Dataset Information

Sleep characteristics in type 1 diabetes and associations with glycemic control: systematic review and meta-analysis.

ABSTRACT:

Objectives

The association between inadequate sleep and type 2 diabetes has garnered much attention, but little is known about sleep and type 1 diabetes (T1D). Our objectives were to conduct a systematic review and meta-analysis comparing sleep in persons with and without T1D, and to explore relationships between sleep and glycemic control in T1D.

Methods

Studies were identified from Medline and Scopus. Studies reporting measures of sleep in T1D patients and controls, and/or associations between sleep and glycemic control, were selected.

Results

A total of 22 studies were eligible for the meta-analysis. Children with T1D had shorter sleep duration (mean difference [MD] = -26.4 minutes; 95% confidence interval [CI] = -35.4, -17.7) than controls. Adults with T1D reported poorer sleep quality (MD in standardized sleep quality score = 0.51; 95% CI = 0.33, 0.70), with higher scores reflecting worse sleep quality) than controls, but there was no difference in self-reported sleep duration. Adults with TID who reported sleeping >6 hours had lower hemoglobin A1c (HbA1c) levels than those sleeping ≤6 hours (MD = -0.24%; 95% CI = -0.47, -0.02), and participants reporting good sleep quality had lower HbA1c than those with poor sleep quality (MD = -0.19%; 95% CI = -0.30, -0.08). The estimated prevalence of obstructive sleep apnea (OSA) in adults with TID was 51.9% (95% CI = 31.2, 72.6). Patients with moderate-to-severe OSA had a trend toward higher HbA1c (MD = 0.39%, 95% CI = -0.08, 0.87).

Conclusion

T1D was associated with poorer sleep and high prevalence of OSA. Poor sleep quality, shorter sleep duration, and OSA were associated with suboptimal glycemic control in T1D patients.

SUBMITTER: Reutrakul S

PROVIDER: S-EPMC9554893 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Publications

Sleep characteristics in type 1 diabetes and associations with glycemic control: systematic review and meta-analysis.

Reutrakul Sirimon S Thakkinstian Ammarin A Anothaisintawee Thunyarat T Chontong Sasipas S Borel Anne-Laure AL Perfect Michelle M MM Janovsky Carolina Castro Porto Silva CC Kessler Romain R Schultes Bernd B Harsch Igor Alexander IA van Dijk Marieke M Bouhassira Didier D Matejko Bartlomiej B Lipton Rebecca B RB Suwannalai Parawee P Chirakalwasan Naricha N Schober Anne-Katrin AK Knutson Kristen L KL

Sleep medicine 20160608

<h4>Objectives</h4>The association between inadequate sleep and type 2 diabetes has garnered much attention, but little is known about sleep and type 1 diabetes (T1D). Our objectives were to conduct a systematic review and meta-analysis comparing sleep in persons with and without T1D, and to explore relationships between sleep and glycemic control in T1D.<h4>Methods</h4>Studies were identified from Medline and Scopus. Studies reporting measures of sleep in T1D patients and controls, and/or assoc ...[more]

PMID: 27692274

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Project description:IntroductionPrior primary studies have examined the prevalence and factors associated with glycaemic control among patients with type 2 diabetes mellitus, but studies with evidence-based synthesis of the primary data remained unknown. Hence, we aimed to determine the prevalence of poor glycemic control and identify determinants of poor glycemic control in patients with type 2 diabetes in Ethiopia.MethodsWe performed searches in the online databases of PubMed, Google Scholar, Scopus, Science Direct, and the Cochrane Library. Microsoft Excel was used to extract data, and STATA statistical software (v. 16) was used for analysis. Publication bias was explored by forest plots, Begg's rank test, and Egger's regression test. To check for heterogeneity, I2 was computed. Subgroup analysis was conducted based on region and publication year. In addition, the pooled odds ratio for associated factors was calculated.ResultsOut of 1,045 studies assessed, 23 studies were included fulfilling our inclusion criteria. In all, 6,643 individuals were enrolled in the study. It was estimated that 61.11% of type 2 diabetes patients had poor glycemic control (95% CI, 57.14-65.19). The subgroup analysis by study region and publication year revealed that the highest prevalence was observed in the Addis Ababa region (68.57%) and studies published before 2019 (61.76%), respectively. Poor glycemic control was associated with older age > 50 years (AOR = 2.12; 95% CI: 1.27-2.97), not attending formal education (AOR = 3.60; 95% CI: 2.75, 4.46), having diabetes for longer duration (10 years; AOR = 2.57; 95% CI: 1.65-3.49), having comorbidity (AOR = 2.43; 95% CI: 2.05-2.80), and low adherence to diabetes management (AOR = 3.67; 95% CI: 2.41-4.92).ConclusionOur findings indicate a high prevalence of poor glycemic control among people with type 2 diabetes in Ethiopia. Being older, not attending formal education, having a longer duration of diabetes, having comorbidity, and having low adherence to diabetes management were all associated. Therefore, we recommend health organizations implement measures to monitor and control patients' blood glucose levels. Patient education and training of healthcare professionals could serve as a short-term strategy to achieve adequate glycemic control.Systematic review registrationPROSPERO, identifier CRD42022349792, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022349792.

Project description:This systematic review aimed to evaluate the effectiveness and safety of probiotics for glycemic control in adults with impaired glucose control, including prediabetes and type 2 diabetes mellitus (T2DM). We searched PubMed, Embase, and Cochrane databases, and trial registries up to February 2019. We included randomized controlled trials (RCTs) of participants with prediabetes or T2DM. Eligible trials compared probiotics versus either placebo, no intervention, or comparison probiotics, or compared synbiotics versus prebiotics. Primary outcomes were mean change in fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) from baseline to short term (<12 wk) and long term (≥12 wk). We performed meta-analyses using the random-effects model. We included 28 RCTs (1947 participants). Overall, probiotics reduced FBG more than the placebo/no intervention group with a mean difference (MD) of -12.99 mg/dL (95% CI: -23.55, -2.42; P value: 0.016) over the short term; and -2.99 mg/dL (95% CI: -5.84, -0.13; P value: 0.040) over the long term. There was also some evidence for reduced HbA1c in the probiotics group at both short term (MD: -0.17; 95% CI: -0.37, 0.02; P value: 0.084) and long term (MD: -0.14; 95% CI: -0.34, 0.06; P value: 0.172), however, these did not reach statistical significance possibly because only a few trials reported HbA1c as an outcome. Subgroup analyses showed a greater reduction in HbA1c in participants not receiving insulin therapy than those receiving insulin therapy. Furthermore, the effect of probiotics on the reduction of FBG was more pronounced in participants with FBG >130 mg/dL and those not receiving insulin therapy than their counterparts. Probiotics were also effective in lowering serum cholesterol over the short and long term. In conclusion, we found that probiotics may have a glucose-lowering effect in T2DM participants. The effect appeared to be stronger in participants with poorly controlled diabetes and those not on insulin therapy. Systematic review registration: CRD42019121682.

Project description:ObjectiveThe purpose of this study was to systematically determine the effect of dragon fruit on glycemic control in prediabetes and type 2 diabetes.MethodsElectronic databases including MEDLINE, CENTRAL, CINAHL, Scopus, ScienceDirect®, Proquest, Web of Science®, LILACS, NAPRALERT, SciFinder, Clinicalkey, Herbmed, NCCIH and Google Scholar were searched from their earliest inception up to March 2017 for relevant randomized controlled trials (RCTs) which compared dragon fruit with placebo or no treatment in prediabetes or type 2 diabetes. Clinicaltrials.gov, clinicaltrialresults.org, and ISRCTN registry were also searched. Personal contact with experts and historical search of related articles was undertaken. Outcome of interest were fasting plasma glucose (FPG) and 2 hours post-prandial glucose (2HPP). Study selection, data extraction and study quality assessment were performed independently by two investigators. Disagreements were resolved by a third reviewer. Treatment effect was estimated with mean difference (MD). Effect estimates were pooled using inverse-variance weighted method. Heterogeneity was assessed with the Q statistic and quantified with the I2 statistic. DerSimonian and Laird random-effects model was used when the Q-statistic was significant at the level of 0.1, otherwise a fixed-effects model was used.ResultsAmong 401 studies identified from literature search, 4 RCTs involving 36 prediabetes subjects and 109 type 2 diabetes patients were included in the analysis. In prediabetes, FPG reduction was significant with MD of -15.1 mg/dL (95% CI: -23.8 to -6.5 mg/dL, P-value = 0.0006). Meta-analysis in type 2 diabetes showed no effect of dragon fruit on FPG (MD -26.5 mg/dL, 95% CI: -72.6 mg/dL to 19.6 mg/dL) and in 2HPP (MD -30.5 mg/dL, 95% CI: -80.9 mg/dL to 19.9 mg/dL).ConclusionThe available evidence in prediabetes is interesting. This will shed some light on diabetes prevention. The effect in T2DM was not significant. However, a trend towards greater blood glucose reduction with higher dose was observed.

Project description:BackgroundDigital technologies for type 2 diabetes mellitus (T2DM) care hold great potential to improve patients' health in the long term. Only a subset of telemedicine offerings are digital interventions that meet the criteria for prescribable digitale Gesundheitsanwendung (digital health apps; DiGAs) in Germany. Digital treatments further provide vast amounts of patient data that are important to generate evidence.ObjectiveThis systematic review aims to analyze the efficacy of multimodal digital therapies that mainly meet the DiGA criteria for patients with T2DM and to elicit the potential of such therapies. This includes evidence from randomized controlled trials (RCTs) as well as from real-world data. The outcome of interest was a reduction in glycated hemoglobin (hemoglobin A1c [HbA1c]; long-term blood glucose measurements).MethodsA systematic literature search was conducted in the literature bases PubMed, LIVIVO, and Cochrane, based on the predefined PICO (Population; Intervention; Control; Outcome) scheme. Identified studies were assessed for risk of bias, pragmatism, and overall quality of evidence. Meta-analyses were conducted for between group differences using RCTs only, and for within-group differences using RCTs and non-RCTs, to examine the effect of the interventions on HbA1c.ResultsIn total, 795 records were identified, of which 24 were eligible for this systematic review and 23 studies were eligible for the meta-analysis. The results of the meta-analyses showed significant and clinically relevant reductions in HbA1c in patients with T2DM. Regarding the between-group difference for HbA1c reduction, the pooled effect of the RCTs showed a reduction of -0.36% (95% CI -0.59% to -0.14%; P<.001), favoring app-based interventions. The average mean within-group reduction in HbA1c was -0.79 (95% CI -1.02 to -0.55), with no significant difference between RCTs (-0.69, 95% CI -1.13 to -0.24) and non-RCTs (-0.87, 95% CI -1.16 to -0.57; P<.01, differences between RCTs and RCTs P=.44). A pragmatism rating showed that both study types were on average (very) pragmatic, that is, close to usual care. However, the overall quality of evidence was low to very low.ConclusionsThis systematic review shows that digital therapies that mainly meet the DiGA criteria can effectively improve HbA1c in patients with T2DM. The integration of digital health care into usual care holds great potential and should be considered as a complementary option to usual care in the future.Trial registrationPROSPERO CRD42023440203; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=440203.

Dataset Information

Sleep characteristics in type 1 diabetes and associations with glycemic control: systematic review and meta-analysis.

Objectives

Methods

Results

Conclusion

Publications

Sleep characteristics in type 1 diabetes and associations with glycemic control: systematic review and meta-analysis.

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