Drug combinations may elevate the risk of proarrhythmia. The aim of the present study was to investigate whether combinations of non-cardiovascular agents induce an additive increase in the proarrhythmic risk. In 12 female rabbit hearts, a drug combination of cotrimoxazole (300 µM), ondansetron (5 µM) and domperidone (1 µM) was infused after obtaining baseline data. In another 13 hearts, a combination of cotrimoxazole (300 µM), ondansetron (5 µM) and erythromycin (300 µM) was infused. Monophasic action potentials and ECG displayed a significant QT prolongation in all groups. This was accompanied by a significant increase in action potential duration. Of note, addition of each drug resulted in a further increase in the QT interval. Furthermore, a significant elevation of spatial dispersion of repolarization was observed. Lowering of potassium concentration in bradycardic AV-blocked hearts provoked early afterdepolarizations and torsade de pointes (TDP) in both study groups. Under baseline conditions, no episodes of TDP recorded. After administration of the first agent, TDP occurred in 5 of 12 hearts (37 episodes) and 5 of 13 hearts (26 episodes), respectively. After additional infusion of the second drug, TDP were recorded in 7 of 12 hearts (55 episodes) and 8 of 13 hearts (111 episodes). After additional infusion of the third drug, TDP occurred in 11 of 12 hearts (118 episodes) and 9 of 13 hearts (88 episodes). Combined treatment with several non-cardiovascular QT-prolonging agents resulted in a remarkable occurrence of proarrhythmia. An additive and significant prolongation of cardiac repolarization combined with an increased spatial dispersion of repolarization represents the underlying electrophysiological mechanism.
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http://dx.doi.org/10.1007/s12012-017-9416-0 | DOI Listing |
Emergencias
December 2024
Servicio de Urgencias, Hospital Clínic Barcelona, IDIBAPS, Universitat de Barcelona, España.
Objective: To describe the characteristics of patients diagnosed with acute heart failure (AHF) in emergency departments (EDs) who develop cardiogenic shock (CS) not associated with ST-segment elevation acute coronary syndrome (STACS).
Methods: Information for patients diagnosed with AHF in 23 Spanish EDs and registered between 2009 and 2019 were included for analysis if the patients developed symptoms consistent with CS. We described baseline clinical characteristics related to cardiac decompensation and CS, as well as 30-day mortality.
BMJ Open
December 2024
Disease Elimination, Burnet Institute, Melbourne, Victoria, Australia
Introduction: Opioid overdose and blood-borne virus transmission are key health risks for people who inject drugs. Existing study methods that record data on injecting drug risks mostly rely on retrospective self-reporting that, while valid, are limited to being broad and subject to recall bias. The In-The-Moment-Expanded (ITM-Ex) study will evaluate the feasibility and acceptability of multiple novel data collection methods to capture in situ drug injecting data.
View Article and Find Full Text PDFZhongguo Zhong Yao Za Zhi
December 2024
Guang'anmen Hospital, China Academy of Chinese Medical Sciences Beijing 100053, China.
The prevalence of cardiovascular diseases in China has shown a rising trend. With the patient number of about 8.9 million, heart failure has brought a heavy burden to public health and wellness.
View Article and Find Full Text PDFBackground: Atrial fibrillation (AF) has a significant impact on health and quality of life. The relationship of AF burden and temporal patterns of AF on patient symptoms, outcomes, and healthcare utilization is unknown. Insertable cardiac monitors (ICMs) are a strategic and as yet untapped, tool to investigate these relationships.
View Article and Find Full Text PDFHeart Rhythm O2
December 2024
Cardiology Department, Bichat Hospital, Paris, France.
Background: Detection of atrial tachyarrhythmias (ATA) on long-term electrocardiogram (ECG) recordings is a prerequisite to reduce ATA-related adverse events. However, the burden of editing massive ECG data is not sustainable. Deep learning (DL) algorithms provide improved performances on resting ECG databases.
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