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Objective30-day survival after cardiac arrest is low, 12.4% and 36% for out-of-hospital and in-hospital cardiac arrest, respectively. Heart failure is a known risk condition for cardiac arrest. Improving our ability to identify patients at high risk of cardiac arrest would enable prevention. We aimed to develop a prediction model for cardiac arrest to be used in patients newly diagnosed with heart failure.DesignA nationwide registry-based observational study.SettingData were sourced from the Swedish Heart Failure Registry (1 January 2005 to 31 December 2021).ParticipantsThis cohort included 45 068 patients discharged from hospital after first hospitalisation for newly diagnosed heart failure. Patients discharged from hospital with palliative care and/or implantable defibrillators were excluded.Outcome measure and analysisThe primary outcome was defined as cardiac arrest registered in the Swedish Registry for Cardiopulmonary Resuscitation until final follow-up (15 November 2022). Patients who died without resuscitation were treated as competing events. A Random Survival Forest model for competing risk was developed using predictors from the heart failure registry. The model was evaluated with Brier score, observed versus predicted cumulative incidence, Concordance-index (C-index) and time-dependent area under the curve of a receiver operating characteristics graph (AUC-ROC).ResultsIn this cohort, 2399 (5%) patients had received cardiopulmonary resuscitation (CPR) (5%), and 31 989 (71%) patients died without resuscitation. Our model with 82 predictors had a low Brier score indicating a capacity to accurately predict cumulative incidence of cardiac arrest on a group level. However, the model also had a low C-index 0.52 and low AUC-ROC 0.63–0.65.ConclusionOur Random Survival Forest model for competing risk could not accurately predict cardiac arrest in individual patients newly diagnosed with heart failure, because the event death without attempted resuscitation was treated as a competing event. The lack of information on transitions to palliative care and Do-Not-Attempt-CPR-orders limits the clinical relevance of any cardiac arrest prediction model.

Previous studies have shown that a high body mass index (BMI) is a risk factor for severe COVID-19. The aim of the present study was to assess whether a high BMI affects the risk of death or prolonged length of stay (LOS) in patients with COVID-19 during intensive care in Sweden. In this observational, register-based study, we included patients with COVID-19 from the Swedish Intensive Care Registry admitted to intensive care units (ICUs) in Sweden. Outcomes assessed were death during intensive care and ICU LOS [greater than or equal to]14 days. We used logistic regression models to evaluate the association (odds ratio [OR] and 95% confidence interval [CI]) between BMI and the outcomes. Valid weight and height information could be retrieved in 1,649 patients (1,227 (74.4%) males) with COVID-19. We found a significant association between BMI and the risk of the composite outcome death or LOS [greater than or equal to]14 days in survivors (OR per standard deviation [SD] increase 1.30, 95%CI 1.16-1.44, adjusted for sex, age and comorbidities), and this association remained after further adjustment for severity of illness (simplified acute physiology score; SAPS3) at ICU admission (OR 1.30 per SD, 95%CI 1.17-1.45). Individuals with a BMI [greater than or equal to] 35 kg/m.sup.2 had a doubled risk of the composite outcome. A high BMI was also associated with death during intensive care and a prolonged LOS in survivors assessed as separate outcomes. In this large cohort of Swedish ICU patients with COVID-19, a high BMI was associated with increasing risk of death and prolonged length of stay in the ICU. Based on our findings, we suggest that individuals with obesity should be more closely monitored when hospitalized for COVID-19.

Background There has been in increase in the use of systems for organizing lay responders for suspected out-of-hospital cardiac arrests (OHCAs) dispatch using smartphone-based technology. The purpose is to increase survival rates; however, such systems are dependent on people’s commitment to becoming a lay responder. Knowledge about the characteristics of such volunteers and their motivational factors is lacking. Therefore, we explored characteristics and quantified the underlying motivational factors for joining a smartphone-based cardiopulmonary resuscitation (CPR) lay responder system. Methods In this descriptive cross-sectional study, 800 consecutively recruited lay responders in a smartphone-based mobile positioning first-responder system (SMS-lifesavers) were surveyed. Data on characteristics and motivational factors were collected, the latter through a modified version of the validated survey “Volunteer Motivation Inventory” (VMI). The statements in the VMI, ranked on a Likert scale (1–5), corresponded to(a) intrinsic (an inner belief of doing good for others) or (b) extrinsic (earning some kind of reward from the act) motivational factors. Results A total of 461 participants were included in the final analysis. Among respondents, 59% were women, 48% between 25 and 39 years of age, 37% worked within health care, and 66% had undergone post-secondary school. The most common way (44%) to learn about the lay responder system was from a CPR instructor. A majority (77%) had undergone CPR training at their workplace. In terms of motivation, where higher scores reflect greater importance to the participant, intrinsic factors scored highest, represented by the category values (mean 3.97) followed by extrinsic categories reciprocity (mean 3.88) and self-esteem (mean 3.22). Conclusion This study indicates that motivation to join a first responder system mainly depends on intrinsic factors, i.e. an inner belief of doing good, but there are also extrinsic factors, such as earning some kind of reward from the act, to consider. Focusing information campaigns on intrinsic factors may be the most important factor for successful recruitment. When implementing a smartphone-based lay responder system, CPR instructors, as a main information source to potential lay responders, as well as the workplace, are crucial for successful recruitment.

Abstract Aims To study aetiologies of in-hospital cardiac arrests (IHCAs) and their association with 30-day survival. Methods and results Observational study with data from national registries. Specific aetiologies (n = 22) of IHCA patients between April 2018 and December 2020 were categorized into cardiac vs. non-cardiac and six main aetiology categories: myocardial ischemia, other cardiac causes, pulmonary causes, infection, haemorrhage, and other non-cardiac causes. Main endpoints were proportions in each aetiology, 30-day survival, and favourable neurological outcome (Cerebral Performance Category scale 1–2) at discharge. Among, 4320 included IHCA patients (median age 74 years, 63.1% were men), approximate 50% had cardiac causes with a 30-day survival of 48.4% compared to 18.7% among non-cardiac causes (P < 0.001). The proportion in each category were: myocardial ischemia 29.9%, pulmonary 21.4%, other cardiac causes 19.6%, other non-cardiac causes 11.6%, infection 9%, and haemorrhage 8.5%. The odds ratio (OR) for 30-day survival compared to myocardial ischemia for each category were: other cardiac causes OR 1.48 (CI 1.24–1.76); pulmonary causes OR 0.36 (CI 0.3–0.44); infection OR 0.25 (CI 0.18–0.33); haemorrhage OR 0.22 (CI 0.16–0.3); and other non-cardiac causes OR 0.56 (CI 0.45–0.69). IHCA caused by myocardial ischemia had the best favourable neurological outcome while those caused by infection had the lowest OR 0.06 (CI 0.03–0.13). Conclusion In this nationwide observational study, aetiologies with cardiac and non-cardiac causes of IHCA were evenly distributed. IHCA caused by myocardial ischemia and other cardiac causes had the strongest associations with 30-day survival and neurological outcome. Graphical Abstract Graphical Abstract

Background: There has been in increase in the use of systems for organizing lay responders for suspected out‐of‐ hospital cardiac arrests (OHCAs) dispatch using smartphone‐based technology. The purpose is to increase survival rates; however, such systems are dependent on people’s commitment to becoming a lay responder. Knowledge about the characteristics of such volunteers and their motivational factors is lacking. Therefore, we explored character‐ istics and quantified the underlying motivational factors for joining a smartphone‐based cardiopulmonary resuscita‐ tion (CPR) lay responder system. Methods: In this descriptive cross‐sectional study, 800 consecutively recruited lay responders in a smartphone‐based mobile positioning first‐responder system (SMS‐lifesavers) were surveyed. Data on characteristics and motivational factors were collected, the latter through a modified version of the validated survey “Volunteer Motivation Inventory” (VMI). The statements in the VMI, ranked on a Likert scale (1–5), corresponded to(a) intrinsic (an inner belief of doing good for others) or (b) extrinsic (earning some kind of reward from the act) motivational factors. Results: A total of 461 participants were included in the final analysis. Among respondents, 59% were women, 48% between 25 and 39 years of age, 37% worked within health care, and 66% had undergone post‐secondary school. The most common way (44%) to learn about the lay responder system was from a CPR instructor. A majority (77%) had undergone CPR training at their workplace. In terms of motivation, where higher scores reflect greater importance to the participant, intrinsic factors scored highest, represented by the category values (mean 3.97) followed by extrinsic categories reciprocity (mean 3.88) and self-esteem (mean 3.22). Conclusion: This study indicates that motivation to join a first responder system mainly depends on intrinsic factors, i.e. an inner belief of doing good, but there are also extrinsic factors, such as earning some kind of reward from the act, to consider. Focusing information campaigns on intrinsic factors may be the most important factor for successful recruitment. When implementing a smartphone‐based lay responder system, CPR instructors, as a main information source to potential lay responders, as well as the workplace, are crucial for successful recruitment.