scholarly journals The Relationship between Diabetic Neuropathy and Sleep Apnea Syndrome: A Meta-Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Kazuya Fujihara ◽  
Satoru Kodama ◽  
Chika Horikawa ◽  
Sakiko Yoshizawa ◽  
Ayumi Sugawara ◽  
...  

Aims. High prevalence of sleep apnea syndrome (SAS) has been reported in patients with diabetes. However, whether diabetic neuropathy (DN) contributes to this high prevalence is controversial. Our aim of this study is to compare the prevalence of SAS between patients with and without DN.Methods. Systematic literature searches were conducted for cross-sectional studies that reported the number of patients with DN and SAS using MEDLINE (from 1966 to Nov 5, 2012) and EMBASE (from 1974 to Nov 5, 2012). Odds ratios (ORs) of SAS related to DN were pooled with the Mantel-Haenszel method.Results. Data were obtained from 5 eligible studies (including 6 data sets, 880 participants, and 429 cases). Overall, the pooled OR of SAS in patients with DN compared with that in non-DN patients was significant (OR (95% CI), −1.95 (1.03–3.70)). The pooled OR of SAS was 1.90 (0.97–3.71) in patients with type 2 diabetes. Excluding data on patients with type 1 diabetes, a higher OR was observed in younger patients (mean age <60 years) than in those ≥60 years among whom the OR remained significant (3.82; 95% CI, 2.24–6.51 and 1.17; 95% CI, 0.81–1.68).Conclusions. Current meta-analysis suggested the association of some elements of neuropathy with SAS in type 2 diabetes. Further investigations are needed to clarify whether the association is also true for patients with type 1 diabetes.

2013 ◽  
Vol 60 (12) ◽  
pp. 1289-1294 ◽  
Author(s):  
Daisuke Tamada ◽  
Michio Otsuki ◽  
Susumu Kashine ◽  
Ayumu Hirata ◽  
Toshiharu Onodera ◽  
...  

2017 ◽  
Vol 9 (7) ◽  
pp. 718-718
Author(s):  
Adriana Rusu ◽  
Cornelia Gabriela Bala ◽  
Gabriela Roman

2020 ◽  
Vol 24 (28) ◽  
pp. 1-232
Author(s):  
Kirsty Winkley ◽  
Rebecca Upsher ◽  
Daniel Stahl ◽  
Daniel Pollard ◽  
Architaa Kasera ◽  
...  

Background For people with diabetes mellitus to achieve optimal glycaemic control, motivation to perform self-management is important. The research team wanted to determine whether or not psychological interventions are clinically effective and cost-effective in increasing self-management and improving glycaemic control. Objectives The first objective was to determine the clinical effectiveness of psychological interventions for people with type 1 diabetes mellitus and people with type 2 diabetes mellitus so that they have improved (1) glycated haemoglobin levels, (2) diabetes self-management and (3) quality of life, and fewer depressive symptoms. The second objective was to determine the cost-effectiveness of psychological interventions. Data sources The following databases were accessed (searches took place between 2003 and 2016): MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, PsycINFO, EMBASE, Cochrane Controlled Trials Register, Web of Science, and Dissertation Abstracts International. Diabetes conference abstracts, reference lists of included studies and Clinicaltrials.gov trial registry were also searched. Review methods Systematic review, aggregate meta-analysis, network meta-analysis, individual patient data meta-analysis and cost-effectiveness modelling were all used. Risk of bias of randomised and non-randomised controlled trials was assessed using the Cochrane Handbook (Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011;343:d5928). Design Systematic review, meta-analysis, cost-effectiveness analysis and patient and public consultation were all used. Setting Settings in primary or secondary care were included. Participants Adolescents and children with type 1 diabetes mellitus and adults with types 1 and 2 diabetes mellitus were included. Interventions The interventions used were psychological treatments, including and not restricted to cognitive–behavioural therapy, counselling, family therapy and psychotherapy. Main outcome measures Glycated haemoglobin levels, self-management behaviours, body mass index, blood pressure levels, depressive symptoms and quality of life were all used as outcome measures. Results A total of 96 studies were included in the systematic review (n = 18,659 participants). In random-effects meta-analysis, data on glycated haemoglobin levels were available for seven studies conducted in adults with type 1 diabetes mellitus (n = 851 participants) that demonstrated a pooled mean difference of –0.13 (95% confidence interval –0.33 to 0.07), a non-significant decrease in favour of psychological treatment; 18 studies conducted in adolescents/children with type 1 diabetes mellitus (n = 2583 participants) that demonstrated a pooled mean difference of 0.00 (95% confidence interval –0.18 to 0.18), indicating no change; and 49 studies conducted in adults with type 2 diabetes mellitus (n = 12,009 participants) that demonstrated a pooled mean difference of –0.21 (95% confidence interval –0.31 to –0.10), equivalent to reduction in glycated haemoglobin levels of –0.33% or ≈3.5 mmol/mol. For type 2 diabetes mellitus, there was evidence that psychological interventions improved dietary behaviour and quality of life but not blood pressure, body mass index or depressive symptoms. The results of the network meta-analysis, which considers direct and indirect effects of multiple treatment comparisons, suggest that, for adults with type 1 diabetes mellitus (7 studies; 968 participants), attention control and cognitive–behavioural therapy are clinically effective and cognitive–behavioural therapy is cost-effective. For adults with type 2 diabetes mellitus (49 studies; 12,409 participants), cognitive–behavioural therapy and counselling are effective and cognitive–behavioural therapy is potentially cost-effective. The results of the individual patient data meta-analysis for adolescents/children with type 1 diabetes mellitus (9 studies; 1392 participants) suggest that there were main effects for age and diabetes duration. For adults with type 2 diabetes mellitus (19 studies; 3639 participants), baseline glycated haemoglobin levels moderated treatment outcome. Limitations Aggregate meta-analysis was limited to glycaemic control for type 1 diabetes mellitus. It was not possible to model cost-effectiveness for adolescents/children with type 1 diabetes mellitus and modelling for type 2 diabetes mellitus involved substantial uncertainty. The individual patient data meta-analysis included only 40–50% of studies. Conclusions This review suggests that psychological treatments offer minimal clinical benefit in improving glycated haemoglobin levels for adults with type 2 diabetes mellitus. However, there was no evidence of benefit compared with control interventions in improving glycated haemoglobin levels for people with type 1 diabetes mellitus. Future work Future work should consider the competency of the interventionists delivering a therapy and psychological approaches that are matched to a person and their life course. Study registration This study is registered as PROSPERO CRD42016033619. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 28. See the NIHR Journals Library website for further project information.


2021 ◽  
Vol 10 (19) ◽  
pp. 4466
Author(s):  
Carla Greco ◽  
Fabio Nascimbeni ◽  
Francesca Carubbi ◽  
Pietro Andreone ◽  
Manuela Simoni ◽  
...  

Aims. The relationship between nonalcoholic fatty liver disease (NAFLD) and diabetic polyneuropathy (DPN) has been demonstrated in many studies, although results were conflicting. This meta-analysis aims to summarize available data and to estimate the DPN risk among NAFLD patients. Materials and methods. We performed a comprehensive literature review until 4 June 2021. Clinical trials analyzing the association between NAFLD and DPN were included. Results. Thirteen studies (9614 participants) were included. DPN prevalence was significantly higher in patients with NALFD, compared to patients without NAFLD (OR (95%CI) 2.48 (1.42–4.34), p = 0.001; I2 96%). This finding was confirmed in type 2 diabetes (OR (95%CI) 2.51 (1.33–4.74), p = 0.005; I2 97%), but not in type 1 diabetes (OR (95%CI) 2.44 (0.85–6.99), p = 0.100; I2 77%). Also, body mass index and diabetes duration were higher in NAFLD subjects compared to those without NAFLD (p < 0.001), considering both type 2 and type 1 diabetes. Conclusion. Despite a high heterogeneity among studies, a significantly increased DPN prevalence among type 2 diabetes subjects with NAFLD was observed. This result was not found in type 1 diabetes, probably due to the longer duration of disease. Physicians should pay more attention to the early detection of DPN, especially in patients with NAFLD.


2020 ◽  
Author(s):  
Jamie RJ Inshaw ◽  
Carlo Sidore ◽  
Francesco Cucca ◽  
M. Irina Stefana ◽  
Daniel J. M. Crouch ◽  
...  

Aims/hypothesis: Given the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal colocalises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. Methods: Using publicly available type 2 diabetes summary statistics from a genomewide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7,467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate<0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined colocalisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a colocalisation posterior probability of ≥0.9 was considered a genuine shared association with both diseases. Results: Of the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals colocalised between both diseases (posterior probability ≥0.9): (i) chromosome 16q23.1, near Chymotripsinogen B1 (CTRB1) / Breast Cancer Anti-Estrogen Resistance Protein 1 (BCAR1), which has been previously identified; (ii) chromosome 11p15.5, near the Insulin (INS) gene; (iii) chromosome 4p16.3, near Transmembrane protein 129 (TMEM129), and (iv) chromosome 1p31.3, near Phosphoglucomutase 1 (PGM1). In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified colocalisation on chromosome 9p24.2, near the GLIS Family Zinc Finger Protein 3 (GLIS3) gene, in this case with a concordant direction of effect. Conclusions/interpretation: That four of five association signals that colocalise between type 1 diabetes and type 2 diabetes are in opposite directions suggests a complex genetic relationship between the two diseases.


Sign in / Sign up

Export Citation Format

Share Document