Severe acute respiratory syndrome coronavirus-2-related and imputable deaths in children:results from the French pediatric national registry

Background Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)is responsible for an important mortality rate worldwide.We aimed to evaluate the actual imputability of SARS-CoV-2 on the mortality rate associated with SARS-CoV-2-related illnesses in the pediatric intensive care unit(PICU).Secondary objectives were to identify risk factors for death.Methods This national multicenter comparative study comprised all patients under 18 years old with positive SARS-CoV-2 polymerase chain reactions(PCRs)[acute corona virus disease 2019(COVID-19)or incidental SARS-CoV-2 infection]and/or pediatric inflammatory multisystem syndrome(PIMS)recorded in the French PICU registry(PICURe)between September 1,2021,and August 31,2022.Included patients were classified and compared according to their living status at the end of their PICU stay.Deceased patients were evaluated by four experts in the field of pediatric infectiology and/or pediatric intensive care.The imputability of SARS-CoV-2 as the cause of death was classified into four categories:certain,very probable,possible,or unlikely,and was defined by any of the first three categories.Results There were 948 patients included of which 43 died(4.5%).From this,26 deaths(67%)could be attributed to SARS-CoV-2 infection,with an overall mortality rate of 2.8%.The imputability of death to SARS-CoV-2 was considered certain in only one case(O.1%).Deceased patients suffered more often from comorbidities,especially heart disease,neurological disorders,hematological disease,cancer,and obesity.None of the deceased patients were admitted for pediatric inflam-matory multisystem syndrome(PIMS).Mortality risk factors were male gender,cardiac comorbidities,cancer,and acute respiratorydistress syndrome.Conclusions SARS-CoV-2 mortality in the French pediatric population was low.Even though the imputability of SARS-Cov-2 on mortality was considered in almost two-thirds of cases,this imputability was considered certain in only one case.

Artificial intelligence in healthcare:past,present and future

Artificial intelligence(AI)aims to mimic human cognitive functions.It is bringing a paradigm shift to healthcare,powered by increasing availability of healthcare data and rapid progress of analytics techniques.We survey the current status of AI applications in healthcare and discuss its future.AI can be applied to various types of healthcare data(structured and unstructured).Popular AI techniques include machine learning methods for structured data,such as the classical support vector machine and neural network,and the modern deep learning,as well as natural language processing for unstructured data.Major disease areas that use AI tools include cancer,neurology and cardiology.We then review in more details the AI applications in stroke,in the three major areas of early detection and diagnosis,treatment,as well as outcome prediction and prognosis evaluation.We conclude with discussion about pioneer AI systems,such as IBM Watson,and hurdles for real-life deployment of AI.

Ambulatory blood pressure profile and stroke recurrence

Objectives To establish a new ambulatory blood pressure(ABP)parameter(24-hour ABP profile)and evaluated its performance on stroke outcome in ischaemic stroke(IS)or transient ischaemic attack(TIA)patients.Methods The prospective cohort consisted of 1996 IS/TIA patients enrolled for ABP monitoring and a 3-month follow-up for stroke recurrence as outcome.Profile groups of systolic blood pressure(SBP)were identified via an advanced functional clustering method,and the associations of the profile groups and conventional ABP parameters with stroke recurrence were examined in a Cox proportional hazards model.Results Three discrete profile groups(n=604,781 and 611 in profiles 1,2 and 3,respectively)in 24-hour ambulatory SBP were identified.Profile 1 resembled most to the normal diurnal blood pressure pattern;profile 2 also dropped at night,but climbed earlier and with higher morning surge;while profile 3 had sustained higher nocturnal SBP without significant nocturnal SBP decline.The incidence of stroke recurrence was 2.9%,3.9%and 5.5%in profiles 1,2 and 3,respectively.After adjustment for covariates,profile 3 was significantly associated with higher risk of stroke recurrence with profile 1 as reference(HR 1.76,95%CI:1.00 to 3.09),while no significant difference was observed between profiles 2 and 1(HR 1.22,95%CI:0.66 to 2.25).None of conventional ABP parameters showed significant associations with the outcome.Conclusions Ambulatory 24-hour SBP profile is associated with short-term stroke recurrence.Profiles of ABP may help improve identification of stroke recurrence by capturing the additive effects of individual ABP parameters.