Evidence map›Paper›PMID 30700252›Full record

ArticleBMC cardiovascular disorders2019

Trends in electrocardiographic abnormalities and risk of cardiovascular mortality in Lithuania, 1986-2015.

Abdonas Tamosiunas, Janina Petkeviciene, Ricardas Radisauskas, Gailute Bernotiene, Dalia Luksiene, Mindaugas Kavaliauskas, Irena Milvidaitė, Dalia Virviciute

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

8 authors at 2 institutions in 1 country.

Abdonas TamosiunasInstitute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Sukileliu av. 15, LT-50162, Kaunas, Lithuania. abdonas.tamosiunas@lsmuni.lt.ORCID 0000-0002-0868-457X
Janina PetkevicieneFaculty of Public Health, Academy of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Ricardas RadisauskasInstitute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Sukileliu av. 15, LT-50162, Kaunas, Lithuania.
Gailute BernotieneInstitute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Sukileliu av. 15, LT-50162, Kaunas, Lithuania.
Dalia LuksieneInstitute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Sukileliu av. 15, LT-50162, Kaunas, Lithuania.
Mindaugas KavaliauskasFaculty of Mathematics and Natural Sciences, Kaunas University of Technology, Kaunas, Lithuania.
Irena MilvidaitėInstitute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Sukileliu av. 15, LT-50162, Kaunas, Lithuania.
Dalia VirviciuteInstitute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Sukileliu av. 15, LT-50162, Kaunas, Lithuania.
Lithuanian University of Health Sciences · LTKaunas University of Technology · LT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to assess the trends in the prevalence of electrocardiographic (ECG) abnormalities from 1986 to 2015 and impact of ECG abnormalities on risk of death from cardiovascular diseases (CVD) in the Lithuanian population aged 40-64 years.

methodsData from four surveys carried out in Kaunas city and five randomly selected municipalities of Lithuania were analysed. A resting ECG was recorded and CVD risk factors were measured in each survey. ECG abnormalities were evaluated using Minnesota Code (MC). Trends in age-standardized prevalence of ECG abnormalities were estimated for both sexes. Multivariate Cox proportional hazards models were used to estimate hazard ratios (HR) for coronary heart disease (CHD) and CVD mortality. Net reclassification index (NRI), integrated discrimination improvement and other indices were used for evaluation of improvement in the prediction of CVD and CHD mortality risk after addition of ECG abnormalities variable to Cox models.

resultsFrom1986 to 2008, the decrease in the prevalence of Q-QS MC was observed in both genders. The prevalence of high R waves increased in men, while the prevalence of ST segment and T wave abnormalities as well as arrhythmias decreased in women. Ischemic changes and possible MI were associated with a 2.5-fold and 4.4-fold higher risk of death from CVD in men and 1.51-fold and 2.56-fold higher mortality risk from CVD in women as compared to individuals with marginal or no ECG abnormalities. The addition of ECG abnormalities to traditional CVD risk factors improved Cox regression models performance. According to NRI, 18.6% of men were correctly reclassified in CVD mortality prediction model and 25.2% of men - in CHD mortality prediction model.

conclusionsthe decreasing trends in the prevalence of ischemia on ECG in women and increasing trends in the prevalence of left VH in men were observed. ECG abnormalities were associated with higher risk of CVD mortality. The addition of ECG abnormalities to the prediction models modestly improved the prediction of CVD mortality beyond traditional CVD risk factors. The use of ECG as routine screening to identify high risk individuals for more intensive preventive interventions warrants further research.

Indexed as

ElectrocardiographyHeart RateAdultAge DistributionAge FactorsArrhythmias, CardiacCross-Sectional StudiesFemaleHealth SurveysHumansLithuaniaMaleMiddle AgedPredictive Value of TestsPrevalencePrognosisCardiovascular diseaseElectrocardiographic abnormalitiesMiddle-aged populationMortalityRisk factorsTrends

Identifiers

PMID30700252
PMCPMC6354422
OpenAlexW2924925373

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.