Dataset Information

Neurologist-Led Management of Implantable Loop-Recorders After Embolic Stroke of Undetermined Source.

ABSTRACT:

Introduction

Upon completion of the workup for stroke, etiology cannot be identified in approximately one-third of the patients, with an embolic stroke of undetermined source (ESUS) accounting for around 50% of these cryptogenic etiologies. Whether management of complex long-term monitoring in order to detect suspected atrial fibrillation (AFib) could be initiated and managed through a neurologist is not sufficiently investigated.

Patients and methods

We recruited all consecutive patients with ESUS who received implantation after neurological adjudication of Reveal LINQ^® loop recorder between January 2016 and July 2020. We collected demographic, clinical, heart- and neuroimaging, laboratory, and electrocardiographic data assessed on prolonged baseline ECG monitoring, number of supraventricular (SVEs) and ventricular (VEs) extrasystolic complexes, and from preimplantation ECG-PQ interval. AFib detection was manually supervised and determined positive when the duration was over 120 s.

Results

We followed a total of 131 patients for a median of 504 days. There were 45 (34%) manually verified AFib diagnoses. In univariate analysis, earlier implantation after ESUS was associated with AFib detection (13 vs. 31 days, p = 0.011). In multivariate analysis, increased rate of AFib was associated with a more prolonged PQ interval (per 50-ms increase) (HR 1.99, 95% CI 1.39-2.85) and number of SVEs (HR 1.29, 95% CI 1.05-1.57) measured on pre-implantation ECG.

Conclusion

We observed similar predictors for Afib after ESUS, albeit with higher frequency than previously reported. This study suggests that the neurologist-led decision, management, and evaluation of ILR after ESUS is feasible.

SUBMITTER: Pikija S

PROVIDER: S-EPMC8831881 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Neurologist-Led Management of Implantable Loop-Recorders After Embolic Stroke of Undetermined Source.

Pikija Slaven S Rösler Cornelia C Leitner Ursula U Zellner Thomas T Bubel Nele N Ganser Bernhard B Hecker Constantin C Mutzenbach Johannes Sebastian JS

Frontiers in neurology 20220128

<h4>Introduction</h4>Upon completion of the workup for stroke, etiology cannot be identified in approximately one-third of the patients, with an embolic stroke of undetermined source (ESUS) accounting for around 50% of these cryptogenic etiologies. Whether management of complex long-term monitoring in order to detect suspected atrial fibrillation (AFib) could be initiated and managed through a neurologist is not sufficiently investigated.<h4>Patients and methods</h4>We recruited all consecutive ...[more]

PMID: 35153991

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Project description:AimsStroke is the most debilitating outcome of atrial fibrillation (AF). The use of implantable loop recorders increases the detection of AF episodes among patients with embolic stroke of undetermined source. The significance of device-detected AF, or subclinical AF, is unknown. This study aimed to compare the incidence of AF detected by implantable loop recorder in patients with and without embolic stroke of undetermined source.Methods and resultsWe retrospectively studied all patients without known AF who were referred to our institution for implantable loop recorder implantation following embolic stroke of undetermined source, syncope, or palpitations from March 2009 to November 2019. The primary endpoint was any detection of AF or atrial flutter by implantable loop recorder. Seven hundred and fifty patients were included and followed up for a mean duration of 731 days (SD 443). An implantable loop recorder was implanted following embolic stroke of undetermined source in 323 and for assessment of syncope, palpitations, or another reason in 427 patients. The incidence of AF was significantly (P < 0.001) higher among patients with embolic stroke of undetermined source compared with the non-embolic stroke of undetermined source group; 48.6% vs. 13.8% (for any duration of AF) and 32.2% vs. 12.4% (for AF lasting ≥30 s) both P < 0.001. Kaplan-Meier analysis showed significantly higher incidence of AF for incremental durations of AF up to >5.5 h, but not >24 h. This was driven by longest AF durations of <6 min and between 5.5 h and 24 h, suggesting a bimodal distribution. In a multivariable Cox regression analysis, embolic stroke of undetermined source independently conferred an almost 5-fold increase in the hazard for any duration of AF.ConclusionThe incidence of AF is significantly higher amongst embolic stroke of undetermined source vs. non-embolic stroke of undetermined source patients monitored constantly by an implantable loop recorder. A high number of embolic stroke of undetermined source survivors have short-duration AF episodes. Further work is needed to determine the optimal treatment strategy of these AF episodes in embolic stroke of undetermined source.

Project description:Background and purposeOne-fifth of ischemic strokes are embolic strokes of undetermined source (ESUS). Their theoretical causes can be classified as cardioembolic versus noncardioembolic. This distinction has important implications, but the categories' proportions are unknown.MethodsUsing data from the Cornell Acute Stroke Academic Registry, we trained a machine-learning algorithm to distinguish cardioembolic versus non-cardioembolic strokes, then applied the algorithm to ESUS cases to determine the predicted proportion with an occult cardioembolic source. A panel of neurologists adjudicated stroke etiologies using standard criteria. We trained a machine learning classifier using data on demographics, comorbidities, vitals, laboratory results, and echocardiograms. An ensemble predictive method including L1 regularization, gradient-boosted decision tree ensemble (XGBoost), random forests, and multivariate adaptive splines was used. Random search and cross-validation were used to tune hyperparameters. Model performance was assessed using cross-validation among cases of known etiology. We applied the final algorithm to an independent set of ESUS cases to determine the predicted mechanism (cardioembolic or not). To assess our classifier's validity, we correlated the predicted probability of a cardioembolic source with the eventual post-ESUS diagnosis of atrial fibrillation.ResultsAmong 1083 strokes with known etiologies, our classifier distinguished cardioembolic versus noncardioembolic cases with excellent accuracy (area under the curve, 0.85). Applied to 580 ESUS cases, the classifier predicted that 44% (95% credibility interval, 39%-49%) resulted from cardiac embolism. Individual ESUS patients' predicted likelihood of cardiac embolism was associated with eventual atrial fibrillation detection (OR per 10% increase, 1.27 [95% CI, 1.03-1.57]; c-statistic, 0.68 [95% CI, 0.58-0.78]). ESUS patients with high predicted probability of cardiac embolism were older and had more coronary and peripheral vascular disease, lower ejection fractions, larger left atria, lower blood pressures, and higher creatinine levels.ConclusionsA machine learning estimator that distinguished known cardioembolic versus noncardioembolic strokes indirectly estimated that 44% of ESUS cases were cardioembolic.

Dataset Information

Neurologist-Led Management of Implantable Loop-Recorders After Embolic Stroke of Undetermined Source.

Introduction

Patients and methods

Results

Conclusion

Publications

Neurologist-Led Management of Implantable Loop-Recorders After Embolic Stroke of Undetermined Source.

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