| 1. |
- Ademuyiwa, Adesoji O., et al.
(author)
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Determinants of morbidity and mortality following emergency abdominal surgery in children in low-income and middle-income countries
- 2016
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In: BMJ Global Health. - : BMJ Publishing Group Ltd. - 2059-7908. ; 1:4
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Journal article (peer-reviewed)abstract
- Background: Child health is a key priority on the global health agenda, yet the provision of essential and emergency surgery in children is patchy in resource-poor regions. This study was aimed to determine the mortality risk for emergency abdominal paediatric surgery in low-income countries globally.Methods: Multicentre, international, prospective, cohort study. Self-selected surgical units performing emergency abdominal surgery submitted prespecified data for consecutive children aged <16 years during a 2-week period between July and December 2014. The United Nation's Human Development Index (HDI) was used to stratify countries. The main outcome measure was 30-day postoperative mortality, analysed by multilevel logistic regression.Results: This study included 1409 patients from 253 centres in 43 countries; 282 children were under 2 years of age. Among them, 265 (18.8%) were from low-HDI, 450 (31.9%) from middle-HDI and 694 (49.3%) from high-HDI countries. The most common operations performed were appendectomy, small bowel resection, pyloromyotomy and correction of intussusception. After adjustment for patient and hospital risk factors, child mortality at 30 days was significantly higher in low-HDI (adjusted OR 7.14 (95% CI 2.52 to 20.23), p<0.001) and middle-HDI (4.42 (1.44 to 13.56), p=0.009) countries compared with high-HDI countries, translating to 40 excess deaths per 1000 procedures performed.Conclusions: Adjusted mortality in children following emergency abdominal surgery may be as high as 7 times greater in low-HDI and middle-HDI countries compared with high-HDI countries. Effective provision of emergency essential surgery should be a key priority for global child health agendas.
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| 2. |
- Alesi, Simon, et al.
(author)
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Efficacy and safety of anti-androgens in the management of polycystic ovary syndrome: a systematic review and meta-analysis of randomised controlled trials.
- 2023
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In: EClinicalMedicine. - 2589-5370. ; 63
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Journal article (peer-reviewed)abstract
- Anti-androgens and combined oral contraceptive pills (COCPs) may mitigate hyperandrogenism-related symptoms of polycystic ovary syndrome (PCOS). However, their efficacy and safety in PCOS remain unclear as previous reviews have focused on non-PCOS populations. To inform the 2023 International Evidence-based Guideline in PCOS, we conducted the first systematic review and meta-analysis investigating the efficacy and safety of anti-androgens in the management of hormonal and clinical features of PCOS.We systematically searched MEDLINE, Embase, PsycInfo, All EBM reviews, and CINAHL up to 28th June 2023 for randomised controlled trials (RCTs) examining oral anti-androgen use, alone or in combination with metformin, COCPs, lifestyle, or other interventions, in women of any age, with PCOS diagnosed by Rotterdam, National Institutes of Health or Androgen Excess & PCOS Society criteria, and using a form of contraception. Non-English studies and studies of less than 6 months duration or which used the same anti-androgen regimen in both/all groups were excluded in order to establish efficacy for the clinical outcomes of interest. Three authors screened articles against selection criteria and assessed risk of bias and quality using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. Critical outcomes (prioritised during guideline development for GRADE purposes) included weight, body mass index (BMI), irregular cycles, hirsutism, liver function, and quality of life. Random effects meta-analyses were conducted where appropriate. This study is registered with PROSPERO, CRD42022345640.From 1660 studies identified in the search, 27 articles comprising 20 unique studies were included. Of these, 13 studies (n=961) were pooled in meta-analysis. Seven studies had a high risk of bias, nine moderate and four low. Anti-androgens included finasteride, flutamide, spironolactone, or bicalutamide. In meta-analysis, anti-androgens+lifestyle were superior to metformin+lifestyle for hirsutism (weighted mean difference [WMD] [95% CI]:-1.59 [-3.06,-0.12], p=0.03; I2=74%), SHBG (7.70nmol/l [0.75, 14.66], p=0.03; I2=0%), fasting insulin and fasting insulin: glucose ratio (-2.11 μU/ml [-3.97,-0.26], p=0.03; I2=0% and-1.12 [-1.44,-0.79], p<0.0001, I2=0%, respectively), but were not superior to placebo+lifestyle for hirsutism (-0.93, [-3.37, 1.51], p=0.45; I2=76%) or SHBG (9.72nmol/l [-0.71, 20.14], p=0.07; I2=31%). Daily use was more effective for hirsutism than use every three days (-3.48 [-4.58,-2.39], p<0.0001, I2=1%), and resulted in lower androstenedione levels (-0.30ng/ml [-0.50,-0.10], p=0.004; I2=0%). Combination treatment with anti-androgens+metformin+lifestyle resulted in lower testosterone compared with metformin+lifestyle (-0.29nmol/l [-0.52,-0.06], p=0.01; I2=61%), but there were no differences in hirsutism when anti-androgens+metformin+lifestyle were compared with either anti-androgens+lifestyle or metformin+lifestyle. In limited meta-analyses (n=2 trials), combining anti-androgens with COCP resulted in poorer lipid profiles compared with COCP±placebo, with no differences in other outcomes.Current evidence does not support the use of anti-androgens preferentially to COCPs to treat hyperandrogenism in PCOS. Anti-androgens could be considered to treat hirsutism in PCOS, where COCPs are contraindicated, poorly tolerated, or present a sub-optimal response after a minimum 6-month period, with consideration of clinical context and individual risk factors and characteristics.National Health and Medical Research Council (NHMRC) of Australia Monash University.
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| 3. |
- Belsti, Yitayeh, et al.
(author)
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Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population : the Monash GDM Machine learning model
- 2023
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In: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 179
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Journal article (peer-reviewed)abstract
- Background: Early identification of pregnant women at high risk of developing gestational diabetes (GDM) is desirable as effective lifestyle interventions are available to prevent GDM and to reduce associated adverse outcomes. Personalised probability of developing GDM during pregnancy can be determined using a risk prediction model. These models extend from traditional statistics to machine learning methods; however, accuracy remains sub-optimal.Objective: We aimed to compare multiple machine learning algorithms to develop GDM risk prediction models, then to determine the optimal model for predicting GDM.Methods: A supervised machine learning predictive analysis was performed on data from routine antenatal care at a large health service network from January 2016 to June 2021. Predictor set 1 were sourced from the existing, internationally validated Monash GDM model: GDM history, body mass index, ethnicity, age, family history of diabetes, and past poor obstetric history. New models with different predictors were developed, considering statistical principles with inclusion of more robust continuous and derivative variables. A randomly selected 80% dataset was used for model development, with 20% for validation. Performance measures, including calibration and discrimination metrics, were assessed. Decision curve analysis was performed.Results: Upon internal validation, the machine learning and logistic regression model's area under the curve (AUC) ranged from 71% to 93% across the different algorithms, with the best being the CatBoost Classifier (CBC). Based on the default cut-off point of 0.32, the performance of CBC on predictor set 4 was: Accuracy (85%), Precision (90%), Recall (78%), F1-score (84%), Sensitivity (81%), Specificity (90%), positive predictive value (92%), negative predictive value (78%), and Brier Score (0.39).Conclusions: In this study, machine learning approaches achieved the best predictive performance over traditional statistical methods, increasing from 75 to 93%. The CatBoost classifier method achieved the best with the model including continuous variables.
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| 4. |
- De Silva, Kushan, et al.
(author)
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A data-driven biocomputing pipeline with meta-analysis on high throughput transcriptomics to identify genome-wide miRNA markers associated with type 2 diabetes
- 2022
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In: Heliyon. - : Elsevier BV. - 2405-8440. ; 8:2, s. 1-11
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Journal article (peer-reviewed)abstract
- BACKGROUND: MicroRNAs (miRNAs) are sought-after biomarkers of complex, polygenic diseases such as type 2 diabetes (T2D). Data-driven biocomputing provides robust and novel avenues for synthesizing evidence from individual miRNA seq studies.OBJECTIVE: To identify miRNA markers associated with T2D, via a data-driven, biocomputing approach on high throughput transcriptomics.MATERIALS AND METHODS: The pipeline consisted of five sequential steps using miRNA seq data retrieved from the National Center for Biotechnology Information Gene Expression Omnibus platform: systematic review; identification of differentially expressed miRNAs (DE-miRNAs); meta-analysis of DE-miRNAs; network analysis; and downstream analyses. Three normalization algorithms (trimmed mean of M-values; upper quartile; relative log expression) and two meta-analytic algorithms (robust rank aggregation; Fisher's method of p-value combining) were integrated into the pipeline. Network analysis was conducted on miRNet 2.0 while enrichment and over-representation analyses were conducted on miEAA 2.0.RESULTS: A total of 1256 DE-miRNAs (821 downregulated; 435 upregulated) were identified from 5 eligible miRNA seq datasets (3 circulatory; 1 adipose; 1 pancreatic). The meta-signature comprised 9 miRNAs (hsa-miR-15b-5p; hsa-miR-33b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p; hsa-miR-483-5p; hsa-miR-539-3p; hsa-miR-1260a; hsa-miR-4454), identified via the two meta-analysis approaches. Two hub nodes (hsa-miR-106b-5p; hsa-miR-15b-5p) with above-average degree and betweenness centralities in the miRNA-gene interactions network were identified. Downstream analyses revealed 5 highly conserved- (hsa-miR-33b-5p; hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p) and 7 highly confident- (hsa-miR-33b-5p; hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p; hsa-miR-483-5p; hsa-miR-539-3p) miRNAs. A total of 288 miRNA-disease associations were identified, in which 3 miRNAs (hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-146a-5p) were highly enriched.CONCLUSIONS: A meta-signature of DE-miRNAs associated with T2D was discovered via in-silico analyses and its pathobiological relevance was validated against corroboratory evidence from contemporary studies and downstream analyses. The miRNA meta-signature could be useful for guiding future studies on T2D. There may also be avenues for using the pipeline more broadly for evidence synthesis on other conditions using high throughput transcriptomics.
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| 5. |
- De Silva, Kushan, et al.
(author)
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Causality of anthropometric markers associated with polycystic ovarian syndrome : Findings of a Mendelian randomization study
- 2022
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In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 17:6 June
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Journal article (peer-reviewed)abstract
- Introduction Using body mass index (BMI) as a proxy, previous Mendelian randomization (MR) studies found total causal effects of general obesity on polycystic ovarian syndrome (PCOS). Hitherto, total and direct causal effects of general- and central obesity on PCOS have not been comprehensively analyzed. Objectives To investigate the causality of central- and general obesity on PCOS using surrogate anthropometric markers. Methods Summary GWAS data of female-only, large-sample cohorts of European ancestry were retrieved for anthropometric markers of central obesity (waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR)) and general obesity (BMI and its constituent variables–weight and height), from the IEU Open GWAS Project. As the outcome, we acquired summary data from a large-sample GWAS (118870 samples; 642 cases and 118228 controls) within the FinnGen cohort. Total causal effects were assessed via univariable two-sample Mendelian randomization (2SMR). Genetic architectures underlying causal associations were explored. Direct causal effects were analyzed by multivariable MR modelling. Results Instrumental variables demonstrated no weak instrument bias (F > 10). Four anthropometric exposures, namely, weight (2.69–77.05), BMI (OR: 2.90–4.06), WC (OR: 6.22–20.27), and HC (OR: 6.22–20.27) demonstrated total causal effects as per univariable 2SMR models. We uncovered shared and non-shared genetic architectures underlying causal associations. Direct causal effects of WC and HC on PCOS were revealed by two multivariable MR models containing exclusively the anthropometric markers of central obesity. Other multivariable MR models containing anthropometric markers of both central- and general obesity showed no direct causal effects on PCOS. Conclusions Both and general- and central obesity yield total causal effects on PCOS. Findings also indicated potential direct causal effects of normal weight-central obesity and more complex causal mechanisms when both central- and general obesity are present. Results underscore the importance of addressing both central- and general obesity for optimizing PCOS care.
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| 6. |
- De Silva, Kushan, et al.
(author)
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Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans : a bioinformatics analytic workflow
- 2022
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In: Functional & Integrative Genomics. - : Springer. - 1438-793X .- 1438-7948. ; 22, s. 1003-1029
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Journal article (peer-reviewed)abstract
- Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.
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| 7. |
- De Silva, Kushan, et al.
(author)
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Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans : a bioinformatics analytic workflow
- 2022
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In: Functional & integrative genomics. - : Springer Science and Business Media LLC. - 1438-793X .- 1438-7948. ; 22:5, s. 1003-1029
-
Journal article (peer-reviewed)abstract
- Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.
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| 8. |
- De Silva, Kushan, et al.
(author)
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Nutritional markers of undiagnosed type 2 diabetes in adults : Findings of a machine learning analysis with external validation and benchmarking.
- 2021
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In: PLOS ONE. - : PLOS. - 1932-6203. ; 16:5
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Journal article (peer-reviewed)abstract
- OBJECTIVES: Using a nationally-representative, cross-sectional cohort, we examined nutritional markers of undiagnosed type 2 diabetes in adults via machine learning.METHODS: A total of 16429 men and non-pregnant women ≥ 20 years of age were analysed from five consecutive cycles of the National Health and Nutrition Examination Survey. Cohorts from years 2013-2016 (n = 6673) was used for external validation. Undiagnosed type 2 diabetes was determined by a negative response to the question "Have you ever been told by a doctor that you have diabetes?" and a positive glycaemic response to one or more of the three diagnostic tests (HbA1c > 6.4% or FPG >125 mg/dl or 2-hr post-OGTT glucose > 200mg/dl). Following comprehensive literature search, 114 potential nutritional markers were modelled with 13 behavioural and 12 socio-economic variables. We tested three machine learning algorithms on original and resampled training datasets built using three resampling methods. From this, the derived 12 predictive models were validated on internal- and external validation cohorts. Magnitudes of associations were gauged through odds ratios in logistic models and variable importance in others. Models were benchmarked against the ADA diabetes risk test.RESULTS: The prevalence of undiagnosed type 2 diabetes was 5.26%. Four best-performing models (AUROC range: 74.9%-75.7%) classified 39 markers of undiagnosed type 2 diabetes; 28 via one or more of the three best-performing non-linear/ensemble models and 11 uniquely by the logistic model. They comprised 14 nutrient-based, 12 anthropometry-based, 9 socio-behavioural, and 4 diet-associated markers. AUROC of all models were on a par with ADA diabetes risk test on both internal and external validation cohorts (p>0.05).CONCLUSIONS: Models performed comparably to the chosen benchmark. Novel behavioural markers such as the number of meals not prepared from home were revealed. This approach may be useful in nutritional epidemiology to unravel new associations with type 2 diabetes.
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| 9. |
- Forslund, Maria, 1978, et al.
(author)
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Different kinds of oral contraceptive pills in polycystic ovary syndrome: a systematic review and meta-analysis.
- 2023
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In: European journal of endocrinology. - 1479-683X. ; 189:1
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Journal article (peer-reviewed)abstract
- To compare between different combined oral contraceptive pills (COCPs) as part of the update of the International Evidence-Based Guidelines on the Assessment and Management of polycystic ovary syndrome (PCOS).A systematic review and meta-analysis was performed, Prospero CRD42022345640.MEDLINE, EMBASE, All EBM, CINAHL, and PsycINFO was searched on July, 8, 2022, for studies including women with PCOS, comparing 2 different COCPs in randomized controlled trials.A total of 1660 studies were identified, and 19 randomized controlled trials (RCTs) were included.Fourth-generation COCP resulted in lower body mass index (BMI) (mean difference [MD] 1.17kg/m2 [95% confidence interval {CI} 0.33; 2.02]) and testosterone (MD 0.60nmol/L [95% CI 0.13; 1.07]) compared with third-generation agents, but no difference was seen in hirsutism.Ethinyl estradiol (EE)/cyproterone acetate (CPA) was better in reducing hirsutism as well as biochemical hyperandrogenism (testosterone [MD 0.38nmol/L {95% CI 0.33-0.43}]) and BMI (MD 0.62kg/m2 [95% CI 0.05-1.20]) compared with conventional COCPs.There was no difference in hirsutism between high and low EE doses. No evidence regarding natural estrogens in COCP was identified.With current evidence, combined regimens containing an antiandrogen (EE/CPA) may be better compared with conventional COCPs in reducing hyperandrogenism, but EE/CPA will not be recommended as a first-line COCP treatment by the pending PCOS guideline update, due to higher venous thrombotic events (VTE) risk in the general population. Later-generation progestins offer theoretical benefits, but better evidence on clinical outcomes is needed in women with PCOS.The protocol for the systematic review was registered prospectively in Prospero, CRD42022345640.
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| 10. |
- Melin, Johanna, et al.
(author)
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Metformin and combined oral contraceptive pills in the management of polycystic ovary syndrome: a systematic review and meta-analysis.
- 2024
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In: The Journal of clinical endocrinology and metabolism. - 1945-7197. ; 109:2
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Journal article (peer-reviewed)abstract
- Polycystic ovary syndrome (PCOS) is affecting more than every tenth woman.As part of the 2023 International PCOS Guidelines update, comparisons between combined oral contraceptive pills (COCP), metformin and combination treatment were evaluated.Ovid Medline, Embase, PsycINFO, All EBM and CINAHL were searched.Women with PCOS included in randomized controlled trials (RCT).We calculated mean differences (MD) and 95% confidence intervals (CI) regarding anthropometrics, metabolic and hyperandrogenic outcomes. Meta-analyses and quality assessment using GRADE was performed.The search identified 1660 publications, 36 RCTs were included. For hirsutism no differences were seen when comparing metformin versus COCP, nor when comparing COCP versus combination treatment with metformin and COCP. Metformin was inferior on free androgen index (FAI) (7.08, 95% CI 4.81; 9.36), sex hormone binding globulin (SHBG) (-118.61 nmol/l, 95% CI -174.46; -62.75) and testosterone (0.48 nmol/l,95% CI 0.32; 0.64) compared with COCP. COCP was inferior for FAI (0.58, 95% CI 0.36; 0.80) and SHBG (-16.61 nmol/L, 95% CI -28.51; -4.71) compared with combination treatment, whereas testosterone did not differ. Metformin lowered insulin (-27.12 pmol/l, 95%CI -40.65; -13.59) and triglycerides (-0.15 mmol/l, 95%CI -0.29; -0.01) compared with COCP. COCP was inferior for insulin (17.03 pmol/l, 95%CI 7.79; 26.26) and insulin resistance (0.44, 95%CI 0.17; 0.70) compared with combination treatment.The choice of metformin or COCP treatment should be based on symptoms, noting that there are some biochemical benefits from combination treatment, targeting both major endocrine disturbances seen in PCOS; hyperinsulinemia and hyperandrogenism.
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