The early experiences of a single tertiary Italian emergency department treating COVID-19 in children.
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ABSTRACT:
SUBMITTER: Brisca G
PROVIDER: S-EPMC7361914 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Around 42,000 children suffer from severe sepsis each year in the US alone, resulting in significant morbidity, mortality and billion dollar expenditures in the US healthcare system. Sepsis recognition is a clinical challenge in children. Biomarkers are needed to tailor appropriate antimicrobial therapies and improve risk stratification. The goal of this study was to determine if gene expression profiles from peripheral blood were associated with pathogen type and sepsis severity in children treated for suspected sepsis.
2020-01-01 | GSE119217 | GEO
Project description:The restrictive measures required to face the recent outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may impact patterns of healthcare utilization. Our aim was to provide an insight into the change in the use of a pediatric emergency department (ED) during the SARS-CoV-2 pandemic. The medical records of the children seen in our pediatric ED during March and April 2020 were retrospectively reviewed. Consequently, these were compared to the medical records of 2018 and 2019 from the same time period and from other control periods (January-February 2019 and 2020, and July-August 2018 and 2019). The total number of ED visits declined by 73% from 2019 to 2020 (3051 vs 818). Significant variations were observed in the distribution of children between triage categories: the proportion of patients who was given a green-code showed a 0.59-fold decrease in comparison to 2019 (95% CI 0.5-0.69), while a relative increase in the proportion of yellow codes was observed (OR 1.46, 95% CI 1.2-1.78).Conclusion: Quarantine measures significantly impacted on the total number of patients and on the reasons for visiting them in our pediatric ED. This substantial decrease in pediatric care may either be due to lower rates of acute infections because of social distancing, or to parents' or caregivers' reticence to risk exposure to SARS-CoV-2 in a health-care setting. What is known: • A recent outbreak of a novel coronavirus responsible for a severe acute respiratory syndrome is spreading globally. • Restrictive measures may impact patterns of healthcare utilization, as observed in other previous outbreaks. What is new: • This study shows significant variations in the distribution of children among triage categories during the COVID-19 pandemic. • Discharge diagnosis was significantly different as well, in particular a relative increase in the proportion of children presenting with traumatic injuries and a decrease of viral infections were observed.
| S-EPMC7787709 | biostudies-literature
Project description:BackgroundAcute asthma in children can be life-threatening and must be treated promptly in the emergency setting. Intravenous magnesium sulfate is recommended by various guidelines for cases of acute asthma that have not responded to first-line treatment with bronchodilators and steroids. The treatment has recently been shown to reduce the need for hospital admission for adults compared with placebo, but it is unclear whether it is equally effective for children.ObjectivesTo assess the safety and efficacy of intravenous magnesium sulfate (IV MgSO4) in children treated for acute asthma in the emergency department (ED).Search methodsWe identified studies by searching the Cochrane Airways Review Group Specialised Register up to 23 February 2016. We also searched ClinicalTrials.gov and reference lists of other reviews, and we contacted study authors to ask for additional information.Selection criteriaWe included randomised controlled trials of children treated in the ED for exacerbations of asthma if they compared any dose of IV MgSO4 with placebo.Data collection and analysisTwo review authors screened the results of the search and independently extracted data from studies meeting the inclusion criteria. We resolved disagreements through discussion and contacted study authors in cases of missing data and other uncertainties relating to the studies.We analysed dichotomous data as odds ratios and continuous data as mean differences, both using fixed-effect models. We assessed each study for risk of bias and rated the quality of evidence for each outcome with GRADE and presented the results in a 'Summary of findings' table. There was insufficient evidence to conduct the planned subgroup analyses.Main resultsFive studies (182 children) met the inclusion criteria, and four contributed data to at least one meta-analysis. The included studies were overall at low risk of bias, but our confidence in the evidence was generally low, mainly due to the small sample sizes. Treatment with IV MgSO4 reduced the odds of admission to hospital by 68% (odds ratio (OR) 0.32, 95% confidence interval (CI) 0.14 to 0.74; children = 115; studies = 3; I(2) = 63%). This result was based on data from just three studies including 115 children. Meta-analysis for the secondary outcomes was extremely limited by paucity of data. We performed meta-analysis for the outcome 'return to the emergency department within 48 hours', which showed a very imprecise effect estimate that was not statistically significant (OR 0.40, 95% CI 0.02 to 10.30; children = 85; studies = 2; I(2) = 0%). Side effects and adverse events were not consistently reported and meta-analysis was not possible, however few side effects or adverse events were reported.Authors' conclusionsIV MgSO4 may reduce the need for hospital admission in children presenting to the ED with moderate to severe exacerbations of asthma, but the evidence is extremely limited by the number and size of studies. Few side effects of the treatment were reported, but the data were extremely limited.
| S-EPMC6599814 | biostudies-literature
Project description:ObjectiveProning has been shown to improve oxygenation and mortality in certain populations of intubated patients with acute respiratory distress syndrome. Small observational analyses of COVID-19 patients suggest awake proning may lead to clinical improvement. Data on safety and efficacy is lacking. We sought to describe the effect of proning on oxygenation in nonintubated COVID-19 patients. We also evaluated feasibility, safety, and other physiological and clinical outcomes associated with this intervention.MethodsWe conducted a prospective, observational cohort study of nonintubated patients with COVID-19 who underwent proning per an Emergency Department (ED) clinical protocol. Patients with mild to moderate respiratory distress were included. We calculated change in oxygenation by comparing the oxygen saturation to fraction of inspired oxygen ratio (SpO2:FiO2) during the five minutes prior to proning and first 30 min of proning. We also captured data on respiratory rate, duration of proning, need for intubation, intensive care unit admission, survival to discharge.ResultsFifty-two patients were enrolled. Thirty were excluded for not meeting protocol inclusion criteria or missing baseline oxygenation data, leaving 22 for analysis. The SpO2:FiO2 ratio increased by a median of 5 (IQR: 0-15) in the post-proning period compared to the pre-proning period (median: 298 (IQR: 263-352) vs 295 (IQR: 276-350), p = 0.01). Respiratory rate did not change significantly between time periods. No immediate adverse events occurred during proning. Five patients (23%) were intubated within 48 h of admission.ConclusionEarly, awake proning may be feasible in select COVID-19 patients and was associated with improved oxygenation.
| S-EPMC7713606 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) is a pandemic overwhelming the health care systems worldwide. Lung ultrasound (LUS) use has been proposed to identify suspected COVID-19 patients and direct them to the isolation area in the emergency department (ED) or to discharge them for outpatient treatment.ObjectiveOur aim was to retrospectively investigate the use of LUS in the ED to identify COVID-19 pneumonia (CP).MethodsWe performed a retrospective single-center study including all patients accessing the ED who underwent LUS examination for suspicion of COVID-19 during the initial outbreak. Demographics, clinical parameters, laboratory values, imaging features, and outcome variables were collected. The receiver operating characteristic (ROC) curve was used to evaluate diagnostic accuracy.ResultsA total of 41% patients were COVID-19-positive; 67% of them were diagnosed with CP. The ROC curve of the LUS score showed an area under the curve of 0.837 (95% CI 0.75-0.92) and with a cutoff value ≥3 identified 28 of 31 patients with CP and 11 of 15 without (sensitivity 90%, 95% CI 74-97%; specificity 75%, 95% CI 56-76%). LUS in combination with nasopharyngeal swab has a sensitivity of 100% (95% CI 74-97%) and a specificity of 61% (95% CI 44-67%).ConclusionsLUS is a promising technique for early identification of CP in patients who accessed the ED in an active epidemic time. The LUS score shows a sensitivity of 90% for CP, allowing to quickly direct patients with COVID-19 to the ED isolation area or to discharge them for outpatient treatment.
| S-EPMC7801958 | biostudies-literature
Project description:BackgroundResponses to the COVID-19 pandemic include strict public health measures, such as national lockdowns. During these measures, paediatric emergency department attendances have declined and the prevalence of presenting complaints has changed. This study sought to identify whether dog bite attendance and victim demographics changed during COVID-19 public health measures.MethodsAn audit was conducted of emergency department attendance data from a UK tertiary paediatric hospital between January 2016 and September 2020. Dog bite attendance and victim demographics were explored using χ2 tests and multivariable Poisson regression. The mean monthly percentage of attendance due to dog bites in 2020 was compared against predicted percentages based on previous years' data.ResultsDog bite attendance rose in conjunction with the introduction of COVID-19 public health measures and reached a peak in July 2020 (44 dog bites, 1.3% of all attendances were due to dog bites). This was a threefold increase in dog bite attendance. By September 2020, attendance had returned to normal. The demographic profile of child dog bite victims remained the same. Boys had the highest attendance rates in 7-12 year-olds, girls in 4-6 year-olds. Girls showed higher attendance rates in the summer, while boys' attendance rates were constant throughout the year. COVID-19 public health measures were associated with a 78% increase in attendance for boys and a 66% increase in girls.ConclusionsCOVID-19 national public health measures were associated with an increase in paediatric emergency department dog bite attendance, and may be due to increased child exposure to dogs via 'stay at home' orders and school closures. National lockdowns are likely to continue globally throughout the COVID-19 pandemic; this is likely to result in more dog bites. Urgent public health communication and injury prevention strategies are needed to help prevent these avoidable injuries.
| S-EPMC8023759 | biostudies-literature
Project description:BackgroundTriage implementation in resource-limited emergency departments (EDs) has traditionally relied on intensive in-person training. This study sought to evaluate the impact of a novel digital-based learning strategy focused on the Interagency Integrated Triage Tool, a three-tier triage instrument recommended by the World Health Organization.MethodsA mixed methods study utilising pre-post intervention methods was conducted in two EDs in Papua New Guinea. The primary outcome was the mean change in knowledge before and after completion of a voluntary, multimodal training program, primarily delivered through a digital learning platform accessible via smartphone. Secondary outcomes included the change in confidence to perform selected clinical tasks, and acceptability of the learning methods.FindingsAmong 136 eligible ED staff, 91 (66.9%) completed the digital learning program. The mean knowledge score on the post-training exam was 87.5% (SD 10.4), a mean increase of 12.9% (95% CI 10.7-15.1%, p < 0.0001) from the pre-training exam. There were statistically significant improvements in confidence for 13 of 15 clinical tasks, including undertaking a triage assessment and identifying an unwell patient.In an evaluation survey, 100% of 30 respondents agreed or strongly agreed the online learning platform was easy to access, use and navigate, and that the digital teaching methods were appropriate for their learning needs. In qualitative feedback, respondents reported that limited internet access and a lack of dedicated training time were barriers to participation.InterpretationThe use of digital learning to support triage implementation in resource-limited EDs is feasible and effective when accompanied by in-person mentoring. Adequate internet access is an essential pre-requisite.FundingDevelopment of the Kumul Helt Skul learning platform was undertaken as part of the Clinical Support Program (Phase II), facilitated by Johnstaff International Development on behalf of the Australian Government Department of Foreign Affairs and Trade through the PNG-Australia Partnership. RM is supported by a National Health and Medical Research Council Postgraduate Scholarship and a Monash Graduate Excellence Scholarship, while PC is supported by a Medical Research Future Fund Practitioner Fellowship. Funders had no role in study design, results analysis or manuscript preparation.
| S-EPMC9901330 | biostudies-literature
Project description:BackgroundExtensive literature has shown an association of Adverse Childhood Experiences (ACEs) with adverse health outcomes; however, its ability to predict events or stratify risks is less known. Individuals with mental illness and ACE exposure have been shown to visit emergency departments (ED) more often than those in the general population. This study thus examined the ability of the ACEs checklist to predict ED visits within the subsequent year among children and adolescents presenting to mental health clinics with pre-existing mental health issues.MethodsThe study analyzed linked data (n = 6100) from two databases provided by Alberta Health Services (AHS). The Regional Access and Intake System (RAIS 2016-2018) database provided data on the predictors (ACE items, age, sex, residence, mental health program type, and primary diagnosis) regarding children and adolescents (aged 0-17 years) accessing addiction and mental health services within Calgary Zone, and the National Ambulatory Care Reporting System (NACRS 2016-2019) database provided data on ED visits. A 25% random sample of the data was reserved for validation purposes. Two Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression models, each employing a different method to tune the shrinkage parameter lambda (namely cross-validated and adaptive) and performing 10-fold cross-validation for a set of 100 lambdas in each model were examined.ResultsThe adaptive LASSO model had a slightly better fit in the validation dataset than the cross-validated model; however, it still demonstrated poor discrimination (AUC 0.60, sensitivity 37.8%, PPV 49.6%) and poor calibration (over-triaged in low-risk and under-triaged in high-risk subgroups). The model's poor performance was evident from an out-of-sample deviance ratio of - 0.044.ConclusionThe ACEs checklist did not perform well in predicting ED visits among children and adolescents with existing mental health concerns. The diverse causes of ED visits may have hindered accurate predictions, requiring more advanced statistical procedures. Future studies exploring other machine learning approaches and including a more extensive set of childhood adversities and other important predictors may produce better predictions. Furthermore, despite highly significant associations being observed, ACEs may not be deterministic in predicting health-related events at the individual level, such as general ED use.
| S-EPMC8465692 | biostudies-literature
Project description:Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 million estimated deaths worldwide. While epidemiological and clinical characteristics of COVID-19 have been reported, risk factors underlying the transition from mild to severe disease among patients remain poorly understood. In this retrospective study, we analysed data of 879 confirmed SARS-CoV-2 positive patients admitted to a two-site NHS Trust hospital in London, England, between January 1st and May 26th, 2020, with a majority of cases occurring in March and April. We extracted anonymised demographic data, physiological clinical variables and laboratory results from electronic healthcare records (EHR) and applied multivariate logistic regression, random forest and extreme gradient boosted trees. To evaluate the potential for early risk assessment, we used data available during patients' initial presentation at the emergency department (ED) to predict deterioration to one of three clinical endpoints in the remainder of the hospital stay: admission to intensive care, need for invasive mechanical ventilation and in-hospital mortality. Based on the trained models, we extracted the most informative clinical features in determining these patient trajectories. Considering our inclusion criteria, we have identified 129 of 879 (15%) patients that required intensive care, 62 of 878 (7%) patients needing mechanical ventilation, and 193 of 619 (31%) cases of in-hospital mortality. Our models learned successfully from early clinical data and predicted clinical endpoints with high accuracy, the best model achieving area under the receiver operating characteristic (AUC-ROC) scores of 0.76 to 0.87 (F1 scores of 0.42-0.60). Younger patient age was associated with an increased risk of receiving intensive care and ventilation, but lower risk of mortality. Clinical indicators of a patient's oxygen supply and selected laboratory results, such as blood lactate and creatinine levels, were most predictive of COVID-19 patient trajectories. Among COVID-19 patients machine learning can aid in the early identification of those with a poor prognosis, using EHR data collected during a patient's first presentation at ED. Patient age and measures of oxygenation status during ED stay are primary indicators of poor patient outcomes.
| S-EPMC7892838 | biostudies-literature
Project description:The aim of this study was to record the demographic and epidemiological data on adult patients with headache who attend the emergency department (ED) and the diagnoses that made by the neurologists in the ED of a tertiary care hospital in metropolitan Thessaloniki (Greece). In an open prospective study, demographic and epidemiological data were collected on all patients who reported headache (as chief complaint or not) and presented to the ED of Papageorgiou Hospital between August 2007 and July 2008. Headache patients accounted for 1.3% of all ED patients and for 15.5% of patients primarily referred to the ED neurologist. Tension type headache was the most frequent diagnosis, followed by secondary headaches and migraine. The large number of patients without final ED diagnosis and ward admission for further evaluation sheds a light on the immense workload of Greek ED physicians. Furthermore, we found evidence for the misuse of Emergency Medical Services by chronic headache patients. These findings indicate shortcomings in the pre-hospital (primary care) management of headache patients in the Greek National Health System to an extent unreported so far.
| S-EPMC3452293 | biostudies-literature