Evidence map›Paper›PMID 27488611›Full record

ArticleJournal of human hypertension2017

Correlation between visit-to-visit and short-term blood pressure variability calculated using different methods and glomerular filtration rate.

J Wang, B Jiang, L Song, C Yang, Y Wu, S Chen, C Li, H Zhao, F Wang, S Wu

Abstract read
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In one paragraph

Article in Journal of human hypertension, 2017. 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
–field-weighted citation impact
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.

  1. Article
  2. Observational
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

10 authors.

J WangMedical Informatics Center, Peking University, Beijing, People's Republic of China.
B JiangDepartment of Orthopedics and Trauma, Peking University People's Hospital, Beijing, People's Republic of China.
L SongNorth China University of Science and Technology, Tangshan, People's Republic of China.
C YangDepartment of Epidemiology and Biostatistics, Peking University, Beijing, People's Republic of China.
Y WuDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, People's Republic of China.
S ChenDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, People's Republic of China.
C LiDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, People's Republic of China.
H ZhaoDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, People's Republic of China.
F WangSixth Hospital of Peking University, Beijing, People's Republic of China.
S WuDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to explore the correlation between visit-to-visit and short-term blood pressure variability (BPV), including systolic BPV (SBPV) and diastolic BPV (DBPV), calculated using different methods, and the glomerular filtration rate (GFR) in a late, middle-aged population. Using cluster sampling, we randomly selected retired employees of the Kailuan Group who were ⩾60 years and participated in a third health examination for 24-h ambulatory blood pressure monitoring and inspection. Among the 3064 randomly selected observation subjects, 2464 were included based on the criteria. BPV was calculated using s.d., coefficient of variation (CV, s.d./Mean), variability independent of mean (VIM, s.d./Mean

Indexed as

Blood PressureAgedFemaleGlomerular Filtration RateHumansLinear ModelsMaleMiddle Aged

Identifiers

PMID27488611

What OpenQuestion holds

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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.