Literature DB >> 35410386

The oversimplified scoring system may compromise its utility as a predictive model for the development of hypertension.

Yuta Tanaka1, Akinori Higaki2, Takuro Kazatani1, Yoshitaka Kawada1.   

Abstract

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Year:  2022        PMID： 35410386     DOI： 10.1038/s41440-022-00880-w

Source DB:  PubMed          Journal:  Hypertens Res        ISSN： 0916-9636            Impact factor:   3.872


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  4 in total

Review 1.  Influence of age, risk factors, and cardiovascular and renal disease on arterial stiffness: clinical applications.

Authors:  Athanase Benetos; Bernard Waeber; Joseph Izzo; Gary Mitchell; Lawrence Resnick; Roland Asmar; Michel Safar
Journal:  Am J Hypertens       Date:  2002-12       Impact factor: 2.689

2.  Co-authorship network analysis in cardiovascular research utilizing machine learning (2009-2019).

Authors:  Akinori Higaki; Teruyoshi Uetani; Shuntaro Ikeda; Osamu Yamaguchi
Journal:  Int J Med Inform       Date:  2020-09-19       Impact factor: 4.046

3.  Development of a risk prediction score for hypertension incidence using Japanese health checkup data.

Authors:  Mariko Kawasoe; Shin Kawasoe; Takuro Kubozono; Satoko Ojima; Takeko Kawabata; Yoshiyuki Ikeda; Naoya Oketani; Hironori Miyahara; Koichi Tokushige; Masaaki Miyata; Mitsuru Ohishi
Journal:  Hypertens Res       Date:  2021-12-27       Impact factor: 5.528

4.  Potential multicollinearity among NLR and other variables in the prediction model for the COVID-19 mortality.

Authors:  Akinori Higaki
Journal:  Am J Emerg Med       Date:  2021-04-27       Impact factor: 2.469
  4 in total

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