Risk factors for severe COVID-19 in the young-before and after ICU admission.

BACKGROUND: Factors associated with severe COVID-19 and death among young adults are not fully understood, including differences between the sexes. The aim of this study was to identify factors associated with severe COVID-19 requiring intensive care and 90-day mortality among women and men below 50 years of age. METHODS: A register-based study using data from mandatory national registers, where patients with severe COVID-19 admitted to the ICU with need for mechanical ventilation (cases) between March 2020 and June 2021 were matched regarding age, sex, and district of residence with 10 population-based controls. Both the study population and the controls were divided into groups based on age (< 50 years, 50-64, and ≥ 65 years) and sex. Multivariate logistic regression models including socioeconomic factors were used to calculate odds ratios (OR) with 95% confidence intervals (CIs) for associations between severe COVID-19 in the population to compare the magnitude of the risk associations for co-morbidities in the different age categories, and subsequently factors associated with 90-day mortality among patients admitted to ICU. RESULTS: In total, 4921 cases and 49,210 controls (median age 63 years, 71% men) were included. The co-morbidities with the strongest associations with severe COVID-19 for the young population compared to older patients were chronic kidney disease (OR 6.80 [3.61-12.83]), type 2 diabetes (OR 6.31 [4.48-8.88]), hypertension (OR 5.09 [3.79-6.84]), rheumatoid arthritis (OR 4.76 [2.29-9.89]), obesity (OR 3.76 [2.88-4.92]), heart failure (OR 3.06 [1.36-6.89]), and asthma (OR 3.04 [2.22-4.16]). When comparing women vs. men < 50 years of age, stronger associations were seen for women regarding type 2 diabetes (OR 11.25 [6.00-21.08] vs OR 4.97 [3.25-7.60]) and hypertension (OR 8.76 [5.10-15.01] vs OR 4.09 [2.86-5.86]). The factors associated with 90-day mortality in the young were previous venous thromboembolism (OR 5.50 [2.13-14.22]), chronic kidney disease (OR 4.40 [1.64-11.78]) and type 2 diabetes (OR 2.71 [1.39-5.29]). These associations with 90-day mortality were foremost driven by the female population. CONCLUSION: Chronic kidney failure, type 2 diabetes, hypertension, rheumatoid arthritis, obesity, heart failure, and asthma were the strongest risk factors associated with severe COVID-19 requiring ICU-care in individuals < 50 years compared to the older population. However, after ICU admission, previous thromboembolism, chronic kidney failure, and type 2 diabetes were associated with increased 90-day mortality. The risk associations for co-morbidities were generally stronger among younger individuals compared to older and in women compared to men.

Inequalities in Income and Education Are Associated With Survival Differences After Out-of-Hospital Cardiac Arrest: Nationwide Observational Study.

BACKGROUND: Despite the acknowledged importance of socioeconomic factors as regards cardiovascular disease onset and survival, the relationship between individual-level socioeconomic factors and survival after out-of-hospital cardiac arrest is not established. Our aim was to investigate whether socioeconomic variables are associated with 30-day survival after out-of-hospital cardiac arrest. METHODS: We linked data from the Swedish Registry for Cardiopulmonary Resuscitation with individual-level data on socioeconomic factors (ie, educational level and disposable income) from Statistics Sweden. Confounding and mediating variables included demographic factors, comorbidity, and Utstein resuscitation variables. Outcome was 30-day survival. Multiple modified Poisson regression was used for the main analyses. RESULTS: A total of 31 373 out-of-hospital cardiac arrests occurring in 2010 to 2017 were included. Crude 30-day survival rates by income quintiles were as follows: Q1 (low), 414/6277 (6.6%); Q2, 339/6276 (5.4%); Q3, 423/6275 (6.7%); Q4, 652/6273 (10.4%); and Q5 (high), 928/6272 (14.8%). In adjusted analysis, the chance of survival by income level followed a gradient-like increase, with a risk ratio of 1.86 (95% CI, 1.65-2.09) in the highest-income quintile versus the lowest. This association remained after adjusting for comorbidity, resuscitation factors, and initial rhythm. A higher educational level was associated with improved 30-day survival, with the risk ratio associated with postsecondary education ≥4 years being 1.51 (95% CI, 1.30-1.74). Survival disparities by income and educational level were observed in both men and women. CONCLUSIONS: In this nationwide observational study using individual-level socioeconomic data, higher income and higher educational level were associated with better 30-day survival after out-of-hospital cardiac arrest in both sexes.

Expanding the first link in the chain of survival - Experiences from dispatcher referral of callers to AED locations.

INTRODUCTION: Early use of automated external defibrillators (AED) increases survival in cases of out-of-hospital cardiac arrest (OHCA). Dispatchers play important roles in identifying OHCA, dispatching ambulances and providing callers with telephone-assisted cardiopulmonary resuscitation. Guidelines recommend that AED registries be linked to dispatch centres as tools to refer callers to nearby AED. AIM: The aim of this study was to investigate to what extent dispatchers, when provided with a tool to display AED locations and accessibility, referred callers to nearby AED. METHODS: An application providing real-time visualization of AED locations and accessibility was implemented at four dispatch centres in Sweden. Dispatchers were instructed to refer callers to nearby AED when OHCA was suspected. Such cases were prospectively collected, and geographic information systems were used to identify those located ≤100m from an AED. Audio recordings of emergency calls were assessed to evaluate the AED referral rate. RESULTS: Between February and August 2014, 3009 suspected OHCA calls were received. In 6.6% of those calls (200/3009), an AED was ≤100m from the suspected OHCA. The AED was accessible and the caller was not alone on scene in 24% (47/200) of these cases. In two of those 47 cases (4.3%), the dispatcher referred the caller to the AED. CONCLUSION: Despite a tool for dispatchers to refer callers to a nearby AED, referral was rare. Only a minority of the suspected OHCA cases occurred ≤100m from an AED. We identified AED accessibility and callers being alone on scene as obstacles for AED referral.

Favourable cost-benefit in an early defibrillation programme using dual dispatch of ambulance and fire services in out-of-hospital cardiac arrest.

AIMS: Out-of-hospital cardiac arrest is fatal without treatment, and time to defibrillation is an extremely important factor in relation to survival. We performed a cost-benefit analysis of dual dispatch defibrillation by ambulance and fire services in the County of Stockholm, Sweden. METHODS AND RESULTS: A cost-benefit analysis was performed to evaluate the effects of dual dispatch defibrillation. The increased survival rates were estimated from a real-world implemented intervention, and the monetary value of a life ( 2.2 million) was applied to this benefit by using results from a recent stated-preference study. The estimated costs include defibrillators (including expendables/maintenance), training, hospitalisation/health care, fire service call-outs, overhead resources and the dispatch centre. The estimated number of additional saved lives was 16 per year, yielding a benefit-cost ratio of 36. The cost per quality-adjusted life years (QALY) was estimated to be 13,000, and the cost per saved life was 60,000. CONCLUSIONS: The intervention of dual dispatch defibrillation by ambulance and fire services in the County of Stockholm had positive economic effects. For the cost-benefit analysis, the return on investment was high and the cost-effectiveness showed levels below the threshold value for economic efficiency used in Sweden. The cost-utility analysis categorises the cost per QALY as medium.