Evidence map›Paper›PMID 42907907›Full record

ArticleBMC sports science, medicine & rehabilitation2026

Modelling complex sports adaptation with electrocardiography: analysis of standard ECG, heart rate variability and QRST integral changes in elite athletes.

Dóra Boroncsok, Máté Babity, Márk Zámodics, Anna Menyhárt-Hetényi, Gergely Tuboly, György Kozmann, Regina Benkő, Alexandra Fábián, Zsuzsanna Ladányi, Dorottya Balla and 4 more

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Article in BMC sports science, medicine & rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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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

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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.

Dóra Boroncsok *Heart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0009-0009-0859-8194
Máté Babity *Heart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0001-5334-5430
Márk ZámodicsHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0001-8031-1295
Anna Menyhárt-HetényiHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0009-0009-7266-2365
Gergely TubolyDepartment of Electrical Engineering and Information Systems, University of Pannonia, Egyetem street 10, Veszprém, 8200, Hungary.ORCID http://orcid.org/0000-0003-4361-8612
György KozmannDepartment of Electrical Engineering and Information Systems, University of Pannonia, Egyetem street 10, Veszprém, 8200, Hungary.
Regina BenkőHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.
Alexandra FábiánHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0002-8449-0638
Zsuzsanna LadányiHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0002-6258-1985
Dorottya BallaHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0002-5177-8483
Hajnalka VágóHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0002-3568-3572
Attila KovácsHeart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0000-0003-2320-6434
Béla Merkely *Heart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary. sportkardiokutatas@gmail.com.ORCID http://orcid.org/0000-0001-6514-0723
Orsolya Kiss *Heart and Vascular Center, Semmelweis University, Városmajor street 68, Budapest, 1122, Hungary.ORCID http://orcid.org/0009-0009-1692-5351

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBasic resting electrocardiographic changes caused by regular intense exercise are known characteristics of the athlete's heart. Through detailed analysis of short-term ECG recordings, our aim was to study electrocardiographic, heart rate variability, and ventricular heterogeneity changes of the athlete's heart as a function of factors influencing sports adaptation.

methodsAnalysis of 1-minute resting lead I ECG recordings was used to determine standard ECG parameters, time-domain indicators of heart rate variability, and mean and standard deviation of QRST integrals. Statistical analysis was performed in Python development environment.

results500 healthy athletes (age: 19[16-24]y, male: 55%, training: 16.7 ± 6.5 h/w) were compared with 100 non-athlete controls (age: 21[17-23]y, male: 51%). Athletes had lower heart rate (68[61-78]vs.82[73-91]BPM, p < 0.001), increased p-wave amplitude (89[71-108]vs.80[62-96]µV, p < 0.001), PQ interval (152[140-168]vs.142[132-152]ms, p < 0.001), QRS width (90[82-100]vs.82[78-90]ms, p < 0.001), T-wave amplitude (257[198-311]vs.195[146-248]µV, p < 0.001), SDNN (64.7[47.2-87.2]vs.50.6[36.5-66.3]ms, p < 0.001), RMSSD (52.6[34.8-78.3]vs.36.4[26.8-52.6]ms, p < 0.001), pNN50 (31.1[12.7-50.9]vs.14.7[4.9-31.6]%, p < 0.001) and mean QRST integral (34.9[28.3-43.4]vs.26.1[19.7-33.9]mV*ms, p < 0.001) compared to controls. Mixed athletes had wider QRS compared to power athletes (94[90-102]vs.88[84-96]ms, p < 0.005). Male athletes had lower QTc, increased PQ interval, QRS width, T-wave amplitude, mean QRST integral, and its deviation. In the control group, females had higher resting heart rate and QTc duration, while AVNN and the relative deviation of QRST integral were lower. Many of the above parameters also showed weak correlation with age and weekly exercise hours.

conclusionsOur findings indicate that a 1-minute lead I ECG recording can detect electrical differences between athletes and non-athlete controls and may provide a practical framework for future longitudinal studies of athletic cardiac adaptation.

Indexed as

Athlete’s heartElectrocardiographyHeart rate variabilitySports adaptationVentricular heterogeneity

Identifiers

PMID42907907
PMCPMC13688776

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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.