Connecting omics signatures and revealing biological mechanisms with iLINCS.

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.

Pandemic-Related Shifts in New Patients Admitted to Children's Hospitals.

OBJECTIVES: During the coronavirus disease 2019 pandemic, professional organizations recommended preferential transfer of pediatric patients from general hospitals to children's hospitals. Patients previously receiving all care at other facilities would be new to children's hospitals. As a proxy for care consolidation, we sought to describe changes in new patient encounters at children's hospitals and test associations between local severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidences and new patient encounters. METHODS: This retrospective cohort study included patients aged 6 months to 18 years admitted to children's hospitals from March 15, 2019, to June 30, 2019 (control) and 2020 (pandemic period). Primary outcome was odds ratio of being a new versus established patient by study period. Generalized linear models estimated odds of being a new patient with adjustment for diagnosis. Analyses were also stratified by local SARS-CoV-2 transmission. RESULTS: There were 205 283 encounters (45.3% new patients). New patients were more common in the pandemic period than in the control (46.4 vs 44.7%, OR 1.07, 95% confidence interval [CI]: 1.05 to 1.09). After adjusting for diagnosis, pandemic new patients were no more common than control new patients (adjusted odds ratio 1.00, 95% CI: 0.98 to 1.02). Compared with hospitals experiencing low local SARS-CoV-2 transmission, admission encounters at both medium and high transmission hospitals were more likely to be new (adjusted odds ratio 1.08, 95% CI: 1.03 to 1.14 and 1.09, 95% CI: 1.03 to 1.15, respectively). CONCLUSIONS: During the early coronavirus disease 2019 pandemic, proportional increases in new patients to children's hospitals appeared to be due to changes in diagnoses but were also associated with local SARS-CoV-2 transmission. Pediatric care consolidation may have occurred; how this may have impacted outcomes for hospitalized children is unclear.

Safety Events in Children's Hospitals During the COVID-19 Pandemic.

BACKGROUND AND OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has impacted hospitals, potentially affecting quality and safety. Our objective was to compare pediatric hospitalization safety events during the pandemic versus previous years. METHODS: In this retrospective cohort study of hospitalizations in the Pediatric Health Information System, we compared Pediatric Quality Indicator (PDI) rates from March 15 to May 31, 2017-2019 (pre-COVID-19), with those from March 15 to May 31, 2020 (during COVID-19). Generalized linear mixed-effects models with adjustment for patient characteristics (eg, diagnosis, clinical severity) were used. RESULTS: There were 399 113 discharges pre-COVID-19 and 88 140 during COVID-19. Unadjusted PDI rates were higher during versus pre-COVID-19 for overall PDIs (6.39 vs 5.05; P < .001). In adjusted analyses, odds of postoperative sepsis were higher during COVID-19 versus pre-COVID-19 (adjusted odds ratio 1.28 [95% confidence interval 1.04-1.56]). The remainder of the PDIs did not have increased adjusted odds during compared with pre-COVID-19. CONCLUSIONS: Postoperative sepsis rates increased among children hospitalized during COVID-19. Efforts are needed to improve safety of postoperative care for hospitalized children.