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Out-of-hospital cardiac arrest (OHCA) is a leading cause of global mortality. Regional variations in reporting frameworks and survival mean the exact burden of OHCA to public health is unknown. Nevertheless, overall prognosis and neurological outcome are relatively poor following OHCA and have remained almost static for the past three decades. In this Series paper, we explore the aetiology of OHCA. Coronary artery disease remains the predominant cause, but there is a diverse range of other potential cardiac and non-cardiac causes to be aware of. Additionally, we describe how investigators and key stakeholders in resuscitation science have formulated specific Utstein data element domains in an attempt to standardise the definitions and outcomes reported in OHCA research so that management pathways can be improved. Finally, we identify the predictors of survival after OHCA and what primary and secondary prevention strategies can be instigated to mitigate the devastating sequelae of this growing public health issue.

On February 28, 2020, public health officials in the Seattle area were informed of a Covid-19 infection at a long-term care facility. An investigation identified 167 infected persons associated with the facility, including residents, health care personnel, and visitors; more than a third of the 101 residents identified died.

Type I interferons (IFN-α and IFN-β) are important for protection against many viral infections, whereas type II interferon (IFN-γ) is essential for host defense against some bacterial and parasitic pathogens. Study of IFN responses in human leprosy revealed an inverse correlation between IFN-β and IFN-γ gene expression programs. IFN-γ and its downstream vitamin D—dependent antimicrobial genes were preferentially expressed in self-healing tuberculoid lesions and mediated antimicrobial activity against the pathogen Mycobacterium leprae in vitro. In contrast, IFN-β and its downstream genes, including interleukin-10 (IL-10), were induced in monocytes by M. leprae in vitro and preferentially expressed in disseminated and progressive lepromatous lesions. The IFN-γ—induced macrophage vitamin D—dependent antimicrobial peptide response was inhibited by IFN-β and by IL-10, suggesting that the differential production of IFNs contributes to protection versus pathogenesis in some human bacterial infections.

In this trial, over 23,000 patients with out-of-hospital cardiac arrest were assigned to standard CPR with a chest compression-to-ventilation ratio of 30:2 or to continuous chest compressions. There was no significant between-group difference in survival to hospital discharge. Standard cardiopulmonary resuscitation (CPR) consists of manual chest compressions to maintain blood flow and positive-pressure ventilation to maintain oxygenation until spontaneous circulation is restored. 1 Chest compressions are interrupted frequently by ventilations given as rescue breathing during the treatment of out-of-hospital cardiac arrest. 2 – 4 These interruptions reduce blood flow and potentially reduce the effectiveness of CPR. 5 One strategy to reduce the interruption of compressions is to provide asynchronous positive-pressure ventilation while not pausing for ventilations. The interruption of chest compressions has been associated with decreased survival in animals with cardiac arrest. 6 In nonasphyxial arrest, continuous compressions were as effective as compressions . . .

Abstract Rationale Severe sepsis is common and highly morbid, yet the epidemiology of severe sepsis at the frontier of the health care system—pre-hospital emergency care—is unknown. Objectives We examined the epidemiology of pre-hospital severe sepsis among emergency medical services (EMS) encounters, relative to acute myocardial infarction and stroke. Methods Retrospective study using a community-based cohort of all nonarrest, nontrauma King County EMS encounters from 2000 to 2009 who were transported to a hospital. Measurements and Main Results Overall incidence rate of hospitalization with severe sepsis among EMS encounters, as well as pre-hospital characteristics, admission diagnosis, and outcomes. Among 407,176 EMS encounters, we identified 13,249 hospitalizations for severe sepsis, of whom 2,596 died in the hospital (19.6%). The crude incidence rate of severe sepsis was 3.3 per 100 EMS encounters, greater than for acute myocardial infarction or stroke (2.3 per 100 and 2.2 per 100 EMS encounters, respectively). More than 40% of all severe sepsis hospitalizations arrived at the emergency department after EMS transport, and 80% of cases were diagnosed on admission. Pre-hospital care intervals, on average, exceeded 45 minutes for those hospitalized with severe sepsis. One-half or fewer of patients with severe sepsis were transported by paramedics (n = 7,114; 54%) or received pre-hospital intravenous access (n = 4,842; 37%). Conclusions EMS personnel care for a substantial and increasing number of patients with severe sepsis, and spend considerable time on scene and during transport. Given the emphasis on rapid diagnosis and intervention for sepsis, the pre-hospital interval may represent an important opportunity for recognition and care of sepsis.

Stewart Cole and colleagues report the genome sequence and comparative analyses of Brazilian, Indian, North American and Thai strains of Mycobacterium leprae , the etiologial agent of leprosy. They define 16 sub-types of M. leprae and examine their geographical distribution. Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae , an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6× coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38× coverage) and NHDP63 (46× coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy.

Triggering antimicrobial mechanisms in macrophages infected with intracellular pathogens, such as mycobacteria, is critical to host defense against the infection. To uncover the unique and shared antimicrobial networks induced by the innate and adaptive immune systems, gene expression profiles generated by RNA sequencing (RNAseq) from human monocyte-derived macrophages (MDMs) activated with TLR2/1 ligand (TLR2/1L) or IFN-γ were analyzed. Weighed gene correlation network analysis identified modules of genes strongly correlated with TLR2/1L or IFN-γ that were linked by the \"defense response\" gene ontology term. The common TLR2/1L and IFN-γ inducible human macrophage host defense network contained 16 antimicrobial response genes, including S100A12, which was one of the most highly induced genes by TLR2/1L. There is limited information on the role of S100A12 in infectious disease, leading us to test the hypothesis that S100A12 contributes to host defense against mycobacterial infection in humans. We show that S100A12 is sufficient to directly kill Mycobacterium tuberculosis and Mycobacterium leprae. We also demonstrate that S100A12 is required for TLR2/1L and IFN-γ induced antimicrobial activity against M. leprae in infected macrophages. At the site of disease in leprosy, we found that S100A12 was more strongly expressed in skin lesions from tuberculoid leprosy (T-lep), the self-limiting form of the disease, compared to lepromatous leprosy (L-lep), the progressive form of the disease. These data suggest that S100A12 is part of an innate and adaptive inducible antimicrobial network that contributes to host defense against mycobacteria in infected macrophages.

Low socioeconomic status is associated with poor cardiovascular health. We evaluated the association between socioeconomic status and the incidence of sudden cardiac arrest, a condition that accounts for a substantial proportion of cardiovascular-related deaths, in seven large North American urban populations. Using a population-based registry, we collected data on out-of-hospital sudden cardiac arrests occurring at home or at a residential institution from Apr. 1, 2006, to Mar. 31, 2007. We limited the analysis to cardiac arrests in seven metropolitan areas in the United States (Dallas, Texas; Pittsburgh, Pennsylvania; Portland, Oregon; and Seattle–King County, Washington) and Canada (Ottawa and Toronto, Ontario; and Vancouver, British Columbia). Each incident was linked to a census tract; tracts were classified into quartiles of median household income. A total of 9235 sudden cardiac arrests were included in the analysis. For all sites combined, the incidence of sudden cardiac arrest in the lowest socioeconomic quartile was nearly double that in the highest quartile (incidence rate ratio [IRR] 1.9, 95% confidence interval [CI] 1.8–2.0). This disparity was greater among people less than 65 years old (IRR 2.7, 95% CI 2.5–3.0) than among those 65 or older (IRR 1.3, 95% CI 1.2–1.4). After adjustment for study site and for population age structure of each census tract, the disparity across socioeconomic quartiles for all ages combined was greater in the United States (IRR 2.0, 95% CI 1.9–2.2) than in Canada (IRR 1.8, 95% CI 1.6–2.0) (p < 0.001 for interaction). The incidence of sudden cardiac arrest at home or at a residential institution was higher in poorer neighbourhoods of the US and Canadian sites studied, although the association was attenuated in Canada. The disparity across socioeconomic quartiles was greatest among people younger than 65. The association between socioeconomic status and incidence of sudden cardiac arrest merits consideration in the development of strategies to improve survival from sudden cardiac arrest, and possibly to identify opportunities for prevention.

Out-of-hospital cardiac arrest is a leading cause of death worldwide. Rapid diagnosis and initiation of cardiopulmonary resuscitation (CPR) is the cornerstone of therapy for victims of cardiac arrest. Yet a significant fraction of cardiac arrest victims have no chance of survival because they experience an unwitnessed event, often in the privacy of their own homes. An under-appreciated diagnostic element of cardiac arrest is the presence of agonal breathing, an audible biomarker and brainstem reflex that arises in the setting of severe hypoxia. Here, we demonstrate that a support vector machine (SVM) can classify agonal breathing instances in real-time within a bedroom environment. Using real-world labeled 9-1-1 audio of cardiac arrests, we train the SVM to accurately classify agonal breathing instances. We obtain an area under the curve (AUC) of 0.9993 ± 0.0003 and an operating point with an overall sensitivity and specificity of 97.24% (95% CI: 96.86–97.61%) and 99.51% (95% CI: 99.35–99.67%). We achieve a false positive rate between 0 and 0.14% over 82 h (117,985 audio segments) of polysomnographic sleep lab data that includes snoring, hypopnea, central, and obstructive sleep apnea events. We also evaluate our classifier in home sleep environments: the false positive rate was 0–0.22% over 164 h (236,666 audio segments) of sleep data collected across 35 different bedroom environments. We prototype our proof-of-concept contactless system using commodity smart devices (Amazon Echo and Apple iPhone) and demonstrate its effectiveness in identifying cardiac arrest-associated agonal breathing instances played over the air.