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AIMS: This study aimed to examine whether socioeconomic differences exist in long-term outcomes after out-of-hospital cardiac arrest (OHCA).METHODS: We included 2309 30-day OHCA survivors ≥ 30 years of age from the Danish Cardiac Arrest Registry, 2001-2014, divided in tertiles of household income (low, medium, high). Absolute probabilities were estimated using logistic regression for 1-year outcomes and cause-specific Cox regression for 5-year outcomes. Differences between income-groups were standardized with respect to age, sex, education and comorbidities.RESULTS: High-income compared to low-income patients had highest 1-year (96.4% vs. 84.2%) and 5-year (87.6% vs. 64.1%) survival, and lowest 1-year (11.3% vs. 7.4%) and 5-year (13.7% vs. 8.6%) risk of anoxic brain damage/nursing home admission. The corresponding standardized probability differences were 8.2% (95%CI 4.7-11.6%) and 13.9% (95%CI 8.2-19.7%) for 1- and 5-year survival, respectively; and -4.5% (95%CI -8.2 to -1.2%) and -5.1% (95%CI -9.3 to -0.9%) for 1- and 5-year risk of anoxic brain damage/nursing home admission, respectively. Among 831 patients < 66 years working prior to OHCA, 72.1% returned to work within 1 year and 80.8% within 5 years. High-income compared to low-income patients had the highest chance of 1-year (76.4% vs. 58.8%) and 5-year (85.3% vs. 70.6%) return to work with the corresponding absolute probability difference of 18.0% (95%CI 3.8-32.7%) for 1-year and 9.4% (95%CI -3.4 to 22.3%) for 5-year.CONCLUSION: Patients of high socioeconomic status had higher probability of long-term survival and return to work, and lower risk of anoxic brain damage/nursing home admission after OHCA compared to patients of low socioeconomic status.

Denmark implemented early widespread social distancing to reduce pressure on the healthcare system from the coronavirus disease 2019 (COVID-19) pandemic, with the aims to reduce mortality. Unintended consequences might be delays in treatment for other diseases and subsequent mortality. We examined national all-cause mortality comparing weeks 1–27 in 2020 and 2015–2019. This registry-based study used Danish national registry data until 5 July 2020. We examined all-cause mortality rates among all deaths recorded from 2015 to 2020 and among chronic conditions (cardiovascular (cardiac & circulatory), chronic pulmonary, chronic kidney disease, cancer, and diabetes), comparing each week in 2020 to weeks in 2015–2019. In 2020, there were 28,363 deaths in weeks 1–27 (30 December 2019–5 July 2020), the mean deaths in 2015–2019 were 28,630 deaths (standard deviation 784). Compared to previous years, the mortality rate in weeks 3–10 of 2020 was low, peaking in week 14 (17.6 per 100,000 persons in week 9, 19.9 per 100,000 in week 14). Comorbidity prevalence among deceased individuals was similar in 2020 and 2015–2019: 71.1% of all deceased had a prior cardiovascular diagnosis, 30.0% of all deceased had a prior cardiac diagnosis. There were 493 deaths with COVID-19 in weeks 11–27, (59.8% male), and 75.1% had a prior cardiovascular diagnosis. Weekly mortality rates for pre-existing chronic conditions peaked in week 14, and then declined. During the COVID-19 pandemic, due to timely lockdown measures, the mortality rate in Denmark has not increased compared to the mortality rates in the same period during 2015–2019. Electronic supplementary material The online version of this article (10.1007/s10654-020-00680-x) contains supplementary material, which is available to authorized users.

Background It remains challenging to identify patients at risk of out‐of‐hospital cardiac arrest (OHCA). We aimed to examine health care contacts in patients before OHCA compared with the general population that did not experience an OHCA. Methods and Results Patients with OHCA with a presumed cardiac cause were identified from the Danish Cardiac Arrest Registry (2001–2014) and their health care contacts (general practitioner [GP]/hospital) were examined up to 1 year before OHCA. In a case‐control study (1:9), OHCA contacts were compared with an age‐ and sex‐matched background population. Separately, patients with OHCA were examined by the contact type (GP/hospital/both/no contact) within 2 weeks before OHCA. We included 28 955 patients with OHCA. The weekly percentages of patient contacts with GP the year before OHCA were constant (25%) until 1 week before OHCA when they markedly increased (42%). Weekly percentages of patient contacts with hospitals the year before OHCA gradually increased during the last 6 months (3.5%–6.6%), peaking at the second week (6.8%) before OHCA; mostly attributable to cardiovascular diseases (21%). In comparison, there were fewer weekly contacts among controls with 13% for GP and 2% for hospital contacts ( P Conclusions The health care contacts of patients with OHCA nearly doubled leading up to the OHCA event, with more than half of patients having health care contacts within 2 weeks before arrest. This could have implications for future preventive strategies.

Aims We examined associations between symptom presentation and chance of receiving an emergency dispatch and 30-day mortality among patients with acute myocardial infarction (MI). Methods and results Copenhagen, Denmark has a 24-h non-emergency medical helpline and an emergency number 1-1-2 (equivalent to 9-1-1). Both services register symptoms/purpose of calls. Among patients with MI as either hospital diagnosis or cause of death within 72 h after a call, the primary symptom was categorized as chest pain, atypical symptoms (breathing problems, unclear problem, central nervous system symptoms, abdominal/back/urinary, other cardiac symptoms, and other atypical symptoms), unconsciousness, non-informative symptoms, and no recorded symptoms. We identified 4880 emergency and 3456 non-emergency calls from patients with MI. The most common symptom was chest pain (N = 5219) followed by breathing problems (N = 556). Among patients with chest pain, 95% (3337/3508) of emergency calls and 76% (1306/1711) of non-emergency calls received emergency dispatch. Mortality was 5% (163/3508) and 3% (49/1711) for emergency/non-emergency calls, respectively. For atypical symptoms 62% (554/900) and 17% (137/813) of emergency/non-emergency calls received emergency dispatch and mortality was 23% (206/900) and 15% (125/813). Among unconscious, patients 99%/100% received emergency dispatch and mortality was 71%/75% for emergency/non-emergency calls. Standardized 30-day mortality was 4.3% for chest pain and 15.6% for atypical symptoms, and associations between symptoms and emergency dispatch remained in subgroups of age and sex. Conclusion Myocardial infarction patients presenting with atypical symptoms when calling for help have a reduced chance of receiving an emergency dispatch and increased 30-day mortality compared to MI patients with chest pain.

Aim As proxy for initiation of the first link in the Chain of Survival by the dispatcher, we aimed to investigate the effect of time to first dispatch on 30-day survival among patients with OHCA ultimately receiving the highest-level emergency medical response. Methods We linked data on all OHCA unwitnessed by emergency medical services (EMS) treated by Copenhagen EMS from 2016 through 2018 to corresponding emergency call records. Among patients receiving highest priority emergency response, we calculated time to dispatch as time from start of call to time of first dispatch. Results We included 3548 patients with OHCA. Of these, 94.1% received the highest priority response (median time to dispatch 0.84 min, 25th–75th percentile 0.58–1.24 min). Patients with time to dispatch within one minute compared to three or more minutes were more likely to receive bystander cardiopulmonary resuscitation (77.3 vs 54.2%), bystander defibrillation (11.5 vs 6.5%) and defibrillation by emergency medical services (24.1 vs 7.5%) and were 2.6-fold more likely to survive 30 days after the OHCA (P = 0.004). Results from multivariate logistic regression were similar: odds ratio (OR) of survival 0.83 per minute increase (95% confidence interval 0.70–1.00, P = 0.04). However, survival was similar between those who received highest priority response and those who did not: OR of survival 0.88 (95% confidence interval 0.53–1.46, P = 0.61). Conclusion Rapid time to dispatch among patients with highest priority response was significantly associated with a higher probability of 30-day survival following OHCA.

Background Emergency medical dispatchers' (EMD) recognition of out-of-hospital cardiac arrest (OHCA) is an essential part of the first link in the Chain of Survival. However, it is unknown whether the time-to-recognition of OHCA by EMD during an emergency call is associated with survival. Purpose To investigate the effect of time-to-recognition on 30-day survival among patients with recognised OHCA. Methods We linked data on OHCAs occurring in the Capital Region of Denmark from 2016 through 2017 to records of corresponding emergency calls. We defined recognition as dispatching an ambulance with an appropriate priority level and subsequently defined time-to-recognition as the time from start of the call to the time of dispatching the ambulance. Among patients with recognised OHCA, we performed uni- and multivariate logistic regression to investigate the association of time-to-recognition and 30-day survival and reported odds ratios (OR) with 95% confidence intervals (CI). Results Among 2,382 patients with OHCA, 94.2% were recognised, in which median age was 73.6 years, 61.6% were males and median time-to-recognition was 0.8 minutes (interquartile range 0.7 minutes). Patients for whom time-to-recognition was up to (but not including) one minute had more than three-fold higher probability of surviving 30 days (15.5%) compared to patients for whom time-to-recognition was three or more minutes (4.5%) (Figure 1). Time-to-recognition was significantly associated with 30-day survival: OR 0.75 per minute (95% CI 0.62–0.91, P Conclusion Rapid recognition of OHCA by EMD resulted in improved survival rate of patients. This was particularly evident when time-to-recognition was three or more minutes. Figure 1 Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Hjerteforeningen