Background: This systematic review synthesizes the literature on incidence of obesity during childhood. Methods: We searched PubMed, Excerpta Medica database (EMBASE), and Cumulative Index to Nursing and Allied Health Literature (CINAHL), and used the Web of Science tool in June 2015. Studies were included if they were published in English, presented results from primary or secondary analyses, used data about children in the US, provided obesity incidence data on children 0 to 18 years born after 1970, and did not pertain to clinically defined populations (disease, medication use, etc.). Author(s), study year, study design, location, sample size, age, and obesity incidence estimates were abstracted.Results: Nineteen studies were included, three of which used nationally representative data. The median study-specific annual obesity incidences among studies using U.S. Centers for Disease Control and Prevention (CDC) growth charts were 4.0%, 3.2%, and 1.8% for preschool (2.0-4.9 years), school aged (5.0-12.9 years), and adolescence (13.0-18.0 years), respectively. This pattern of declining obesity incidence with age was consistent between and within studies.Conclusions: Studies of childhood obesity in the US indicate declining incidence with age. Childhood obesity prevention efforts should be targeted to ages before obesity onset. Longitudinal data and consistent obesity definitions that correlate with long-term morbidity are needed to better characterize the life history of obesity.
These findings highlight the need for more prospective research into multicomponent physical activity interventions. Rigorous testing, including randomized controlled trials of large-scale implementations, is needed to examine how these school-based interventions might be used to improve the physical activity and fitness of larger populations of children.
Acute respiratory failure (ARF) is a common problem in medicine that utilizes significant healthcare resources and is associated with high morbidity and mortality. Classification of acute respiratory failure is complicated, and it is often determined by the level of mechanical support that is required, or the discrepancy between oxygen supply and uptake. These phenotypes make acute respiratory failure a continuum of syndromes, rather than one homogenous disease process. Early recognition of the risk factors for new or worsening acute respiratory failure may prevent that process from occurring. Predictive analytical methods using machine learning leverage clinical data to provide an early warning for impending acute respiratory failure or its sequelae. The aims of this review are to summarize the current literature on ARF prediction, to describe accepted procedures and common machine learning tools for predictive tasks through the lens of ARF prediction, and to demonstrate the challenges and potential solutions for ARF prediction that can improve patient outcomes.
We report 2 fatal exacerbations of systemic capillary leak syndrome (SCLS), also known as Clarkson disease, associated with coronavirus disease (COVID-19) in the United States. One patient carried an established diagnosis of SCLS and the other sought treatment for new-onset hypotensive shock, hemoconcentration, and anasarca, classic symptoms indicative of an SCLS flare. Both patients had only mild-to-moderate symptoms of COVID-19. This clinical picture suggests that these patients succumbed to complications of SCLS induced by infection with severe acute respiratory syndrome coronavirus 2. Persons with known or suspected SCLS may be at increased risk for developing a disease flare in the setting of mild-to-moderate COVID-19 infection.
BackgroundA prospective, multi-center study (RECON) was conducted to evaluate the clinical outcomes of pericardial closure using a decellularized extracellular matrix (ECM) graft derived from porcine small intestinal submucosa.MethodsPatients indicated for open cardiac surgery with pericardial closure using ECM were eligible for the RECON study cohort. Postoperative complications and readmission of the RECON patients were compared to the patient cohort in the Nationwide Readmissions Database (NRD). Inverse probability of treatment weighting was used to control the differences in patient demographics, comorbidities, and risk factors.ResultsA total of 1420 patients at 42 centers were enrolled, including 923 coronary artery bypass grafting (CABG) surgeries and 436 valve surgeries. Significantly fewer valve surgery patients in the RECON cohort experienced pleural effusion (3.1% vs. 13.0%; p < 0.05) and pericardial effusion (1.5% vs. 2.6%; p < 0.05) than in the NRD cohort. CABG patients in the RECON cohort were less likely to suffer bleeding (1.2% vs. 2.9%; p < 0.05) and pericardial effusion (0.2% vs. 2.2%, p < 0.05) than those in the NRD cohort. The 30-day all-cause hospital readmission rate was significantly lower among RECON patients than NRD patients following both valve surgery (HR: 0.34; p < 0.05) and CABG surgery (HR: 0.42; p < 0.05). In the RECON study, 14.4% of CABG patients and 27.0% of valve patients had postoperative atrial fibrillation as compared to previously reported risks, which generally ranges from 20 to 30% after CABG and from 35 to 50% after valve surgery.ConclusionsPericardial closure with ECM following cardiac surgery is associated with a reduction in the proportion of patients with pleural effusion, pericardial effusion, and 30-day readmission compared to a nationwide database.Trial registrationNCT02073331, Registered on February 27, 2014.Electronic supplementary materialThe online version of this article (10.1186/s13019-019-0871-5) contains supplementary material, which is available to authorized users.
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