Effects of remote ischaemic preconditioning on peri-operative myocardial injury and clinical outcomes in patients undergoing elective cardiac bypass surgery

Ischaemic heart disease (IHD) is a major cause of morbidity and mortality in the world. Coronary artery bypass graft (CABG) surgery is the revascularisation strategy of choice in a significant number of patients, particularly those with diabetes mellitus and complex coronary disease. During cardiac surgery, the myocardium is subjected to peri-operative myocardial injury (PMI), which has been associated with worse short and long-term clinical outcomes. Higher-risks patients are currently being operated on with subsequent higher risk of PMI and worse prognosis: therefore new strategies are required to potentiate the innate mechanisms of cardioprotection. In this regard, remote ischaemic preconditioning (RIPC) is a promising non-invasive intervention able to reduce PMI in these patients: however, not all the studies have shown significant cardioprotection with RIPC for a number of factors, amongst which the intensity of the preconditioning stimulus may play a significant role. We therefore investigated whether an enhanced RIPC stimulus, given with transient simultaneous multi-limb ischaemia/reperfusion, was able to reduce PMI and improve short-term clinical outcomes in patients undergoing elective cardiac surgery: we demonstrated that our preconditioning stimulus can significantly reduce PMI, length of intensive care unit (ICU) stay and incidence of atrial fibrillation (AF) in these patients. In addition, further retrospective analyses showed improved myocardial protection in preconditioned diabetic patients undergoing CABG surgery and in control CABG subjects receiving combined antegrade and retrograde cardioplegia compared to control CABG patients having antegrade cardioplegia or intermittent cross-clamp-fibrillation. We also conducted a multi-centre, double-blinded randomised control clinical trial, in which we investigated the effects of RIPC on clinical outcomes at 1 year in high-risk patients undergoing elective CABG surgery with or without valve surgery (the ERICCA trial). The results of this study are due to be presented in March 2015 and have the potential to significantly impact on clinical practice in cardiac surgery

Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG

Background: Atrial fibrillation (AF) is the most common supraventricular arrhythmia, characterized by disorganized atrial electrical activity, maintained by localized arrhythmogenic atrial drivers. Pulmonary vein isolation (PVI) allows to exclude PV-related drivers. However, PVI is less effective in patients with additional extra-PV arrhythmogenic drivers. Objectives: To discriminate whether AF drivers are located near the PVs vs extra-PV regions using the noninvasive 12-lead electrocardiogram (ECG) in a computational and clinical framework, and to computationally predict the acute success of PVI in these cohorts of data. Methods: AF drivers were induced in 2 computerized atrial models and combined with 8 torso models, resulting in 1128 12-lead ECGs (80 ECGs with AF drivers located in the PVs and 1048 in extra-PV areas). A total of 103 features were extracted from the signals. Binary decision tree classifier was trained on the simulated data and evaluated using hold-out cross-validation. The PVs were subsequently isolated in the models to assess PVI success. Finally, the classifier was tested on a clinical dataset (46 patients: 23 PV-dependent AF and 23 with additional extra-PV sources). Results: The classifier yielded 82.6% specificity and 73.9% sensitivity for detecting PV drivers on the clinical data. Consistency analysis on the 46 patients resulted in 93.5% results match. Applying PVI on the simulated AF cases terminated AF in 100% of the cases in the PV class. Conclusion: Machine learning–based classification of 12-lead-ECG allows discrimination between patients with PV drivers vs those with extra-PV drivers of AF. The novel algorithm may aid to identify patients with high acute success rates to PVI

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

Offset of pharmacodynamic effects and safety of remifentanil in intensive care unit patients with various degrees of renal impairment

INTRODUCTION: This open label, multicentre study was conducted to assess the times to offset of the pharmacodynamic effects and the safety of remifentanil in patients with varying degrees of renal impairment requiring intensive care. METHODS: A total of 40 patients, who were aged 18 years or older and had normal/mildly impaired renal function (estimated creatinine clearance ≥ 50 ml/min; n = 10) or moderate/severe renal impairment (estimated creatinine clearance <50 ml/min; n = 30), were entered into the study. Remifentanil was infused for up to 72 hours (initial rate 6–9 μg/kg per hour), with propofol administered if required, to achieve a target Sedation–Agitation Scale score of 2–4, with no or mild pain. RESULTS: There was no evidence of increased offset time with increased duration of exposure to remifentanil in either group. The time to offset of the effects of remifentanil (at 8, 24, 48 and 72 hours during scheduled down-titrations of the infusion) were more variable and were statistically significantly longer in the moderate/severe group than in the normal/mild group at 24 hours and 72 hours. These observed differences were not clinically significant (the difference in mean offset at 72 hours was only 16.5 min). Propofol consumption was lower with the remifentanil based technique than with hypnotic based sedative techniques. There were no statistically significant differences between the renal function groups in the incidence of adverse events, and no deaths were attributable to remifentanil use. CONCLUSION: Remifentanil was well tolerated, and the offset of pharmacodynamic effects was not prolonged either as a result of renal dysfunction or prolonged infusion up to 72 hours

Interaction of Cardiovascular Nonmodifiable Risk Factors, Comorbidities and Comedications With Ischemia/Reperfusion Injury and Cardioprotection by Pharmacological Treatments and Ischemic Conditioning

Risc cardiovascular; Isquèmia/reperfusióCardiovascular risk; Ischemia/reperfusionRiesgo cardiovascular; Isquemia/reperfusiónPreconditioning, postconditioning, and remote conditioning of the myocardium enhance the ability of the heart to withstand a prolonged ischemia/reperfusion insult and the potential to provide novel therapeutic paradigms for cardioprotection. While many signaling pathways leading to endogenous cardioprotection have been elucidated in experimental studies over the past 30 years, no cardioprotective drug is on the market yet for that indication. One likely major reason for this failure to translate cardioprotection into patient benefit is the lack of rigorous and systematic preclinical evaluation of promising cardioprotective therapies prior to their clinical evaluation, since ischemic heart disease in humans is a complex disorder caused by or associated with cardiovascular risk factors and comorbidities. These risk factors and comorbidities induce fundamental alterations in cellular signaling cascades that affect the development of ischemia/reperfusion injury and responses to cardioprotective interventions. Moreover, some of the medications used to treat these comorbidities may impact on cardioprotection by again modifying cellular signaling pathways. The aim of this article is to review the recent evidence that cardiovascular risk factors as well as comorbidities and their medications may modify the response to cardioprotective interventions. We emphasize the critical need for taking into account the presence of cardiovascular risk factors as well as comorbidities and their concomitant medications when designing preclinical studies for the identification and validation of cardioprotective drug targets and clinical studies. This will hopefully maximize the success rate of developing rational approaches to effective cardioprotective therapies for the majority of patients with multiple comorbidities. Significance Statement Ischemic heart disease is a major cause of mortality; however, there are still no cardioprotective drugs on the market. Most studies on cardioprotection have been undertaken in animal models of ischemia/reperfusion in the absence of comorbidities; however, ischemic heart disease develops with other systemic disorders (e.g., hypertension, hyperlipidemia, diabetes, atherosclerosis). Here we focus on the preclinical and clinical evidence showing how these comorbidities and their routine medications affect ischemia/reperfusion injury and interfere with cardioprotective strategies.P.F. was supported by the National Research, Development and Innovation Office of Hungary (Research Excellence Program–TKP, National Heart Program NVKP 16-1-2016-0017) and by the Higher Education Institutional Excellence Program of the Ministry of Human Capacities in Hungary, within the framework of the Therapeutic Development thematic program of Semmelweis University. D.D. is supported by grants from National Institutes of Health National Heart, Lung, and Blood Institute [R01-HL136389, R01-HL131517, R01-HL089598, and R01-HL163277], the German Research Foundation [DFG, Do 769/4-1], the European Union (large-scale integrative project MAESTRIA, no. 965286). G.H. is supported by the German Research Foundation [SFB 1116 B8]. D.H. is supported by the Duke–NUS Signature Research Programme funded by the Ministry of Health, Singapore Ministry of Health’s National Medical Research Council under its Clinician Scientist–Senior Investigator scheme [NMRC/CSA-SI/0011/2017], Centre Grant [CGAug16M006], and Collaborative Centre Grant scheme [NMRC/CGAug16C006]. I.A. is supported from Boehringer-Ingelheim for the investigation of the effects of empagliflozin on the myocardium and from the European Union (ERDF) and Greek national funds through the Operational Program “Competitiveness, Entrepreneurship and Innovation,” under the call “RESEARCH – CREATE – INNOVATE” (project code: 5048539). S.M.D. acknowledges the support of the British Heart Foundation [PG/19/51/34493 and PG/16/85/32471]. S.L. is supported by the South African National Research Foundation and received COST Seed funding from the Department of Science and Innovation in South Africa. M.R-M. is supported by the Instituto de Salud Carlos III of the Spanish Ministry of Health [FIS-PI19-01196] and a grant from the Spanish Society of Cardiology [SEC/FEC-INV-BAS 217003]. C.J.Z. is supported by a grant from European Foundation for the Study of Diabetes (EFSD), a research grant from Boehringer-Ingelheim and an institutional grant from Amsterdam UMC Cardiovascular Research. R.S. is supported by Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) [Project number 268555672—SFB 1213, Project B05]