Evidence map›Paper›PMID 31183553›Full record

ArticleInternational journal of biometeorology2019

Geographical distribution of the P-R interval reference value of Chinese healthy adults.

Fan Yang, Miao Ge, Tianyu Li, Lu Chai

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of biometeorology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Fan YangInstitute of Health Geography, of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China.
Miao GeInstitute of Health Geography, of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China. gemiao@snnu.edu.cn.
Tianyu LiInstitute of Health Geography, of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China.
Lu ChaiInstitute of Health Geography, of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China.

Funding

National Natural Science Foundation of China 40971060
6 · The paper itself

Abstract

To explore the relationship between the geographical factors and P-R interval reference value of healthy adults, and to elucidate the geographical distribution of the P-R interval reference value in Chinese adults, to provide the basis for the standard of P-R interval reference value in different regions. The P-R interval reference value of 64,753 healthy adults in 341 cities (counties) level hospitals, research institutes, and universities in China was collected, and 15 geographical data and P-R interval reference value of healthy people were studied, and then 10 geographical factors with correlation were extracted for further analysis. Using spatial autocorrelation analysis to determine the autocorrelation of data space, using backward regression and ridge regression to construct forecast model, and the optimal prediction model is selected by comparing and evaluating the prediction effect of each model, the spatial distribution map of P-R interval reference value of Chinese healthy adults was constructed by statistical analysis. There was a significant correlation between normal reference value of adult P-R interval reference value and geographical factors. The regression model of normal reference value and geographical factors of adult P-R interval reference value was established by ridge regression analysis method: [Formula: see text] =149.2 + 0.02590X

Indexed as

GeographyHealth StatusAdultChinaHumansReference ValuesRegression AnalysisSpatial AnalysisBackward regression analysisGeographical factorsP-R intervalRidge regression analysisSpatial statistics analysis

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.