Evidence map›Paper›PMID 18354420›Full record

ArticleJournal of human hypertension2008

The electrocardiogram is an unreliable method of identifying left ventricular hypertrophy in stable, treated angina patients.

D S C Ang, L L Ti, A D Struthers

Abstract read
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In one paragraph

Article in Journal of human hypertension, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 36% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 2 institutions in 1 country.

D S C AngDivision of Medicine and Therapeutics, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK. s.c.ang@dundee.ac.uk
L L Ti
A D Struthers
Ninewells Hospital · GBUniversity of Dundee · GB

Funding

British Heart Foundation
6 · The paper itself

Abstract

In coronary artery disease (CAD), a potentially reversible factor leading to cardiac death is left ventricular hypertrophy (LVH). While the electrocardiogram (ECG) is a widely available way to diagnose LVH, its sensitivity and specificity has never been assessed in this particular patient group where added ischaemic changes on ECG might complicate things. Furthermore, there are at least 11 different ECG criteria proposed to identify LVH. We sought to determine how many cases of echocardiography (echo) LVH would be missed if all of these different ECG criteria were applied in a group of stable, treated angina patients. A total of 241 consecutive patients with angiographically confirmed CAD were prospectively recruited and 11 ECG criteria were assessed on each subject and compared with the presence or absence of LVH on echo. Individual sensitivity, specificity, positive predictive value and negative predictive value were calculated for each ECG LVH criteria. The prevalence of echo LVH in the entire CAD population was 43%. All the proposed ECG criteria were poor at identifying echo LVH. The Cornell product yielded the highest rate of change value but still missed up to 80% of the echo LVH cases. We conclude that in a group of stable, treated angina patients, ECG is an unreliable method of identifying LVH. As LVH is very common in this patient population, screening by means of echo might be indicated. This will enable intensified efforts to ensure LVH regression, which is associated with reduction in both cardiovascular morbidity and mortality.

Indexed as

ElectrocardiographyAgedAngina PectorisBlood PressureFemaleHumansHypertrophy, Left VentricularMaleMiddle AgedSensitivity and Specificity

Identifiers

PMID18354420
OpenAlexW2006292985

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.