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Cardiac alterations are frequently observed after acute neurological disorders. Takotsubo syndrome (TTS) represents an acute heart failure syndrome and is increasingly recognized as part of the spectrum of cardiac complications observed after neurological disorders. A systematic investigation of TTS patients with neurological disorders has not been conducted yet. The aim of the study was to expand insights regarding neurological disease entities triggering TTS and to investigate the clinical profile and outcomes of TTS patients after primary neurological disorders. The International Takotsubo Registry is an observational multicenter collaborative effort of 45 centers in 14 countries (ClinicalTrials.gov, identifier NCT01947621). All patients in the registry fulfilled International Takotsubo Diagnostic Criteria. For the present study, patients were included if complete information on acute neurological disorders were available. 2402 patients in whom complete information on acute neurological status were available were analyzed. In 161 patients (6.7%) an acute neurological disorder was identified as the preceding triggering factor. The most common neurological disorders were seizures, intracranial hemorrhage, and ischemic stroke. Time from neurological symptoms to TTS diagnosis was ≤ 2 days in 87.3% of cases. TTS patients with neurological disorders were younger, had a lower female predominance, fewer cardiac symptoms, lower left ventricular ejection fraction, and higher levels of cardiac biomarkers. TTS patients with neurological disorders had a 3.2-fold increased odds of in-hospital mortality compared to TTS patients without neurological disorders. In this large-scale study, 1 out of 15 TTS patients had an acute neurological condition as the underlying triggering factor. Our data emphasize that a wide spectrum of neurological diseases ranging from benign to life-threatening encompass TTS. The high rates of adverse events highlight the need for clinical awareness.

A study of 1005 family practice attenders at King Fahad National Guard Hospital was conducted during February 1993 to determine the prevalence of hyperlipidaemia and its association with participants' sociodemographic characteristics and clinical problems. The percentage of patients with total serum cholesterol concentration (TSCC) of 5.2-6.8 mmol/l was 39.3%, while those with TSCC exceeding 6.8 mmol/l was 9.5%. Hypertriglyceridaemia (TG > 2.5 mmol/l) was found in 5%. TSCC increased progressively with age up to the seventh decade. TSCC was higher among obese and diabetic patients than others. Obesity body mass index (BMI) > 29.9 kg/m2 was found in 32.8%, diabetes mellitus in 24.2%, hypertension in 11.1% and both diabetes and hypertension in 6.4%. There is an urgent need to equip primary health care teams with training and resources to help them give proper dietary advice, modify the local lifestyle and screen at least high-risk groups for hyperlipidaemia and other coronary risk factors.

AimsTakotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine‐learning (ML) based model to predict the risk of in‐hospital death and to perform a clustering of TTS patients to identify different risk profiles.Methods and resultsA Ridge Logistic Regression‐based ML model for predicting in‐hospital death was developed on 3482 TTS patients from the International Takotsubo Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). 31 clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the receiver‐operating characteristic curve (AUC), Sensitivity and Specificity. As secondary endpoint, a K‐Medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the ten most relevant features emerging from the main model. The overall incidence of in‐hospital death was 5.2%. The InterTAK‐ML model showed an AUC of 0.89 (0.85‐0.92), Sensitivity 0.85 (0.78‐0.95) and Specificity 0.76 (0.74‐0.79) in the internal validation cohort and an AUC of 0.82 (0.73‐0.91), a sensitivity of 0.74 (0.61‐0.87) and a specificity of 0.79 (0.77‐0.81) in the external cohort for in‐hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in‐hospital death (28.8% vs 15.5% vs 5.4% vs 0.8% vs 0.5%) which were consistent also in the external cohort.ConclusionA ML‐based approach for the identification of TTS patients at risk of adverse short‐term prognosis is feasible and effective. The InterTAK‐ML model showed unprecedented discriminative capability for the prediction of in‐hospital death.This article is protected by copyright. All rights reserved.

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Painful left bundle branch block (LBBB) syndrome is a rare cause of episodic chest pain associated with transient LBBB in the absence of flow-limiting coronary artery disease and myocardial ischaemia on functional testing. The aetiology of this phenomenon is not clear, but in many reported cases, these transient episodes of LBBB are rate related. The mechanism of chest pain is not well understood. Still, it is postulated that sudden loss of the ventricular contraction synchrony, which happens in LBBB, will induce a different perception of heartbeat in the brain with possible translation to the chest pain. Various treatment modalities were attempted in the past, including exercise training, medical therapy with beta-blockers and calcium channel blockers or device therapy with right ventricle pacing, biventricular pacing and lately, His-bundle pacing. This case report presents a woman with intermittent episodes of typical angina with periodic LBBB changes on her ECG. Telemetry monitoring and treadmill exercise tests show a 100% association between angina episodes and LBBB changes on ECG. Her transthoracic echocardiogram shows normal left ventricle structure and function, and her coronary angiogram shows no flow-limiting coronary artery disease. She has been successfully treated by His-bundle pacing, and her symptoms entirely resolved on her serial follow-up.