| 1. |
- Axelsson, Karl-Jonas, et al.
(författare)
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Adaptation of ventricular repolarization dispersion during heart rate increase in humans: A roller coaster process.
- 2021
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Ingår i: Journal of electrocardiology. - : Elsevier BV. - 1532-8430 .- 0022-0736. ; 68, s. 90-100
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Tidskriftsartikel (refereegranskat)abstract
- Regional differences in ventricular activation sequence and action potential duration and morphology result in dispersion in ventricular repolarization (VR). VR dispersion is a key factor in arrhythmogenesis. We studied the adaptation of global VR dispersion in humans during normal and abnormal ventricular activation, and the relation to the QT adaptation (hysteresis).We measured global VR dispersion as T amplitude, T area, and ventricular gradient (VG), using continuous Frank vectorcardiography, in response to abrupt and sustained atrial (AP) or ventricular pacing (VP) aiming at 120 bpm, in 21 subjects with permanent pacemakers.Following pacing start, VR adaptation showed an initially rapid and complex tri-phasic pattern, most pronounced for T amplitude. There were major differences in the patterns of VR dispersion adaptation following abrupt AP vs VP, confirming that the adaptation pattern is activation dependent. In response to AP, an instantaneous decrease in VR dispersion occurred, followed by an increase and then a slow decrease, all at a lower level than baseline. In contrast, following VP there was an immediate increase to ~4× baseline in T amplitude and T area (but not in VG), with a subsequent biphasic adaptation lasting longer during VP than AP. The initial rapid changes occurred within the time for QT adaptation to reach steady-state.Our results corroborate and expand data from animal and invasive human studies, showing similarities of the adaptation pattern on different scales. The initial rapidly changing VR adaptation phase presumably reflects a window of increased vulnerability to arrhythmias.
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| 2. |
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| 3. |
- Baturova, Maria A., et al.
(författare)
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P-wave characteristics as electrocardiographic markers of atrial abnormality in prediction of incident atrial fibrillation – The Malmö Preventive Project
- 2024
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Ingår i: Journal of Electrocardiology. - 0022-0736 .- 1532-8430. ; 82, s. 125-130
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Tidskriftsartikel (refereegranskat)abstract
- Background: P-wave indices reflect atrial abnormalities contributing to atrial fibrillation (AF). We aimed to assess a comprehensive set of P-wave characteristics for prediction of incident AF in a population-based setting. Methods: Malmö Preventative Project (MPP) participants were reexamined in 2002–2006 with electrocardiographic (ECG) and echocardiographic examinations and followed for 5 years. AF-free subjects (n = 983, age 70 ± 5 years, 38% females) with sinus rhythm ECGs were included in the study. ECGs were digitally processed using the Glasgow algorithm. P-wave duration, axis, dispersion, P-terminal force in lead V1 and interatrial block (IAB) were evaluated. ECG risk score combining the morphology, voltage and length of P-wave (MVP score) was calculated. New-onset diagnoses of AF were obtained from nation-wide registers. Results: During follow up, 66 patients (7%) developed AF. After adjustment for age and gender, the independent predictors of AF were abnormal P-wave axis > 75° (HR 1.63 CI95% 1.95–11.03) and MVP score 4 (HR 6.17 CI 95% 1.76–21.64), both correlated with LA area: Person r − 0.146, p < 0.001 and 0.192, p < 0.001 respectively. Advanced IAB (aIAB) with biphasic P-wave morphology in leads III and aVF was the most prevalent variant of aIAB and predicted AF in a univariate model (HR 2.59 CI 95% 1.02–6.58). Conclusion: P-wave frontal axis and MVP score are ECG-based AF predictors in the population-based cohort. Our study provides estimates for prevalence and prognostic importance of different variants of aIAB, providing a support to use biphasic P-wave morphology in lead aVF as the basis for aIAB definition.
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| 4. |
- Bergfeldt, Lennart, 1950, et al.
(författare)
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Spatial peak and mean QRS-T angles: A comparison of similar but different emerging risk factors for cardiac death.
- 2020
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Ingår i: Journal of electrocardiology. - : Elsevier BV. - 1532-8430 .- 0022-0736. ; 61, s. 112-120
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Tidskriftsartikel (refereegranskat)abstract
- The spatial peak and mean QRS-T angles are scientifically but not clinically established risk factors for cardiovascular events including cardiac death. The study aims were to compare these angles, assess their association with hypertension (HT) and diabetes mellitus (DM), and explore the relation between the mean QRS-T angle and the ventricular gradient (VG; reflecting electrical heterogeneity), which both are derived from the QRSarea and Tarea vectors.Altogether 1094 participants (aged 50-65years, 550 women) from the pilot of the population-based Swedish CArdioPulmonary bioImage Study with Frank vectorcardiographic recordings were included and divided into 5 subgroups: apparently healthy n=320; HT n=311; DM n=33; DM+HT n=53; miscellaneous conditions n=377. Abnormal peak and mean QRS-T angles were defined as >95th percentile.Peak QRS-T angles were generally narrower than the mean QRS-T angles; both were narrower in women than in men. Abnormal peak (>124°) and/or mean (>119°) QRS-T angles were found in 73 participants (6.7%). The concordance regarding abnormal versus normal-borderline QRS-T angles was good (Cohen's kappa 0.61). The prevalence of abnormal angles varied from 2.5% in healthy to 21.2% in DM. There was an inverse logarithmical relation between the mean QRS-T angle and the VG.The peak and mean QRS-T angles are not interchangeable but complementary. DM, HT, sex and absence of disease are important determinants of both QRS-T angles. The mean QRS-T angle and the VG relationship is complex. All three VCG derived measures reflect related but differing electrophysiological properties and have potential prognostic value vis-à-vis cardiovascular events.
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| 5. |
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| 6. |
- Habineza, Theogene, et al.
(författare)
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End-to-end risk prediction of atrial fibrillation from the 12-Lead ECG by deep neural networks
- 2023
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Ingår i: Journal of Electrocardiology. - : Elsevier. - 0022-0736 .- 1532-8430. ; 81, s. 193-200
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Tidskriftsartikel (refereegranskat)abstract
- Background: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas-cular diseases such as stroke and heart failure. Machine learning methods have shown promising results in evaluating the risk of developing atrial fibrillation from the electrocardiogram. We aim to develop and evaluate one such algorithm on a large CODE dataset collected in Brazil.Methods: We used the CODE cohort to develop and test a model for AF risk prediction for individual patients from the raw ECG recordings without the use of additional digital biomarkers. The cohort is a collection of ECG recordings and annotations by the Telehealth Network of Minas Gerais, in Brazil. A convolutional neural network based on a residual network architecture was implemented to produce class probabilities for the classification of AF. The probabilities were used to develop a Cox proportional hazards model and a Kaplan-Meier model to carry out survival analysis. Hence, our model is able to perform risk prediction for the development of AF in patients without the condition.Results: The deep neural network model identified patients without indication of AF in the presented ECG but who will develop AF in the future with an AUC score of 0.845. From our survival model, we obtain that patients in the high-risk group (i.e. with the probability of a future AF case being >0.7) are 50% more likely to develop AF within 40 weeks, while patients belonging to the minimal-risk group (i.e. with the probability of a future AF case being less than or equal to 0.1) have >85% chance of remaining AF free up until after seven years.Conclusion: We developed and validated a model for AF risk prediction. If applied in clinical practice, the model possesses the potential of providing valuable and useful information in decision- making and patient management processes.
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| 7. |
- Holmqvist, Fredrik, et al.
(författare)
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Study of ECG-derived atrial fibrillatory rate for prediction of the outcome of cardioversion of short duration atrial fibrillation (CASAF)
- 2023
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Ingår i: Journal of Electrocardiology. - 0022-0736. ; 81, s. 20-22
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Tidskriftsartikel (refereegranskat)abstract
- Aims: The present study aimed at testing the hypothesis that atrial fibrillatory rate (AFR) is predictive of sinus rhythm maintenance after electrical cardioversion. Methods and results: The study comprised 32 patients admitted for cardioversion of atrial fibrillation of short duration (mean duration 3.8 ± 7.7 days). AFR was estimated using frequency power spectrum analysis of QRST-cancelled ECG. At six-weeks follow-up 22% of the patients had relapsed to AF. The pre-cardioversion mean AFR of those was 332 ± 64 fpm compared to 378 ± 59 fpm among patients maintaining sinus rhythm (p = 0.12). Conclusion: AFR was not predictive of sinus rhythm maintenance in patients of short duration AF undergoing cardioversion. This is in stark contrast with the earlier reported findings. Clinical trial registration: NCT02112318 (http://www.clinicaltrials.gov).
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| 8. |
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| 9. |
- Lindow, Thomas, et al.
(författare)
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Optimal measuring point for ST deviation in chest pain patients with possible acute coronary syndrome
- 2020
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Ingår i: Journal of Electrocardiology. - : Elsevier BV. - 1532-8430 .- 0022-0736. ; 58, s. 165-170
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: In the ECG, significant ST elevation or depression according to specific amplitude criteria can be indicative of acute coronary syndrome (ACS). Guidelines state that the ST amplitude should be measured at the J point, but data to support that this is the optimal measuring point for ACS detection is lacking. We evaluated the impact of different measuring points for ST deviation on the diagnostic accuracy for ACS in unselected emergency department (ED) chest pain patients.MATERIAL AND METHODS: We included 14,148 adult patients with acute chest pain and an ECG recorded at a Swedish ED between 2010 and 2014. ST deviation was measured at the J point (STJ) and at 20, 40, 60 and 80 ms after the J point. A discharge diagnosis of ACS or not at the index visit was noted in all patients.RESULTS: In total, 1489 (10.5%) patients had ACS. ST amplitude criteria at STJ had a sensitivity of 28% and a specificity of 92% for ACS. With these criteria, the highest positive and negative predictive values for ACS were obtained near the J point, but the optimal point varied with ST deviation, age group and sex. The overall best measuring points were STJ and ST20.CONCLUSIONS: This study indicates that the diagnostic accuracy of the ECG criteria for ACS is very low in ED chest pain patients, and that the optimal measuring point for the ST amplitude in the detection of ACS differs between ST elevation and depression, and between patient subgroups.
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| 10. |
- Lindow, Thomas, et al.
(författare)
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Pheochromocytoma – An ECG diagnosis?
- 2020
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Ingår i: Journal of Electrocardiology. - : Elsevier BV. - 0022-0736. ; 58, s. 7-9
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Tidskriftsartikel (refereegranskat)abstract
- Pheochromocytoma is a rare catecholamine-secreting tumor in the adrenal medulla. In some cases, the first symptoms are cardiovascular. We report on two patients with pheochromocytoma, who both presented with bidirectional ventricular tachycardia (BDVT). We elaborate on the mechanisms of BDVT in the setting of pheochromocytoma.
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| 11. |
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| 12. |
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| 13. |
- Nyström, Axel, et al.
(författare)
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Prior electrocardiograms not useful for machine learning predictions of major adverse cardiac events in emergency department chest pain patients
- 2024
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Ingår i: Journal of Electrocardiology. - Philadelphia, PA : Elsevier. - 0022-0736 .- 1532-8430. ; 82, s. 42-51
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Tidskriftsartikel (refereegranskat)abstract
- At the emergency department (ED), it is important to quickly and accurately determine which patients are likely to have a major adverse cardiac event (MACE). Machine learning (ML) models can be used to aid physicians in detecting MACE, and improving the performance of such models is an active area of research. In this study, we sought to determine if ML models can be improved by including a prior electrocardiogram (ECG) from each patient. To that end, we trained several models to predict MACE within 30 days, both with and without prior ECGs, using data collected from 19,499 consecutive patients with chest pain, from five EDs in southern Sweden, between the years 2017 and 2018. Our results indicate no improvement in AUC from prior ECGs. This was consistent across models, both with and without additional clinical input variables, for different patient subgroups, and for different subsets of the outcome. While contradicting current best practices for manual ECG analysis, the results are positive in the sense that ML models with fewer inputs are more easily and widely applicable in practice. © 2023 The Authors
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| 14. |
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| 15. |
- Sedova, Ksenia A, et al.
(författare)
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Terminal T-wave inversion predicts reperfusion tachyarrhythmias in STEMI
- 2022
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Ingår i: Journal of Electrocardiology. - : Elsevier BV. - 1532-8430 .- 0022-0736. ; 71, s. 28-31
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: A reliable electrocardiographic predictor of ventricular fibrillation (VF) in patients with ST elevation myocardial infarction (STEMI) is lacking so far. Previous experimental/simulation study suggested a terminal T-wave inversion (TTWI) in ischemia-related ECG leads corresponding to anterior infarct localization as an independent predictor of reperfusion VF (rVF). This T-wave characteristic has never been tested as a rVF predictor in clinical settings. The aim of this study was to test if terminal T-wave inversion (TTWI) at admission ECG (before reperfusion) can serve as a predictor of ventricular fibrillation during reperfusion (rVF) in patients with anterior STEMI undergoing primary PCI.METHODS AND RESULTS: Study population included consecutive patients with anterior infarct localization admitted for primary PCI (n = 181, age 65 [57; 76] years, 66% male). Of those, 14 patients had rVF (rVF group, age 59 [47; 76] years, 64% male) and patients without rVF comprised the No-rVF group (n = 167, age 65 [57; 76] years, 66% male). Association of TTWI with rVF was analyzed using logistic regression analysis adjusted for relevant clinical and electrocardiographic covariates. The prevalence of TTWI in rVF group was 62% comparing to 23% in the No-rVF group, p = 0.005. TTWI was associated with increased risk of rVF (OR 5.51; 95% CI 1.70-17.89; p = 0.004) and remained a significant predictor after adjustment for age, gender, history of MI prior to index admission, VF before reperfusion, Tpeak-Tend, maximal ST elevation, and QRS duration (OR 23.49; 95% CI 3.14-175.91; p = 0.002).CONCLUSIONS: The terminal T-wave inversion in anterior leads before PCI independently predicted rVF in patients with anterior MI thus confirming the previous experimental/simulation findings.
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| 16. |
- Zeijlon, Rickard, et al.
(författare)
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The role of admission electrocardiogram in predicting outcome in patients hospitalized for COVID-19.
- 2022
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Ingår i: Journal of electrocardiology. - : Elsevier BV. - 0022-0736 .- 1532-8430. ; 75, s. 10-18
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Tidskriftsartikel (refereegranskat)abstract
- Abnormal electrocardiogram (ECG) has been associated with poor outcome in patients hospitalized for COVID-19. However, the independent association between admission ECG and the risk of a poor outcome remains to be established. Our aim was to determine if abnormal admission ECG predicts treatment at intensive care unit or in-hospital death within 30days in patients hospitalized for COVID-19.We analyzed the propensity weighted association between abnormal admission ECG and outcome in patients hospitalized for COVID-19 (March to May 2020). All adult patients hospitalized for COVID-19 at the three centers of Sahlgrenska University Hospital (Gothenburg, Sweden) were eligible for inclusion (N=439). Patients with available admission ECG within six hours from admission were included.238 patients (age 62±16years, 74% male) were included. 103 patients had normal ECG and 135 patients had abnormal ECG. 99 patients were admitted to intensive care unit or died in-hospital within 30days. Abnormal ECG was associated with increased risk of the outcome (odds ratio 2.11 [95% confidence interval 1.21-3.66]).Abnormal admission ECG was associated with increased risk of treatment at intensive care unit or in-hospital death within 30days; and could be considered a high-risk criterion in patients hospitalized for COVID-19.
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