 466 785 (81.9%) were ischaemic strokes (ISs); 447 609 (14.9%) were intracerebral haemorrhages (ICHs); and 95 810 (3.2%) were subarachnoid haemorrhages (SAHs). The average age of patients admitted was 66 years old, and nearly 60% were male. A total of 1555 (0.1%), 2774 (0.6%) and 1347 (1.4%) paediatric strokes (age <18 years) were identified among IS, ICH and SAH, respectively. Over one-third (1 063 892 (35.3%)) of the patients were covered by urban resident basic medical insurance, followed by urban employee basic medical insurance (699 513 (23.2%)) and new rural cooperative medical schema (489 361 (16.3%)). The leading risk factor was hypertension (67.4% for IS, 77.2% for ICH and 49.1% for SAH), and the leading comorbidity was pneumonia or pulmonary infection (10.1% for IS, 31.4% for ICH and 25.2% for SAH). In-hospital death/discharge against medical advice rate was 8.3% for stroke inpatients, ranging from 5.8% for IS to 19.5% for ICH. The median and IQR of length of stay was 10.0 (7.0-14.0) days, ranging from 10.0 (7.0-13.0) in IS to 14.0 (8.0-22.0) in SAH. Data from the Chinese Stroke Center Alliance demonstrated that the composite scores of guideline-recommended key performance indicators for patients with IS, ICH and SAH were 0.77±0.21, 0.72±0.28 and 0.59±0.32, respectively.

Indexed as

AdolescentAdultAgedAged, 80 and overAge DistributionAge FactorsCerebrovascular DisordersChildChild, PreschoolChinaComorbidityFemaleHealth Status DisparitiesHumansIncidenceInfantstatisticsstroke

Identifiers

PMID32826385
PMCPMC7548521
OpenAlexW3080103475

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.