Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 22% 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
3 citing papers in PubMed, 7 citations in OpenAlex.
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 at 3 institutions in 2 countries.
Marina ShapkinaInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.ORCID 0000-0002-8577-8801
Andrey RyabikovInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.
Ekaterina MazdorovaInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.
Anastasia TitarenkoInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.ORCID 0000-0002-2631-8485
Ekaterina AvdeevaInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.
Elena MazurenkoInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.ORCID 0000-0003-3351-1993
Lilia ShcherbakovaInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.
Hynek PikhartInstitute of Epidemiology and Health Care, University College London, London WC1E6BT, UK.
Martin BobakInstitute of Epidemiology and Health Care, University College London, London WC1E6BT, UK.
Sofia MalyutinaInstitute of Internal and Preventive Medicine-Branch of Federal State Budgeted Research Institution, "Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences", 630090 Novosibirsk, Russia.ORCID 0000-0001-6539-0466
Institute of Cytology and Genetics · RUUniversity College London · GBNovosibirsk State Medical University · RU
Funding
Health disparities and agingin societies in transitionR01AG023522 · NIA · UNIVERSITY COLLEGE LONDON · PI MARMOT, MICHAEL G · 2004 to 2008
$2.2M
NIA NIH HHS 1RO1AG23522Russian Foundation for Basic Research 20-313-90015Russian Science Foundation 20-15-00371Wellcome Trust WT064947Wellcome Trust WT081081
6 · The paper itself
Abstract
Atrial fibrillation (AF) is the most common arrhythmia and a predictor of the complications of atherosclerotic cardiovascular diseases (ASCVDs), particularly thromboembolic events and the progression of heart failure. We analyzed the determinants of the 13-year risk of incident AF in a Russian population cohort of middle and elderly age. A random population sample (
Indexed as
agingarterial hypertensionatherosclerosisatrial fibrillationCox regression analysisdeterminantsdiabetes mellitusHAPIEE studyobesityprevalenceRussian population cohort
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.
The Determinants of the 13-Year Risk of Incident Atrial Fibrillation in a Russian Population Cohort of Middle and Elderly Age. · full record | OpenQuestion