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2021 ◽  
Vol 19 (1) ◽  
Erik Kindgren ◽  
Johnny Ludvigsson

Abstract Background The aetiology of juvenile idiopathic arthritis (JIA) is poorly understood. It has been shown that use of antibiotics is associated with JIA. However, whether the association is due to increased occurrence of infection in these individuals is unknown. The purpose of this investigation was to measure the association between number of infections and use of antibiotics during childhood with development of JIA. Methods In ABIS (All Babies in Southeast Sweden) a population-based prospective birth cohort of 17,055 children, data were collected on infections and antibiotic exposure during pregnancy and childhood. 102 individuals with JIA were identified. Multivariable logistic regression analyses were performed, adjusting for confounding factors. Results Exposure to antibiotics during the periods 1–12 months, 1–3 years and 5–8 years was significantly associated with increased risk for JIA. The odds of developing JIA were three times higher in those exposed to antibiotics during the first 3 years of life compared with those not exposed (aOR 3.17; 95% CI 1.11–9.03, p = 0.031), and more than twice as high in those exposed to antibiotics during the first 5 years of life compared with those not exposed (aOR 2.18; 95% CI 1.36–3.50, p = 0.001). The odds of developing JIA were 78% higher in those exposed to antibiotics during the first 8 years of life compared with those not exposed (aOR 1.78; 95% CI 1.15–2.73, p = 0.009). Occurrence of infection during fetal life or childhood showed no significant association with the risk of developing JIA, after confounder adjustment. The cumulative number of courses of antibiotics was significantly higher during childhood for the individuals who developed JIA (p < 0.001). Penicillins were more frequently used than non-penicillins, but both had an equal effect on the risk of developing JIA. Conclusions Exposure to antibiotics early in life is associated with later onset of JIA in a large birth cohort from the general population. The relationship was dose dependent. These results suggest that further, more restrictive, antibiotic policies during the first years of life would be advisable.

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Jessica Sjölund ◽  
Inger Kull ◽  
Anna Bergström ◽  
Jacob Järås ◽  
Jonas F. Ludvigsson ◽  

Abstract Background Studies on allergy-related diseases in relation to abdominal pain-related functional gastrointestinal disorders (AP-FGIDs) in children are few and results are contradictory. We examined the associations between childhood allergy-related diseases and adolescent AP-FGIDs in general and irritable bowel syndrome (IBS) in particular. Method Prospective population-based birth cohort study of 4089 children born in Sweden 1994-1996. We analysed data from 2949 children with complete follow-up at 16 years (y) and no diagnosis of inflammatory bowel disease or coeliac disease at 12y or 16y. Asthma, rhinitis, eczema, and food hypersensitivity (FH) were assessed through questionnaires at 1–2y, 4y, 8y, 12y, and 16y. AP-FGIDs and IBS were assessed through questionnaires at 16y and defined according to the Rome III criteria. Associations between childhood allergy-related diseases and any AP-FGID and IBS and 16y respectively were examined using binomial generalized linear models with a log link function and described as relative risk with 95% confidence intervals. Results The prevalence of any AP-FGID and IBS at 16y were 12.0% and 6.0% respectively. Eczema at 1–2y, 4y, and 8y, and FH at 12y and 16y were associated with an increased risk for any AP-FGID at 16y. Asthma and FH at 12y and 16y were associated with an increased risk for IBS at 16y. The relative risk for IBS at 16y increased with increasing number of concurrent allergy-related diseases at 16y, but linear trend for relative risk was only borderline statistically significant (P for trend = 0.05). Conclusions This prospective population-based study demonstrated positive associations between childhood allergy-related diseases and adolescent AP-FGIDs, including IBS, implicating shared pathophysiology among these disorders.

2021 ◽  
Vol 21 (1) ◽  
Melkamu Dires Asabu

Abstract Background Risky sexual behavior is a major public health concern of Ethiopians. Although studying the autonomy of women in refusing risky sex is significant to take proper actions, the issue is not yet studied. Accordingly, this population-based nationwide study was aimed at assessing women’s autonomy in refusing risky sex and its associated factors in Ethiopia. Method The sample was limited to married women of 2011 (n = 8369) and 2016 (n = 8403) Ethiopian Demographic and Health Survey data. Women's autonomy in refusing risky sex was measured based on wives' response to 'not having sex because husbands have other women. To examine associated factors, socio-demographic variables were computed using binary logistic regression. Result The finding revealed that the trend of women’s autonomy in refusing risky sex had declined from 78.9% in 2011 to 69.5% in 2016. Women aged from 25 to 34 were less likely autonomous in refusing sex compared to those who aged less than 24 years old (AOR = .7064; 95% CI 0.605, 0.965). The autonomy of women with higher educational status was three times more likely higher than those who have no formal education (AOR = 3.221; 95% CI 1.647, 6.300 respectively. The autonomy of women who are from rich households was more likely higher in comparison to women from poor households (AOR = 1.523; 95% CI 1.28, 1.813). The autonomy of women those who live in Tigray 2.9 times (AOR = 2.938; 95% CI 2.025, 4.263), Amhara 4.8 times (AOR = 4.870; 95% CI 3.388, 7.000), SNNP 1.9 times (AOR = 1.900; 95% CI 1.355, 2.664), and Addis Ababa 3.8 times (AOR = 3.809; 95% CI 2.227, 6.516) more likely higher than those who reside in Dire Dawa. Conclusion The autonomy of women in refusing risky sex has declined from 2011 to 2016. This infers that currently, women are more victimized than previously. Hence, possible interventions like empowering women shall be taken to protect women from certain health problems of risky sexual behavior.

Pharmaceutics ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1480
Sundus Khalid ◽  
Muhammad Fawad Rasool ◽  
Imran Imran ◽  
Abdul Majeed ◽  
Hamid Saeed ◽  

Diazepam is one of the most prescribed anxiolytic and anticonvulsant that is administered through intravenous (IV), oral, intramuscular, intranasal, and rectal routes. To facilitate the clinical use of diazepam, there is a need to develop formulations that are convenient to administer in ambulatory settings. The present study aimed to develop and evaluate a physiologically based pharmacokinetic (PBPK) model for diazepam that is capable of predicting its pharmacokinetics (PK) after IV, oral, intranasal, and rectal applications using a whole-body population-based PBPK simulator, Simcyp®. The model evaluation was carried out using visual predictive checks, observed/predicted ratios (Robs/pred), and the average fold error (AFE) of PK parameters. The Diazepam PBPK model successfully predicted diazepam PK in an adult population after doses were administered through IV, oral, intranasal, and rectal routes, as the Robs/pred of all PK parameters were within a two-fold error range. The developed model can be used for the development and optimization of novel diazepam dosage forms, and it can be extended to simulate drug response in situations where no clinical data are available (healthy and disease).

2021 ◽  
pp. jech-2021-216778
Per E. Gustafsson ◽  
Miguel San Sebastian ◽  
Osvaldo Fonseca-Rodriguez ◽  
Anne-Marie Fors Connolly

BackgroundThe backdrop of the ubiquitous social inequalities has increasingly come into foreground in research on the COVID-19 pandemic, but the lack of high-quality population-based studies limits our understanding of the inequitable outcomes of the disease. The present study seeks to estimate social gradients in COVID-19 hospitalisations, intensive care admissions and death by education, income and country of birth, while taking into account disparities in comorbidities.MethodsWe used a register-based retrospective open cohort design enrolling all 74 659 confirmed SARS-CoV-2-positive cases aged >25 years in Sweden during the first wave of the pandemic (until 14 September 2020). Information was retrieved from multiple registers and linked by the unique Swedish personal identity number concerning COVID-19 case identification; COVID-19 hospitalisations, intensive care admissions and death; comorbidities as measured by the Charlson Comorbidity Index; and sociodemographic information. Social gradients were estimated by the Relative Index of Inequality (RII) using Cox regression.ResultsAdjusted analyses showed significant social gradients in COVID-19 hospitalisation, intensive care admission, across education, income and country of birth, which were unaffected by adjustment for comorbidities. Education and country of birth gradients were stronger for hospitalisation and intensive care admissions but small to non-existent for death. In contrast, income gradients were consistent across all three COVID-19 outcomes.ConclusionSocial gradients in severe COVID-19 outcomes are widespread in Sweden, but appear to be unrelated to pre-existing health disparities. Inequitable outcomes of SARS-CoV-2 infection may therefore be at least partially avoidable and could rely on equitable management of confirmed COVID-19 cases.

2021 ◽  
Javier Fatou Gómez ◽  
Pejman Shoeibi Omrani ◽  
Stefan Philip Christian Belfroid

Abstract In gas wells, decreased/unstable production can occur due to difficult-to-predict dynamic effects resulted from late-life phenomena, such as liquid loading and flooding. To minimize the negative impact of these effects, maximize production and extend the wells’ lifetime, wells are often operated in an intermittent production regime. The goal of this work is to find the optimum production and shut-in cycles to maximize intermittent gas production as a decision support to operators. A framework suitable for single and multiple wells was developed by coupling a Deep Learning forward model trained on historical data with a population-based global optimizer, Particle Swarm Optimization (PSO). The forward model predicts the production rates and wellhead pressure during production and shut-in conditions, respectively. The PSO algorithm optimizes the operational criteria given operational and environmental objectives, such as maximizing production, minimizing start-up/shut-in actions, penalizing emissions under several constraints such as planned maintenances and meeting a contract production value. The accuracy of the Deep Learning models was tested on synthetic and field data. On synthetic data, mature wells were tested under different reservoir conditions such as initial water saturation, permeability and flow regimes. The relative errors in the predicted total cumulative production ranged between 0.5 and 4.6% for synthetic data and 0.9% for field data. The mean errors for pressure prediction were of 2-3 bar. The optimization framework was benchmarked for production optimization and contract value matching for a single-well (on field data) and a cluster of wells (synthetic data). Single-well production optimization of a North Sea well achieved a 3% production increase, including planned maintenances. Production optimization for six wells resulted in a 21% production increase for a horizon of 30 days, while contract value matching yielded 29/30 values within 3% of the target. The most optimum, repeatable and computationally efficient results were obtained using critical pressure/gas flowrates as operational criteria. This could enable real-time gas production optimization and operational decision-making in a wide range of well conditions and operational requirements.

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