Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Emergence and persistence of hantavirus in rodent reservoirs role of glucocorticoid hormone /

Rodent-borne hantaviruses have received considerable attention in recent years due to the high mortality rate in humans that their infections cause. Anthropogenic stressors are key factors in the emergence of hantavirus-associated diseases. Urbanization, deforestation, noise pollution, artificial lighting and electromagnetic fields are the most common forms of human impact on the environment. An increased systemic concentration of the immunosuppressive class of steroid hormone glucocorticoid is a frequent consequence of chronic anthropogenic stress. Elevated glucocorticoid levels play a crucial role in modulating immune tolerance of rodents, thereby enabling establishment of the host-pathogen interaction. Glucocorticoids support virus persistence in the reservoir host by activating an organ-specific regulatory response mediated by T regulatory lymphocytes to reduce inflammatory and antiviral responses, principally via production of cytokines interleukin-10 and transforming growth factor-β. In-depth analysis of this mechanism would help to understand how rodents maintain a disease-free condition. This may have implications for a cost-effective intervention strategy against hantavirus and other zoonotic human pathogens

Effects of anthropogenic events and viral persistence on rodent reservoirs of hantavirus infection understanding host-pathogen interactions facilitates novel approaches to intervention strategies /

Hantaviruses are primarily rodent-borne pathogens which have received considerable attention recently due to their high mortality rates in humans. In order to find the causes of rapid transmission and emergence of hantavirus-associated diseases anthropogenic changes are a priority. These include deforestation, urbanization, noise pollution, light pollution and electromagnetic fields, all of which have been shown to profoundly affect rodent physiology and immunology. Moreover, anthropogenic events promote human-rodent co-habitation and thereby provide a driver to increase rates of transmission and, by extrapolation, levels of infection in humans. Such environmental disruption acts as a chronic stressor to rodents and causes elevated concentrations of glucocorticoids, which are a major class of immunosuppressive hormone. Glucocorticoids are responsible for altering the immune tolerance of rodents, thereby rendering them susceptible to infection. Glucocorticoids induce regulatory T lymphocytes to reduce inflammatory and antiviral responses and to activate regulatory responses, principally through production of the cytokines interleukin-10 and transforming growth factor-β to support viral persistence. In order to develop a low-cost intervention strategy for hantavirus infection consideration should be given to a systemic approach to therapy. This would both aim to achieve a reduction of anthropogenic stressors and to gain a greater understanding of host-pathogen interactions

Dengue epidemiology and pathogenesis: Images of the future viewed through a mirror of the past

Taylor-Robinson, AW ORCiD: 0000-0001-7342-8348Every year, millions of individuals throughout the world are seriously affected by dengue virus. The unavailability of a vaccine and of anti-viral drugs has made this mosquito-borne disease a serious health concern. Not only does dengue cause fatalities but it also has a profoundly negative economic impact. In recent decades, extensive research has been performed on epidemiology, vector biology, life cycle, pathogenesis, vaccine development and prevention. Although dengue research is still not at a stage to suggest definite hopes of a cure, encouraging significant advances have provided remarkable progress in the fight against infection. Recent developments indicate that both anti-viral drug and vaccine research should be pursued, in parallel with vector control programs

An artificial neural network classification method employing longitudinally monitored immune biomarkers to predict the clinical outcome of critically ill COVID-19 patients

Background The severe form of COVID-19 can cause a dysregulated host immune syndrome that might lead patients to death. To understand the underlying immune mechanisms that contribute to COVID-19 disease we have examined 28 different biomarkers in two cohorts of COVID-19 patients, aiming to systematically capture, quantify, and algorithmize how immune signals might be associated to the clinical outcome of COVID-19 patients. Methods The longitudinal concentration of 28 biomarkers of 95 COVID-19 patients was measured. We performed a dimensionality reduction analysis to determine meaningful biomarkers for explaining the data variability. The biomarkers were used as input of artificial neural network, random forest, classification and regression trees, k-nearest neighbors and support vector machines. Two different clinical cohorts were used to grant validity to the findings. Results We benchmarked the classification capacity of two COVID-19 clinicals studies with different models and found that artificial neural networks was the best classifier. From it, we could employ different sets of biomarkers to predict the clinical outcome of COVID-19 patients. First, all the biomarkers available yielded a satisfactory classification. Next, we assessed the prediction capacity of each protein separated. With a reduced set of biomarkers, our model presented 94% accuracy, 96.6% precision, 91.6% recall, and 95% of specificity upon the testing data. We used the same model to predict 83% and 87% (recovered and deceased) of unseen data, granting validity to the results obtained. Conclusions In this work, using state-of-the-art computational techniques, we systematically identified an optimal set of biomarkers that are related to a prediction capacity of COVID-19 patients. The screening of such biomarkers might assist in understanding the underlying immune response towards inflammatory diseases