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- Drake, TM, et al.
(author)
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Surgical site infection after gastrointestinal surgery in children: an international, multicentre, prospective cohort study
- 2020
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In: BMJ global health. - : BMJ. - 2059-7908. ; 5:12
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Journal article (peer-reviewed)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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- Petkov, S, et al.
(author)
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Short-term oral pre-exposure prophylaxis against HIV-1 modulates the transcriptome of foreskin tissue in young men in Africa
- 2022
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In: Frontiers in immunology. - : Frontiers Media SA. - 1664-3224. ; 13, s. 1009978-
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Journal article (peer-reviewed)abstract
- Whilst short-term oral pre-exposure prophylaxis (PrEP) with antiretroviral drugs in men who have sex with men has shown protection against HIV-1 infection, the impact of this regimen on the in vivo foreskin transcriptome is unknown. We collected foreskin tissue after voluntary medical male circumcision from 144 young men (72 from Uganda and 72 from South Africa) randomized to one to two doses of either oral tenofovir (TFV) disoproxil fumarate (FTC-TDF) or tenofovir alafenamide (FTC-TAF) or no drug (untreated controls). This novel approach allowed us to examine the impact of short-term oral PrEP on transcriptome of the male genital tract. A single dose of FTC-TDF did not affect the foreskin transcriptome in relation to control arm, however one dose of FTC-TAF induced upregulation of four genes AKAP8, KIAA0141, HSCB and METTL17. Following two doses of either FTC-TDF or FTC-TAF, there was an increase in 34 differentially expressed genes for FTC-TDF and 15 for FTC-TAF, with nine DEGs in common: KIAA0141, SAFB2, CACTIN, FXR2, AKAP8, HSCB, CLNS1A, DDX27 and DCAF15. Functional analysis of differentially expressed genes revealed modulation of biological processes related to mitochondrial stress (KIAA0141, HSCB and METTL17), anti-viral and anti-inflammatory pathways (CACTIN and AKAP8). Our results show that short-course on-demand oral PrEP in men modulates genes in foreskin tissue which are likely unfavorable to HIV acquisition and replication. We also describe an upregulated expression of genes involved in diverse mitochondria biology which may potentially result in worsened mitochondria-related. These results warrant further studies to assess the role of short-course and prolonged oral PrEP on biological processes of the foreskin mucosa.
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- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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- Thomas, HS, et al.
(author)
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- 2019
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swepub:Mat__t
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