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A. Basics
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01. History of Cardiology
02. Clinical Skills
03. Imaging
04. Arrhythmias, General
05. Atrial Fibrillation
06. Supraventricular Tachycardia (non-AF)
07. Syncope and Bradycardia
08. Ventricular Arrhythmias and Sudden Cardiac Death (SCD)
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32. Cardiovascular Nursing
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From Syncope to Pacemaker: Evaluating PREDICT-PPM, DROP, and EGSYS Scores in ILR-Monitored Patients with Suspected Bradycardia
Session:
Sessão de Posters 09 - Síncope, ILR e cardioneuromodulação
Speaker:
João Gouveia Fiuza
Congress:
CPC 2026
Topic:
C. Arrhythmias and Device Therapy
Theme:
07. Syncope and Bradycardia
Subtheme:
07.2 Syncope and Bradycardia - Epidemiology, Prognosis, Outcome
Session Type:
Posters Eletrónicos
FP Number:
---
Authors:
João Gouveia Fiuza; Mariana Duarte Almeida; Francisco Rodrigues dos Santos; Oliver Kungel; Luís Afonso Santos; Gonçalo RM Ferreira; João Miguel Santos; Júlio Gil; António Costa
Abstract
<p style="text-align:justify"><strong>Introduction: </strong>Implantable loop recorders (ILR) are recommended to investigate unexplained syncope of suspected bradycardic origin. While several risk scores exist for syncope evaluation, their performance in predicting permanent pacemaker implantation (PPMi) in this specific population remains unclear. The PREDICT-PPM score was recently developed locally for this purpose, while DROP and EGSYS scores are widely used.</p> <p style="text-align:justify"><strong>Purpose:</strong> To compare the performance of PREDICT-PPM, DROP, and EGSYS scores in predicting pacemaker implantation after ILR in patients with unexplained suspected bradycardic syncope.</p> <p style="text-align:justify"><strong>Methods:</strong> Retrospective study of 119 consecutive patients who underwent ILR implantation for unexplained suspected bradycardic syncope. PREDICT-PPM, DROP and EGSYS scores were calculated at baseline. The primary outcome was PPMi during ILR monitoring. Chi-square and Mann-Whitney U tests were used for group comparisons. Discrimination for PPM implantation was assessed with ROC curve analysis.</p> <p style="text-align:justify"><strong>Results: </strong>Mean age 62±17 years; 60.5% were women. PPMi occurred in 17.6% (n=21). Median follow-up was 25.5 months. All patients without PPMi had a minimum follow-up of 1-year.<br /> PREDICT PPM score showed good discrimination (AUC 0.844, p<0.001). Patients with PREDICT-PPM ≥2.75 had significantly higher PPMi (60.9% vs 7.5%; x²=35.39, p<0.001).<br /> DROP score showed moderate discrimination (AUC 0.753, p<0.001). Risk stratification showed excellent gradient: low risk (<2 points, n=67) had 14.9% PPMi rate; intermediate risk (2 points, n=18) had 27.8%; and high risk (≥3 points, n=7) had 85.7% PPMi rate (x²=18.34, p<0.001).<br /> EGSYS score demonstrated modest discrimination (AUC 0.630, p=0.054). Patients with EGSYS ≥1.5 had higher PPMi rate (30.4% vs 6.8%; x²=10.70, p<0.001), although the standard classification (<3 vs ≥3) showed no significant difference (p=0.21).<br /> When comparing the three scores, PREDICT-PPM showed numerically higher AUC compared to DROP (0.844 vs 0.753) and EGSYS (0.844 vs 0.630). The scores demonstrated complementary performance profiles: PREDICT-PPM with high specificity (90.1%), EGSYS with high sensitivity (81.0%), and DROP with balanced characteristics.</p> <p style="text-align:justify"><strong>Conclusion:</strong> In patients with suspected bradycardic syncope undergoing ILR monitoring, all scores demonstrated discriminative ability for PPMi, with PREDICT-PPM showing the highest AUC. These findings support further external validation and highlight complementary roles that may aid clinical decision-making.<br /> </p>
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