Relationship between activity and sleep, as measured through a wearable accelerometer, and appropriate cardioverter-defibrillator interventions: a prospective SafeHeart substudy.

INTRODUCTION: Physical activity has shown association with ventricular arrhythmia, however, the role of specific behavioral patterns over a 24-hour cycle remains unknown. Therefore, we aimed to explore associations between physical behavior and appropriate implantable cardioverter-defibrillator (ICD) therapy. METHODS: We included patients with an ICD at two European sites, who wore wrist-based accelerometers capturing 24-hour movement and sleep behaviors for 28 days. Behavioral measures included activity volume, duration and intensity, sleep duration and efficiency. Patients were followed for 12 months for the outcome of appropriate ICD therapy. Cox proportional hazard models with restricted cubic splines were used for the analysis. Lastly, the predictive capacity was tested. RESULTS: : A total of 253 ICD patients were included (mean age 63.8 (±10.2), 50 (19.8%) female). During follow-up, 40 patients (15.8%) received appropriate ICD therapy; 32 ATP only (12.6%), 5 shock only (2.0%) and 3 combined ATP and shock (1.2%). In the adjusted model, high inactive duration (HR 1.40 (95% 1.10-1.78), peak walking cadence (HR 1.07 (95% 1.03-1.12) and total sleep duration (HR 1.50 (1.02-2.22) were associated with the outcome. The dose-response relationship was U-shaped for inactive duration with a cutoff at 16 hours, and linear for peak cadence and sleep. The prediction model reached an AUROC of 0.70 ±0.03, with highest accuracy in the first months. CONCLUSION: Wearable-derived 24-hour movement and sleep behaviors collected over 28 days were associated with later appropriate ICD therapy risk. Testing of the predictive value of digital biomarkers for enhanced risk stratification of ventricular arrhythmia warrants larger prospective studies. TRIAL REGISTRATION: National Trial Registration (NL9218, http://onderzoekmetmensen.nl/).

Deep behavioural representation learning reveals risk profiles for malignant ventricular arrhythmias.

We aimed to identify and characterise behavioural profiles in patients at high risk of SCD, by using deep representation learning of day-to-day behavioural recordings. We present a pipeline that employed unsupervised clustering on low-dimensional representations of behavioural time-series data learned by a convolutional residual variational neural network (ResNet-VAE). Data from the prospective, observational SafeHeart study conducted at two large tertiary university centers in the Netherlands and Denmark were used. Patients received an implantable cardioverter-defibrillator (ICD) between May 2021 and September 2022 and wore wearable devices using accelerometer technology during 180 consecutive days. A total of 272 patients (mean age of 63.1 ± 10.2 years, 81% male) were eligible with a total sampling of 37,478 days of behavioural data (138 ± 47 days per patient). Deep representation learning identified five distinct behavioural profiles: Cluster A (n = 46) had very low physical activity levels and a disturbed sleep pattern. Cluster B (n = 70) had high activity levels, mainly at light-to-moderate intensity. Cluster C (n = 63) exhibited a high-intensity activity profile. Cluster D (n = 51) showed above-average sleep efficiency. Cluster E (n = 42) had frequent waking episodes and poor sleep. Annual risks of malignant ventricular arrhythmias ranged from 30.4% in Cluster A to 9.8% and 9.5% for Clusters D-E, respectively. Compared to low-risk profiles (D-E), Cluster A demonstrated a three-to-four fold increased risk of malignant ventricular arrhythmias adjusted for clinical covariates (adjusted HR 3.63, 95% CI 1.54-8.53, p < 0.001). These behavioural profiles may guide more personalised approaches to ventricular arrhythmia and SCD prevention.

Long-term adherence to a wearable for continuous behavioural activity measuring in the SafeHeart implantable cardioverter defibrillator population.

Aims: Wearable health technologies are increasingly popular. Yet, wearable monitoring only works when devices are worn as intended, and adherence reporting lacks standardization. In this study, we aimed to explore the long-term adherence to a wrist-worn activity tracker in the prospective SafeHeart study and identify patient characteristics associated with adherence. Methods and results: This study enrolled 303 participants, instructed to wear a wrist-worn accelerometer day and night for 6 months. Long-term adherence was defined as valid days (≥22 h of wear time) divided by expected days, and daily adherence as mean hours of wear time per 24 h period. Optimal, moderate, and low long-term and daily adherence groups were defined as long-term adherence above or below 95 and 75% and daily adherence above or below 90 and 75%. Regression models were used to identify patient characteristics associated with long-term adherence. In total, 296 participants [median age 64 years; interquartile range (IQR) 57-72; 19% female] were found eligible, yielding 44 003 days for analysis. The median long-term adherence was 88.2% (IQR 74.6-96.5%). A total of 83 (28%), 127 (42.9%), and 86 (29.1%) participants had optimal, moderate, and low long-term adherence, and 163 (55.1%), 87 (29.4%), and 46 (15.5%) had optimal, moderate, and low daily adherence, respectively. Age and smoking habits differed significantly between adherence levels, and increasing changeover intervals improved the degree of long-term adherence. Conclusion: Long-term adherence to a wearable activity tracker was 88.2% over a 6-month period. Older age and longer changeover interval were positively associated with long-term adherence. This serves as a benchmark for future studies that rely on wearable devices. Trial registration number: The National Trial Registration number: NL9218 (https://onderzoekmetmensen.nl/).

Ethics of Wearable-Based Out-of-Hospital Cardiac Arrest Detection.

Out-of-hospital cardiac arrest is a major health problem, and immediate treatment is essential for improving the chances of survival. The development of technological solutions to detect out-of-hospital cardiac arrest and alert emergency responders is gaining momentum; multiple research consortia are currently developing wearable technology for this purpose. For the responsible design and implementation of this technology, it is necessary to attend to the ethical implications. This review identifies relevant ethical aspects of wearable-based out-of-hospital cardiac arrest detection according to four key principles of medical ethics. First, aspects related to beneficence concern the effectiveness of the technology. Second, nonmaleficence requires preventing psychological distress associated with wearing the device and raises questions about the desirability of screening. Third, grounded in autonomy are empowerment, the potential reidentification from continuously collected data, issues of data access, bystander privacy, and informed consent. Finally, justice concerns include the risks of algorithmic bias and unequal technology access. Based on this overview and relevant legislation, we formulate design recommendations. We suggest that key elements are device accuracy and reliability, dynamic consent, purpose limitation, and personalization. Further empirical research is needed into the perspectives of stakeholders, including people at risk of out-of-hospital cardiac arrest and their next-of-kin, to achieve a successful and ethically balanced integration of this technology in society.

The association of depression and patient and resuscitation characteristics with survival after out-of-hospital cardiac arrest: a cohort study.

AIMS: Out-of-hospital cardiac arrest (OHCA) is a leading cause of death worldwide, with cardiovascular disease (CVD) being a key risk factor. This study aims to investigate disparities in patient/OHCA characteristics and survival after OHCA among patients with vs. without depression. METHODS AND RESULTS: This is a retrospective cohort study using data from the AmsteRdam REsuscitation Studies (ARREST) registry from 2008 to 2018. History of comorbidities, including depression, was obtained from the patient's general practitioner. Out-of-hospital cardiac arrest survival was defined as survival at 30 days post-OHCA or hospital discharge. Logistic regression models were used to obtain crude and adjusted odds ratios (ORs) for the association between depression and OHCA survival and possible effect modification by age, sex, and comorbidities. The potential mediating effects of initial heart rhythm and provision of bystander cardiopulmonary resuscitation were explored. Among 5594 OHCA cases, 582 individuals had pre-existing depression. Patients with depression had less favourable patient and OHCA characteristics and lower odds of survival after adjustment for age, sex, and comorbidities [OR 0.65, 95% confidence interval (CI) 0.51-0.82], with similar findings by sex and age groups. The association remained significant among the Utstein comparator group (OR 0.63, 95% CI 0.45-0.89) and patients with return of spontaneous circulation (OR 0.60, 95% CI 0.42-0.85). Initial rhythm and bystander cardiopulmonary resuscitation partially mediated the observed association (by 27 and 7%, respectively). CONCLUSION: Out-of-hospital cardiac arrest patients with depression presented more frequently with unfavourable patient and OHCA characteristics and had reduced chances of survival. Further investigation into potential pathways is warranted.

Long-Term Socioeconomic and Mental Health Changes After Out-of-Hospital Cardiac Arrest in Women and Men.

BACKGROUND: Long-term effects of out-of-hospital cardiac arrest (OHCA) may affect the ability to work and mental health. Our aim was to analyze 5-year changes in socioeconomic and mental health outcomes after OHCA in women and men. METHODS: We included 259 women and 996 men from North Holland, the Netherlands, who survived 30 days after OHCA occurred between 2009 and 2015. We assessed changes in employment, income, primary earner status, and anxiety/depression (using medication proxies) from the year before the OHCA to 5 years after with generalized linear mixed models, stratified by sex. We tested differences in changes by sex with interaction terms. Additionally, we explored yearly changes. The 5-year changes after OHCA were compared with changes in a sex- and age-matched sample of people without OHCA. Differences were tested using an interaction term of time and OHCA status. RESULTS: In both women and men (median age [Q1, Q3]: 51 [45, 55] and 54 [48, 57] years, respectively), decreases from before OHCA to 5 years thereafter were observed in the proportion employed (from 72.8% to 53.4% [women] and 80.9% to 63.7% [men]) and the median income. No change in primary earner status was observed in either sex. Dispensing of anxiety/depression medication increased only in women, especially after 1 year (odds ratio, 5.68 [95% CI, 2.05-15.74]) and 5 years (odds ratio, 5.73 [95% CI, 1.88-17.53]). Notable differences between women and men were observed for changes in primary earner status and anxiety/depression medication (eg, at year 1, odds ratio for women, 6.71 [95% CI, 1.96-23.01]; and for men, 0.69 [95% CI, 0.33-1.45]). However, except for anxiety/depression medication in women, similar changes were also observed in the general population. CONCLUSIONS: OHCA survivors experience changes in employment, income, and primary earner status similar to the general population. However, women who survived OHCA more often received anxiety/depression medication in the years following OHCA.

Incidence and Survival of Out-of-Hospital Cardiac Arrest in Public Housing Areas in 3 European Capitals.

BACKGROUND: Strategies to reach out-of-hospital cardiac arrests (called cardiac arrest) in residential areas and reduce disparities in care and outcomes are warranted. This study investigated incidences of cardiac arrests in public housing areas. METHODS: This register-based cohort study included cardiac arrest patients from Amsterdam (the Netherlands) from 2016 to 2021, Copenhagen (Denmark) from 2016 to 2021, and Vienna (Austria) from 2018 to 2021. Using Poisson regression adjusted for spatial correlation and city, we compared cardiac arrest incidence rates (number per square kilometer per year and number per 100 000 inhabitants per year) in public housing and other residential areas and examined the proportion of cardiac arrests within public housing and adjacent areas (100-m radius). RESULTS: Overall, 9152 patients were included of which 3038 (33.2%) cardiac arrests occurred in public housing areas and 2685 (29.3%) in adjacent areas. In Amsterdam, 635/1801 (35.3%) cardiac arrests occurred in public housing areas; in Copenhagen, 1036/3077 (33.7%); and in Vienna, 1367/4274 (32.0%). Public housing areas covered 42.4 (12.6%) of 336.7 km2 and 1 024 470 (24.6%) of 4 164 700 inhabitants. Across the capitals, we observed a lower probability of 30-day survival in public housing versus other residential areas (244/2803 [8.7%] versus 783/5532 [14.2%]). The incidence rates and rate ratio of cardiac arrest in public housing versus other residential areas were incidence rate, 16.5 versus 4.1 n/km2 per year; rate ratio, 3.46 (95% CI, 3.31-3.62) and incidence rate, 56.1 versus 36.8 n/100 000 inhabitants per year; rate ratio, 1.48 (95% CI, 1.42-1.55). The incidence rates and rate ratios in public housing versus other residential areas were consistent across the 3 capitals. CONCLUSIONS: Across 3 European capitals, one-third of cardiac arrests occurred in public housing areas, with an additional third in adjacent areas. Public housing areas exhibited consistently higher cardiac arrest incidences per square kilometer and 100 000 inhabitants and lower survival than other residential areas. Public housing areas could be a key target to improve cardiac arrest survival in countries with a public housing sector.

Ethical use of artificial intelligence to prevent sudden cardiac death: an interview study of patient perspectives.

BACKGROUND: The emergence of artificial intelligence (AI) in medicine has prompted the development of numerous ethical guidelines, while the involvement of patients in the creation of these documents lags behind. As part of the European PROFID project we explore patient perspectives on the ethical implications of AI in care for patients at increased risk of sudden cardiac death (SCD). AIM: Explore perspectives of patients on the ethical use of AI, particularly in clinical decision-making regarding the implantation of an implantable cardioverter-defibrillator (ICD). METHODS: Semi-structured, future scenario-based interviews were conducted among patients who had either an ICD and/or a heart condition with increased risk of SCD in Germany (n = 9) and the Netherlands (n = 15). We used the principles of the European Commission's Ethics Guidelines for Trustworthy AI to structure the interviews. RESULTS: Six themes arose from the interviews: the ability of AI to rectify human doctors' limitations; the objectivity of data; whether AI can serve as second opinion; AI explainability and patient trust; the importance of the 'human touch'; and the personalization of care. Overall, our results reveal a strong desire among patients for more personalized and patient-centered care in the context of ICD implantation. Participants in our study express significant concerns about the further loss of the 'human touch' in healthcare when AI is introduced in clinical settings. They believe that this aspect of care is currently inadequately recognized in clinical practice. Participants attribute to doctors the responsibility of evaluating AI recommendations for clinical relevance and aligning them with patients' individual contexts and values, in consultation with the patient. CONCLUSION: The 'human touch' patients exclusively ascribe to human medical practitioners extends beyond sympathy and kindness, and has clinical relevance in medical decision-making. Because this cannot be replaced by AI, we suggest that normative research into the 'right to a human doctor' is needed. Furthermore, policies on patient-centered AI integration in clinical practice should encompass the ethics of everyday practice rather than only principle-based ethics. We suggest that an empirical ethics approach grounded in ethnographic research is exceptionally well-suited to pave the way forward.

Sex Differences in Out-of-Hospital Cardiac Arrest Survival Trends.

BACKGROUND: Out-of-hospital cardiac arrest survival rates have improved over time. This study established whether improvements were similar for women and men, and to what extent resuscitation characteristics or in-hospital procedures contributed to sex differences in temporal trends. METHODS AND RESULTS: This retrospective cohort study included 3386 women and 8564 men from North Holland, the Netherlands, who experienced an out-of-hospital cardiac arrest from a cardiac cause in 2005 to 2017. Yearly rates of 30-day survival and secondary outcomes were calculated. Sex differences in temporal trends were evaluated with age-adjusted Poisson regression analysis, including interaction for sex and out-of-hospital cardiac arrest year. Resuscitation characteristics and in-hospital procedures were added to the model, and a spline at 2013 was considered. During the study period, the average 30-day survival was 24.9% in men and 15.7% in women. The 30-day survival rate increased in men (20% to 27.2%; P<0.001) but not in women (15.0% to 11.6%; P=0.40). The increase in the 30-day survival rate was 3% higher per year in men than in women (rate ratio, 1.03 [95% CI, 1.00-1.05]), with a stronger difference after 2013. Men had a larger increase in survival rate to the hospital arrival than women in 2005 to 2013, and, after 2013, an advantage over women in survival rate after hospital arrival. The sex differences were partly explained by differing trends in shockable initial rhythm (eg, adjusted rate ratio, 1.01 [95% CI, 0.99-1.03] for 30-day survival) and provision of in-hospital procedures. CONCLUSIONS: Changes in rates of 30-day survival, survival to hospital arrival, and, after 2013, survival from hospital arrival to 30 days were more beneficial in men than women. The differences in trends were partly explained by shockable initial rhythm and in-hospital procedures.

Rationale and design of the BECA project: Smartwatch-based activation of the chain of survival for out-of-hospital cardiac arrest.

Aim: Out-of-hospital cardiac arrest is a major health problem, and the overall survival rate is low (4.6%-16.4%). The initiation of the current chain of survival depends on the presence of a witness of the cardiac arrest, which is not present in 29.7%-63.4% of the cases. Furthermore, a delay in starting this chain is common in witnessed out-of-hospital cardiac arrest. This project aims to reduce morbidity and mortality due to out-of-hospital cardiac arrest by developing a smartwatch-based solution to expedite the chain of survival in the case of (un)witnessed out-of-hospital cardiac arrest. Methods: Within the 'Beating Cardiac Arrest' project, we aim to develop a demonstrator product that detects out-of-hospital cardiac arrest using photoplethysmography and accelerometer analysis, and autonomously alerts emergency medical services. A target group study will be performed to determine who benefits the most from this product. Furthermore, several clinical studies will be conducted to capture or simulate data on out-of-hospital cardiac arrest cases, as to develop detection algorithms and validate their diagnostic performance. For this, the product will be worn by patients at high risk for out-of-hospital cardiac arrest, by volunteers who will temporarily interrupt blood flow in their arm by inflating a blood pressure cuff, and by patients who undergo cardiac electrophysiologic and implantable cardioverter defibrillator testing procedures. Moreover, studies on psychosocial and ethical acceptability will be conducted, consisting of surveys, focus groups, and interviews. These studies will focus on end-user preferences and needs, to ensure that important individual and societal values are respected in the design process.

Sudden cardiac arrest in infants and children: proposal for a diagnostic workup to identify the etiology. An 18-year multicenter evaluation in the Netherlands.

Sudden cardiac arrest (SCA) studies are often population-based, limited to sudden cardiac death, and excluding infants. To guide prevention opportunities, it is essential to be informed of pediatric SCA etiologies. Unfortunately, etiologies frequently remain unresolved. The objectives of this study were to determine paediatric SCA etiology, and to evaluate the extent of post-SCA investigations and to assess the performance of previous cardiac evaluation in detecting conditions predisposing to SCA. In a retrospective cohort (2002-2019), all children 0-18 years with out-of-hospital cardiac arrest (OHCA) referred to Erasmus MC Sophia Children's Hospital or the Amsterdam UMC (tertiary-care university hospitals), with cardiac or unresolved etiologies were eligible for inclusion. SCA etiologies, cardiac and family history and etiologic investigations in unresolved cases were assessed. The etiology of arrest could be determined in 52% of 172 cases. Predominant etiologies in children ≥ 1 year (n = 99) were primary arrhythmogenic disorders (34%), cardiomyopathies (22%) and unresolved (32%). Events in children < 1 year (n = 73) were largely unresolved (70%) or caused by cardiomyopathy (8%), congenital heart anomaly (8%) or myocarditis (7%). Of 83 children with unresolved etiology a family history was performed in 51%, an autopsy in 51% and genetic testing in 15%. Pre-existing cardiac conditions presumably causative for SCA were diagnosed in 9%, and remained unrecognized despite prior evaluation in 13%. CONCLUSION: SCA etiology remained unresolved in 83 of 172 cases (48%) and essential diagnostic investigations were often not performed. Over one-fifth of SCA patients underwent prior cardiac evaluation, which did not lead to recognition of a cardiac condition predisposing to SCA in all of them. The diagnostic post-SCA approach should be improved and the proposed standardized pediatric post-SCA diagnostics protocol may ensure a consistent and systematic evaluation process increasing the diagnostic yield. WHAT IS KNOWN: • Arrests in infants remain unresolved in most cases. In children > 1 year, predominant etiologies are primary arrhythmia disorders, cardiomyopathy and myocarditis. • Studies investigating sudden cardiac arrest are often limited to sudden cardiac death (SCD) in 1 to 40 year old persons, excluding infants and successfully resuscitated children. WHAT IS NEW: • In patients with unresolved SCA events, the diagnostic work up was often incompletely performed. • Over one fifth of victims had prior cardiac evaluation before the arrest, with either a diagnosed cardiac condition (9%) or an unrecognized cardiac condition (13%).

Early modelling of the effects and healthcare costs of the Dutch citizen-rescuer system for out-of-hospital cardiac arrests.

OBJECTIVES: 1) to analyse the total average healthcare costs of a patient with an out-of-hospital cardiac arrest (OHCA), as well as estimating the operational costs of the citizen-rescuer system (CRS); 2) to conduct an early modelling of the effects and healthcare costs of the Dutch CRS in comparison to no CRS. METHODS: A health economic modelling study was conducted. Adult patients with OHCA from cardiac causes in the province of Limburg (the Netherlands) were included. The time horizon was from OHCA occurrence up to one year after hospital discharge. First, the total average healthcare costs of OHCA patients were analysed as well as the yearly operating costs of the CRS. Second, an early modelling was conducted to compare from the healthcare perspective the healthcare costs of OHCA patients with the CRS being activated but no responders attended (CRS-NV) versus the CRS being activated with attendance of ≥1 responder(s) (CRS-V). RESULTS: The total average healthcare costs per patient are €42,533. The yearly operating costs for the CRS are approximately €1.5 million per year in the Netherlands. The early modelling of costs and effects showed that the incremental healthcare costs per patient thus were €4,131 in the CRS-V versus the CRS-NV group (€25,184 in the CRS-V group and €21,053 in the CRS-NV group). Incremental quality-adjusted life years (QALYs) was 5 per 100 patients (16 per 100 patients in the CRS-V group versus 11 per 100 patients in the CRS-NV group). The incremental cost-effectiveness ratio (ICER) was €79,662 per QALY for the CRS-V group. CONCLUSION: This study shows that patients in the CSR-V group had additional health care costs of €4,131 per patient compared to patients in the CRS-NV group. This increase is caused by patients surviving more often, who then continue to utilise health services, which results in a (logic) increase in healthcare costs. For future research, accurate and up-to-date data on effectiveness and costs of the CRS needs to be collected.

Dispatch of Volunteer Responders to Out-of-Hospital Cardiac Arrests.

BACKGROUND: Systems for dispatch of volunteer responders to collect automated external defibrillators and/or to provide cardiopulmonary resuscitation (CPR) in cases of nearby out-of-hospital cardiac arrest (OHCA) are widely implemented. OBJECTIVES: This study aimed to investigate whether the activation of a volunteer responder system to OHCAs was associated with higher rates of bystander CPR, bystander defibrillation, and 30-day survival vs no system activation. METHODS: This was a retrospective observational analysis within the ESCAPE-NET (European Sudden Cardiac Arrest network: Towards Prevention, Education, New Effective Treatment) collaborative research network. Included were cases of OHCA between 2015 and 2019 from 5 European sites with volunteer responder systems. At all sites, systems were activated by dispatchers at the emergency medical communication center in response to suspected OHCA. Exposed cases (system activation) were compared with nonexposed cases (no system activation). Risk ratios (RRs) were calculated for the outcomes of bystander CPR, bystander defibrillation, and 30-day survival after inverse probability treatment weighting. Missing data were handled using multiple imputation. RESULTS: In total, 9,553 cases were included. In 4,696 cases, the volunteer responder system was activated, and in 4,857 it was not. The pooled RRs were 1.30 (95% CI: 1.15-1.47) for bystander CPR, 1.89 (95% CI: 1.36-2.63) for bystander defibrillation, and 1.22 (95% CI: 1.07-1.39) for 30-day survival. CONCLUSIONS: Activation of a volunteer response system in cases of OHCA was associated with a higher chance of bystander CPR, bystander defibrillation, and 30-day survival vs no system activation. A randomized controlled trial is necessary to determine fully the causal effect of volunteer responder systems.

The opioid tramadol blocks the cardiac sodium channel Nav1.5 in HEK293 cells.

AIMS: Opioids are associated with increased risk of sudden cardiac death. This may be due to their effects on the cardiac sodium channel (Nav1.5) current. In the present study, we aim to establish whether tramadol, fentanyl, or codeine affects Nav1.5 current. METHODS AND RESULTS: Using whole-cell patch-clamp methodology, we studied the effects of tramadol, fentanyl, and codeine on currents of human Nav1.5 channels stably expressed in HEK293 cells and on action potential (AP) properties of freshly isolated rabbit ventricular cardiomyocytes. In fully available Nav1.5 channels (holding potential -120 mV), tramadol exhibited inhibitory effects on Nav1.5 current in a concentration-dependent manner with an IC50 of 378.5 ± 33.2 µm. In addition, tramadol caused a hyperpolarizing shift of voltage-gated (in)activation and a delay in recovery from inactivation. These blocking effects occurred at lower concentrations in partially inactivated Nav1.5 channels: during partial fast inactivation (close-to-physiological holding potential -90 mV), IC50 of Nav1.5 block was 4.5 ± 1.1 µm, while it was 16 ± 4.8 µm during partial slow inactivation. The tramadol-induced changes on Nav1.5 properties were reflected by a reduction in AP upstroke velocity in a frequency-dependent manner. Fentanyl and codeine had no effect on Nav1.5 current, even when tested at lethal concentrations. CONCLUSION: Tramadol reduces Nav1.5 currents, in particular, at close-to-physiological membrane potentials. Fentanyl and codeine have no effects on Nav1.5 current.

Data-driven sudden cardiac arrest research in Europe: Experts' perspectives on ethical challenges and governance strategies.

Background: Observational studies using large-scale databases and biobanks help improve prevention and treatment of sudden cardiac arrest (SCA) but the lack of guidance on data protection issues in this setting may harm patients' rights and the research enterprise itself. This qualitative study explored the ethical aspects of observational SCA research, as well as solutions. Methods: European experts in SCA research, medical ethics and health law reflected on this topic through semi-structured interviews (N = 29) and a virtual roundtable conference (N = 18). The ESCAPE-NET project served as a discussion case. Findings were coded and thematically analysed. Results: The first theme concerned the potential benefits and harms (at individual and group level) of observational data-based SCA studies and included the following sub-themes: societal value, scientific validity, data privacy, disclosure of genetic findings, stigma and discrimination, and medicalisation of sudden death. The second theme involved governance through 'privacy by design', 'privacy by policy' and associated regulation and oversight. Sub-themes were: de-identification of data, informed consent (broad and deferred), ethics review, and harmonisation. Conclusions: Researchers and scientific societies should be aware that ethico-legal issues may arise during data-driven studies in SCA and other emergencies. These can be mitigated by combining technical data protection safeguards with appropriate informed consent policies and proportional ethics oversight. To ensure responsible conduct of data research in emergency medicine, we recommend the establishment of 'codes of conduct' which should be developed in interdisciplinary groups and together with patient representatives.

Validation of the ARIC prediction model for sudden cardiac death in the European population: The ESCAPE-NET project.

BACKGROUND: Sudden cardiac death is responsible for 10% to 20% of all deaths in Europe. The current study investigates how well the risk of sudden cardiac death can be predicted. To this end, we validated a previously developed prediction model for sudden cardiac death from the Atherosclerosis Risk in Communities study (USA). METHODS: Data from participants of the Copenhagen City Heart Study (CCHS) (n=9988) was used to externally validate the previously developed prediction model for sudden cardiac death. The model's performance was assessed through discrimination (C-statistic) and calibration by the Hosmer-Lemeshow goodness-of-fit (HL) statistics suited for censored data and visual inspection of calibration plots. Additional validation was performed using data from the Hoorn Study (N=2045), employing the same methods. RESULTS: During ten years of follow-up of CCHS participants (mean age: 58.7 years, 56.2% women), 425 experienced SCD (4.2%). The prediction model showed good discrimination for sudden cardiac death risk (C-statistic: 0.81, 95% CI: 0.79-0.83). Calibration was robust (HL statistic: P=0.8). Visual inspection of the calibration plot showed that the calibration could be improved. Sensitivity was 89.8%, and specificity was 60.6%. The positive and negative predictive values were 10.1% and 99.2%. Model performance was similar in the Hoorn Study (C-statistic: 0.81, 95% CI: 0.77-0.85 and the HL statistic: 1.00). CONCLUSION: Our study showed that the previously developed prediction model in North American adults performs equally well in identifying those at risk for sudden cardiac death in a general North-West European population. However, the positive predictive value is low.