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Simplified tool for predicting pacemaker implantation in patients with bradycardic syncope undergoing implantable loop recorder monitoring: the PREDICT-PPM score
Session:
SESSÃO DE POSTERS 55 - ARRITMOLOGIA: NOVOS DESAFIOS
Speaker:
João Gouveia Fiuza
Congress:
CPC 2025
Topic:
C. Arrhythmias and Device Therapy
Theme:
07. Syncope and Bradycardia
Subtheme:
07.3 Syncope and Bradycardia - Diagnostic Methods
Session Type:
Cartazes
FP Number:
---
Authors:
João Gouveia Fiuza; Gonçalo RM Ferreira; Mariana Duarte Almeida; Francisco Rodrigues Santos; Oliver Kungel; Vanda Devesa Neto; João Miguel Santos; Júlio Gil Pereira; António Costa
Abstract
<p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong>Introduction: </strong>Implantable loop recorders (ILR) are a valuable tool for investigating unexplained syncope. Identifying clinical predictors for permanent pacemaker implantation (PPMi) can enhance patient selection, improve resource utilization, and potentially prevent unnecessary interventions. </span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong>Purpose: </strong>To create a simplified score to predict PPMi in patients with suspected bradycardic syncope undergoing ILR monitoring.</span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong>Methods: </strong>Retrospective study of 119 patients that underwent ILR implantation for suspected bradycardic syncope. Baseline characteristics, symptoms and electrocardiographic parameters were analyzed. Chi-square and Mann-Whitney U were used for comparison between groups. A multivariate logistic regression analysis was performed to identify independent predictors of PPMi. To create PREDICT-PPM score, we assigned points to each variable based on the logistic regression analysis. The natural logarithm of the OR was calculated for each variable, providing a proportional representation of the variable's contribution to the outcome. For simplicity, these weights were then rounded to the nearest whole number. Each variable was assigned points proportional its contribution to the outcome. </span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong>Results:</strong> Mean age was 62±17 years; 60.5% were women. After ILR placement, 17.6% of patients underwent PPMi. </span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif">We found that patients with second degree Mobitz I conduction abnormality (p<0.001), first-degree AV block (p=0.024), sinus pauses (p<0.005), abnormal baseline electrocardiogram (sinus bradycardia, AV conduction, intraventricular conduction or repolarization abnormalities) (p=0.01), abnormal 24-hour Holter monitoring (non-significant pauses or significant burden of premature contractions) (p<0.005), typical symptoms (p<0.001) and fall with associated trauma (p<0.001) had more PPMi. </span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif">Logistic regression identified independent predictors. Two points were assigned to fall with trauma and two points to typical complaints (OR 4.89, p=0.01 and OR 7.45, p<0.001, respectively). First-degree AV block was assigned 1.5 points, reflecting its moderate contribution to the prediction of PPMi (OR 4.58, p=0.06). </span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif">Using ROC curve analysis, we obtained an AUC of 0.846 (p < 0.001). The optimal cutoff score of 2.75 achieved a sensitivity of 66.7% and a specificity of 90.5% (Youden’s Index = 0.572). Patients were then classified as high or low risk. High risk group was significantly associated with PPMi (60.9% vs 7.5%, χ² = 35.39, p < 0.01).</span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong>Conclusion:</strong> The PREDICT-PPM score predicts PPMi in patients with suspected bradycardic syncope undergoing ILR monitoring. Given its high specificity, it has potential to identify patients with low risk, potentially reducing unnecessary procedures and improving cost-effectiveness. Future prospective studies with larger cohorts are needed to validate this scoring system and confirm its impact on clinical outcomes.</span></span></p>
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