Identification of a morning out-of-hospital cardiac arrest cluster of high-incidence: towards a chrono-preventive care strategy.

RATIONALE, AIMS, AND OBJECTIVES: The human body is regulated by intrinsic factors which follow a 24-hour biological clock. Implications of a circadian rhythm in the out-of-hospital cardiac arrest (OHCA) are studied but the literature is not consistent. The main objective of our study was to identify temporal cluster of high or low incidence of OHCA occurrence during a day. METHODS: Multicentre comparative study based on the French national OHCA registry data between 2013 and 2017. After describing the population, the detection of significant temporal clusters of OHCA incidence was achieved using temporal scan statistics based on a Poisson model adjusted for age and gender. Then, comparisons between identified patients clusters and the rest of the population were performed. RESULTS: During the study, 37 163 medical OHCA victims were included. The temporal scan revealed a significant 3-hour high incidence temporal cluster between 8:00 am and 10:59 am (Relative R = 1.76, P < .001). In the identified cluster, OHCA occurred more out of the home with fewer witnesses, and advanced life support was less attempted in the cluster. No difference was observed on the return of spontaneous circulation, survival at hospital admission, and survival 30 days after the OHCA or at hospital discharge. CONCLUSIONS: We observed a three-hour morning high incidence peak of OHCA. This high incidence could be explained by different physiological changes in the morning. These changes are well known and the evidence of a morning peak of cardiovascular disease should enable medical teams to adapt care strategy and hospital organization.

Assessment of changes in cardiopulmonary resuscitation practices and outcomes on 1005 victims of out-of-hospital cardiac arrest during the COVID-19 outbreak: registry-based study.

BACKGROUND: The COVID-19 outbreak requires a permanent adaptation of practices. Cardiopulmonary resuscitation (CPR) is also involved and we evaluated these changes in the management of out-of-hospital cardiac arrest (OHCA). METHODS: OHCA of medical origins identified from the French National Cardiac Arrest Registry between March 1st and April 31st 2020 (COVID-19 period), were analysed. Different resuscitation characteristics were compared with the same period from the previous year (non-COVID-19 period). RESULTS: Overall, 1005 OHCA during the COVID-19 period and 1620 during the non-COVID-19 period were compared. During the COVID-19 period, bystanders and first aid providers initiated CPR less frequently (49.8% versus 54.9%; difference, - 5.1 percentage points [95% CI, - 9.1 to - 1.2]; and 84.3% vs. 88.7%; difference, - 4.4 percentage points [95% CI, - 7.1 to - 1.6]; respectively) as did mobile medical teams (67.3% vs. 75.0%; difference, - 7.7 percentage points [95% CI, - 11.3 to - 4.1]). First aid providers used defibrillators less often (66.0% vs. 74.1%; difference, - 8.2 percentage points [95% CI, - 11.8 to - 4.6]). Return of spontaneous circulation (ROSC) and D30 survival were lower during the COVID-19 period (19.5% vs. 25.3%; difference, - 5.8 percentage points [95% CI, - 9.0 to - 2.5]; and 2.8% vs. 6.4%; difference, - 3.6 percentage points [95% CI, - 5.2 to - 1.9]; respectively). CONCLUSIONS: During the COVID-19 period, we observed a decrease in CPR initiation regardless of whether patients were suspected of SARS-CoV-2 infection or not. In the current atmosphere, it is important to communicate good resuscitation practices to avoid drastic and lasting reductions in survival rates after an OHCA.

Socioeconomic status and incidence of cardiac arrest: a spatial approach to social and territorial disparities.

OBJECTIVE: Cardiac arrest (CA) is considered a major public health issue. Few studies have focused on geographic variations in incidence and socioeconomic characteristics. The aim of this study is to identify clusters of municipalities with high or low CA incidence, and find socioeconomic factors associated with them. PATIENTS AND METHODS: CA data from three Parisian counties, representing 123 municipalities, were extracted from the French CA registry. Socioeconomic data for each municipality were collected from the French national institute of statistics. We used a statistical approach combining Bayesian methods to study geographical CA incidence variations, and scan statistics, to identify CA incidence clusters of municipalities. Finally, we compared clusters of municipalities in terms of socioeconomic factors. RESULTS: Strong geographical variations were found among 123 municipalities: 34 presented a significantly increased risk of incidence and 37 presented a significantly low risk. Scan statistics identified seven significant spatial clusters of CA incidence, including three clusters with low incidence (the relative risk varied from 0.23 to 0.54) and four clusters with high incidence (the relative risk varied from 1.43 to 2). Clusters of municipalities with a high CA incidence are characterized by a lower socioeconomic status than the others (low and normal CA incidence clusters). Analysis showed a statistically significant relationship between social deprivation factors and high incidence. CONCLUSION: This study shows strong geographical variations in CA incidence and a statistically significant relationship between over-incidence and social deprivation variables.

Prehospital pain treatment: an economic productivity factor in emergency medicine?

RATIONALE AND OBJECTIVES: Analgesia is a recommended practice for pain treatment in prehospital emergency medicine, but all experts note suboptimal pain relief or oligoanalgesia. The increase in the Care Workload (CW) and the Medical Treatment Duration (MTD) linked to analgesia are two explanatory factors, and they are representative of the unavailability of a prehospital team. The unavailability of a team is an opportunity cost which is probably the most important cost within the framework of prehospital emergency. The aim of this study was to analyse the influence of analgesia use on the availability of prehospital emergency teams. METHODS: This study was a prospective, multicentre cohort study conducted in 10 French Mobile Emergency and Resuscitation Services (MERS) between September 2001 and June 2003. A case-control study was performed including 568 case patients who received analgesia matched with controls based on diagnosis and severity. The pairs were compared for MTD and CW. RESULTS: No significant difference between cases and controls was found concerning MTD (P = 0.134). Conversely, a difference was found for CW (P < 10(-4)), with a mean value of 53.7 Project Recherche Nursing (PRN) points for the cases and 45.8 PRN points for the controls. CONCLUSIONS: This study shows that analgesia generates an additional CW without increasing the MTD, and does not hinder the MERS teams' availability. This economic result should improve adherence to these clinical practice guidelines. Thus, analgesia appears to be a factor of productivity in the current context of economic pressures in terms of the funding of the healthcare system.

Methodological approach for the evaluation of the performances of medical intensive care units.

PURPOSE: The purpose of the study was to present a methodological approach enabling the comparison of clinical and economic performances of intensive care units and a graphical visualization based on these 2 dimensions. PATIENTS AND METHODS: A retrospective analysis of a database of 666 patients admitted in intensive care units over a period of 2 consecutive months. RESULTS: Calculation of clinical performance is based on the difference between the mortality observed and forecast from the Simplified Acute Physiology Score version 2. The evaluation of resource consumption is carried out from the measure of medical and paramedical care workload. These 2 scores are modeled on the basis of the length of stay and the severity state of the patient. The economic performance is calculated on the basis of the difference between the resource consumption observed and forecast. The graphs are constructed by taking up as coordinates the values of the clinical and economic performances of each center. CONCLUSION: These graphs enable the identification of the most deviating intensive care units to study, for example, their organizational, technical, or human resource setup accounting for their position.