In one paragraphArticle in Hypertension research : official journal of the Japanese Society of Hypertension, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
24 authors.
Qi-Fang HuangDepartment of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0000-0002-9780-4237 De-Wei AnDepartment of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0000-0002-1395-7050 Lucas S AparicioServicio de Clínica Médica, Sección Hipertensión Arterial, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.ORCID 0000-0002-8704-7287 Yi-Bang ChengDepartment of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0000-0002-3822-3504 Fang-Fei WeiDepartment of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID 0000-0002-4254-5215 José BoggiaUnidad Académica de Nefrología, Hospital de Clínicas Dr Manuel Quintela, Universidad de la República, Montevideo, Uruguay.ORCID 0000-0002-1564-8534 Chang-Sheng ShengDepartment of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0000-0003-2685-0663 Katarzyna Stolarz-SkrzypekFirst Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, Poland.ORCID 0000-0002-7057-7302 Wiktoria WojciechowskaFirst Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, Poland.ORCID 0000-0003-3075-3508 Marek RajzerFirst Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, Poland.ORCID 0000-0001-7074-7263 Natasza Gilis-MalinowskaHypertension Unit, Department of Hypertension and Diabetology, Medical University of Gdańsk, Gdańsk, Poland.ORCID 0000-0002-6633-202X Krzysztof NarkiewiczHypertension Unit, Department of Hypertension and Diabetology, Medical University of Gdańsk, Gdańsk, Poland.ORCID 0000-0001-5949-5018 Kalina Kawecka-JaszczFirst Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, Poland.ORCID 0000-0002-8660-2867 Ji-Guang WangDepartment of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID 0000-0001-8511-1524 Yan Li *Department of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. liyanshch@163.com.ORCID 0000-0002-5825-5968 Jan A Staessen *Department of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. jan.staessen@appremed.org.ORCID 0000-0002-3026-1637 International database of central arterial properties for risk stratification investigators
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
Multiple articles focused on the central arterial systolic (SPTI) and diastolic (DPTI) pressure-time indexes and the subendocardial viability ratio (SEVR). However, whether these indexes contribute to risk stratification in the general population is unknown. SPTI, DPTI and SEVR were noninvasively measured by the SphygmoCor technology. Incidence rates and standardized (per 1-SD increment) multivariable-adjusted hazard ratios (HRs) for cardiovascular (primary) and cardiac endpoints and stroke were evaluated in the International Database of Central Arterial Properties for Risk Stratification (n = 5099). Model refinement was assessed by the area under the curve (AUC) and the integrated discrimination (IDI) and net reclassification (NRI) improvement. Over 4 years (median), 215 cardiovascular, 133 cardiac endpoints and 79 strokes occurred. For SPTI, fully adjusted HRs were 1.37 (95% CI: 1.18-1.59), 1.35 (1.11-1.64) and 1.33 (1.05-1.69) for the cardiovascular and cardiac endpoints and stroke. The corresponding HRs for DPTI were 1.49 (1.31-1.69), 1.23 (1.02-1.48) and 1.74 (1.46-2.07). For SEVR, none of the HRs reached significance. Analyses with these indexes categorized by quartiles were confirmatory. Analyses stratified by various risk factors did not reveal subgroup differences. For the cardiovascular endpoint, adding SPTI or DPTI to the base model improved the AUC, while adding SPTI or DPTI combined with mean arterial pressure, increased IDI by ~1.7% and NRI by ~17% (P < 0.001 for all). Whereas cardiovascular and cardiac endpoints and stroke were related with the non-invasively measured SPTI and DPTI, SEVR was not.
Indexed as
Arterial PressureCardiovascular DiseasesAgedBlood PressureFemaleHumansMaleRisk FactorsStrokecardiovascular diseaseCentral arterial pressure-time indexesdigital hypertensionpopulation sciencerisk stratification
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