An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources

Neonatal Hyperbilirubinemia. Evidence for a Role of the Erythrocyte Enzyme Activities Involved in the Detoxification of Oxygen Radicals

Determinations of erythrocyte enzyme scavengers of oxygen radicals (glutathione-peroxidase, superoxide-dismutase and catalase) and determinations of erythrocytes age-dependent glycolytic activities (glucose-6-phosphatedehydrogenase, pyruvate-kinase and glucose-phosphate-isomerase) were carried out in cord blood and in the blood taken on the 4th day of life in 152 newborn infants with different peak bilirubin levels. The enzyme activities scavenging oxygen radicals, glutathione-peroxidase and superoxide-dismutase were significantly lower in infants with peak bilirubinemia higher than 214 μmol/l, compared to less-jaundiced neonates, both at birht and on the 4th day of life; their values correlated negatively with peak bilirubinemia at birth and on the 4th day of life. Glycolytic age-dependent enzyme activities were significantly higher in more jaundiced newborn infants only on the 4th day of life, when their values correlated positively with peak bilirubinemia. The results of this investigation suggest that a deficiency of factors protecting from oxygen toxicity, may play a role in the development of neonatal hemolysis and jaundice

Body mass index and complications following major gastrointestinal surgery: a prospective, international cohort study and meta-analysis.

AIM: Previous studies reported conflicting evidence on the effects of obesity on outcomes after gastrointestinal surgery. The aims of this study were to explore the relationship of obesity with major postoperative complications in an international cohort and to present a meta-analysis of all available prospective data. METHODS: This prospective, multicentre study included adults undergoing both elective and emergency gastrointestinal resection, reversal of stoma or formation of stoma. The primary end-point was 30-day major complications (Clavien-Dindo Grades III-V). A systematic search was undertaken for studies assessing the relationship between obesity and major complications after gastrointestinal surgery. Individual patient meta-analysis was used to analyse pooled results. RESULTS: This study included 2519 patients across 127 centres, of whom 560 (22.2%) were obese. Unadjusted major complication rates were lower in obese vs normal weight patients (13.0% vs 16.2%, respectively), but this did not reach statistical significance (P = 0.863) on multivariate analysis for patients having surgery for either malignant or benign conditions. Individual patient meta-analysis demonstrated that obese patients undergoing surgery for malignancy were at increased risk of major complications (OR 2.10, 95% CI 1.49-2.96, P < 0.001), whereas obese patients undergoing surgery for benign indications were at decreased risk (OR 0.59, 95% CI 0.46-0.75, P < 0.001) compared to normal weight patients. CONCLUSIONS: In our international data, obesity was not found to be associated with major complications following gastrointestinal surgery. Meta-analysis of available prospective data made a novel finding of obesity being associated with different outcomes depending on whether patients were undergoing surgery for benign or malignant disease