Reduction in paediatric intensive care admissions during COVID-19 lockdown in Maryland, USA
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ABSTRACT:
SUBMITTER: Graciano A
PROVIDER: S-EPMC7640529 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC8335407 | biostudies-literature
Project description:Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Instead, using plasma proteomes quantifying 302 plasma protein groups at 387 timepoints in 57 critically ill patients on invasive mechanical ventilation, we found 14 proteins that showed trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81, n=49). We tested the established predictor on an independent validation cohort (AUROC of 1.0, n=24). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care.
2022-03-03 | PXD029009 | Pride
Project description:BackgroundInfluenza virus predictably causes an annual epidemic resulting in a considerable burden of illness in Australia. Children are disproportionately affected and can experience severe illness and complications, which occasionally result in death.MethodsWe conducted a retrospective descriptive study using data collated in the Australian and New Zealand Paediatric Intensive Care (ANZPIC) Registry of influenza-related intensive care unit (ICU) admissions over a 17-year period (1997-2013, inclusive) in children <16 years old. National laboratory-confirmed influenza notifications were used for comparison.ResultsBetween 1997 and 2013, a total of 704 influenza-related ICU admissions were recorded, at a rate of 6.2 per 1,000 all-cause ICU admissions. Age at admission ranged from 0 days and 15.9 years (median = 2.1 years), with 135 (19.2%) aged <6 months. Pneumonia/pneumonitis and bronchiolitis were the most common primary diagnoses among influenza-related admissions (21.9% and 13.6%, respectively). More than half of total cases (59.2%) were previously healthy (no co-morbidities recorded), and in the remainder, chronic lung disease (16.7%) and asthma (12.5%) were the most common co-morbidities recorded. Pathogen co-detection occurred in 24.7% of cases, most commonly with respiratory syncytial virus or a staphylococcal species. Median length of all ICU admissions was 3.2 days (range 2.0 hours- 107.4 days) and 361 (51.3%) admissions required invasive respiratory support for a median duration of 4.3 days (range 0.2 hours- 107.5 days). There were 27 deaths recorded, 14 (51.9%) in children without a recorded co-morbidity.ConclusionInfluenza causes a substantial number of ICU admissions in Australian children each year with the majority occurring in previously healthy children.
| S-EPMC4811543 | biostudies-literature
Project description:IntroductionIntensive care has played a pivotal role during the COVID-19 pandemic as many patients developed severe pulmonary complications. The availability of information in pediatric intensive care units (PICUs) remains limited. The purpose of this study is to characterize COVID-19 positive admissions (CPAs) in the United States and to determine factors that may impact those admissions.Materials and methodsThis is a retrospective cohort study using data from the COVID-19 Virtual Pediatric System (VPS) dashboard containing information regarding respiratory support and comorbidities for all CPAs between March and April 2020. The state-level data contained 13 different factors from population density, comorbid conditions, and social distancing score. The absolute CPA count was converted to frequency using the state's population. Univariate and multivariate regression analyses were performed to assess the association between CPA frequency and admission endpoints.ResultsA total of 205 CPAs were reported by 167 PICUs across 48 states. The estimated CPA frequency was 2.8 per million children in a one-month period. A total of 3,235 tests were conducted of which 6.3% were positive. Children above 11 years of age comprised 69.7% of the total cohort and 35.1% had moderated or severe comorbidities. The median duration of a CPA was 4.9 days (1.25-12.00 days). Out of the 1,132 total CPA days, 592 (52.2%) involved mechanical ventilation. The inpatient mortalities were 3 (1.4%). Multivariate analyses demonstrated an association between CPAs with greater population density (beta coefficient 0.01, p < 0.01). Multivariate analyses also demonstrated an association between pediatric type 1 diabetes mellitus with increased CPA duration requiring advanced respiratory support (beta coefficient 5.1, p < 0.01) and intubation (beta coefficient 4.6, p < 0.01).ConclusionsInpatient mortality during PICU CPAs is relatively low at 1.4%. CPA frequency seems to be impacted by population density. Type 1 DM appears to be associated with increased duration of HFNC and intubation. These factors should be included in future studies using patient-level data.
| S-EPMC7704189 | biostudies-literature
Project description:National (and global) vaccination provides an opportunity to control the COVID-19 pandemic, which disease suppression by societal lockdown and individual behavioural changes will not. We modelled how vaccination through the UK's vaccine priority groups impacts deaths, hospital and ICU admissions from COVID-19. We used the UK COVID-19 vaccines delivery plan and publicly available data to estimate UK population by age group and vaccination priority group, including frontline health and social care workers and individuals deemed 'extreme clinical vulnerable' or 'high risk'. Using published data on numbers and distributions of COVID-19-related hospital and ICU admissions and deaths, we modelled the impact of vaccination by age group. We then modified the model to account for hospital and ICU admission, and death among health and social care workers and the population with extreme clinical vulnerability and high risk. Our model closely matches the government's estimates for mortality after vaccination of priority groups 1-4 and groups 1-9. The model shows vaccination will have a much slower impact on hospital and ICU admissions than on deaths. The early prioritisation of healthcare staff and clinically vulnerable patients increases the impact of vaccination on admissions and also protects the healthcare service. An inflection point, when 50% of the adult population has been vaccinated - with deaths reduced by 95% and hospital admissions by 80% - may be a useful point for re-evaluating vaccine prioritisation. Our model suggests substantial reductions in hospital and ICU admissions will not occur until late March and into April 2021.
| S-EPMC8013188 | biostudies-literature
Project description:The world is in the grip of pandemic COVID-19 (SARS-CoV-2). Children appear to be only mildly affected but for those countries that are still preparing for their first wave of infections, it is salutary to have some estimates with which to plan for eventual contingencies. These assessments would include acute hospital admission requirements, intensive care admissions and deaths per given population. It is also useful to have an estimate of how many paediatric admissions to expect per given population. However it is only very recently that paediatric epidemiological data has become available. This paper will create an interactive spreadsheet model to estimate population and paediatric admissions for a given population, with the author's country, Malta, as a worked example for both.
| S-EPMC7151441 | biostudies-literature
Project description:Background: After the COVID-19 pandemic reached France in January 2020, a national lockdown including school closures was officially imposed from March 17, 2020, to May 10, 2020. Pediatric intensive care units (PICUs) admit critically ill infants, children and teenagers with severe acute conditions, in particular infectious and traumatic diseases. We hypothesized that PICU admissions would be considerably modified by the lockdown. Aims: The objectives of the study were to describe the type of admissions to French PICUs and to compare the occupation of PICU beds according to local epidemic conditions during the French national lockdown period, compared with the same period the previous year. Methods: We conducted a retrospective multicenter study in 14 French PICUs. All children aged from 7 days to 18 years admitted to one of the 14 participating PICUs over two 3-month period (March 1, 2020, to May 31, 2020 and March 1, 2019, to May 31, 2019) were included. Analysis was based on data extracted from the medicalized information systems program (a national database used in all French hospitals, into which all admissions and their diagnoses are coded for the purpose of calculating hospital funding). Each main diagnosis was reclassified in 13 categories, corresponding to normal PICU admissions. Results: We analyzed a total of 3,040 admissions, 1,323 during the 2020 study period and 1,717 during the same period in 2019. Total admissions decreased by 23% [incidence rate ratio (IRR) 0.77, 95% CI 0.71-0.83, p < 0.001], in particular for viral respiratory infections (-36%, IRR 0.64, 95% CI 0.44-0.94, p = 0.001). Admissions for almost all other diagnostic categories decreased, except intoxications and diabetes which increased, while admissions for cardiac and hemodynamic disorders were stable. Patient age and the sex ratio did not differ between the two periods. Median length of stay in the PICU was longer in 2020 [4 (IQR 2-9) vs. 3 (IQR 1-8) days, p = 0.002] in 2019. Mortality remained stable. Conclusions: In this large national study, we showed a decrease in the number of PICU admissions. The most severe patients were still admitted to intensive care and overall mortality remained stable.
| S-EPMC8709570 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) can lead to multiorgan damage and fatal outcomes. MicroRNAs (miRNAs) are detectable in blood, reflecting cell activation and tissue injury. We performed small RNA-Seq in healthy controls (N=11), non-severe (N=18) and severe (N=16) COVID-19 patients
2021-11-17 | GSE176498 | GEO
Project description:The aim of the present study is to evaluate if an independent association exists between liver enzyme elevations (LEE) and the risk of mortality or intensive care unit (ICU) admissions in patients with COVID-19. This was a single-center observational study, recruiting all consecutive adults with COVID-19. The elevation of aspartate aminotransferase (AST) or alanine aminotransferase (ALT) to the highest level between COVID-19 diagnosis and hospital discharge was categorized according to a standardized toxicity grade scale. In total, 799 patients were included in this study, 39% of which were female, with a mean age of 69.9 (±16.0) years. Of these patients, 225 (28.1%) developed LEE of grade ≥2 after a median of three days (interquartile range (IQR): 0-8 days) from the diagnosis of COVID-19, and they were estimated to have a higher hazard of death or ICU admission (adjusted hazard ratio (aHR): 1.46, 95% confidence interval (CI): 1.14-1.88). The clinical and laboratory variables associated with the development of LEE were male sex, higher respiratory rate, higher gamma glutamyl transpeptidase (GGT) and lower albumin levels at baseline. Among the analyzed treatments, steroids, tocilizumab and darunavir/ritonavir correlated with LEE. In conclusion, LEE were associated with mortality and ICU admission among COVID-19 patients. While the origin of LEE is probably multifactorial, LEE evaluation could add information to the clinical and laboratory variables that are commonly evaluated during the course of COVID-19.
| S-EPMC7766471 | biostudies-literature
Project description:We assessed the impact of COVID-19 vaccination in Italy, by estimating numbers of averted COVID-19 cases, hospitalisations, ICU admissions and deaths between January and September 2021, by age group and geographical macro areas. Timing and speed of vaccination programme implementation varied slightly between geographical areas, particularly for older adults. We estimated that 445,193 (17% of expected; range: 331,059-616,054) cases, 79,152 (32%; range: 53,209-148,756) hospitalisations, 9,839 ICU admissions (29%; range: 6,434-16,276) and 22,067 (38%; range: 13,571-48,026) deaths were prevented by vaccination.
| S-EPMC8619872 | biostudies-literature