Evidence map›Paper›PMID 38629743›Full record

ArticleEuropean journal of preventive cardiology2024

Predictive value of 8-year blood pressure measures in intracerebral haemorrhage risk over 5 years.

Yiqian Zhang, Yinqi Ding, Canqing Yu, Dianjianyi Sun, Pei Pei, Huaidong Du, Ling Yang, Yiping Chen, Dan Schmidt, Daniel Avery and 6 more

Open access · hybridAbstract read
In one paragraph

Article in European journal of preventive cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 5 countries.

Yiqian ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.
Yinqi DingDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.ORCID 0000-0002-0019-0014
Dianjianyi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.ORCID 0000-0002-9645-2946
Pei PeiPeking University Center for Public Health and Epidemic Preparedness and Response, 38 Xueyuan Road, Haidian District, Beijing 100191, China.
Huaidong DuMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.ORCID 0000-0002-9814-0049
Ling YangMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
Yiping ChenMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
Dan SchmidtClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK.
Daniel AveryClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK.
Jianwei ChenLiuyang Centers for Disease Control and Prevention, NO.11 Section 2 Lihua Road, Jili Subdistrict, Liuyang, Changsha, Hunan 410300, China.
Junshi ChenChina National Center for Food Safety Risk Assessment, 37 Guangqu Road, Chaoyang District, Beijing 100022, China.
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.ORCID 0000-0001-7916-3870
China Kadoorie Biobank Collaborative Group
Peking University · CNUniversity of Oxford · GBPopulation Council · INChina National Center for Food Safety Risk Assessment · CNNuffield Health · GB

Funding

Chinese Ministry of Science and Technology 2011BAI09B01Kadoorie Charitable FoundationNational Key R&D Program of China 2016YFC0900500National Natural Science Foundation of China 82192904Wellcome Trust 088158Wellcome Trust 104085Wellcome Trust 202922Wellcome Trust 212946Wellcome Trust 212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, and 088158/Z/09/Z
6 · The paper itself

Abstract

aimsThe relationships between long-term blood pressure (BP) measures and intracerebral haemorrhage (ICH), as well as their predictive ability on ICH, are unclear. In this study, we aim to investigate the independent associations of multiple BP measures with subsequent 5-year ICH risk, as well as the incremental value of these measures over a single-point BP measurement in ICH risk prediction. METHODS AND

resultsWe included 12 398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every 4-5 years. The following long-term BP measures were calculated: mean, minimum, maximum, standard deviation, coefficient of variation, average real variability, and cumulative BP exposure (cumBP). Cox proportional hazard models were used to examine the associations between these measures and ICH. The potential incremental value of these measures in ICH risk prediction was assessed using Harrell's C statistics, continuous net reclassification improvement (cNRI), and relative integrated discrimination improvement (rIDI). The hazard ratios (95% confidence intervals) of incident ICH associated with per standard deviation increase in cumulative systolic BP and cumulative diastolic BP were 1.62 (1.25-2.10) and 1.59 (1.23-2.07), respectively. When cumBP was added to the conventional 5-year ICH risk prediction model, the C-statistic change was 0.009 (-0.001, 0.019), the cNRI was 0.267 (0.070-0.464), and the rIDI was 18.2% (5.8-30.7%). Further subgroup analyses revealed a consistent increase in cNRI and rIDI in men, rural residents, and participants without diabetes. Other long-term BP measures showed no statistically significant associations with incident ICH and generally did not improve model performance.

conclusionThe nearly 10-year cumBP was positively associated with an increased 5-year risk of ICH and could significantly improve risk reclassification for the ICH risk prediction model that included single-point BP measurement.

Indexed as

Blood PressureCerebral HemorrhagePredictive Value of TestsAdultAgedBlood Pressure DeterminationChinaFemaleHumansHypertensionIncidenceMaleMiddle AgedPrognosisRisk AssessmentRisk FactorsBlood pressure variabilityCumulative blood pressureIncremental valueIntracerebral haemorrhageLong termRisk prediction

Identifiers

PMID38629743
PMCPMC7616516
OpenAlexW4394869065

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.