Background: We investigate whether deep learning (DL) neural networks can reduce erroneous human "judgment calls" on bedside echocardiograms and help distinguish Takotsubo syndrome (TTS) from anterior wall ST segment elevation myocardial infarction (STEMI). Methods: We developed a single-channel (DCNN[2D SCI]), a multi-channel (DCNN[2D MCI]), and a 3-dimensional (DCNN[2D+t]) deep convolution neural network, and a recurrent neural network (RNN) based on 17,280 still-frame images and 540 videos from 2-dimensional echocardiograms in 10 years (1 January 2008 to 1 January 2018) retrospective cohort in University of Iowa (UI) and eight other medical centers. Echocardiograms from 450 UI patients were randomly divided into training and testing sets for internal training, testing, and model construction. Echocardiograms of 90 patients from the other medical centers were used for external validation to evaluate the model generalizability. A total of 49 board-certified human readers performed human-side classification on the same echocardiography dataset to compare the diagnostic performance and help data visualization. Findings: The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation. DCNN(2D+t) (area under the curve [AUC] 0¢787 vs. 0¢699, P = 0¢015) and RNN models (AUC 0¢774 vs. 0¢699, P = 0¢033) outperformed human readers in differentiating TTS and STEMI by reducing human erroneous judgement calls on TTS. Interpretation: Spatio-temporal hybrid DL neural networks reduce erroneous human "judgement calls" in distinguishing TTS from anterior wall STEMI based on bedside echocardiographic videos.
Background: Catheter ablation is being increasingly performed for rhythm control of atrial fibrillation (AF). Heart failure (HF) frequently coexists with AF because they share common risk factors. Study Question: This study aims at identifying the characteristics and procedural outcomes of patients with HF undergoing catheter ablation of AF. Study Design: In this retrospective cohort study, we analyzed 264 consecutive patients who underwent catheter ablation for AF. Seventy-three patients (28%) had a known history of stage C HF either with reduced ejection fraction or preserved ejection fraction. Measures and Outcomes: We compared procedural outcomes between patients who had known HF with those who did not. Results: Patients with HF were more likely to have higher rates of atrial fibrillation recurrence at both 3 months (odds ratio 2.9, confidence interval = 1.5–5.7, P = 0.0022) and 1 year after the procedure (odds ratio 2.3, confidence interval 1.2–4.3, P = 0.0097) and risk factors for recurrence of AF including left atrial enlargement, persistent AF, and a higher CHA2DS2-VASc score. However, on logistic regression analysis adjusting for left atrial size, atrial fibrillation type (persistent vs. paroxysmal), and CHA2DS2-VASc score as covariates, there was no significant difference in AF recurrence rates at both 3 months and 1 year. Recurrence rates did not differ significantly between patients with HF either with reduced ejection fraction or preserved ejection fraction. Among patients with paroxysmal AF, HF was predictive of AF recurrence at both 3 months and 1 year after ablation. The procedure length was longer in patients with HF, but there were no differences in periprocedural complications. Conclusion: Patients with HF undergoing catheter ablation of AF tend to have more risk factors for recurrence, but after adjustment for risk factors, the recurrence rates were similar at 3 months and 1 year. Among patients with paroxysmal atrial fibrillation, HF was predictive of higher recurrence rates.
We completed a systematic review of published Takotsubo syndrome (TTS) cases during COVID-19 pandemic and performed clustering and feature importance analysis, and statistical testing for independence on the demographic, clinical and imaging parameters. Compared with the data before the COVID-19 pandemic, TTS was increasingly diagnosed in physical stress (mostly COVID-19 pneumonia)-triggered male patients without psychiatric/neurologic disorders, warranting further investigation to establish new reference criteria to improve diagnostic specificity. In clustering analysis, the gender and in-patient mortality primarily contributed to the automated classification of the TTS. Both the gender and in-patient mortality showed significant correlations with COVID-19 infection/pneumonia. There is effect modification of gender on outcomes in patients with COVID-19 infection and TTS, with male patients having significantly worse inpatient mortality. Meanwhile, significantly more male TTS patients were classified as “high-risk” following InterTAK prognostic scores, suggestive of male COVID-19/TTS survivors will likely have worse long-term outcome.
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