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- Drake, TM, et al.
(författare)
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Surgical site infection after gastrointestinal surgery in children: an international, multicentre, prospective cohort study
- 2020
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Ingår i: BMJ global health. - : BMJ. - 2059-7908. ; 5:12
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Tidskriftsartikel (refereegranskat)abstract
- Surgical site infection (SSI) is one of the most common healthcare-associated infections (HAIs). However, there is a lack of data available about SSI in children worldwide, especially from low-income and middle-income countries. This study aimed to estimate the incidence of SSI in children and associations between SSI and morbidity across human development settings.MethodsA multicentre, international, prospective, validated cohort study of children aged under 16 years undergoing clean-contaminated, contaminated or dirty gastrointestinal surgery. Any hospital in the world providing paediatric surgery was eligible to contribute data between January and July 2016. The primary outcome was the incidence of SSI by 30 days. Relationships between explanatory variables and SSI were examined using multilevel logistic regression. Countries were stratified into high development, middle development and low development groups using the United Nations Human Development Index (HDI).ResultsOf 1159 children across 181 hospitals in 51 countries, 523 (45·1%) children were from high HDI, 397 (34·2%) from middle HDI and 239 (20·6%) from low HDI countries. The 30-day SSI rate was 6.3% (33/523) in high HDI, 12·8% (51/397) in middle HDI and 24·7% (59/239) in low HDI countries. SSI was associated with higher incidence of 30-day mortality, intervention, organ-space infection and other HAIs, with the highest rates seen in low HDI countries. Median length of stay in patients who had an SSI was longer (7.0 days), compared with 3.0 days in patients who did not have an SSI. Use of laparoscopy was associated with significantly lower SSI rates, even after accounting for HDI.ConclusionThe odds of SSI in children is nearly four times greater in low HDI compared with high HDI countries. Policies to reduce SSI should be prioritised as part of the wider global agenda.
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- Abbafati, Cristiana, et al.
(författare)
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- 2020
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Tidskriftsartikel (refereegranskat)
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| 6. |
- Mansouri, Kamel, et al.
(författare)
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CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity
- 2020
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Ingår i: Journal of Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 128:2, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast (TM) metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast (TM)/Tox21 HTS in vitro assays.RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of similar to 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment.
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