The Impacts of COVID-19 Pandemic on the Food Sector and on Supermarket Employees in France during the First Lockdown Period.

During the first lockdown period due to the COVID-19 pandemic, from the 17 March 2020 to the 11 May 2020 in France, essential professionals (nursing staff, police officers, supermarket staff, etc.) continued to be physically present at their workplaces. The present study focuses on exploring impacts of the pandemic on supermarket staff and on the food sector in France: COVID transmission among supermarket workers, working conditions, food supply, etc. For that, two anonymous surveys were addressed to supermarket employees and to supermarket supervisors. In total, 1746 responses from employees and 171 responses from supervisors were recorded all over France. Over 70% of employees and almost 50% of supervisors were women and over 50% of employees were between 25 and 40 years old. The following main trends in terms of physical and psychological impacts are revealed: 7% of employees working during the lockdown reported having COVID, although a still poorly developed screening and lack of diagnostic tests during the first lockdown should be kept in mind. The working conditions changed; higher work load, a more stressful environment, inappropriate client attitude, a lack of recognition, fatigue, and shortages were reported. A lack of government recognition, namely no prime allocations to supermarket staff during the lockdown period, is also often mentioned. Finally, no priority was given for store employees in terms of childcare.

Impact of puberty as threshold to differentiate outcome of out-of-hospital cardiac arrest care groups: a nationwide observational study in France.

BACKGROUND: Since 2005, the international guidelines for out-of-hospital cardiac arrest (OHCA) use puberty to differentiate paediatric and adult care. This threshold is mainly relied on the more frequent respiratory aetiologies in children. Hitherto, to the best of our knowledge, no study has compared the characteristics and outcomes of non-pubescent children, adolescents and adult patients with OHCA. In this study, we intended to describe the characteristics, outcome and factors associated with survival of patients who experienced OHCA in the three groups: children, adolescents (pubescent<18 years) and adults (<65 years), to assess the pertinence of the guidelines. METHODS: Data from the French national cardiac arrest registry (2012-2017) were used in this nationwide observational study. Victims of OHCA who were <65 years old were included. The characteristics and outcomes of children and adolescents, and adolescents and adults were compared. Logistic regression was performed in each group to identify factors associated with survival at day 30. RESULTS: We included 934 children, 433 adolescents and 26 952 adults. Respiratory aetiology was more frequent and shockable rhythm less frequent in children compared with adolescents (25.5% vs 17.2%, p=0.025 and 2.4% vs 6.8%, p<0.001, respectively). However, these differences were not observed between adolescents and adults (17.2% vs 14.1%, p=0.266 and 6.8% vs 10%, p=0.055, respectively). Between children and adolescents, and adolescents and adults, there was no significant difference in survival at day 30 (8.6%vs 9.8% and 9.8% vs 8.5%, respectively). For all groups, shockable initial rhythm was a factor of survival. CONCLUSION: Frequency of respiratory aetiologies and shockable rhythm were common in adolescents and adults and different between children and adolescents. These results indicate that puberty as a threshold in international guidelines seems to be relevant.

Can We Define Termination Of Resuscitation Criteria In Out-Of-Hospital Hanging?

OBJECTIVE: Survival rate of cardiac arrest due to hanging (H-CA) victims is low. Hence, this leads to the question of the utility of resuscitation in these patients. The objective was to investigate whether there are predictive criteria for survival with a good neurological outcome or predictive criteria for non-survival or survival with a poor neurological outcome enabling us to define the termination of resuscitation rules in these patients. METHODS: Between July 1, 2011 and January 1, 2016, we included 1,689 out-of-hospital cardiac arrests due to hanging. We compared the characteristics of survivors with a good neurological outcome at day 30 with the others. RESULTS: The study population was mainly composed of males with a median age of 48 [37-60]. The overall survival was 2.1%, among which 48.6% had a good neurological outcome. Survivors benefited more often from immediate basic life support than the rest of the subjects, which was corroborated by the shorter no-flow durations. We did not record any difference in terms of advanced cardiac life support initiation frequency and technique between survivors with a good neurological outcome and the rest. Nevertheless, ACLS duration was longer in survivors with a good neurological outcome than in others. CONCLUSIONS: Basic life support (BLS) was the decisive criterion for 15/17 survivors. However, a detailed analysis showed 2 survivors presenting no BLS before the arrival of mobile medical teams and non-shockable rhythms who survived at day 30 with a good neurological outcome. These results lead us to consider that mobile medical team intervention and ACLS attempt are not futile, and the benefit justifies the cost. Thus, we cannot define any rule for the termination of resuscitation.

Traumatic cardiac arrest is associated with lower survival rate vs. medical cardiac arrest - Results from the French national registry.

INTRODUCTION: The survival from traumatic vs. medical out-of-hospital cardiac arrest (OHCA) are not yet well described. The objective of this study was to compare survival to hospital discharge and 30-day survival of non-matched and matched traumatic and medical OHCA cohorts. MATERIAL & METHODS: National case-control, multicentre study based on the French national cardiac arrest registry. Following descriptive analysis, we compared survival rates of traumatic and medical cardiac arrest patients after propensity score matching. RESULTS: Compared with medical OHCA (n = 40,878) trauma victims (n = 3209) were younger, more likely to be male and away from home at the time and less likely to be resuscitated. At hospital admission and at 30 days their survival odds were lower (OR: respectively 0.456 [0.353;0.558] and 0.240 [0.186;0.329]). After adjustment the survival odds for traumatic OHCA were 2.4 times lower at admission (OR: 0.416 [0.359;0.482]) and 6 times lower at day 30 (OR: 0.168 [0.117;0.241]). CONCLUSIONS: The survival rates for traumatic OHCA were lower than for medical OHCA, with wider difference in matched vs. non-matched cohorts. Although the probability of survival is lower for trauma victims, the efforts are not futile and pre-hospital resuscitation efforts seem worthwhile.

PFIM 4.0, an extended R program for design evaluation and optimization in nonlinear mixed-effect models.

BACKGROUND AND OBJECTIVE: Nonlinear mixed-effect models (NLMEMs) are increasingly used for the analysis of longitudinal studies during drug development. When designing these studies, the expected Fisher information matrix (FIM) can be used instead of performing time-consuming clinical trial simulations. The function PFIM is the first tool for design evaluation and optimization that has been developed in R. In this article, we present an extended version, PFIM 4.0, which includes several new features. METHODS: Compared with version 3.0, PFIM 4.0 includes a more complete pharmacokinetic/pharmacodynamic library of models and accommodates models including additional random effects for inter-occasion variability as well as discrete covariates. A new input method has been added to specify user-defined models through an R function. Optimization can be performed assuming some fixed parameters or some fixed sampling times. New outputs have been added regarding the FIM such as eigenvalues, conditional numbers, and the option of saving the matrix obtained after evaluation or optimization. Previously obtained results, which are summarized in a FIM, can be taken into account in evaluation or optimization of one-group protocols. This feature enables the use of PFIM for adaptive designs. The Bayesian individual FIM has been implemented, taking into account a priori distribution of random effects. Designs for maximum a posteriori Bayesian estimation of individual parameters can now be evaluated or optimized and the predicted shrinkage is also reported. It is also possible to visualize the graphs of the model and the sensitivity functions without performing evaluation or optimization. RESULTS: The usefulness of these approaches and the simplicity of use of PFIM 4.0 are illustrated by two examples: (i) an example of designing a population pharmacokinetic study accounting for previous results, which highlights the advantage of adaptive designs; (ii) an example of Bayesian individual design optimization for a pharmacodynamic study, showing that the Bayesian individual FIM can be a useful tool in therapeutic drug monitoring, allowing efficient prediction of estimation precision and shrinkage for individual parameters. CONCLUSION: PFIM 4.0 is a useful tool for design evaluation and optimization of longitudinal studies in pharmacometrics and is freely available at http://www.pfim.biostat.fr.

Evolution of Survival in Cardiac Arrest with Age in Elderly Patients: Is Resuscitation a Dead End?

BACKGROUND: Even if age is not considered the key prognostic factor for survival in cardiac arrest (CA), some studies question whether cardiopulmonary resuscitation (CPR) in the elderly could be futile. OBJECTIVE: The aim of this study was to describe differences in out-of-hospital CA survival rates according to age stratification based on the French National CA registry (RéAC). The second objective was to analyze the differences in resuscitation interventions according to age. METHODS: We performed a retrospective cohort study based on data extracted from the RéAC. All 18,249 elderly patients (>65 years old) with non-traumatic CA recorded between July 2011 and March 2015 were included. Patients' ages were stratified into 5-year increments. RESULTS: Cardiopulmonary resuscitation (CPR) was started significantly more often in younger patients (p = 0.019). Ventilation and automated external defibrillation by bystanders were started without any difference between age subgroups (p = 0.147 and p = 0.123, respectively). No difference in terms of rate of external chest compressions or ventilation initiation was found between the subgroups (p = 0.357 and p = 0.131, respectively). Advanced cardiac life support was started significantly more often in younger patients (p = 0.023). Total CPR duration, return of spontaneous circulation, and survival at hospital admission and at 30 days or hospital discharge decreased significantly with age (p < 10-3). The survival decrease was linear, with a loss of 3% survival chances each 5-year interval. CONCLUSIONS: This study found that survival in older persons decreased linearly by 3% every 5 years. However, this diminished rate of survival could be the consequence of a shorter duration and less advanced life support.

Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology.

PURPOSE: In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e., when no adaptation is performed, using wrong prior parameters. METHODS: We evaluated two one-stage designs, ξ0 and ξ*, optimised for prior and true population parameters, Ψ0 and Ψ*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ξ0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from Ψ*. RESULTS: Estimation results of two-stage ADs and ξ * were close and much better than those obtained with ξ 0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three- and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design. CONCLUSIONS: Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement.

Influence of covariance between random effects in design for nonlinear mixed-effect models with an illustration in pediatric pharmacokinetics.

Nonlinear mixed-effect models are used increasingly during drug development. For design, an alternative to simulations is based on the Fisher information matrix. Its expression was derived using a first-order approach, was then extended to include covariance and implemented into the R function PFIM. The impact of covariance on standard errors, amount of information, and optimal designs was studied. It was also shown how standard errors can be predicted analytically within the framework of rich individual data without the model. The results were illustrated by applying this extension to the design of a pharmacokinetic study of a drug in pediatric development.

Optimal sampling times for a drug and its metabolite using SIMCYP(®) simulations as prior information.

BACKGROUND: Since 2007, it is mandatory for the pharmaceutical companies to submit a Paediatric Investigation Plan to the Paediatric Committee at the European Medicines Agency for any drug in development in adults, and it often leads to the need to conduct a pharmacokinetic study in children. Pharmacokinetic studies in children raise ethical and methodological issues. Because of limitation of sampling times, appropriate methods, such as the population approach, are necessary for analysis of the pharmacokinetic data. The choice of the pharmacokinetic sampling design has an important impact on the precision of population parameter estimates. Approaches for design evaluation and optimization based on the evaluation of the Fisher information matrix (M(F)) have been proposed and are now implemented in several software packages, such as PFIM in R. OBJECTIVES: The objectives of this work were to (1) develop a joint population pharmacokinetic model to describe the pharmacokinetic characteristics of a drug S and its active metabolite in children after intravenous drug administration from simulated plasma concentration-time data produced using physiologically based pharmacokinetic (PBPK) predictions; (2) optimize the pharmacokinetic sampling times for an upcoming clinical study using a multi-response design approach, considering clinical constraints; and (3) evaluate the resulting design taking data below the lower limit of quantification (BLQ) into account. METHODS: Plasma concentration-time profiles were simulated in children using a PBPK model previously developed with the software SIMCYP(®) for the parent drug and its active metabolite. Data were analysed using non-linear mixed-effect models with the software NONMEM(®), using a joint model for the parent drug and its metabolite. The population pharmacokinetic design, for the future study in 82 children from 2 to 18 years old, each receiving a single dose of the drug, was then optimized using PFIM, assuming identical times for parent and metabolite concentration measurements and considering clinical constraints. Design evaluation was based on the relative standard errors (RSEs) of the parameters of interest. In the final evaluation of the proposed design, an approach was used to assess the possible effect of BLQ concentrations on the design efficiency. This approach consists of rescaling the M(F), using, at each sampling time, the probability of observing a concentration BLQ computed from Monte-Carlo simulations. RESULTS: A joint pharmacokinetic model with three compartments for the parent drug and one for its active metabolite, with random effects on four parameters, was used to fit the simulated PBPK concentration-time data. A combined error model best described the residual variability. Parameters and dose were expressed per kilogram of bodyweight. Reaching a compromise between PFIM results and clinical constraints, the optimal design was composed of four samples at 0.1, 1.8, 5 and 10 h after drug injection. This design predicted RSE lower than 30 % for the four parameters of interest. For this design, rescaling M(F) for BLQ data had very little influence on predicted RSE. CONCLUSION: PFIM was a useful tool to find an optimal sampling design in children, considering clinical constraints. Even if it was not forecasted initially by the investigators, this approach showed that it was really necessary to include a late sampling time for all children. Moreover, we described an approach to evaluate designs assuming expected proportions of BLQ data are omitted.