Evaluating Clinician Sub-speciality in the Use of Implantable Loop Recorders for Patients with Unexplained Syncope: A Pilot Study
Description
This study investigated whether clinician sub-specialty influences the diagnostic yield or time to diagnosis of implantable loop recorders (ILRs) in adults undergoing investigation for unexplained syncope. We hypothesised that diagnostic outcomes may differ between patients referred by electrophysiologists and general cardiologists. We also investigated whether patient characteristics, particularly age, were associated with ILR outcomes. This dataset comprises a retrospective single-centre cohort of 85 adults who underwent ILR implantation at Flinders Medical Centre, South Australia, between January 2021 and February 2025. Patients were identified from ILR implantation records and included if they were aged 18 years or above, and had unexplained syncope likely to be cardiogenic. Clinical, referral and ILR outcome data were retrospectively extracted from medical records. Patients were categorised according to whether the ILR was referred/prescribed by a cardiologist (n=34) or electrophysiologist (n=51). The primary outcome was detection of a clinically significant arrhythmia during ILR monitoring. Time to diagnosis was a secondary outcome measured from ILR implantation to detection of a clinically significant arrhythmia. Patients without an arrhythmia during available follow-up were treated as censored observations for time-to-event analysis. Diagnostic yield was assessed using logistic regression, while time to diagnosis was assessed using Cox proportional hazards regression. A clinically significant arrhythmia was detected in 23/85 patients (27.1%). Diagnostic yield did not differ significantly between cardiologist-referred patients (8/34, 23.5%) and electrophysiologist-referred patients (15/51, 29.4%; p=0.550). There was also no statistically significant difference in time to diagnosis between the cardiologist and electrophysiologist groups (1126.97 vs 961.41 days; p=0.174). Increasing patient age was independently associated with greater diagnostic yield (OR 1.034 per year; p=0.036) and shorter time to diagnosis (HR 1.029 per year; p=0.044). This may reflect the greater prevalence of clinically significant conduction disease or arrhythmia in older patients. Overall, the findings provide no evidence that clinician sub-specialty significantly influences ILR diagnostic yield or time to diagnosis in this cohort. The dataset is intended to support reproducibility and secondary analysis of ILR outcomes in unexplained syncope. Users should account for the retrospective, single-centre design, relatively small sample size, potential referral and selection bias, missing data and censoring when interpreting or reanalysing the data. Secondary outcomes may have smaller sample sizes where outcome data were unavailable.
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Steps to reproduce
Identify all patients who underwent implantable loop recorder (ILR) implantation at Flinders Medical Centre between January 2021 and February 2025. A total of 199 patients received an ILR during this period. Identify the subgroup who received an ILR specifically for investigation of unexplained syncope (n=143). Apply the predefined inclusion criteria: adults with unexplained arrhythmic syncope based on clinical assessment in accordance with the 2018 European Society of Cardiology Guidelines, deemed to require an ILR, and undergoing ILR implantation at Flinders Medical Centre. Exclude patients with known structural heart disease or an identified alternative cause of syncope. Exclude patients with incomplete outcome data, including patients whose follow-up occurred with a physician outside Flinders Medical Centre or who failed to attend follow-up. This resulted in the final analytical cohort of 85 patients. Retrieve clinical and follow-up information from physical medical records and the SA Health Statewide Electronic Medical Record and Patient Administration System (Sunrise EMR & PAS). Categorise patients according to referring clinician type: cardiology specialist or electrophysiology specialist. The primary outcome is detection of a clinically significant arrhythmia, defined as an arrhythmia detected during ILR interrogation that was associated with a syncopal episode or considered by the treating physician to be the likely cause of syncope. Calculate diagnostic yield as the proportion of patients with a clinically significant arrhythmia. Record secondary outcomes including time to arrhythmia diagnosis (days), arrhythmia type, pacemaker implantation and complications. Summarise continuous variables using mean ± standard deviation or median (interquartile range), and categorical variables using frequencies and percentages. Assess categorical associations using chi-square tests. Perform binary logistic regression to assess factors associated with arrhythmia detection, adjusting for patient age. Analyse time to diagnosis using Kaplan–Meier survival analysis and Cox proportional hazards regression, adjusting for patient age. Follow-up is measured from ILR implantation until arrhythmia detection or censoring. Report odds ratios and hazard ratios with 95% confidence intervals; p<0.05 is considered statistically significant. The original analysis identified clinically significant arrhythmia in 23/85 patients (27.1%). No statistically significant difference in diagnostic yield was observed between cardiologist- and electrophysiologist-referred patients. Increasing age was associated with both higher diagnostic yield and shorter time to diagnosis.
Institutions
- Flinders UniversitySouth Australia, Adelaide