Dataset Information

The value of transesophageal echocardiography for embolic strokes of undetermined source.

ABSTRACT:

Objective

Our aim was to evaluate the diagnostic yield of transesophageal echocardiography (TEE) in consecutive patients with ischemic stroke (IS) fulfilling the diagnostic criteria of embolic strokes of undetermined source (ESUS).

Methods

We prospectively evaluated consecutive patients with acute IS satisfying ESUS criteria who underwent in-hospital TEE examination in 3 tertiary care stroke centers during a 12-month period. We also performed a systematic review and meta-analysis estimating the cumulative effect of TEE findings on therapeutic management for secondary stroke prevention among different IS subgroups.

Results

We identified 61 patients with ESUS who underwent investigation with TEE (mean age 44 ± 12 years, 49% men, median NIH Stroke Scale score = 5 points [interquartile range: 3-8]). TEE revealed additional findings in 52% (95% confidence interval [CI]: 40%-65%) of the study population. TEE findings changed management (initiation of anticoagulation therapy, administration of IV antibiotic therapy, and patent foramen ovale closure) in 10 (16% [95% CI: 9%-28%]) patients. The pooled rate of reported anticoagulation therapy attributed to abnormal TEE findings among 3,562 acute IS patients included in the meta-analysis (12 studies) was 8.7% (95% CI: 7.3%-10.4%). In subgroup analysis, the rates of initiation of anticoagulation therapy on the basis of TEE investigation did not differ (p = 0.315) among patients with cryptogenic stroke (6.9% [95% CI: 4.9%-9.6%]), ESUS (8.1% [95% CI: 3.4%-18.1%]), and IS (9.4% [95% CI: 7.5%-11.8%]).

Conclusions

Abnormal TEE findings may decisively affect the selection of appropriate therapeutic strategy in approximately 1 of 7 patients with ESUS.

SUBMITTER: Katsanos AH

PROVIDER: S-EPMC5027807 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Publications

The value of transesophageal echocardiography for embolic strokes of undetermined source.

Katsanos Aristeidis H AH Bhole Rohini R Frogoudaki Alexandra A Giannopoulos Sotirios S Goyal Nitin N Vrettou Agathi-Rosa AR Ikonomidis Ignatios I Paraskevaidis Ioannis I Pappas Konstantinos K Parissis John J Kyritsis Athanassios P AP Alexandrov Anne W AW Triantafyllou Nikos N Malkoff Marc D MD Voumvourakis Konstantinos K Alexandrov Andrei V AV Tsivgoulis Georgios G

Neurology 20160803 10

<h4>Objective</h4>Our aim was to evaluate the diagnostic yield of transesophageal echocardiography (TEE) in consecutive patients with ischemic stroke (IS) fulfilling the diagnostic criteria of embolic strokes of undetermined source (ESUS).<h4>Methods</h4>We prospectively evaluated consecutive patients with acute IS satisfying ESUS criteria who underwent in-hospital TEE examination in 3 tertiary care stroke centers during a 12-month period. We also performed a systematic review and meta-analysis ...[more]

PMID: 27488602

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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

The value of transesophageal echocardiography for embolic strokes of undetermined source.

Objective

Methods

Results

Conclusions

Publications

The value of transesophageal echocardiography for embolic strokes of undetermined source.

Similar Datasets

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