Analysis of the impact of the SARS-CoV-2 infection on the pediatric population hospitalized during the pandemic in the Greater Paris University Hospitals

BackgroundThe clinical characteristics, disease progression and outcome in children affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection appear significantly milder compared to older individuals. Nevertheless, the trends in hospitalization and clinical characteristics in the pediatric population seem to be different over time across the different epidemic waves.ObjectiveOur aim was to understand the impact of the different COVID-19 variants in the pediatric population hospitalized in the Pediatric Departments of the Public Hospital in the Greater Paris area by the analysis performed with the Assistance Publique-Hopitaux de Paris (AP-HP) Health Data Warehouse.MethodsThis is a retrospective cohort study including 9,163 patients under 18 years of age, hospitalized from 1 March 2020 to 22 March 2022, in the Paris area, with confirmed infection by SARS-CoV-2. Three mutually exclusive groups with decreasing severity (Pediatric Inflammatory Multisystem Syndrome (PIMS), symptomatic infection, mild or asymptomatic infection) were defined and described regarding demography, medical history, complication of the SARS-CoV-2 infection, and treatment during admission. Temporal evolution was described by defining three successive waves (March–September 2020, October 2020–October 2021, and November 2021–March 2022) corresponding to the emergence of the successive variants.ResultsIn the study period, 9,163 pediatric patients with SARS-CoV-2 infection were hospitalized in 21 AP-HP hospitals. The number of patients with SARS-CoV-2 infection increased over time for each wave of the pandemic (the mean number of patients per month during the first wave was 332, 322 during the 2nd, and 595 during the third wave). In the medical history, the most associated concomitant disease was chronic respiratory disease. Patients hospitalized during the third wave presented a higher incidence of pulmonary involvement (10.2% compared to 7% and 6.5% during the first and second waves, respectively). The highest incidence of PIMS was observed during the first and second waves (4.2% in the first and second waves compared to 2.3% in the 3rd wave).DiscussionThis analysis highlighted the high incidence of hospitalized children in the Greater Paris Area during the third wave of SARS-CoV-2 pandemic corresponding to the Omicron Covid-19 variant, which is probably an expression of a concomitant SARS-CoV-2, while a decreased incidence of PIMS complication was observed during the same period

Discrete-time optimal control of electric hot water tank

International audienceThe paper exposes a discrete time model with three states to represent the dynamics of an Electric Hot Water Tank (EHWT). This models stands halfway between distributed parameters equations and totally lumped single integrators. It allows a faithful reproduction of observed behaviors, especially those induced by stratification. It is also instrumental in formulating optimal control problems aiming at maximizing performance under comfort constraints. In particular, it is shown how to recast such problems as a Mixed-Integer Linear Program (MILP) so that the problem can be solved with off-the-shelf software packages. Numerical results are presented

Dynamical modeling for electric hot water tank

International audienceTo quantify the potential of electric hot water tanks (EHWT) in general demand response programs, there is a need for models with prediction capabilities at a reasonable computational cost. As can be experimentally observed, the input-output response of EHWT is relatively complex. This paper presents two models of EHWT, one in the form of two simple one-dimensional partial differential equations and the other as a hybrid system decoupling the phenomena acting on the EHWT, in sequences. An experimental validation compares the performance of these models. The conclusion is that the hybrid model is more accurate and less computationally intensive

An optimization algorithm for load-shifting of large sets of electric hot water tanks

International audienceLarge sets of Electric Hot Water Tanks (EHWT) found in numerous countries appear as very relevant for load-shifting applications. An EHWT heats water over relatively long periods of time, for later consumption. The simple time-of-use pricing strategy applied to most consumers increases the overall electricity consumption in the beginning of the night, while hot water is used much later, in the next daytime. With the development of home automation, more advanced strategies could enable improved cost-reductions for both users and the electricity producer. An efficient and robust improvement is to reschedule each EHWT heating, while keeping the heating periods undivided (to minimize the malicious impacts of complex dynamic effects taking place inside each EHWT), so that an objective load curve for the whole set of EHWT is reached. The first contribution of this article is to formulate the rescheduling of EHWT heating with comfort constraints as an optimization problem. The second contribution is a heuristic to solve this problem with less than 1% optimality loss for representative test cases with large sets of EHWT (typically hundreds of thousands)

Statistical properties of domestic hot water consumption

International audienceThis article studies some of the statistical properties of domestic hot water (DHW) consumption. The study is based on experimental data obtained for a group of households, over a 1 year period. To describe the consumptions, we consider three representative statistical properties of the drain sequence associated to each household: i) the distribution of the magnitude of the drains, ii) a daily pattern of the start times of consumptions, iii) the time between two successive drains. A remarkable outcome of the study is that the time between two successive drains follows a bimodal Weibull distribution. This opens perspectives for piloting applications

Modeling populations of electric hot water tanks with Fokker-Planck equations

International audienceThis article proposes a distributed parameters model for a pool of electric hot water tanks (EHWT). EHWT are electric appliances found in numerous homes where they produce hot water for domestic usages. Designing smart piloting for them requires a careful description of several variables of interest and their dynamics. When the number of such devices is large, these dynamics can be lumped into Fokker-Planck equations. In this case, these equations are driven by in-domain control which defines the heating policies in a stochastic manner. The main contribution of this article is the Fokker-Planck model of a pool of EHWT

Observational Study of Chlorpromazine in Hospitalized Patients with Covid-19 Running title: Chlorpromazine in hospitalized patients with Covid-19

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External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals

International audiencePurposeThe Coronavirus disease 2019 (COVID-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for COVID-19.MethodsWe used “COVID-19 Evidence Alerts” (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicenter cohort of adult patients hospitalized for COVID-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer.ResultsWe included 14,343 consecutive patients, 2583 (18%) died and 5067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC > 0.75 to predict in-hospital mortality; 2 had an AUC > 0.70 to predict the composite outcome.ConclusionSeven prognostic scores were fairly accurate to predict death in hospitalized COVID-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients

Obesity Doubles Mortality in Patients Hospitalized for Severe Acute Respiratory Syndrome Coronavirus 2 in Paris Hospitals, France: A Cohort Study on 5,795 Patients

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