Electrocardiographic signs to differentiate between chronic thromboembolic pulmonary hypertension and acute pulmonary embolism

Electrocardiographic signs to differentiate between chronic thromboembolic pulmonary hypertension and acute pulmonary embolism | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Electrocardiographic signs to differentiate between chronic thromboembolic pulmonary hypertension and acute pulmonary embolism Marcin Waligóra, Klaudia Zaczyńska, Jakub Stępniewski, Emilia Lis, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6239391/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Background: Acute pulmonary embolism (APE) and chronic thromboembolic pulmonary hypertension (CTEPH) both cause dyspnoea and right ventricular (RV) overload, but require different management. Electrocardiography (ECG) is widely available, yet its role in distinguishing APE from CTEPH remains underexplored.. Aim: To identify ECG parameters differentiating APE from CTEPH and develop a predictive mode. Methods: We included 184 patients: those hospitalized with intermediate-high-risk APE and patients with confirmed CTEPH. ECG parameters were analyzed using logistic regression. A predictive equation and simplified scoring model (CTEPH ECG SCORE) were developed and validated. Results: CTEPH patients showed higher rates of right axis deviation (RAD), qR pattern in V1, increased precordial ECG voltage, and prolonged P-wave duration. APE patients had higher heart rates, more frequent right bundle branch blocks, and greater T-wave inversions (TWI). The CTEPH ECG SCORE distinguished CTEPH from APE with high accuracy (AUC = 0.95). CTEPH ECG SCORE = 0.5 + (4 × RAD) + (0.5 × Sokolow-Lyon index) – (3 × HR >100) – (0.5 × TWI range). Conclusions: ECG can serve as a valuable tool for distinguishing CTEPH from APE. Health sciences/Cardiology Health sciences/Medical research Health sciences/Signs and symptoms/Respiratory signs and symptoms Pulmonary Embolism Hypertension Pulmonary Electrocardiography Right Ventricular Dysfunction Figures Figure 1 Figure 2 Figure 3 Introduction Acute pulmonary embolism (APE) is the sudden blockage of one or more pulmonary arteries caused by blood clots, typically originating from deep vein thrombosis. Treatment includes anticoagulation, thrombolysis in severe cases, and surgical or catheter-directed thrombectomy in life-threatening situations[1]. In some patients, the clots fail to dissolve completely, leading to chronic thromboembolic pulmonary hypertension (CTEPH), a condition characterized by persistent pulmonary hypertension due to unresolved thrombi. The primary treatment for CTEPH is pulmonary endarterectomy, while inoperable cases are managed with balloon pulmonary angioplasty[2,3], and, in selected patients, targeted pulmonary hypertension medications. Both conditions share dyspnoea as a key symptom; however, in CTEPH, dyspnoea is typically chronic and exercise-induced, whereas in APE, it is more acute and often occurs at rest. In some cases, acute or subacute dyspnoea may be the initial presentation of both APE and acutely decompensated CTEPH,. Differentiating between APE and CTEPH is critical, as their management strategies are distinct and tailored to their underlying pathophysiology[4]. While the European Society of Cardiology guidelines highlight the potential role of CT angiography in distinguishing CTEPH from APE[5], this approach requires specialized expertise, and no standardized clinical pathway currently exists. On the other hand, electrocardiography (ECG) is readily available in every emergency department, yet its diagnostic role is often overlooked. This might be due to a lack of data supporting its usefulness in differentiating acute (APE) from chronic (CTEPH) right ventricular (RV) overload. To address this gap, our study aimed to compare ECG patterns in APE and CTEPH to aid physicians in distinguishing between these two manifestations of venous thromboembolic disease. Methods 2.1. Patients and group assignment For this study, we selected consecutive patients with intermediate-high-risk APE who were hospitalized at our centre between 1 January 2018 and 30 May 2024. We focused on this subset of patients with APE because they are often considered for urgent reperfusion therapies [1,6–10], such as fibrinolysis, surgical embolectomy, or percutaneous embolectomy. As these interventions are ineffective in the context of chronic pulmonary vascular diseases such as CTEPH differentiation between APE and CTEPH is especially important [11–13]. The APE cohort was divided into a derivation cohort (patients diagnosed before 1 October 2023) and a validation cohort (patients diagnosed between 1 October 2023 and 30 May 2024). Each group was set to contain an equal number of patients and was limited by the number of available CTEPH cases. As a comparator we used ECGs from patients with CTEPH who were consecutively diagnosed at our centre between January 2015 and May 2024. The study protocol was developed in accordance with the European Society of Cardiology (ESC) guidelines and approved by the Jagiellonian University Ethics Committee (No. 122.6120.237.2015), followed by the Bioethical Committee of the Physicians and Dentists Chamber in Kraków, Poland (No. 186/KBL/OIL/2017). Informed consent was obtained from all participants and/or their legal guardians. The study was conducted in compliance with the principles of the Declaration of Helsinki. 2.2. ECG analysis A standard 12‑lead surface electrocardiogram (10 mm = 1 mV, 25 mm/s) was recorded in a supine position at patient’s first presentation to our department. Among various ECG parameters linked to RV pathology, we selected those previously reported as clinically significant and associated with prognosis in patients with PE or pulmonary hypertension. The following parameters were analysed: · Rhythm parameters: o sinus tachycardia (>100 bpm) [14,15], o P-wave duration and amplitude [16], o atrial fibrillation[17], · Electrical axis deviation: o right axis deviation (RAD) (>90 degrees) [18–20], · QRS complex characteristics: o qR pattern in lead V 1 : defined as the presence of a q wave of ≥0.2 mV and a ventricular depolarization duration of <120 ms [16,21,22], o QRS fragmentation: R-wave notch or S-wave notch in lead V 1 [18,23,24], o incomplete or complete right bundle branch block (RBBB): incomplete RBBB is defined as a QRS duration between 110 and 120 ms, and complete RBBB, as a QRS duration >120 ms[25,26], o QRS duration (ms) [17,26,27], o precordial ECG voltage (Sokolow-Lyon index for RV hypertrophy [RVH]): sum of the R wave in lead V 1 and the maximum depth of the S wave in leads V 5 or V 6 [28], o R wave amplitude in V 1 [29], · Repolarization patterns: o T wave inversions (TWI) in precordial leads: extent of TWI across precordial leads, quantified as 0 (no TWI) to 6 (TWI from V 1 to V 6 ) [14,15,30–33]; o TWI in inferior wall leads: II, III, aVF [26], o ST-segment changes: ST-segment elevations or depressions [31,34,35]; ST-segment ischemic pattern defined as either ST-segment elevation in at least one of leads III, aVR, and V 1 through V 4 , or ST-segment depression in at least two lateral leads (I, aVL, V 4 through V 6 ) [31]. · Daniel’s score for PE: a 21-point ECG scoring system for PE based on sinus tachycardia (2 points), incomplete RBBB (2 points), complete RBBB (3 points), T-wave inversion in leads V 1 through V 4 (0 to 12 points), S wave in lead I (0), Q wave in lead III (1 points), inverted T in lead III (1 points), and entire SIQIIITIII pattern [36], 2.3. Statistical analysis Categorical variables were presented as counts and percentages, and continuous variables as medians (IQRs). The Shapiro–Wilk test was used to assess normality. Group comparisons were performed using the Mann–Whitney U test for continuous variables and the χ 2 or Fisher exact test for categorical variables. In case of small group (n ≤5) comparison, Yates correction was applied. A P value of less than 0.05 was considered statistically significant. To differentiate patients with APE from those with CTEPH, ECG parameters were first compared between the two groups to identify variables with significant differences. These variables ( P <0.05) were then entered in a multivariate logistic regression model using forward stepwise selection. The probability of CTEPH (P CTEPH ) was calculated using the following equation derived from the coefficients of the multivariate logistic regression model: where CTEPH score represents the linear combination of the independent predictors identified in the multivariate logistic regression model and is calculated as: CTEPH score = constant + B1 x Factor1 + B2 x Factor2 + …. . The coefficients were derived from the multivariate logistic regression analysis and reflect each predictor’s contribution to the final score. The resulting probability was expressed as a percentage, indicating the likelihood that a patient has CTEPH. The sensitivity and specificity of the model were determined using receiver operating characteristic (ROC) curve analysis, which identified the optimal cut-off value for the CTEPH score . For clinical simplicity, the constants from the CTEPH score equation were rounded to the nearest 0.5, resulting in a simplified equation that we called CTEPH ECG SCORE. CTEPH ECG SCOREwas then tested via ROC analysis, and its area under the ROC curve (AUC) difference from the original model was assessed to verify whether it differed significantly in terms of performance. To validate the robustness and generalizability of the predictive model, we applied a nonparametric bootstrapping. A total of 1000 random resamples were computed from the derivation cohort (n = 142) with replacement, and the AUC was calculated for each iteration. All statistical analyses were performed using Dell Statistica, version 13.3 (TIBCO Software Inc., Palo Alto, California, United States) and MedCalc, version 19.2.6 (MedCalc Software, Ostend, Belgium). Results 3.1. Patients The study included 184 patients: 71 with CTEPH and 113 with APE. The derivation APE cohort consisted of the first 71 consecutive patients and the validation cohort of the subsequent 42 patients with this condition. No differences were observed between the derivation and validation cohorts in terms of clinical or ECG parameters (Supplementary Tables 1 and 2). The detailed clinical characteristics of patients with CTEPH and the derivation APE cohort are presented in Table 1. 3.2. Comparison of ECG parameters in APE and CTEPH Patients with APE compared to those with CTEPH demonstrated a higher heart rate, higher occurrence of incomplete or complete RBBB, and higher prevalence of sinus tachycardia. Additionally, TWI in precordial leads, particularly in leads V 1 through V 3 , were more frequent in that cohort. In contrast, patients with CTEPH more often had RAD, qR patterns in lead V 1 , higher precordial ECG voltage, increased P-wave amplitude and duration, and P waves greater than 2.5 mm. Detailed comparisons are presented in Table 2. 3.3. CTEPH probability equation Parameters that differed between APE and CTEPH were then tested using stepwise logistic regression to predict diagnosis of CTEPH. The analysis identified presence of RAD and precordial ECG voltage >10.5 mm as independent predictors that increased probability of CTEPH, with odds ratios (OR) of 21 (95%, CI 8.4–56) and 12.5 (95%, CI 5–31.1), respectively. Conversely, heart rate exceeding 100 bpm (OR, 0.05), extent of TWI in precordial leads (as continuous number of leads) (OR, 0.75; 95% CI, 0.64–0.89) were associated with a decreased probability of CTEPH. The detailed results are presented in Table 3. Based on multivariate analysis (Table 3 and Fig. 1) we built the following probability equation for CTEPH: CTEPH score = 0.3482 + (-3.64 if heart rate >100 bpm) + (-0.44 x precordial TWI range) + (4.05 if RAD) + (2.06 if Sokolow-Lyon index for RVH). Higher scores corresponded to an increased probability of CTEPH. Using this model, the mean (SD) probability of CTEPH was 17.8% (23.5%) in the APE baseline group and 83.7% (22.8%) in the CTEPH group ( P <0.0001 as compared to both APE groups). The optimal cut-off threshold for distinguishing between APE and CTEPH was established at CTEPH score of -0.52 with a sensitivity of 94.4% and specificity of 84.5% (AUC, 0.953; 95% CI, 0.91–0.982; P <0.0001). This threshold indicated that CTEPH should be considered when the estimated probability based on the score was ≥37.3%. Classification using this cut-off resulted in 84.5% of patients in the APE group and 94.4% in the CTEPH group being correctly categorized. However, 11 patients with APE had ECG suggesting CTEPH, while 4 patients with confirmed CTEPH had ECG suggesting of APE. 3.4. Simplified scoring system: CTEPH ECG SCORE To improve the clinical practicality of the CTEPH probability model, we simplified the equation by rounding the coefficients to the nearest 0.5. This resulted in a user-friendly scoring system, referred to as the SCORE equation, calculated as follows: CTEPH ECG SCORE = 0.5 + (4 x RAD) + (0.5 x Sokolow-Lyon index for RVH) – (3 x heart rate >100 ) - (0.5 x TWI range in precordial leads) The optimal cut-off threshold for the CTEPH ECG SCORE was set at ≥0, yielding a specificity of 84.5% and sensitivity of 94.4% in the baseline cohort. The AUC for the CTEPH ECG SCORE was 0.95 (95% CI, 0.89–0.98; P <0.0001), with no significant difference compared to the original CTEPH score model (AUC difference, 0.0002; P = 0.86). The negative predictive value for excluding CTEPH using the simplified SCORE was 93.75% (95% CI, 85.21%–97.5%). The results of the ROC analysis are depicted in Figure 2. The simplified SCORE is presented in Table 4. Values of zero or above indicate a higher probability of CTEPH, while negative values suggest a possible diagnosis of APE. 3.5. Internal validation — model validation using bootstrapping To assess the robustness and reliability of the CTEPH predictive model, bootstrapping was performed within initial 142 patients with 1000 resamples from the derivation cohort. The mean AUC across all bootstrapped samples was 0.945 (95% CI, 0.941–0.954), demonstrating high and consistent discriminatory performance of the model. The distribution of bootstrapped AUC values is shown in Figure 3. 3.6. CTEPH ECG SCORE performance in the validation cohort In the validation APE cohort, mean (SD) probability of PE calculated from the score was 83.5% (20.7%), with a mean (SD) simplified score of -2.33 (1.85) (range, -6 to 2.5). In this cohort, the SCORE equation correctly excluded CTEPH in 88.1% of cases (37 out of 42 patients), while 11.9% required further assessment beyond the CTEPH ECG SCORE alone. Discussion In the present study, we propose an ECG-based model to aid in distinguishing between patients with dyspnoea who, during the diagnostic workup, may be suspected of having APE or CTEPH. Our findings demonstrate that several ECG patterns traditionally associated with PE are also frequently observed in CTEPH, challenging previous assumptions about their specificity. The study highlights key ECG features that can help differentiate between acute and chronic RV overload. 4.1. Common ECG patterns in APE and CTEPH In our study, we found several ECG patterns commonly associated with APE in patients with CTEPH. For example, the SIQIIITIII pattern, often considered a hallmark of APE, was equally prevalent in patients with CTEPH. This observation is consistent with previous studies suggesting that SIQIIITIII reflects RV dilation rather than a process specific to acute embolism [37–39]. Our results indicate that this pattern is a marker of RV strain, which can occur in both acute and chronic settings, thus limiting its diagnostic specificity. Another notable finding was the higher prevalence of the qR pattern in lead V 1 among patients with CTEPH compared to those with APE. Defined as a prominent Q wave of ≥0.2 mV with a ventricular depolarization duration of <120 ms [21,22], this pattern may be attributed to severe interventricular septal shift and chronic RV dilation, both of which are characteristic of pulmonary hypertension. These findings highlight the importance of considering the chronicity of RV strain when interpreting ECG findings. Notably, tachycardia was more more specific in APE as opposed to CTEPH. Notably unjustified treatment for tachycardia, which is a result of underlying RV uncoupling, is common[40] and results in worse outcome in RV impairing conditions[41]. 4.2. RAD and RV overload RAD was one of the strongest predictors of CTEPH in our study, corroborating findings from previous research [18–20]. RAD primarily results from an increase in RV mass, which shifts the depolarization vector rightward. In the context of APE, RAD may be observed in patients with significant RV strain leading to a higher risk of mortality. However, in CTEPH, RAD is more consistently present due to chronic pressure overload and hypertrophy, making it a potential marker for identifying chronic pulmonary vascular disease. 4.3. ECG markers of RV hypertrophy in CTEPH Timely identification of patients with potential CTEPH is crucial for accurate diagnosis and appropriate management. Several studies have explored the association between ECG markers and CTEPH. Klok et al identified a combination of ECG features as a useful predictor of CTEPH. These included rSR’ or RSr’ patterns in lead V 1 , an R:S ratio greater than 1 in V 1 with an R wave exceeding 0.5 mV, and a QRS axis greater than 90°. Their model reached a sensitivity of 94%; however, a specificity of only 65% was achieved [42]. In the present study, RAD and signs of RVH proved to be more reliable predictors, whereas the presence of RBBBs was found to be less informative. Our focus on ECG markers in patients with intermediate-high-risk PE is particularly relevant in clinical practice, where rapid decisions regarding reperfusion therapies, such as thrombolysis or embolectomy, must be made. Since these interventions are generally ineffective in patients with underlying chronic pulmonary vascular disease, early differentiation between APE and CTEPH is essential to ensure appropriate management strategies [5]. 4.4. Differentiating RV hypertrophy from dilatation One of the key challenges in ECG interpretation is distinguishing between RVH and RV dilatation. This distinction is clinically significant, as RVH results from increased muscle mass due to chronic pressure overload, whereas RV dilatation reflects chamber enlargement caused by volume overload. Both conditions can present with overlapping ECG features, including RAD, TWI, and signs of RV strain[14,21,30]. In CTEPH, prolonged pressure overload leads to both RV hypertrophy and dilatation, further complicating the interpretation of ECG findings. Our study highlights this limitation, suggesting that while ECG can serve as a valuable initial screening tool, it may not be sufficient to fully differentiate between these conditions without additional imaging or hemodynamic assessments. 4.5. Strengths and limitations The strengths of our study lie in its practicality and accessibility. Since ECG is a routine and readily available diagnostic tool, the proposed predictive model can be easily implemented in various clinical settings. Another strength is the high diagnostic performance and simplified approach of our CTEPH ECG SCORE model. The robustness of the model was further validated internally through a bootstrapping validation process and externally in a validation cohort of patients with PE. Despite these strengths, the study has certain limitations. One key limitation is the absence of a validation cohort of patients with CTEPH, meaning that only a cohort of patients with PE was used to validate the model’s ability to exclude CTEPH. Additionally, the study focuses exclusively on ECG parameters and does not incorporate other diagnostic tools or biomarkers, which could potentially enhance the accuracy of diagnostic workup of CTEPH. Conclusion The present study demonstrates that ECG can be a valuable tool in differentiating CTEPH from APE. The CTEPH ECG SCORE equation exhibits high accuracy in differentiating between these two conditions, making it a practical addition to existing diagnostic approaches. Declarations Acknowledgements: We sincerely appreciate the language assistance provided by Małgorzata Kurowska ( [email protected] ) Competing interests: The authors declare no competing interests. Data Availability: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Funding: This work was supported by the Research Grant of the Jagiellonian University Medical College [grant number N41/DBS/001378]. References Pruszczyk P, Kopeć G. Catheter directed therapies: an option for elderly frail patients with pulmonary embolism requiring reperfusion. EuroIntervention 2023;19:708–9. https://doi.org/10.4244/EIJ-E-23-00047. Lang IM, Andreassen AK, Andersen A, Bouvaist H, Coghlan G, Escribano-Subias P, et al. Balloon pulmonary angioplasty for chronic thromboembolic pulmonary hypertension: a clinical consensus statement of the ESC working group on pulmonary circulation and right ventricular function. 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The role of ST-segment elevation in lead aVR in the risk assessment of patients with acute pulmonary embolism. Clin Res Cardiol 2012;101:329–37. https://doi.org/10.1007/S00392-011-0395-Z. Daniel KR, Courtney DM, Kline JA. Assessment of cardiac stress from massive pulmonary embolism with 12-lead ECG. Chest 2001;120:474–81. https://doi.org/10.1378/CHEST.120.2.474. Shopp JD, Stewart LK, Emmett TW, Kline JA. Findings From 12-lead Electrocardiography That Predict Circulatory Shock From Pulmonary Embolism: Systematic Review and Meta-analysis. Acad Emerg Med 2015;22:1127–37. https://doi.org/10.1111/ACEM.12769. Ley L, Höltgen R, Bogossian H, Ghofrani HA, Bandorski D. Electrocardiogram in patients with pulmonary hypertension. J Electrocardiol 2023;79:24–9. https://doi.org/10.1016/J.JELECTROCARD.2023.02.007. Lewczuk J, Ajlan AW, Piszko P, Jagas J, Mikulewicz M, Wrabec K. Electrocardiographic signs of right ventricular overload in patients who underwent pulmonary embolism event(s). Are they useful in diagnosis of chronic thromboembolic pulmonary hypertension? J Electrocardiol 2004;37:219–25. https://doi.org/10.1016/j.jelectrocard.2004.04.003. Kopeć G, Kurzyna M, Mroczek E, Chrzanowski Ł, Mularek-kubzdela T, Skoczylas I, et al. Characterization of Patients with Pulmonary Arterial Hypertension: Data from the Polish Registry of Pulmonary Hypertension (BNP-PL). J Clin Med 2020;9. https://doi.org/10.3390/JCM9010173. Waligóra M, Kurzyna M, Mularek-Kubzdela T, Skoczylas I, Chrzanowski Ł, Błaszczak P, et al. Effects of β-Blockers on the Outcomes in Patients With Pulmonary Arterial Hypertension Stratified by the Presence of Comorbid Conditions: A Multicenter Prospective Cohort Study (BNP-PL). Chest 2024. https://doi.org/10.1016/J.CHEST.2024.10.051. Klok FA, Surie S, Kempf T, Eikenboom J, Van Straalen JP, Van Kralingen KW, et al. A simple non-invasive diagnostic algorithm for ruling out chronic thromboembolic pulmonary hypertension in patients after acute pulmonary embolism. Thromb Res 2011;128:21–6. https://doi.org/10.1016/J.THROMRES.2011.03.004. Tables Tables are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files 20250317tables.docx 20250218suppl.docx Cite Share Download PDF Status: Published Journal Publication published 25 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 06 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviews received at journal 26 Feb, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviewers agreed at journal 25 Feb, 2026 Reviewers invited by journal 25 Feb, 2026 Editor assigned by journal 04 Jul, 2025 Editor invited by journal 19 Mar, 2025 Submission checks completed at journal 18 Mar, 2025 First submitted to journal 16 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6239391","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":597536691,"identity":"a450b045-60f5-4246-bdf0-538f7d558fc2","order_by":0,"name":"Marcin Waligóra","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Marcin","middleName":"","lastName":"Waligóra","suffix":""},{"id":597536697,"identity":"228b4c0a-3390-4ee9-9182-35015d92f650","order_by":1,"name":"Klaudia Zaczyńska","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Klaudia","middleName":"","lastName":"Zaczyńska","suffix":""},{"id":597536709,"identity":"e001441c-93ab-4965-b3ef-95893efc848b","order_by":2,"name":"Jakub Stępniewski","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Jakub","middleName":"","lastName":"Stępniewski","suffix":""},{"id":597536713,"identity":"4daec628-2d12-4617-bfd9-2f46205ead05","order_by":3,"name":"Emilia Lis","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Emilia","middleName":"","lastName":"Lis","suffix":""},{"id":597536723,"identity":"cf7dbc98-4c90-4a8a-abe6-043cf3091265","order_by":4,"name":"Julia Hypnar","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Hypnar","suffix":""},{"id":597536726,"identity":"7857d228-6774-49b8-83d5-8aec6703bf8b","order_by":5,"name":"Wojciech Magoń","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Wojciech","middleName":"","lastName":"Magoń","suffix":""},{"id":597536729,"identity":"54cc1bf3-6dc1-42da-8595-4df540eebac8","order_by":6,"name":"Kamil Jonas","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Kamil","middleName":"","lastName":"Jonas","suffix":""},{"id":597536732,"identity":"f93632a2-29fa-4f58-82ae-3dc8d04f81ce","order_by":7,"name":"Barbara Wziątek","email":"","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Wziątek","suffix":""},{"id":597536735,"identity":"63fcb1dc-818d-498e-acba-a437059ae5d4","order_by":8,"name":"Grzegorz Kopeć","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYDADCQYGZhAlB+IceECCFgtjsJYEErRUJDaAePi0yEcff/jwS8U9e8nZhx8bfGyTSJ8fdvgh0BY7Od0G7FoMzyUkG8ucKWaW5kszTpzZJpG78XaaAVBLsrHZARxaehiOSUu2JbDJ8TAYH+bdBtQyOwGk5UDiNpxaGNt/A7XwyPGwfwZpSTecnf4BrxZ5HmY2xo9tCRLSPDzGyUAtCfLSOfhtMeBhY5ZmOJNgINnDU2w485+E4QbpnIIDCQa4/SLfw/7w44+KBHuJM+ybJT6cqZOXn52++cOHCjs5XFoMgOLMPOgiQBK7crAtDQwMjD/QRUbBKBgFo2AUIAMAAWharSpDhbMAAAAASUVORK5CYII=","orcid":"","institution":"Jagiellonian University Medical College","correspondingAuthor":true,"prefix":"","firstName":"Grzegorz","middleName":"","lastName":"Kopeć","suffix":""}],"badges":[],"createdAt":"2025-03-16 20:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6239391/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6239391/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-48092-3","type":"published","date":"2026-04-25T15:58:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":103733843,"identity":"a0c49867-37fd-46b8-9a35-8dc0e25dd5be","added_by":"auto","created_at":"2026-03-02 09:29:45","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1518526,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot illustrating the odds ratios (OR) with 95% CI for factors distinguishing CTEPH from APE in a multivariate logistic regression model. Positive OR values (right of the vertical dashed line at OR = 1) favour the diagnosis of CTEPH, while negative OR values (left of the line) favour APE.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6239391/v1/127dd8b597c6ae36c4888a26.jpg"},{"id":103733849,"identity":"ed50272c-1f32-459d-b24f-3cf7b76a667f","added_by":"auto","created_at":"2026-03-02 09:29:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1838809,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic curves for our CTEPH\u003csub\u003escore\u003c/sub\u003e (panel A) and simplified version: CTEPH ECG SCORE (panel B). Negative predictive value for both scores was 93.75% (95% CI, 85.21%–97.5%). A: The optimal cut-off threshold was established at score level of -0.52 with a sensitivity of 94.4% (95% CI, 84.76%–98.27%) and a specificity of 84.5% (95% CI, 76.17%–82.74%). Area under the ROC curve (AUC) was 0.953 (95% CI 0.91–0.982, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.0001). B: The optimal cut-off threshold was established at score level of \u0026gt;-0,5 with a sensitivity of 94.37% and specificity of 84.1%, AUC 0.954 (95% CI, 0.905–0.982, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.0001). No differences between the original score and simplified score were observed (AUC difference of 0.0002, \u003cem\u003eP\u003c/em\u003e = 0.86).\u0026nbsp;\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6239391/v1/62111bd187b6d496975ef0a1.jpg"},{"id":103733852,"identity":"8a250c6c-6e1e-4df7-ad05-a8f7a715a4bf","added_by":"auto","created_at":"2026-03-02 09:29:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1994041,"visible":true,"origin":"","legend":"\u003cp\u003eBootstrapped distribution of the area under the receiver operating characteristic curve (AUC) for the CTEPH ECG SCORE model. The histogram depicts AUC values derived from 1000 bootstrapped resamples of the initial cohort comprising 71 patients with acute pulmonary embolism and 71 patients with chronic thromboembolic pulmonary hypertension.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6239391/v1/479396151ad3d993d5b4264e.jpg"},{"id":107927771,"identity":"b0f61f6c-283d-46e1-bd30-88aac62339e4","added_by":"auto","created_at":"2026-04-27 16:04:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5579249,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6239391/v1/ad92d112-9366-4850-a6f7-d42ee2d37803.pdf"},{"id":103733833,"identity":"1785bdfb-592e-45ed-b012-94e196d69c67","added_by":"auto","created_at":"2026-03-02 09:29:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2208207,"visible":true,"origin":"","legend":"","description":"","filename":"20250317tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6239391/v1/ac93c1be1ec2f2dfdf96463f.docx"},{"id":103733850,"identity":"c132e775-3e5c-44ae-92a3-af48b9bf01e1","added_by":"auto","created_at":"2026-03-02 09:29:46","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2504771,"visible":true,"origin":"","legend":"","description":"","filename":"20250218suppl.docx","url":"https://assets-eu.researchsquare.com/files/rs-6239391/v1/0694911a021b265faf34aff9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electrocardiographic signs to differentiate between chronic thromboembolic pulmonary hypertension and acute pulmonary embolism","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute pulmonary embolism (APE) is the sudden blockage of one or more pulmonary arteries caused by blood clots, typically originating from deep vein thrombosis. Treatment includes anticoagulation, thrombolysis in severe cases, and surgical or catheter-directed thrombectomy in life-threatening situations[1].\u003c/p\u003e\n\u003cp\u003eIn some patients, the clots fail to dissolve completely, leading to chronic thromboembolic pulmonary hypertension (CTEPH), a condition characterized by persistent pulmonary hypertension due to unresolved thrombi. The primary treatment for CTEPH is pulmonary endarterectomy, while inoperable cases are managed with balloon pulmonary angioplasty[2,3], and, in selected patients, targeted pulmonary hypertension medications.\u003c/p\u003e\n\u003cp\u003eBoth conditions share dyspnoea as a key symptom; however, in CTEPH, dyspnoea is typically chronic and exercise-induced, whereas in APE, it is more acute and often occurs at rest. In some cases, acute or subacute dyspnoea may be the initial presentation of both APE and acutely decompensated CTEPH,.\u003c/p\u003e\n\u003cp\u003eDifferentiating between APE and CTEPH is critical, as their management strategies are distinct and tailored to their underlying pathophysiology[4]. While the European Society of Cardiology guidelines highlight the potential role of CT angiography in distinguishing CTEPH from APE[5], this approach requires specialized expertise, and no standardized clinical pathway currently exists. On the other hand, electrocardiography (ECG) is readily available in every emergency department, yet its diagnostic role is often overlooked. This might be due to a lack of data supporting its usefulness in differentiating acute (APE) from chronic (CTEPH) right ventricular (RV) overload. To address this gap, our study aimed to compare ECG patterns in APE and CTEPH to aid physicians in distinguishing between these two manifestations of venous thromboembolic disease.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1. Patients and group assignment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor this study, we selected consecutive patients with intermediate-high-risk APE who were hospitalized at our centre between 1 January 2018 and 30 May 2024. We focused on this subset of patients with APE because they are often considered for urgent reperfusion therapies [1,6\u0026ndash;10], such as fibrinolysis, surgical embolectomy, or percutaneous embolectomy. As these interventions are ineffective in the context of chronic pulmonary vascular diseases such as CTEPH differentiation between APE and CTEPH is especially important [11\u0026ndash;13].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe APE cohort was divided into a derivation cohort (patients diagnosed before 1 October 2023) and a validation cohort (patients diagnosed between 1 October 2023 and 30 May 2024). Each group was set to contain an equal number of patients and was limited by the number of available CTEPH cases.\u003c/p\u003e\n\u003cp\u003eAs a comparator we used ECGs from patients with CTEPH who were consecutively diagnosed at our centre between January 2015 and May 2024.\u003c/p\u003e\n\u003cp\u003eThe study protocol was developed in accordance with the European Society of Cardiology (ESC) guidelines and approved by the Jagiellonian University Ethics Committee (No. 122.6120.237.2015), followed by the Bioethical Committee of the Physicians and Dentists Chamber in Krak\u0026oacute;w, Poland (No. 186/KBL/OIL/2017). Informed consent was obtained from all participants and/or their legal guardians. The study was conducted in compliance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e2.2. ECG analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA standard 12‑lead surface electrocardiogram (10 mm = 1 mV, 25 mm/s) was recorded in a supine position at patient\u0026rsquo;s first presentation to our department.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong various ECG parameters linked to RV pathology, we selected those previously reported as clinically significant and associated with prognosis in patients with PE or pulmonary hypertension. The following parameters were analysed:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Rhythm parameters:\u003c/p\u003e\n\u003cp\u003eo sinus tachycardia (\u0026gt;100 bpm)\u0026nbsp;[14,15],\u003c/p\u003e\n\u003cp\u003eo P-wave duration and amplitude\u0026nbsp;[16],\u003c/p\u003e\n\u003cp\u003eo atrial fibrillation[17],\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Electrical axis deviation:\u003c/p\u003e\n\u003cp\u003eo right axis deviation (RAD) (\u0026gt;90 degrees)\u0026nbsp;[18\u0026ndash;20],\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; QRS complex characteristics:\u003c/p\u003e\n\u003cp\u003eo qR pattern in lead V\u003csub\u003e1\u003c/sub\u003e:\u0026nbsp;defined as the presence of a q wave of \u0026ge;0.2 mV and a ventricular depolarization duration of \u0026lt;120 ms\u0026nbsp;[16,21,22],\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo QRS fragmentation: R-wave notch or S-wave notch in lead V\u003csub\u003e1\u003c/sub\u003e [18,23,24],\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo incomplete or complete right bundle branch block (RBBB): incomplete RBBB is defined as a QRS duration between 110 and 120 ms, and complete RBBB, as a QRS duration \u0026gt;120 ms[25,26],\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo QRS duration (ms)\u0026nbsp;[17,26,27],\u003c/p\u003e\n\u003cp\u003eo precordial ECG voltage (Sokolow-Lyon index for RV hypertrophy [RVH]): sum of the R wave in lead V\u003csub\u003e1\u003c/sub\u003e and the maximum depth of the S wave in leads V\u003csub\u003e5\u003c/sub\u003e or V\u003csub\u003e6\u003c/sub\u003e [28],\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo R wave amplitude in V\u003csub\u003e1\u003c/sub\u003e [29],\u003c/p\u003e\n\u003cp\u003e\u0026middot; Repolarization patterns:\u003c/p\u003e\n\u003cp\u003eo T wave inversions (TWI) in precordial leads: extent of TWI across precordial leads, quantified as 0 (no TWI) to 6 (TWI from V\u003csub\u003e1\u003c/sub\u003e to V\u003csub\u003e6\u003c/sub\u003e)\u0026nbsp;[14,15,30\u0026ndash;33];\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo TWI in inferior wall leads: II, III, aVF\u0026nbsp;[26],\u003c/p\u003e\n\u003cp\u003eo ST-segment changes: ST-segment elevations or depressions\u0026nbsp;[31,34,35]; ST-segment ischemic pattern defined as either ST-segment elevation in at least one of leads III, aVR, and V\u003csub\u003e1\u003c/sub\u003e through V\u003csub\u003e4\u003c/sub\u003e, or ST-segment depression in at least two lateral leads (I, aVL, V\u003csub\u003e4\u003c/sub\u003e through V\u003csub\u003e6\u003c/sub\u003e)\u0026nbsp;[31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Daniel\u0026rsquo;s score for PE: a 21-point ECG scoring system for PE based on sinus tachycardia (2 points), incomplete RBBB (2 points), complete RBBB (3 points), T-wave inversion in leads V\u003csub\u003e1\u003c/sub\u003e through V\u003csub\u003e4\u003c/sub\u003e (0 to 12 points), S wave in lead I (0), Q wave in lead III (1 points), inverted T in lead III (1 points), and entire SIQIIITIII pattern\u0026nbsp;[36],\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCategorical variables were presented as counts and percentages, and continuous variables as medians (IQRs). The Shapiro\u0026ndash;Wilk test was used to assess normality. Group comparisons were performed using the Mann\u0026ndash;Whitney U test for continuous variables and the \u0026chi;\u003csup\u003e2\u003c/sup\u003e or Fisher exact test for categorical variables. In case of small group (n \u0026le;5) comparison, Yates \u0026nbsp;correction was applied. A \u003cem\u003eP\u003c/em\u003e value of less than 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eTo differentiate patients with APE from those with CTEPH, ECG parameters were first compared between the two groups to identify variables with significant differences. These variables (\u003cem\u003eP\u003c/em\u003e \u0026lt;0.05) were then entered in a multivariate logistic regression model using forward stepwise selection.\u003c/p\u003e\n\u003cp\u003eThe probability of CTEPH (P\u003csub\u003eCTEPH\u003c/sub\u003e) was calculated using the following equation derived from the coefficients of the multivariate logistic regression model:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere CTEPH\u003csub\u003escore\u003c/sub\u003e represents the linear combination of the independent predictors identified in the multivariate logistic regression model and is calculated as:\u003c/p\u003e\n\u003cp\u003eCTEPH\u003csub\u003escore\u003c/sub\u003e = constant + B1 x Factor1 + B2 x Factor2 + \u0026hellip;. .\u003c/p\u003e\n\u003cp\u003eThe coefficients were derived from the multivariate logistic regression analysis and reflect each predictor\u0026rsquo;s contribution to the final score. The resulting probability was expressed as a percentage, indicating the likelihood that a patient has CTEPH.\u003c/p\u003e\n\u003cp\u003eThe sensitivity and specificity of the model were determined using receiver operating characteristic (ROC) curve analysis, which identified the optimal cut-off value for the CTEPH\u003csub\u003escore\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eFor clinical simplicity, the constants from the CTEPH\u003csub\u003escore\u003c/sub\u003e equation were rounded to the nearest 0.5, resulting in a simplified equation that we called CTEPH ECG SCORE. CTEPH ECG SCOREwas then tested via ROC analysis, and its area under the ROC curve (AUC) difference from the original model was assessed to verify whether it differed significantly in terms of performance.\u003c/p\u003e\n\u003cp\u003eTo validate the robustness and generalizability of the predictive model, we applied a nonparametric bootstrapping. A total of 1000 random resamples were computed from the derivation cohort (n = 142) with replacement, and the AUC was calculated for each iteration.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using Dell Statistica, version 13.3 (TIBCO Software Inc., Palo Alto, California, United States) and MedCalc, version 19.2.6 (MedCalc Software, Ostend, Belgium).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e3.1. Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 184 patients: 71 with CTEPH and 113 with APE. The derivation APE cohort consisted of the first 71 consecutive patients and the validation cohort of the subsequent 42 patients with this condition. No differences were observed between the derivation and validation cohorts in terms of clinical or ECG parameters (Supplementary Tables 1 and 2). The detailed clinical characteristics of patients with CTEPH and the derivation APE cohort are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Comparison of ECG parameters in APE and CTEPH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients with APE compared to those with CTEPH demonstrated a higher heart rate, higher occurrence of incomplete or complete RBBB, and higher prevalence of sinus tachycardia. Additionally, \u0026nbsp;TWI in precordial leads, particularly in leads V\u003csub\u003e1\u003c/sub\u003e through V\u003csub\u003e3\u003c/sub\u003e, were more frequent in that cohort.\u003c/p\u003e\n\u003cp\u003eIn contrast, patients with CTEPH more often had RAD, qR patterns in lead V\u003csub\u003e1\u003c/sub\u003e, higher precordial ECG voltage, increased P-wave amplitude and duration, and P waves greater than 2.5 mm. Detailed comparisons are presented in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. CTEPH probability equation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParameters that differed between APE and CTEPH were then tested using stepwise logistic regression to predict diagnosis of CTEPH. The analysis identified presence of RAD and precordial ECG voltage\u0026nbsp;\u0026gt;10.5 mm\u0026nbsp;as independent predictors that increased probability of CTEPH, with odds ratios (OR) of 21 (95%, CI 8.4\u0026ndash;56) and 12.5 (95%, CI 5\u0026ndash;31.1), respectively. Conversely, heart rate exceeding 100 bpm (OR, 0.05), extent of TWI in precordial leads (as continuous number of leads) \u0026nbsp;(OR, 0.75; 95% CI, 0.64\u0026ndash;0.89) were associated with a decreased probability of CTEPH. The detailed results are presented in Table 3.\u003c/p\u003e\n\u003cp\u003eBased on multivariate analysis (Table 3 and Fig. 1) we built\u0026nbsp;the\u0026nbsp;following probability equation for CTEPH:\u003c/p\u003e\n\u003cp\u003eCTEPH\u003csub\u003escore\u003c/sub\u003e = 0.3482 + (-3.64 if heart rate \u0026gt;100 bpm) + (-0.44 x precordial TWI range) + (4.05 if RAD) + (2.06 if\u0026nbsp;Sokolow-Lyon index for RVH).\u003c/p\u003e\n\u003cp\u003eHigher scores corresponded to an increased probability of CTEPH. Using this model, the mean (SD) probability of CTEPH was 17.8% (23.5%) in the APE baseline group and 83.7% (22.8%) in the CTEPH group (\u003cem\u003eP\u003c/em\u003e \u0026lt;0.0001 as compared to both APE groups). The optimal cut-off threshold for distinguishing between APE and CTEPH was established at CTEPH\u003csub\u003escore\u003c/sub\u003e of -0.52 with a sensitivity of 94.4% and specificity of 84.5% (AUC, 0.953; 95% CI, 0.91\u0026ndash;0.982; \u003cem\u003eP\u003c/em\u003e \u0026lt;0.0001). This threshold indicated that CTEPH should be considered when the estimated probability based on the score was \u0026ge;37.3%.\u003c/p\u003e\n\u003cp\u003eClassification using this cut-off resulted\u0026nbsp;in 84.5% of patients in the APE group and 94.4% in the CTEPH group being correctly categorized. However, 11 patients with APE had ECG suggesting CTEPH, while 4 patients with confirmed CTEPH had ECG suggesting of APE.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Simplified\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003escoring system: CTEPH ECG SCORE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo improve the clinical practicality of the CTEPH probability model, we simplified the equation by rounding the coefficients to the nearest 0.5. This resulted in a user-friendly scoring system, referred to as the SCORE equation, calculated as follows:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCTEPH ECG SCORE = 0.5 + (4 x RAD) + (0.5 x Sokolow-Lyon index for RVH) \u0026ndash; (3 x heart rate \u0026gt;100 ) - (0.5 x TWI range in precordial leads)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe optimal cut-off threshold for the CTEPH ECG SCORE was set at \u0026ge;0, yielding a specificity of 84.5% and sensitivity of 94.4% in the baseline cohort. The AUC for the CTEPH ECG SCORE was 0.95 (95% CI, 0.89\u0026ndash;0.98; \u003cem\u003eP\u003c/em\u003e \u0026lt;0.0001), with no significant difference compared to the original\u0026nbsp;CTEPH\u003csub\u003escore\u003c/sub\u003e model (AUC difference, 0.0002; \u003cem\u003eP\u003c/em\u003e = 0.86). The negative predictive value for excluding CTEPH using the simplified SCORE was 93.75% (95% CI, 85.21%\u0026ndash;97.5%). The results of the ROC analysis are depicted in Figure 2. The simplified SCORE is presented in Table 4. Values of zero or above indicate a higher probability of CTEPH, while negative values suggest a possible diagnosis of APE.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.\u0026nbsp;Internal validation \u0026mdash; model validation using bootstrapping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the robustness and reliability of the CTEPH predictive model, bootstrapping was performed within initial 142 patients with 1000 resamples from the derivation cohort. The mean AUC across all bootstrapped samples was 0.945 (95% CI, 0.941\u0026ndash;0.954), demonstrating high and consistent discriminatory performance of the model. The distribution of bootstrapped AUC values is shown in Figure 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6. CTEPH ECG SCORE performance in the validation cohort\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the validation APE cohort, mean (SD) probability of PE calculated from the score was 83.5% (20.7%), with a mean (SD) simplified score of -2.33 (1.85) (range, -6 to 2.5). In this cohort, the SCORE equation correctly excluded CTEPH in 88.1% of cases (37 out of 42 patients), while 11.9% required further assessment beyond the CTEPH ECG SCORE alone.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we propose an ECG-based model to aid in distinguishing between patients with dyspnoea who, during the diagnostic workup, may be suspected of having APE or CTEPH. Our findings demonstrate that several ECG patterns traditionally associated with PE are also frequently observed in CTEPH, challenging previous assumptions about their specificity. The study highlights key ECG features that can help differentiate between acute and chronic RV overload.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.\u0026nbsp;Common ECG patterns in APE and CTEPH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our study, we found several ECG patterns commonly associated with APE in patients with CTEPH. For example, the SIQIIITIII pattern, often considered a hallmark of APE, was equally prevalent in patients with CTEPH. This observation is consistent with previous studies suggesting that SIQIIITIII reflects RV dilation rather than a process specific to acute embolism [37\u0026ndash;39]. Our results indicate that this pattern is a marker of RV strain, which can occur in both acute and chronic settings, thus limiting its diagnostic specificity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother notable finding was the higher prevalence of the qR pattern in lead V\u003csub\u003e1\u003c/sub\u003e among patients with CTEPH compared to those with APE. Defined as a prominent Q wave of \u0026ge;0.2 mV with a ventricular depolarization duration of \u0026lt;120 ms [21,22], this pattern may be attributed to severe interventricular septal shift and chronic RV dilation, both of which are characteristic of pulmonary hypertension. These findings highlight the importance of considering the chronicity of RV strain when interpreting ECG findings. Notably, tachycardia was more more specific in APE as opposed to CTEPH. Notably unjustified treatment for tachycardia, which is a result of underlying RV uncoupling, is common[40] and results in worse outcome in RV impairing conditions[41].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2.\u0026nbsp;RAD and RV overload\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRAD was one of the strongest predictors of CTEPH in our study, corroborating findings from previous research [18\u0026ndash;20]. RAD primarily results from an increase in RV mass, which shifts the depolarization vector rightward. In the context of APE, RAD may be observed in patients with significant RV strain leading to a higher risk of mortality. However, in CTEPH, RAD is more consistently present due to chronic pressure overload and hypertrophy, making it a potential marker for identifying chronic pulmonary vascular disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3.\u0026nbsp;ECG markers of RV hypertrophy in CTEPH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTimely identification of patients with potential CTEPH is crucial for accurate diagnosis and appropriate management. Several studies have explored the association between ECG markers and CTEPH. Klok et al identified a combination of ECG features as a useful predictor of CTEPH. These included rSR\u0026rsquo; or RSr\u0026rsquo; patterns in lead V\u003csub\u003e1\u003c/sub\u003e, an R:S ratio greater than 1 in V\u003csub\u003e1\u003c/sub\u003e with an R wave exceeding 0.5 mV, and a QRS axis greater than 90\u0026deg;. Their model reached a sensitivity of 94%; however, a specificity of only 65% was achieved [42]. In the present study, RAD and signs of RVH proved to be more reliable predictors, whereas the presence of RBBBs was found to be less informative.\u003c/p\u003e\n\u003cp\u003eOur focus on ECG markers in patients with intermediate-high-risk PE is particularly relevant in clinical practice, where rapid decisions regarding reperfusion therapies, such as thrombolysis or embolectomy, must be made. Since these interventions are generally ineffective in patients with underlying chronic pulmonary vascular disease, early differentiation between APE and CTEPH is essential to ensure appropriate management strategies [5].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4.\u0026nbsp;Differentiating RV hypertrophy from dilatation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne of the key challenges in ECG interpretation is distinguishing between RVH and RV dilatation. This distinction is clinically significant, as RVH results from increased muscle mass due to chronic pressure overload, whereas RV dilatation reflects chamber enlargement caused by volume overload. Both conditions can present with overlapping ECG features, including RAD, TWI, and signs of RV strain[14,21,30].\u003c/p\u003e\n\u003cp\u003eIn CTEPH, prolonged pressure overload leads to both RV hypertrophy and dilatation, further complicating the interpretation of ECG findings. Our study highlights this limitation, suggesting that while ECG can serve as a valuable initial screening tool, it may not be sufficient to fully differentiate between these conditions without additional imaging or hemodynamic assessments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5.\u0026nbsp;Strengths and limitations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe strengths of our study lie in its practicality and accessibility. Since ECG is a routine and readily available diagnostic tool, the proposed predictive model can be easily implemented in various clinical settings. Another strength is the high diagnostic performance and simplified approach of our CTEPH ECG SCORE model. The robustness of the model was further validated internally through a bootstrapping validation process and externally in a validation cohort of patients with PE.\u003c/p\u003e\n\u003cp\u003eDespite these strengths, the study has certain limitations. One key limitation is the absence of a validation cohort of patients with CTEPH, meaning that only a cohort of patients with PE was used to validate the model\u0026rsquo;s ability to exclude CTEPH. Additionally, the study focuses exclusively on ECG parameters and does not incorporate other diagnostic tools or biomarkers, which could potentially enhance the accuracy of diagnostic workup of CTEPH.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present study demonstrates that ECG can be a valuable tool in differentiating CTEPH from APE. The CTEPH ECG SCORE equation exhibits high accuracy in differentiating between these two conditions, making it a practical addition to existing diagnostic approaches.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e We sincerely appreciate the language assistance provided by Małgorzata Kurowska ([email protected])\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u0026nbsp; This work was supported by the Research Grant of the Jagiellonian University Medical College [grant number N41/DBS/001378].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePruszczyk P, Kopeć G. 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Pol Arch Intern Med 2019;129:451\u0026ndash;9. https://doi.org/10.20452/PAMW.14877.\u003c/li\u003e\n\u003cli\u003eKucher N, Walpoth N, Wustmann K, Noveanu M, Gertsch M. QR in V1--an ECG sign associated with right ventricular strain and adverse clinical outcome in pulmonary embolism. Eur Heart J 2003;24:1113\u0026ndash;9. https://doi.org/10.1016/S0195-668X(03)00132-5.\u003c/li\u003e\n\u003cli\u003eWalig\u0026oacute;ra M, Kopeć G, Jonas K, Tyrka A, Sarnecka A, Miszalski-Jamka T, et al. Mechanism and prognostic role of qR in V1 in patients with pulmonary arterial hypertension. J Electrocardiol 2017;50:476\u0026ndash;83. https://doi.org/10.1016/j.jelectrocard.2017.02.007.\u003c/li\u003e\n\u003cli\u003eQaddoura A, Digby GC, Kabali C, Kukla P, Tse G, Glover B, et al. Use of fragmented QRS in prognosticating clinical deterioration and mortality in pulmonary embolism: A meta-analysis. 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American Journal of Cardiology 1999;84:677\u0026ndash;81. https://doi.org/10.1016/S0002-9149(99)00415-4.\u003c/li\u003e\n\u003cli\u003eWalig\u0026oacute;ra M, Tyrka A, Podolec P, Kopeć G. ECG Markers of Hemodynamic Improvement in Patients with Pulmonary Hypertension. Biomed Res Int 2018;2018. https://doi.org/10.1155/2018/4606053.\u003c/li\u003e\n\u003cli\u003eKukla P, McIntyre WF, Fijorek K, Długopolski R, Mirek-Bryniarska E, Bryniarski KL, et al. T-wave inversion in patients with acute pulmonary embolism: prognostic value. Heart Lung 2015;44:68\u0026ndash;71. https://doi.org/10.1016/J.HRTLNG.2014.10.003.\u003c/li\u003e\n\u003cli\u003eKukla P, McIntyre WF, Fijorek K, Krupa E, Mirek-Bryniarska E, Jastrzębski M, et al. Use of ischemic ECG patterns for risk stratification in intermediate-risk patients with acute PE. 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Acad Emerg Med 2015;22:1127\u0026ndash;37. https://doi.org/10.1111/ACEM.12769.\u003c/li\u003e\n\u003cli\u003eLey L, H\u0026ouml;ltgen R, Bogossian H, Ghofrani HA, Bandorski D. Electrocardiogram in patients with pulmonary hypertension. J Electrocardiol 2023;79:24\u0026ndash;9. https://doi.org/10.1016/J.JELECTROCARD.2023.02.007.\u003c/li\u003e\n\u003cli\u003eLewczuk J, Ajlan AW, Piszko P, Jagas J, Mikulewicz M, Wrabec K. Electrocardiographic signs of right ventricular overload in patients who underwent pulmonary embolism event(s). Are they useful in diagnosis of chronic thromboembolic pulmonary hypertension? J Electrocardiol 2004;37:219\u0026ndash;25. https://doi.org/10.1016/j.jelectrocard.2004.04.003.\u003c/li\u003e\n\u003cli\u003eKopeć G, Kurzyna M, Mroczek E, Chrzanowski Ł, Mularek-kubzdela T, Skoczylas I, et al. Characterization of Patients with Pulmonary Arterial Hypertension: Data from the Polish Registry of Pulmonary Hypertension (BNP-PL). J Clin Med 2020;9. https://doi.org/10.3390/JCM9010173.\u003c/li\u003e\n\u003cli\u003eWalig\u0026oacute;ra M, Kurzyna M, Mularek-Kubzdela T, Skoczylas I, Chrzanowski Ł, Błaszczak P, et al. Effects of \u0026beta;-Blockers on the Outcomes in Patients With Pulmonary Arterial Hypertension Stratified by the Presence of Comorbid Conditions: A Multicenter Prospective Cohort Study (BNP-PL). Chest 2024. https://doi.org/10.1016/J.CHEST.2024.10.051.\u003c/li\u003e\n\u003cli\u003eKlok FA, Surie S, Kempf T, Eikenboom J, Van Straalen JP, Van Kralingen KW, et al. A simple non-invasive diagnostic algorithm for ruling out chronic thromboembolic pulmonary hypertension in patients after acute pulmonary embolism. Thromb Res 2011;128:21\u0026ndash;6. https://doi.org/10.1016/J.THROMRES.2011.03.004.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pulmonary Embolism, Hypertension, Pulmonary, Electrocardiography, Right Ventricular Dysfunction","lastPublishedDoi":"10.21203/rs.3.rs-6239391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6239391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Acute pulmonary embolism (APE) and chronic thromboembolic pulmonary hypertension (CTEPH) both cause dyspnoea and right ventricular (RV) overload, but require different management. Electrocardiography (ECG) is widely available, yet its role in distinguishing APE from CTEPH remains underexplored..\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim:\u003c/strong\u003e To identify ECG parameters differentiating APE from CTEPH and develop a predictive mode.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We included 184 patients: those hospitalized with intermediate-high-risk APE and patients with confirmed CTEPH. ECG parameters were analyzed using logistic regression. A predictive equation and simplified scoring model (CTEPH ECG SCORE) were developed and validated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e CTEPH patients showed higher rates of right axis deviation (RAD), qR pattern in V1, increased precordial ECG voltage, and prolonged P-wave duration. APE patients had higher heart rates, more frequent right bundle branch blocks, and greater T-wave inversions (TWI). The CTEPH ECG SCORE distinguished CTEPH from APE with high accuracy (AUC = 0.95).\u003c/p\u003e\n\u003cp\u003eCTEPH ECG SCORE = 0.5 + (4 × RAD) + (0.5 × Sokolow-Lyon index) – (3 × HR \u0026gt;100) – (0.5 × TWI range).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eECG can serve as a valuable tool for distinguishing CTEPH from APE.\u003c/p\u003e","manuscriptTitle":"Electrocardiographic signs to differentiate between chronic thromboembolic pulmonary hypertension and acute pulmonary embolism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 09:29:30","doi":"10.21203/rs.3.rs-6239391/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-06T10:14:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T20:15:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76420453235750605218876786310776824398","date":"2026-02-27T16:05:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170885982774973740652682448779981884892","date":"2026-02-27T07:31:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-26T12:08:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48802402822162648144005291422839077581","date":"2026-02-26T10:29:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189256839898740493077650305126509531969","date":"2026-02-25T16:16:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-25T14:31:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-04T13:22:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-19T05:56:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-18T08:49:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-16T20:35:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c264fe4e-5805-40fe-9eef-16f0251a79e4","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":63586619,"name":"Health sciences/Cardiology"},{"id":63586621,"name":"Health sciences/Medical research"},{"id":63586623,"name":"Health sciences/Signs and symptoms/Respiratory signs and symptoms"}],"tags":[],"updatedAt":"2026-04-27T16:02:03+00:00","versionOfRecord":{"articleIdentity":"rs-6239391","link":"https://doi.org/10.1038/s41598-026-48092-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-04-25 15:58:44","publishedOnDateReadable":"April 25th, 2026"},"versionCreatedAt":"2026-03-02 09:29:30","video":"","vorDoi":"10.1038/s41598-026-48092-3","vorDoiUrl":"https://doi.org/10.1038/s41598-026-48092-3","workflowStages":[]},"version":"v1","identity":"rs-6239391","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6239391","identity":"rs-6239391","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}