Prevalence of Electrocardiographic Abnormalities in Patients with Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis
1
Department of Emergency Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
2
Acute Care and Emergency Medicine (ACE) Research Cluster, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2025, 14(13), 4750; https://doi.org/10.3390/jcm14134750
Submission received: 12 May 2025
/
Revised: 17 June 2025
/
Accepted: 2 July 2025
/
Published: 4 July 2025
(This article belongs to the Special Issue Recent Advances in Pulmonary Embolism and Thrombosis)
Abstract
Background/Objectives: Acute pulmonary embolism (PE) remains a leading cause of cardiovascular morbidity and mortality. Although computed tomography pulmonary angiography (CTPA) is the gold standard for diagnosis, electrocardiography (ECG) is a widely available, non-invasive tool that may provide diagnostic clues. This study aims to estimate the pooled prevalence of specific ECG abnormalities in patients with confirmed acute PE. Methods: We conducted a systematic review and meta-analysis in accordance with the PRISMA guidelines. We searched PubMed, Embase, Web of Science, Scopus, and the Cochrane Central Register of Controlled Trials until April 2024 for studies reporting prevalence data on ECG abnormalities in confirmed acute PE cases. Pooled prevalence estimates were calculated using a random-effects model, and heterogeneity was assessed using the I2 statistic. Publication bias was evaluated through funnel plots and Egger’s test. Results: Twenty-four studies with 7467 patients were included. The most common ECG abnormalities were sinus tachycardia (31%, 95% CI 22–40%), clockwise rotation (28%, 95% CI 12–45%), T-wave inversion in leads V1–V3 (18%, 95% CI 13–23%), S1Q3T3 pattern (15%, 95% CI 11–19%), and right bundle branch block (14%, 95% CI 10–17%). High heterogeneity was observed across studies, with an I2 value exceeding 95%. Publication bias was detected for both S1Q3T3 and right bundle branch block. Conclusions: Sinus tachycardia and the S1Q3T3 pattern are frequently observed in acute PE, supporting their potential use in clinical recognition. However, significant heterogeneity and publication bias highlight the need for larger, higher-quality studies with standardized ECG protocols to understand ECG’s diagnostic and prognostic role in PE.
1. Introduction
Acute pulmonary embolism (PE) is a significant cause of cardiovascular morbidity and mortality, with an estimated incidence of 60 to 124 cases per 100,000 persons [1,2]. Despite advances in diagnostic imaging, mortality remains high, ranging from 8% to 30%, particularly in cases complicated by diagnostic delay, hemodynamic instability, or underlying comorbid conditions [1].
The clinical presentation of acute PE is notoriously variable, often mimicking other cardiopulmonary disorders [3]. Symptoms may include dyspnea, pleuritic chest pain, syncope, hemoptysis, or may be absent [3,4]. This diagnostic ambiguity contributes to the condition’s under-recognition and underscores the need for adjunctive tools to guide early clinical suspicion. While computed tomography pulmonary angiography (CTPA) is the diagnostic gold standard, its use is limited by availability, radiation exposure, and contrast-related risks [5]. Electrocardiography (ECG), on the other hand, is a universally accessible, rapid, and non-invasive diagnostic modality. Although it lacks the sensitivity and specificity to serve as a definitive diagnostic test, certain ECG patterns—such as sinus tachycardia, the S1Q3T3 pattern, right bundle branch block (RBBB), and T-wave inversions in precordial leads—have been associated with right ventricular strain in the context of PE [6,7]. These findings may offer valuable clinical clues, particularly when advanced imaging is delayed or unavailable [6].
Several recent studies have reported additional ECG abnormalities in acute PE, including right-axis deviation, low voltage, ST segment changes, and atrial arrhythmias [8,9]. While individual studies suggest the potential diagnostic and prognostic utility of these patterns, prevalence estimates vary widely, and their role in risk stratification remains uncertain.
To date, no comprehensive synthesis of the prevalence of ECG findings in confirmed cases of acute PE has been undertaken with sufficient statistical rigor. We therefore conducted a systematic review and meta-analysis to determine the pooled prevalence of specific ECG abnormalities in patients with imaging-confirmed acute PE. The findings aim to inform clinicians on the diagnostic utility of ECG patterns and support the development of improved early recognition strategies.
2. Materials and Methods
2.1. Study Design and Registration
We conducted a systematic review and meta-analysis to estimate the prevalence of ECG findings in patients with confirmed acute PE. The study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines [10]. The protocol was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration ID: CRD42024535571). We used ChatGPT 4.0 and Grammarly to check and correct grammatical errors during the writing of this document. After using these tools, we reviewed, checked, and edited the content as needed, taking full responsibility for its accuracy.
2.2. Search Strategy and Study Selection
A comprehensive literature search was conducted across five databases—PubMed, Embase, Web of Science, Scopus, and the Cochrane Central Register of Controlled Trials—from inception to 8 April 2024. We used a combination of the Medical Subject Heading (MeSH) terms with various spellings and endings: “prevalence,” “epidemiology,” “incidence,” “finding,” “epidemiology,” “pulmonary embolism,” “pulmonary thromboembolic disease,” “electrocardiography,” “electrocardiogram,” “ECG,” and “EKG.” The complete search strategy is provided in Supplementary Table S1. No language restrictions were applied. Additional studies were identified through reference screening and citation tracking of eligible articles and relevant reviews. We extracted the search results from these databases and deleted the duplicates. The remaining articles were added to the Rayyan website for screening.
2.3. Inclusion Criteria and Outcome of Interest
Studies were included if they met the following criteria: (1) patients had confirmed acute PE diagnosed by CTPA, ventilation-perfusion (V/Q) scanning, or pulmonary angiography; (2) ECG findings were systematically reported using 12-lead electrocardiography; and (3) the study provided prevalence data on specific ECG abnormalities. We excluded preclinical studies, case reports, case series, narrative reviews, editorials, and studies without sufficient ECG detail. Only studies published in English were included in the final analysis.
The primary endpoint is the prevalence of ECG abnormalities in confirmed acute PE cases. ECG patterns included the S1Q3T3 pattern, the S1S2S3 pattern, RBBB, right-axis deviation, clockwise rotation, sinus tachycardia, atrial arrhythmia, atrial fibrillation and atrial flutter, low voltage, P pulmonale, and T-wave inversion in precordial leads (leads V1–V3). These abnormalities were selected as mentioned in the standard international guidelines (i.e., European Society of Cardiology 2019) [5].
2.4. Data Extraction and Study Risk of Bias Assessment
Titles and abstracts were independently screened by two reviewers (W.W. and S.K.) using Rayyan (Qatar Computing Research Institute), followed by full-text review of eligible articles. Disagreements were resolved through discussion or by a third person (W.S.).
A standardized data extraction form was used to collect the following variables: first author, publication year, study design, country, enrollment period, sample size, patient demographics, PE confirmation method, and reported ECG findings. All extracted data were entered into Microsoft Excel. Two reviewers (S.K. and W.S.) independently assessed the methodological quality of the included studies using the Joanna Briggs Institute (JBI) critical appraisal checklist for prevalence studies [11]. Discrepancies were resolved through consensus, with the assistance of a third person (W.W.). Studies were categorized as having low risk of bias (score 8–9), some concerns (score 5–7), or high risk of bias (score < 5).
2.5. Statistical Analysis
We calculated pooled prevalence estimates and 95% confidence intervals (CIs) for each ECG finding using a random-effects model (DerSimonian and Laird method) to account for between-study heterogeneity. Heterogeneity was assessed using the I2 statistic and Cochran’s Q test, with I2 values of <25%, 25–50%, and >50% interpreted as low, moderate, and high heterogeneity, respectively [12]. Publication bias was assessed visually using funnel plots and statistically using Begg’s and Egger’s tests. All tests were two-sided, with a p-value of less than 0.05, which was considered statistically significant. All analyses were conducted using STATA MP version 16.0 (StataCorp LLC, College Station, TX, USA).
3. Results
3.1. Study Selection and Characteristics of Included Studies
The literature search yielded 1715 records. After removing duplicates, 1363 studies underwent title and abstract screening, of which 61 full-text articles were assessed for eligibility. A total of 24 studies, comprising 7467 patients with confirmed acute PE, met the inclusion criteria and were included in the final analysis [7,9,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] (Figure 1, PRISMA flow diagram).
The included studies were published between 2000 and 2024 and conducted across 13 countries. Sample sizes ranged from 20 to 1676 patients. All studies confirmed the diagnosis of acute PE via CTPA or ventilation-perfusion scan. Study characteristics and patient demographics are described in Table 1. Fourteen studies (58.3%) were classified as low risk (JBI scores 8–9), and ten studies (41.7%) were considered to have some concerns (JBI scores 5–7). Most concerns arose from unclear sampling methods, inadequate sample size, the absence of consecutive patient inclusion, and a lack of standardized ECG interpretation. Details of the risk of bias for each included study are listed in Supplementary Table S2.
3.2. Prevalence of Electrocardiographic Abnormalities
Eleven distinct ECG abnormalities were identified, and their pooled prevalence rates were estimated. Figure 2 summarizes each abnormality’s prevalence and 95% CIs. The prevalence of the S1Q3T3 pattern was reported in all included studies [7,9,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34], followed by RBBB (21 studies) [7,9,13,14,16,17,18,20,21,22,23,24,25,26,28,29,30,31,32,33,34], right axis deviation (13 studies) [9,13,14,17,20,21,24,25,26,27,30,31,33], and sinus tachycardia (13 studies) [7,13,14,16,17,18,19,21,27,29,31,33,34].
The pooled prevalence of the S1Q3T3 pattern was 15% (95% CI, 11–19%; I2 = 97%, p < 0.001) across 24 studies (Supplementary Figure S1). Among low-risk studies, the prevalence was 15% (95% CI, 9–20%; I2 = 98%), while studies with some concerns showed a slightly higher pooled prevalence of 16% (95% CI, 9–23%; I2 = 95%). No significant difference in prevalence was observed between risk groups (p = 0.748).
Sinus tachycardia was found to be the most prevalent finding in 31% of patients (95% CI, 22–40%; I2 = 97%, p < 0.001) based on data from 13 studies (Supplementary Figure S2). The pooled prevalence from low-risk studies was 34% (95% CI, 21–48%), compared with 27% (95% CI, 23–30%) in studies with some concerns. The difference in pooled estimates between risk groups was statistically significant (p = 0.286).
The details regarding the prevalence and corresponding 95% CIs of other ECG abnormalities are summarized and reported in the Supplementary Figures S3–S11.
Visual inspection of the funnel plots for the two most reported ECG findings (S1Q3T3 and RBBB) revealed mild asymmetry (Supplementary Figures S12 and S13), particularly among smaller studies. Egger’s test indicated publication bias for both findings (p = 0.0238 and p = 0.0239, respectively).
4. Discussion
The most frequently observed ECG abnormalities in acute PE include sinus tachycardia, clockwise rotation, T-wave inversions in precordial leads, S1Q3T3 pattern, and RBBB. These findings are consistent with prior literature and support the clinical relevance of certain ECG features as markers of right ventricular strain in the setting of acute PE [35].
Among these, sinus tachycardia demonstrated the highest pooled prevalence (31%), consistent with its frequent inclusion in clinical prediction rules such as the Wells and revised Geneva scores [36,37]. While non-specific, sinus tachycardia may reflect a compensatory response to impaired hemodynamics, possibly mediated by the release of catecholamine and inflammatory mediators [8,34]. Conversely, the S1Q3T3 pattern, also known as the McGinn–White sign, traditionally regarded as a hallmark of acute PE, was found in 15% of cases, aligning with its high specificity but low sensitivity [33]. This pattern likely reflects acute right ventricular overload and a shift in the cardiac electrical axis due to pulmonary arterial obstruction.
RBBB and right-axis deviation, each associated with elevated right ventricular pressures and dilation, were also commonly observed [31,32,38]. Transient RBBB, in particular, has been reported as reversible with anticoagulation therapy, suggesting a direct hemodynamic effect [32]. Clockwise rotation and delayed R/S transition (V5 or beyond) similarly reflect right ventricular dilatation and conduction delay [8,34]. Notably, these patterns have demonstrated high specificity, and some studies suggest associations with adverse outcomes, including short-term mortality [32].
T-wave inversions in leads V1–V3, found in a significant proportion of patients, are thought to result from subendocardial ischemia of the right ventricle, often secondary to increased wall tension and impaired perfusion [39]. Compared with S1Q3T3 or RBBB, T-wave inversion may offer higher sensitivity and moderate diagnostic accuracy, underscoring its potential diagnostic value in combination with other findings [33,40].
Less prevalent but noteworthy findings included atrial arrhythmias (such as atrial fibrillation and flutter), low-voltage QRS complexes, and the S1S2S3 pattern. Atrial arrhythmias may result from atrial stretch and hypoxia-induced ectopic activity, and their presence may indicate more advanced cardiopulmonary compromise [41]. Although the S1S2S3 pattern is historically linked to right ventricular hypertrophy and chronic pulmonary disease [42], its occurrence in acute PE remains controversial, with some studies suggesting its association with right heart strain and others finding no significant correlation [30].
The pathophysiological basis of these ECG changes is largely attributed to acute pressure overload and right ventricular dilatation, leading to altered depolarization vectors and conduction abnormalities [26], as summarized in Table 2. Such changes may occur transiently and are often reversible following appropriate treatment. Moreover, accumulating evidence suggests that certain ECG features—particularly RBBB and T-wave inversions—may also carry prognostic significance in risk stratification tools, potentially informing decisions regarding thrombolysis or intensive monitoring [43,44,45].
4.1. Strengths and Limitations
This meta-analysis incorporates data from a large international cohort and applies rigorous methodological standards, including pre-registration and risk-of-bias assessment using the JBI checklist [11]. The study also includes a broad spectrum of ECG abnormalities, reflecting the heterogeneous manifestations of PE on ECG. Nevertheless, several limitations merit consideration. First, although we employed rigorous methods to identify and include relevant studies, the overall quality and design of the included studies were variable. Some studies had small sample sizes, lacked uniform diagnostic criteria, or used inconsistent ECG interpretation protocols, which may have introduced bias and affected the reliability of pooled estimates. Future prospective studies with standardized ECG acquisition and interpretation protocols are needed to explore the co-occurrence and temporal dynamics of these findings. Second, heterogeneity across studies was substantial, likely attributable to differences in study design, populations, and timing of ECG acquisition relative to PE diagnosis. Including data from a wide range of geographical regions, age groups, and sexes may have further contributed to this heterogeneity, reflecting variations in healthcare systems, baseline characteristics, and diagnostic practices. Third, incomplete reporting in the primary studies precluded subgroup analyses by sex, age, PE severity, or comorbidities. Additionally, the lack of standardized ECG acquisition protocols and variability in outcome definitions may have affected study comparability. Finally, evidence of publication bias was identified for some findings, particularly among smaller studies, which may influence the robustness of the pooled estimates.
4.2. Clinical Implications and Future Directions
ECG remains a widely accessible and cost-effective tool, and although it is insufficiently sensitive to rule out PE, it may raise clinical suspicion in appropriate contexts. However, International guidelines such as those of the European Society of Cardiology (ESC, 2019) [5] reinforce that the ECG should not replace imaging tests, such as CTPA, which is recommended as the gold standard. Similarly, several reports published earlier mentioned the risk of delays in diagnosis if there is excessive reliance on the ECG [46,47,48]. Furthermore, the initial diagnosis of PE should begin with a structured clinical evaluation, using pre-test probability scores, such as the Wells score or the Geneva score, followed by D-dimer measurement in cases of low or moderate probability. Patients with signs of hemodynamic instability should undergo CTPA immediately, the gold standard examination for diagnostic confirmation. In settings with limited resources or contraindications to CTPA, V/Q scintigraphy and bedside echocardiography can be used. Given the observed prevalence of right heart strain patterns, future studies should explore the additive value of ECG findings in diagnostic algorithms and risk stratification scores. Furthermore, given the inherent overlap of ECG findings, combining a group of findings (i.e., sinus tachycardia and right-axis deviation) would be beneficial to address a characteristic group of ECG abnormalities in patients with acute PE. Further prospective research is also needed to evaluate the temporal evolution of ECG changes in PE and their prognostic significance across varying clinical severities.
5. Conclusions
In conclusion, this systematic review and meta-analysis highlight the high prevalence of several key electrocardiographic abnormalities associated with acute PE, with sinus tachycardia and clockwise rotation being the most frequently observed. These findings underscore the potential diagnostic value of ECG as an accessible and non-invasive tool for clinicians, particularly in settings where advanced imaging may be unavailable or delayed. Identifying right heart strain patterns, such as RBBB and T-wave inversions in precordial leads, further supports the ECG’s role in raising clinical suspicion and guiding early recognition of PE. However, given the variability in prevalence estimates across studies, the need for standardized ECG interpretation and larger, high-quality studies remains critical. Future research should focus on the prognostic significance of these ECG findings and their integration into risk stratification models to enhance patient management. Ultimately, this study provides a foundation for further exploration of ECG’s utility in the early diagnosis and management of acute PE.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm14134750/s1, Figure S1: Forest plot of the prevalence of S1Q3T3 in patients with acute pulmonary embolism; Figure S2. Forest plot of the prevalence of sinus tachycardia in patients with acute pulmonary embolism; Figure S3. Forest plot of the prevalence of right bundle branch block in patients with acute pulmonary embolism; Figure S4. Forest plot of the prevalence of right-axis deviation in patients with acute pulmonary embolism; Figure S5. Forest plot of the prevalence of atrial fibrillation/atrial flutter in patients with acute pulmonary embolism; Figure S6. Forest plot of the prevalence of low voltage in patients with acute pulmonary embolism; Figure S7. Forest plot of the prevalence of T wave inversion in leads V1–V3 in patients with acute pulmonary embolism; Figure S8. Forest plot of the prevalence of atrial arrhythmia in patients with acute pulmonary embolism; Figure S9. Forest plot of the prevalence of clockwise rotation in patients with acute pulmonary embolism; Figure S10. Forest plot of the prevalence of P pulmonale in patients with acute pulmonary embolism; Figure S11. Forest plot of the prevalence of S1S2S3 in patients with acute pulmonary embolism; Figure S12. Funnel plot showing the publication bias among studies reporting the prevalence of S1Q3T3 in acute PE cases; Figure S13. Funnel plot showing the publication bias among studies reporting the prevalence of right bundle branch block in acute PE cases; Table S1. Details of electronic search terms; Table S2. Study’s risk of bias using the Joanna Briggs Institute (JBI) critical appraisal checklist for prevalence studies.
Author Contributions
Conceptualization, S.K., W.S. and W.W.; methodology, S.K. and W.W.; software, S.K. and W.W.; validation, W.W.; formal analysis, W.W.; investigation, S.K., W.S. and W.W.; resources, S.K. and W.W.; data curation, W.W.; writing—original draft preparation, S.K. and W.W.; writing—review and editing, W.W.; funding acquisition, W.W. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Faculty of Medicine, Chiang Mai University, through the Acute Care and Emergency Medicine (ACE) Research Cluster. The APC was funded by the Faculty of Medicine, Chiang Mai University.
Acknowledgments
We gratefully acknowledge Rudklao Sairai for their dedicated work during proposal preparation. We used ChatGPT 4.0 and Grammarly to check and correct grammatical errors during the writing of this document. After using these tools, we reviewed, checked, and edited the content as needed, and we take full responsibility for its content.
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| CI | Confidence interval |
| CTPA | Computed tomography pulmonary angiography |
| ECG | Electrocardiogram |
| PE | Pulmonary embolism |
| RBBB | Right bundle branch block |
| RV | Right ventricle |
References
- Bĕlohlávek, J.; Dytrych, V.; Linhart, A. Pulmonary Embolism, Part I: Epidemiology, Risk Factors and Risk Stratification, Pathophysiology, Clinical Presentation, Diagnosis and Nonthrombotic Pulmonary Embolism. Exp. Clin. Cardiol. 2013, 18, 129–138. [Google Scholar]
- Barnes, G.D.; Muzikansky, A.; Cameron, S.; Giri, J.; Heresi, G.A.; Jaber, W.; Wood, T.; Todoran, T.M.; Courtney, D.M.; Tapson, V.; et al. Comparison of 4 Acute Pulmonary Embolism Mortality Risk Scores in Patients Evaluated by Pulmonary Embolism Response Teams. JAMA Netw. Open 2020, 3, e2010779. [Google Scholar] [CrossRef]
- van Maanen, R.; Trinks-Roerdink, E.M.; Rutten, F.H.; Geersing, G.J. A Systematic Review and Meta-Analysis of Diagnostic Delay in Pulmonary Embolism. Eur. J. Gen. Pract. 2022, 28, 165–172. [Google Scholar] [CrossRef]
- Mansella, G.; Keil, C.; Nickel, C.H.; Eken, C.; Wirth, C.; Tzankov, A.; Peterson, C.J.; Aujesky, D.; Bingisser, R. Delayed Diagnosis in Pulmonary Embolism: Frequency, Patient Characteristics, and Outcome. Respiration 2020, 99, 589–597. [Google Scholar] [CrossRef]
- Konstantinides, S.V.; Meyer, G.; Becattini, C.; Bueno, H.; Geersing, G.-J.; Harjola, V.-P.; Huisman, M.V.; Humbert, M.; Jennings, C.S.; Jiménez, D.; et al. 2019 ESC Guidelines for the Diagnosis and Management of Acute Pulmonary Embolism Developed in Collaboration with the European Respiratory Society (ERS). Eur. Heart J. 2020, 41, 543–603. [Google Scholar] [CrossRef]
- Su, X.-F.; Fan, N.; Yang, X.-M.; Song, J.-M.; Peng, Q.-H.; Liu, X. A Novel Electrocardiography Model for the Diagnosis of Acute Pulmonary Embolism. Front. Cardiovasc. Med. 2022, 9, 825561. [Google Scholar] [CrossRef]
- Geibel, A.; Zehender, M.; Kasper, W.; Olschewski, M.; Klima, C.; Konstantinides, S. V Prognostic Value of the ECG on Admission in Patients with Acute Major Pulmonary Embolism. Eur. Respir. J. 2005, 25, 843–848. [Google Scholar] [CrossRef]
- Co, I.; Eilbert, W.; Chiganos, T. New Electrocardiographic Changes in Patients Diagnosed with Pulmonary Embolism. J. Emerg. Med. 2017, 52, 280–285. [Google Scholar] [CrossRef]
- Bahreini, Z.; Kamali, M.; Kheshty, F.; Bazrafshan Drissi, H.; Boogar, S.S.; Bazrafshan, M. Differentiating Electrocardiographic Indications of Massive and Submassive Pulmonary Embolism: A Cross-Sectional Study in Southern Iran from 2015 to 2020. Clin. Cardiol. 2024, 47, e24252. [Google Scholar] [CrossRef]
- Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. PLoS Med. 2021, 18, e1003583. [Google Scholar] [CrossRef]
- Munn, Z.; Moola, S.; Lisy, K.; Riitano, D.; Tufanaru, C. Chapter 5: Systematic Reviews of Prevalence and Incidence; Aromataris, E., Munn, Z., Eds.; JBI Manual for Evidence Synthesis; Faculty of Health and Medical Sciences, The University of Adelaide: Adelaide, Australia, 2020. [Google Scholar]
- Fletcher, J. What Is Heterogeneity and Is It Important? BMJ 2007, 334, 94–96. [Google Scholar] [CrossRef]
- Rodger, M.; Makropoulos, D.; Turek, M.; Quevillon, J.; Raymond, F.; Rasuli, P.; Wells, P.S. Diagnostic Value of the Electrocardiogram in Suspected Pulmonary Embolism. Am. J. Cardiol. 2000, 86, 807–809. [Google Scholar] [CrossRef]
- Wang, F.; Wang, L.; Yan, C.; Chang, X.; Wang, H.; Zhu, K.; Xu, Y.; Xu, D. Algorithms of Electrocardiographic Changes for Quantitative and Localization Analysis of Thrombus Burden in Patients with Acute Pulmonary Thromboembolism. Rev. Cardiovasc. Med. 2023, 24, 281. [Google Scholar] [CrossRef]
- Zhan, Z.Q.; Wang, C.Q.; Nikus, K.C.; He, C.R.; Wang, J.; Mao, S.; Dong, X.J. Electrocardiogram Patterns during Hemodynamic Instability in Patients with Acute Pulmonary Embolism. Ann. Noninvasive Electrocardiol. 2014, 19, 543–551. [Google Scholar] [CrossRef]
- Weekes, A.J.; Raper, J.D.; Thomas, A.M.; Lupez, K.; Cox, C.A.; Esener, D.; Boyd, J.S.; Nomura, J.T.; Davison, J.; Ockerse, P.M.; et al. Electrocardiographic Findings Associated with Early Clinical Deterioration in Acute Pulmonary Embolism. Acad. Emerg. Med. 2022, 29, 1185–1196. [Google Scholar] [CrossRef]
- Kukla, P.; Długopolski, R.; Krupa, E.; Furtak, R.; Mirek, E.; Bryniarska; Jastrzębski, M.; Wańczura, P.; Bryniarski, L. The Prognostic Value of ST−segment Elevation in the Lead AVR in Patients with Acute Pulmonary Embolism. Kardiol. Pol. 2011, 69, 649–654. [Google Scholar]
- Park, S.J.; Kwon, C.H.; Bae, B.J.; Kim, B.S.; Kim, S.H.; Kim, H.J.; Hwang, H.K.; Chung, S.M. Diagnostic Value of the Corrected QT Difference between Leads V1 and V6 in Patients with Acute Pulmonary Thromboembolism. Medicine 2017, 96, e8430. [Google Scholar] [CrossRef]
- Witting, M.D.; Mattu, A.; Rogers, R.; Halvorson, C. Simultaneous T-Wave Inversions in Anterior and Inferior Leads: An Uncommon Sign of Pulmonary Embolism. J. Emerg. Med. 2012, 43, 228–235. [Google Scholar] [CrossRef]
- Yan, X.X.; Zhang, H.D.; Peng, F.H.; Ding, L.; Mi, L.J.; Zhang, A.K.; Hua, L.; Tang, M. Prognostic Significance of Quantitative Electrocardiographic Parameters in Patients with Non-High-Risk Pulmonary Embolism. Eur. J. Intern. Med. 2024, 120, 46–51. [Google Scholar] [CrossRef]
- Bolt, L.; Lauber, S.; Limacher, A.; Samim, D.; Löwe, A.; Tritschler, T.; Baumgartner, C.; Aujesky, D. Prognostic Value of Electrocardiography in Elderly Patients with Acute Pulmonary Embolism. Am. J. Med. 2019, 132, e835–e843. [Google Scholar] [CrossRef]
- Vanni, S.; Polidori, G.; Vergara, R.; Pepe, G.; Nazerian, P.; Moroni, F.; Garbelli, E.; Daviddi, F.; Grifoni, S. Prognostic Value of ECG Among Patients with Acute Pulmonary Embolism and Normal Blood Pressure. Am. J. Med. 2009, 122, 257–264. [Google Scholar] [CrossRef]
- Casazza, F.; Pacchetti, I.; Rulli, E.; Roncon, L.; Zonzin, P.; Zuin, M.; Becattini, C.; Bongarzoni, A.; Pignataro, L. Prognostic Significance of Electrocardiogram at Presentation in Patients with Pulmonary Embolism of Different Severity. Thromb. Res. 2018, 163, 123–127. [Google Scholar] [CrossRef]
- Cetin, M.S.; Ozcan Cetin, E.H.; Arisoy, F.; Kuyumcu, M.S.; Topaloglu, S.; Aras, D.; Temizhan, A. Fragmented QRS Complex Predicts In-Hospital Adverse Events and Long-Term Mortality in Patients with Acute Pulmonary Embolism. Ann. Noninvasive Electrocardiol. 2016, 21, 470–478. [Google Scholar] [CrossRef]
- Pourafkari, L.; Ghaffari, S.; Tajlil, A.; Akbarzadeh, F.; Jamali, F.; Nader, N.D. Clinical Significance of ST Elevation in Lead AVR in Acute Pulmonary Embolism. Ann. Noninvasive Electrocardiol. 2017, 22, e12368. [Google Scholar] [CrossRef]
- Kukla, P.; Długopolski, R.; Krupa, E.; Furtak, R.; Szełemej, R.; Mirek-Bryniarska, E.; Jastrzebski, M.; Nowak, J.; Wańczura, P.; Bryniarski, L. Electrocardiography and Prognosis of Patients with Acute Pulmonary Embolism. Cardiol. J. 2011, 18, 648–653. [Google Scholar] [CrossRef]
- Kusayama, T.; Furusho, H.; Kinoshita, M.; Kaneko, S.; Usuda, K.; Takamura, M. Characteristics of Synthesized Right-Sided Chest Electrocardiograms in Patients with Acute Pulmonary Embolism. J. Cardiol. 2019, 73, 313–317. [Google Scholar] [CrossRef]
- Obradović, S.; Džudović, B.; Rusović, S.; Subota, V.; Obradović, D. Gender-Related Differences in Clinical Presentation, Electrocardiography, Laboratory Markers and Outcome in Patients with Acute Embolism. Vojnosanit. Pregl. 2016, 73, 844–849. [Google Scholar] [CrossRef]
- Richman, P.B.; Loutfi, H.; Lester, S.J.; Cambell, P.; Matthews, J.; Friese, J.; Wood, J.; Kasper, D.; Chen, F.; Mandell, M. Electrocardiographic Findings in Emergency Department Patients with Pulmonary Embolism. J. Emerg. Med. 2004, 27, 121–126. [Google Scholar] [CrossRef]
- Çağdaş, M.; Karakoyun, S.; Rencüzoğulları, İ.; Karabağ, Y.; Artaç, İ.; İliş, D.; Hamideyin, Ş.; Karayol, S.; Çiftçi, H.; Çınar, T. Diagnostic Value of QRS and S Wave Variation in Patients with Suspicion of Acute Pulmonary Embolism. Am. J. Emerg. Med. 2018, 36, 2197–2202. [Google Scholar] [CrossRef]
- Stein, P.D.; Matta, F.; Sabra, M.J.; Treadaway, B.; Vijapura, C.; Warren, R.; Joshi, P.; Sadiq, M.; Kofoed, J.T.; Hughes, P.; et al. Relation of Electrocardiographic Changes in Pulmonary Embolism to Right Ventricular Enlargement. Am. J. Cardiol. 2013, 112, 1958–1961. [Google Scholar] [CrossRef]
- Novicic, N.; Dzudovic, B.; Subotic, B.; Shalinger-Martinovic, S.; Obradovic, S. Electrocardiography Changes and Their Significance during Treatment of Patients with Intermediate-High and High-Risk Pulmonary Embolism. Eur. Heart J. Acute Cardiovasc. Care 2020, 9, 271–278. [Google Scholar] [CrossRef]
- Thomson, D.; Kourounis, G.; Trenear, R.; Messow, C.-M.; Hrobar, P.; Mackay, A.; Isles, C. ECG in Suspected Pulmonary Embolism. Postgrad. Med. J. 2019, 95, 12–17. [Google Scholar] [CrossRef]
- Zhang, J.; Liu, G.; Wang, S.; Du, W.; Lv, P.; Guo, H.; Sun, Q.; Liu, Y.; Qi, X. The Electrocardiographic Characteristics of an Acute Embolism in the Pulmonary Trunk and the Main Pulmonary Arteries. Am. J. Emerg. Med. 2016, 34, 212–217. [Google Scholar] [CrossRef]
- Qaddoura, A.; Digby, G.C.; Kabali, C.; Kukla, P.; Zhan, Z.-Q.; Baranchuk, A.M. The Value of Electrocardiography in Prognosticating Clinical Deterioration and Mortality in Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis. Clin. Cardiol. 2017, 40, 814–824. [Google Scholar] [CrossRef]
- Wells, P.S.; Anderson, D.R.; Rodger, M.; Stiell, I.; Dreyer, J.F.; Barnes, D.; Forgie, M.; Kovacs, G.; Ward, J.; Kovacs, M.J. Excluding Pulmonary Embolism at the Bedside without Diagnostic Imaging: Management of Patients with Suspected Pulmonary Embolism Presenting to the Emergency Department by Using a Simple Clinical Model and d-Dimer. Ann. Intern. Med. 2001, 135, 98–107. [Google Scholar] [CrossRef]
- Le Gal, G.; Righini, M.; Roy, P.-M.; Sanchez, O.; Aujesky, D.; Bounameaux, H.; Perrier, A. Prediction of Pulmonary Embolism in the Emergency Department: The Revised Geneva Score. Ann. Intern. Med. 2006, 144, 165–171. [Google Scholar] [CrossRef]
- Kim, J.H.; Noseworthy, P.A.; McCarty, D.; Yared, K.; Weiner, R.; Wang, F.; Wood, M.J.; Hutter, A.M.; Picard, M.H.; Baggish, A.L. Significance of Electrocardiographic Right Bundle Branch Block in Trained Athletes. Am. J. Cardiol. 2011, 107, 1083–1089. [Google Scholar] [CrossRef]
- Arrigo, M.; Price, S.; Harjola, V.-P.; Huber, L.C.; Schaubroeck, H.A.I.; Vieillard-Baron, A.; Mebazaa, A.; Masip, J. Diagnosis and Treatment of Right Ventricular Failure Secondary to Acutely Increased Right Ventricular Afterload (Acute Cor Pulmonale): A Clinical Consensus Statement of the Association for Acute CardioVascular Care of the European Society of Cardiology. Eur. Heart J. Acute Cardiovasc. Care 2024, 13, 304–312. [Google Scholar] [CrossRef]
- Laurentius, A.; Ariani, R. Diagnostic Comparison of Anterior Leads T-Wave Inversion and McGinn-White Sign in Suspected Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis. Hong Kong J. Emerg. Med. 2023, 30, 54–60. [Google Scholar] [CrossRef]
- Scridon, A. Autonomic Imbalance and Atrial Ectopic Activity-a Pathophysiological and Clinical View. Front. Physiol. 2022, 13, 1058427. [Google Scholar] [CrossRef]
- Bayés de Luna, A.; Carrió, I.; Subirana, M.T.; Torner, P.; Cosín, J.; Sagués, F.; Guindo, J. Electrophysiological Mechanisms of the SI SII SIII Electrocardiographic Morphology. J. Electrocardiol. 1987, 20, 38–44. [Google Scholar] [CrossRef]
- Shopp, J.D.; Stewart, L.K.; Emmett, T.W.; Kline, J.A. Findings From 12-Lead Electrocardiography That Predict Circulatory Shock From Pulmonary Embolism: Systematic Review and Meta-Analysis. Acad. Emerg. Med. 2015, 22, 1127–1137. [Google Scholar] [CrossRef]
- Digby, G.C.; Kukla, P.; Zhan, Z.-Q.; Pastore, C.A.; Piotrowicz, R.; Schapachnik, E.; Zareba, W.; Bayés de Luna, A.; Pruszczyk, P.; Baranchuk, A.M. The Value of Electrocardiographic Abnormalities in the Prognosis of Pulmonary Embolism: A Consensus Paper. Ann. Noninvasive Electrocardiol. 2015, 20, 207–223. [Google Scholar] [CrossRef]
- Ryu, H.M.; Lee, J.H.; Kwon, Y.S.; Lee, S.H.; Bae, M.H.; Lee, J.H.; Yang, D.H.; Park, H.S.; Cho, Y.; Chae, S.C.; et al. Electrocardiography Patterns and the Role of the Electrocardiography Score for Risk Stratification in Acute Pulmonary Embolism. Korean Circ. J. 2010, 40, 499–506. [Google Scholar] [CrossRef]
- Al-Zaiti, S.S.; Martin-Gill, C.; Zègre-Hemsey, J.K.; Bouzid, Z.; Faramand, Z.; Alrawashdeh, M.O.; Gregg, R.E.; Helman, S.; Riek, N.T.; Kraevsky-Phillips, K.; et al. Machine Learning for ECG Diagnosis and Risk Stratification of Occlusion Myocardial Infarction. Nat. Med. 2023, 29, 1804–1813. [Google Scholar] [CrossRef]
- Tuminah, S.; Indrawati, L.; Riyadina, W.; Wurisastuti, T.; Letelay, A.M.; Sitorus, N.; Putri, A.S.; Isfandari, S.; Irmansyah, I. Number of Comorbidities and the Risk of Delay in Seeking Treatment for Coronary Heart Disease: A Longitudinal Study in Bogor City, Indonesia. Osong Public Health Res. Perspect. 2024, 15, 201–211. [Google Scholar] [CrossRef]
- Kraik, K.; Dykiert, I.A.; Niewiadomska, J.; Ziemer-Szymańska, M.; Mikołajczak, K.; Kreń, M.; Kukiełka, P.; Martuszewski, A.; Harych, T.; Poręba, R.; et al. The Most Common Errors in Automatic ECG Interpretation. Front. Physiol. 2025, 16, 1590170. [Google Scholar] [CrossRef]
Figure 1.
PRISMA flow diagram.
Figure 2.
Pooled prevalence of ECG abnormalities in confirmed acute PE cases.
Figure 3.
12-lead electrocardiogram shows right bundle branch block, T wave inversion in leads V1–V2, and S1Q3T3 pattern (Case courtesy: Dr. Wachira Wongtanasarasin).
Figure 3.
12-lead electrocardiogram shows right bundle branch block, T wave inversion in leads V1–V2, and S1Q3T3 pattern (Case courtesy: Dr. Wachira Wongtanasarasin).
Table 1.
Characteristics of included studies.
| First Author, Year | Country | n | Age (Year), mean ± SD | %Male | Design | Inclusion Criteria | ECG Findings of Interest |
|---|---|---|---|---|---|---|---|
| Wang, 2023 [14] | China | 341 | 69 ± 14 | 50.4 | Multicenter retrospective cohort study |
|
|
| Kusayama, 2019 [27] | Japan | 65 | 67 ± 13 | 32.1 | Retrospective chart review study |
|
|
| Pourafkari, 2017 [25] | United States | 200 | 61 ± 17 | 52.5 | Retrospective observational cohort |
|
|
| Çagdas, 2018 [30] | Turkey | 106 | 60 ± 18 | 50.0 | Retrospective observational cohort |
|
|
| Park, 2017 [18] | South Korea | 89 | 68 ± 15 | 59.5% | Retrospective study |
|
|
| Rodger, 2000 [13] | Canada | 49 | N/A | N/A | Retrospective observational case-control |
|
|
| Bahreini, 2024 [9] | Iran | 250 | 54 ± 19 | 60.0 | Prospective cross-sectional study |
|
|
| Thomson, 2019 [33] | Scotland | 189 | 66 (range 20–93) | 43.4 | Retrospective case-control study |
|
|
| Zhan, 2014 [15] | China | 20 | 58 ± 10 | 40 | Retrospective study |
|
|
| Weekes, 2022 [16] | United States | 1676 | 60 ± 17 | 51.8 | Prospective, observational, multicenter cohort study |
|
|
| Richman, 2004 [29] | United States | 49 | 69 (no SD reported) | NI | Retrospective case-control study |
|
|
| Kukla, 2011 [26] | Poland | 292 | 65 ± 15 | 37.3 | Retrospective study |
|
|
| Novicic, 2020 [32] | Serbia | 110 | 65 ± 13 | 45.5 | Retrospective study |
|
|
| Cetin, 2016 [24] | Turkey | 249 | 66 ± 16 | 33.8 | Prospective study |
|
|
| Obradovic, 2016 [28] | Serbia | 144 | 60 ± 16 | 50 | Ambispective study |
|
|
| Ivan, 2017 [8] | United States | 352 | 68 (range 23-96) | 37.5 | Retrospective study |
|
|
| Casazza, 2018 [23] | Italy | 1194 | 70 ± 16 | 42.8 | Prospective multicenter study |
|
|
| Yan, 2024 [20] | China | 383 | 67 ± 13 | 43 | Prospective observational cohort study |
|
|
| Vanni, 2009 [22] | Italy | 386 | 67 ± 16 | 40 | Prospective study |
|
|
| Bolt, 2019 [21] | Switzerland | 390 | 74 (69–81) 1 | 54 | Prospective multicenter cohort study |
|
|
| Geibel, 2005 [7] | Germany | 508 | 63 ± 15 | 42 | Prospective study |
|
|
| Stein, 2013 [31] | United States | 289 | 61 ± 18 | 44 | Review medical records of hospitalized patients |
|
|
| Witting, 2012 [19] | United States | 97 | 50 ± 15 | NI | Retrospective case-control study |
|
|
| Zhang, 2016 [34] | China | 147 | 56 ± 15 | 41.5 | Retrospective observational cohort |
|
|
1 Data was reported as median (interquartile range). Abbreviations: CT: computed tomography; CTPA: computed tomography pulmonary angiography; ECG: electrocardiogram; ED: emergency department; PE: pulmonary embolism; SD: standard deviation; NI: no information; RBBB: right bundle branch block.
Table 2.
Pathophysiology and electrocardiogram findings in acute pulmonary embolism.
| ECG Finding | Pathophysiology | ECG Characteristics |
|---|---|---|
| S1Q3T3 pattern (Figure 3) | Acute RV strain → altered conduction and repolarization | S wave in lead I, Q wave, and inverted T wave in lead III |
| Right bundle branch block (Figure 3) | RV dilation → delayed right ventricular conduction | RSR’ in V1, wide QRS > 120 ms, terminal S in I and V6 |
| Right axis deviation | RV pressure overload or hypertrophy | QRS axis > +90°, dominant S in I and R in III |
| Sinus tachycardia | Sympathetic activation due to hypoxia, pain, or RV dysfunction | Regular rhythm, HR >100 bpm, normal P waves |
| Atrial fibrillation/Atrial flutter | Atrial strain or ischemia, particularly of the right atrium | Irregularly irregular rhythm (AF); flutter waves with sawtooth pattern (AFL) |
| Low voltage | Pericardial effusion, obesity, or shock state causing diminished signal | QRS < 5 mm in limb leads or <10 mm in precordial leads |
| T-wave inversion in leads V1–V3 (Figure 3) | Subendocardial ischemia of the RV due to pressure overload | Symmetrical T-wave inversion in V1–V3, sometimes extending to V4–V6 |
| Atrial arrhythmia (other) | Right atrial enlargement or hypoxia-related automaticity | Ectopic P waves, PACs, atrial tachycardia |
| Clockwise rotation | RV enlargement causing altered depolarization vectors | R/S transition delayed beyond V4–V5, persistent S waves in V1–V4 |
Abbreviations: AF: Atrial fibrillation; AFL: Atrial flutter; ECG: electrocardiogram; HR: heart rate; PAC: premature atrial contraction; RV: right ventricle.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Krintratun, S.; Srichuachom, W.; Wongtanasarasin, W. Prevalence of Electrocardiographic Abnormalities in Patients with Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis. J. Clin. Med. 2025, 14, 4750. https://doi.org/10.3390/jcm14134750
AMA Style
Krintratun S, Srichuachom W, Wongtanasarasin W. Prevalence of Electrocardiographic Abnormalities in Patients with Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine. 2025; 14(13):4750. https://doi.org/10.3390/jcm14134750
Chicago/Turabian StyleKrintratun, Sarunsorn, Wuttipong Srichuachom, and Wachira Wongtanasarasin. 2025. "Prevalence of Electrocardiographic Abnormalities in Patients with Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis" Journal of Clinical Medicine 14, no. 13: 4750. https://doi.org/10.3390/jcm14134750
APA StyleKrintratun, S., Srichuachom, W., & Wongtanasarasin, W. (2025). Prevalence of Electrocardiographic Abnormalities in Patients with Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine, 14(13), 4750. https://doi.org/10.3390/jcm14134750
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
