Association of HLA-DRB1 and -DQB1 alleles with type 1 (autoimmune) diabetes in African Arabs: systematic review and meta-analysis

2018 ◽  
Vol 48 (2) ◽  
pp. 130-146 ◽  
Author(s):  
Abdelhafidh Hajjej ◽  
Wassim Y. Almawi ◽  
Mouna Stayoussef ◽  
Antonio Arnaiz-Villena ◽  
Lasmar Hattab ◽  
...  
2020 ◽  
Author(s):  
Anthony Pease ◽  
Clement Lo ◽  
Arul Earnest ◽  
Velislava Kiriakova ◽  
Danny Liew ◽  
...  

<b>Background: </b>Time-in-range is a key glycaemic metric, and comparisons of management technologies for this outcome are critical to guide device selection. <p><b> </b></p> <p><b>Purpose: </b>We conducted a systematic review and network meta-analysis to compare and rank technologies for time in glycaemic ranges.</p> <p> </p> <p><b>Data sources: </b>We searched All Evidenced Based Medicine Reviews, CINAHL, EMBASE, MEDLINE, MEDLINE In-Process and other non-indexed citations, PROSPERO, PsycINFO, PubMed, and Web of Science until 24 April, 2019.</p> <p> </p> <p><b>Study selection: </b>We included randomised controlled trials <u>></u>2 weeks duration comparing technologies for management of type 1 diabetes in adults (<u>></u>18 years of age), excluding pregnant women. </p> <p> </p> <p><b>Data extraction: </b>Data were extracted using a predefined template. Outcomes were percent time with sensor glucose levels 3.9–10.0mmol/l (70–180mg/dL), >10.0mmol/L (180mg/dL), and <3.9mmol/L (70mg/dL). </p> <p><b> </b></p> <p><b>Data synthesis: </b>We identified 16,772 publications, of which 14 eligible studies compared eight technologies comprising 1,043 participants. Closed loop systems lead to greater percent time-in-range than any other management strategy and was 17.85 (95% predictive interval [PrI] 7.56–28.14) higher than usual care of multiple daily injections with capillary glucose testing. Closed loop systems ranked best for percent time-in-range or above range utilising surface under the cumulative ranking curve (SUCRA–98.5 and 93.5 respectively). Closed loop systems also ranked highly for time below range (SUCRA–62.2). </p> <p><b> </b></p> <p><b>Limitations: </b>Overall risk of bias ratings were moderate for all outcomes. Certainty of evidence was very low.</p> <p><b> </b></p> <p><b>Conclusions: </b>In the first integrated comparison of multiple management strategies considering time-in-range, we found that the efficacy of closed loop systems appeared better than all other approaches. </p>


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Lontchi-Yimagou ◽  
Charly Feutseu ◽  
Sebastien Kenmoe ◽  
Alexandra Lindsey Djomkam Zune ◽  
Solange Fai Kinyuy Ekali ◽  
...  

AbstractA significant number of studies invoked diabetes as a risk factor for virus infections, but the issue remains controversial. We aimed to examine whether non-autoimmune diabetes mellitus enhances the risk of virus infections compared with the risk in healthy individuals without non-autoimmune diabetes mellitus. In this systematic review and meta-analysis, we assessed case-control and cohort studies on the association between non-autoimmune diabetes and viruses. We searched PubMed, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Web of Science with no language restriction, to identify articles published until February 15, 2021. The main outcome assessment was the risk of virus infection in individuals with non-autoimmune diabetes. We used a random-effects model to pool individual studies and assessed heterogeneity (I2) using the χ2 test on Cochrane’s Q statistic. This study is registered with PROSPERO, number CRD42019134142. Out of 3136 articles identified, we included 68 articles (90 studies, as the number of virus and or diabetes phenotype varied between included articles). The summary OR between non-autoimmune diabetes and virus infections risk were, 10.8(95% CI: 10.3–11.4; 1-study) for SARS-CoV-2; 3.6(95%CI: 2.7–4.9, I2 = 91.7%; 43-studies) for HCV; 2.7(95% CI: 1.3–5.4, I2 = 89.9%, 8-studies;) for HHV8; 2.1(95% CI: 1.7–2.5; 1-study) for H1N1 virus; 1.6(95% CI: 1.2–2.13, I2 = 98.3%, 27-studies) for HBV; 1.5(95% CI: 1.1–2.0; 1-study) for HSV1; 3.5(95% CI: 0.6–18.3 , I2 = 83.9%, 5-studies) for CMV; 2.9(95% CI: 1–8.7, 1-study) for TTV; 2.6(95% CI: 0.7–9.1, 1-study) for Parvovirus B19; 0.7(95% CI: 0.3–1.5 , 1-study) for coxsackie B virus; and 0.2(95% CI: 0–6.2; 1-study) for HGV. Our findings suggest that, non-autoimmune diabetes is associated with increased susceptibility to viruses especially SARS-CoV-2, HCV, HHV8, H1N1 virus, HBV and HSV1. Thus, these viruses deserve more attention from diabetes health-care providers, researchers, policy makers, and stakeholders for improved detection, overall proper management, and efficient control of viruses in people with non-autoimmune diabetes.


2021 ◽  
Vol 210 ◽  
pp. 106370
Author(s):  
Dumisani Enricho Nkhoma ◽  
Charles Jenya Soko ◽  
Pierre Bowrin ◽  
Yankuba B. Manga ◽  
David Greenfield ◽  
...  

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e055374
Author(s):  
Zhi Yang ◽  
Rong Xu ◽  
Jia-rong Wang ◽  
Hua-yan Xu ◽  
Hang Fu ◽  
...  

ObjectiveThis meta-analysis assessed the associations of myocardial fibrosis detected by late gadolinium-enhanced (LGE)-MRI with the risk of major adverse cardiac and cerebrovascular events (MACCEs) and major adverse cardiac events (MACEs) in patients with diabetes.DesignSystematic review and meta-analysis reported in accordance with the guidelines of the Meta-analysis of Observational Studies in Epidemiology statement.Data sourcesWe searched the Medline, Embase and Cochrane by Ovid databases for studies published up to 27 August 2021.Eligibility criteriaProspective or respective cohort studies were included if they reported the HR and 95% CIs for MACCEs/MACEs in patients with either type 1 or 2 diabetes and LGE-MRI-detected myocardial fibrosis compared with patients without LGE-MRI-detected myocardial fibrosis and if the articles were published in the English language.Data extraction and synthesisTwo review authors independently extracted data and assessed the quality of the included studies. Pooled HRs and 95% CIs were analysed using a random effects model. Heterogeneity was assessed using forest plots and I2 statistics.ResultsEight studies with 1121 patients with type 1 or type 2 diabetes were included in this meta-analysis, and the follow-up ranged from 17 to 70 months. The presence of myocardial fibrosis detected by LGE-MRI was associated with an increased risk for MACCEs (HR: 2.58; 95% CI 1.42 to 4.71; p=0.002) and MACEs (HR: 5.28; 95% CI 3.20 to 8.70; p<0.001) in patients with diabetes. Subgroup analysis revealed that ischaemic fibrosis detected by LGE was associated with MACCEs (HR 3.80, 95% CI 2.38 to 6.07; p<0.001) in patients with diabetes.ConclusionsThis study demonstrated that ischaemic myocardial fibrosis detected by LGE-MRI was associated with an increased risk of MACCEs/MACEs in patients with diabetes and may be an imaging biomarker for risk stratification. Whether LGE-MRI provides incremental prognostic information with respect to MACCEs/MACEs over risk stratification by conventional cardiovascular risk factors requires further study.


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