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Abstract Risk factors for pacemaker-induced cardiomyopathy (PICM) have been previously reported, including a high burden of right ventricular pacing, lower left ventricular ejection fraction, a wide QRS duration, and left bundle branch block before pacemaker implantation (PMI). However, predicting the development of PICM remains challenging. This study aimed to use a convolutional neural network (CNN) model, based on clinical findings before PMI, to predict the development of PICM. Out of a total of 561 patients with dual-chamber PMI, 165 (mean age 71.6 years, 89 men [53.9%]) who underwent echocardiography both before and after dual-chamber PMI were enrolled. During a mean follow-up period of 1.7 years, 47 patients developed PICM. A CNN algorithm for prediction of the development of PICM was constructed based on a dataset prior to PMI that included 31 variables such as age, sex, body mass index, left ventricular ejection fraction, left ventricular end-diastolic diameter, left ventricular end-systolic diameter, left atrial diameter, severity of mitral regurgitation, severity of tricuspid regurgitation, ischemic heart disease, diabetes mellitus, hypertension, heart failure, New York Heart Association class, atrial fibrillation, the etiology of bradycardia (sick sinus syndrome or atrioventricular block) , right ventricular (RV) lead tip position (apex, septum, left bundle, His bundle, RV outflow tract), left bundle branch block, QRS duration, white blood cell count, haemoglobin, platelet count, serum total protein, albumin, aspartate transaminase, alanine transaminase, estimated glomerular filtration rate, sodium, potassium, C-reactive protein, and brain natriuretic peptide. The accuracy, sensitivity, specificity, and area under the curve of the CNN model were 75.8%, 55.6%, 83.3% and 0.78 respectively. The CNN model could accurately predict the development of PICM using clinical findings before PMI. This model could be useful for screening patients at risk of developing PICM, ensuring timely upgrades to physiological pacing to avoid missing the optimal intervention window.

A 37-year-old man lost consciousness suddenly due to ventricular fibrillation (VF). After cardioversion, twelve-lead ECG showed a pattern characteristic of type 1 Brugada. An implantable cardioverter defibrillator (ICD) was implanted for Brugada syndrome. In the following three years, VF occurred eight times after consumption of alcohol. Association between the Brugada syndrome and alcohol consumption has rarely been reported. Recently, it was reported that alcohol has inhibitory effect on single cardiac sodium channel gating and it may be that alcohol acted as a sodium channel blocker in this patient. Here we report a case of alcohol-induced VF in Brugada syndrome.

During prolonged fasting, fatty acid (FA) released from adipose tissue is a major energy source for peripheral tissues, including the heart, skeletal muscle and liver. We recently showed that FA binding protein 4 (FABP4) and FABP5, which are abundantly expressed in adipocytes and macrophages, are prominently expressed in capillary endothelial cells in the heart and skeletal muscle. In addition, mice deficient for both FABP4 and FABP5 (FABP4/5 DKO mice) exhibited defective uptake of FA with compensatory up-regulation of glucose consumption in these tissues during fasting. Here we showed that deletion of FABP4/5 resulted in a marked perturbation of metabolism in response to prolonged fasting, including hyperketotic hypoglycemia and hepatic steatosis. Blood glucose levels were reduced, whereas the levels of non-esterified FA (NEFA) and ketone bodies were markedly increased during fasting. In addition, the uptake of the (125)I-BMIPP FA analogue in the DKO livers was markedly increased after fasting. Consistent with an increased influx of NEFA into the liver, DKO mice showed marked hepatic steatosis after a 48-hr fast. Although gluconeogenesis was observed shortly after fasting, the substrates for gluconeogenesis were reduced during prolonged fasting, resulting in insufficient gluconeogenesis and enhanced hypoglycemia. These metabolic responses to prolonged fasting in DKO mice were readily reversed by re-feeding. Taken together, these data strongly suggested that a maladaptive response to fasting in DKO mice occurred as a result of an increased influx of NEFA into the liver and pronounced hypoglycemia. Together with our previous study, the metabolic consequence found in the present study is likely to be attributed to an impairment of FA uptake in the heart and skeletal muscle. Thus, our data provided evidence that peripheral uptake of FA via capillary endothelial FABP4/5 is crucial for systemic metabolism and may establish FABP4/5 as potentially novel targets for the modulation of energy homeostasis.