Evidence map›Paper›PMID 36461637›Full record

ArticleESC heart failure2023

P-wave durations from automated electrocardiogram analysis to predict atrial fibrillation and mortality in heart failure.

Jiandong Zhou, Andrew Li, Martin Tan, Matthew Chung Yan Lam, Lok Tin Hung, Ronald Wing Hei Siu, Sharen Lee, Ishan Lakhani, Jeffrey Shi Kai Chan, Khalid Bin Waleed and 4 more

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

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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

14 authors at 9 institutions in 5 countries.

Jiandong ZhouSchool of Data Science, City University of Hong Kong, Hong Kong, China.
Andrew LiFaculty of Science, University of Calgary, Calgary, Canada.
Martin TanUniversity of Toronto, Toronto, Canada.
Matthew Chung Yan LamLi Ka Shing Institute of Health Sciences, Shenzhen Research Institute, Chinese University of Hong Kong, Shenzhen, China.
Lok Tin HungLi Ka Shing Institute of Health Sciences, Shenzhen Research Institute, Chinese University of Hong Kong, Shenzhen, China.
Ronald Wing Hei SiuLi Ka Shing Institute of Health Sciences, Shenzhen Research Institute, Chinese University of Hong Kong, Shenzhen, China.
Sharen LeeHeart Failure and Structural Heart Disease Unit, Cardiovascular Analytics Group, Hong Kong, China-UK Collaboration, Hong Kong, China.
Ishan LakhaniHeart Failure and Structural Heart Disease Unit, Cardiovascular Analytics Group, Hong Kong, China-UK Collaboration, Hong Kong, China.
Jeffrey Shi Kai ChanHeart Failure and Structural Heart Disease Unit, Cardiovascular Analytics Group, Hong Kong, China-UK Collaboration, Hong Kong, China.
Khalid Bin WaleedDepartment of Cardiology, St George's Hospital NHS Foundation Trust, London, UK.
Tong LiuTianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, 300211, Tianjin, China.
Kamalan JeevaratnamFaculty of Health and Medical Sciences, University of Surrey, GU2 7AL, Guildford, UK.
Qingpeng ZhangSchool of Data Science, City University of Hong Kong, Hong Kong, China.
Gary TseTianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, 300211, Tianjin, China.ORCID 0000-0001-5510-1253
British Heart Foundation · GBChinese University of Hong Kong, Shenzhen · CNCity University of Hong Kong · HKCanterbury Christ Church University · GBSecond Hospital of Tianjin Medical University · CNSt George’s University Hospitals NHS Foundation Trust · GBUniversity of Calgary · CAUniversity of Surrey · GBUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundP-wave indices have been used to predict incident atrial fibrillation (AF), stroke, and mortality. However, such indices derived from automated ECG measurements have not been explored for their predictive values in heart failure (HF). We investigated whether automated P-wave indices can predict adverse outcomes in HF.

methodsThis study included consecutive Chinese patients admitted to a single tertiary centre, presenting with HF but without prior AF, and with at least one baseline ECG, between 1 January 2010 and 31 December 2016, with last follow-up of 31 December 2019.

resultsA total of 2718 patients were included [median age: 77.4, interquartile range (IQR): (66.9-84.3) years; 47.9 males]. After a median follow-up of 4.8 years (IQR: 1.9-9.0 years), 1150 patients developed AF (8.8/year), 339 developed stroke (2.6/year), 563 developed cardiovascular mortality (4.3/year), and 1972 had all-cause mortality (15.1/year). Compared with 101-120 ms as a reference, maximum P-wave durations predicted new-onset AF at ≤90 ms [HR: 1.17(1.11, 1.50), P < 0.01], 131-140 ms [HR: 1.29(1.09, 1.54), P < 0.001], and ≥141 ms [HR: 1.52(1.32, 1.75), P < 0.001]. Similarly, they predicted cardiovascular mortality at ≤90 ms [HR: 1.50(1.08, 2.06), P < 0.001] or ≥141 ms [HR: 1.18(1.15, 1.45), P < 0.001], and all-cause mortality at ≤90 ms [HR: 1.26(1.04, 1.51), P < 0.001], 131-140 ms [HR: 1.15(1.01, 1.32), P < 0.01], and ≥141 ms [HR: 1.31(1.18, 1.46), P < 0.001]. These remained significant after adjusting for significant demographics, past co-morbidities, P-wave dispersion, and maximum P-wave amplitude.

conclusionsExtreme values of maximum P-wave durations (≤90 ms and ≥141 ms) were significant predictors of new-onset AF, cardiovascular mortality, and all-cause mortality.

Indexed as

Atrial FibrillationHeart FailureStrokeAgedElectrocardiographyHeartHumansMaleHeart failureInter-atrial blockMortalityP-wave durationStroke

Identifiers

PMID36461637
PMCPMC10053164
OpenAlexW4310641779

What OpenQuestion holds

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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.