METHODS: A cross-sectional study was conducted in Hospital Universiti Sains Malaysia, Kelantan from November 2013 till May 2016 among Type 2 DM patients (DM with no DR and DM with NPDR). The patients were evaluated for anterior ocular segment biometry [central corneal thickness (CCT), anterior chamber width (ACW), angle opening distance (AOD) and anterior chamber angle (ACA)] by using Anterior Segment Optical Coherence Tomography (AS-OCT). Three ml venous blood was taken for the measurement of HbA1c.
RESULTS: A total of 150 patients were included in this study (DM with no DR: 50 patients, DM with NPDR: 50 patients, non DM: 50 patients as a control group). The mean CCT and ACW showed significant difference among the three groups (p < 0.001 and p = 0.015 respectively). Based on post hoc result, there were significant mean difference of CCT between non DM and DM with NPDR (mean difference 36.14 μm, p < 0.001) and also between non DM and DM with no DR (mean difference 31.48 μm, p = 0.003). The ACW was significantly narrower in DM with NPDR (11.39 mm SD 0.62) compared to DM with no DR (11.76 mm SD 0.53) (p = 0.012). There were no significant correlation between HbA1c and all the anterior ocular segment biometry.
CONCLUSION: Diabetic patients have significantly thicker CCT regardless of retinopathy status whereas ACW was significantly narrower in DM with NPDR group compared to DM with no DR. There was no significant correlations between HbA1c and all anterior ocular segment biometry in diabetic patients regardless of DR status.
OBJECTIVES: To assess the effects of psychological interventions for diabetes-related distress in adults with T2DM.
SEARCH METHODS: We searched the Cochrane Library, MEDLINE, Embase, PsycINFO, CINAHL, BASE, WHO ICTRP Search Portal and ClinicalTrials.gov. The date of the last search was December 2014 for BASE and 21 September 2016 for all other databases.
SELECTION CRITERIA: We included randomised controlled trials (RCTs) on the effects of psychological interventions for DRD in adults (18 years and older) with T2DM. We included trials if they compared different psychological interventions or compared a psychological intervention with usual care. Primary outcomes were DRD, health-related quality of life (HRQoL) and adverse events. Secondary outcomes were self-efficacy, glycosylated haemoglobin A1c (HbA1c), blood pressure, diabetes-related complications, all-cause mortality and socioeconomic effects.
DATA COLLECTION AND ANALYSIS: Two review authors independently identified publications for inclusion and extracted data. We classified interventions according to their focus on emotion, cognition or emotion-cognition. We performed random-effects meta-analyses to compute overall estimates.
MAIN RESULTS: We identified 30 RCTs with 9177 participants. Sixteen trials were parallel two-arm RCTs, and seven were three-arm parallel trials. There were also seven cluster-randomised trials: two had four arms, and the remaining five had two arms. The median duration of the intervention was six months (range 1 week to 24 months), and the median follow-up period was 12 months (range 0 to 12 months). The trials included a wide spectrum of interventions and were both individual- and group-based.A meta-analysis of all psychological interventions combined versus usual care showed no firm effect on DRD (standardised mean difference (SMD) -0.07; 95% CI -0.16 to 0.03; P = 0.17; 3315 participants; 12 trials; low-quality evidence), HRQoL (SMD 0.01; 95% CI -0.09 to 0.11; P = 0.87; 1932 participants; 5 trials; low-quality evidence), all-cause mortality (11 per 1000 versus 11 per 1000; risk ratio (RR) 1.01; 95% CI 0.17 to 6.03; P = 0.99; 1376 participants; 3 trials; low-quality evidence) or adverse events (17 per 1000 versus 41 per 1000; RR 2.40; 95% CI 0.78 to 7.39; P = 0.13; 438 participants; 3 trials; low-quality evidence). We saw small beneficial effects on self-efficacy and HbA1c at medium-term follow-up (6 to 12 months): on self-efficacy the SMD was 0.15 (95% CI 0.00 to 0.30; P = 0.05; 2675 participants; 6 trials; low-quality evidence) in favour of psychological interventions; on HbA1c there was a mean difference (MD) of -0.14% (95% CI -0.27 to 0.00; P = 0.05; 3165 participants; 11 trials; low-quality evidence) in favour of psychological interventions. Our included trials did not report diabetes-related complications or socioeconomic effects.Many trials were small and were at high risk of bias for incomplete outcome data as well as possible performance and detection biases in the subjective questionnaire-based outcomes assessment, and some appeared to be at risk of selective reporting. There are four trials awaiting further classification. These are parallel RCTs with cognition-focused and emotion-cognition focused interventions. There are another 18 ongoing trials, likely focusing on emotion-cognition or cognition, assessing interventions such as diabetes self-management support, telephone-based cognitive behavioural therapy, stress management and a web application for problem solving in diabetes management. Most of these trials have a community setting and are based in the USA.
AUTHORS' CONCLUSIONS: Low-quality evidence showed that none of the psychological interventions would improve DRD more than usual care. Low-quality evidence is available for improved self-efficacy and HbA1c after psychological interventions. This means that we are uncertain about the effects of psychological interventions on these outcomes. However, psychological interventions probably have no substantial adverse events compared to usual care. More high-quality research with emotion-focused programmes, in non-US and non-European settings and in low- and middle-income countries, is needed.
MATERIALS AND METHODS: A total of 100 adults with type 2 diabetes were assessed with 6-day continuous glucose monitoring and HbA1c . Area under the curve (AUC) ≥5.6 mmol/L was defined as AUCTOTAL . AUC equal to or greater than each preprandial glucose for 4-h duration was defined as AUCPPH . The total PPH (AUCTPPH ) was the sum of the various AUCPPH. The postprandial contribution to overall hyperglycemia was calculated as (AUCTPPH / AUCTOTAL ) × 100%.
RESULTS: The present study comprised of Malay, Indian, and Chinese type 2 diabetes patients at 34, 34 and 28% respectively. Overall, the mean PPH significantly decreased as HbA1c advanced (mixed model repeated measures adjusted, beta-estimate = -3.0, P = 0.009). Age (P = 0.010) and hypoglycemia (P = 0.006) predicted the contribution difference. In oral antidiabetic drug-treated patients (n = 58), FH contribution increased from 54% (HbA1c 6-6.9%) to 67% (HbA1c ≥10%). FH predominance was significant in poorly-controlled groups (P = 0.028 at HbA1c 9-9.9%; P = 0.015 at HbA1c ≥10%). Among insulin users (n = 42), FH predominated when HbA1c was ≥10% before adjustment for hypoglycemia (P = 0.047), whereas PPH was numerically greater when HbA1c was <8%.
CONCLUSIONS: FH and PPH contributions were equal in well-controlled Malaysian type 2 diabetes patients in real-world practice. FH predominated when HbA1c was ≥9 and ≥10% in oral antidiabetic drug- and insulin-treated patients, respectively. A unique observation was the greater PPH contribution when HbA1c was <8% despite the use of basal and mealtime insulin in this multi-ethnic cohort, which required further validation.
OBJECTIVES: To assess the effects of sweet potato for type 2 diabetes mellitus.
SEARCH METHODS: We searched several electronic databases, including The Cochrane Library (2013, Issue 1), MEDLINE, EMBASE, CINAHL, SIGLE and LILACS (all up to February 2013), combined with handsearches. No language restrictions were used.
SELECTION CRITERIA: We included randomised controlled trials (RCTs) that compared sweet potato with a placebo or a comparator intervention, with or without pharmacological or non-pharmacological interventions.
DATA COLLECTION AND ANALYSIS: Two authors independently selected the trials and extracted the data. We evaluated risk of bias by assessing randomisation, allocation concealment, blinding, completeness of outcome data, selective reporting and other potential sources of bias.
MAIN RESULTS: Three RCTs met our inclusion criteria: these investigated a total of 140 participants and ranged from six weeks to five months in duration. All three studies were performed by the same trialist. Overall, the risk of bias of these trials was unclear or high. All RCTs compared the effect of sweet potato preparations with placebo on glycaemic control in type 2 diabetes mellitus. There was a statistically significant improvement in glycosylated haemoglobin A1c (HbA1c) at three to five months with 4 g/day sweet potato preparation compared to placebo (mean difference -0.3% (95% confidence interval -0.6 to -0.04); P = 0.02; 122 participants; 2 trials). No serious adverse effects were reported. Diabetic complications and morbidity, death from any cause, health-related quality of life, well-being, functional outcomes and costs were not investigated.
AUTHORS' CONCLUSIONS: There is insufficient evidence about the use of sweet potato for type 2 diabetes mellitus. In addition to improvement in trial methodology, issues of standardization and quality control of preparations - including other varieties of sweet potato - need to be addressed. Further observational trials and RCTs evaluating the effects of sweet potato are needed to guide any recommendations in clinical practice.
OBJECTIVES: To assess the effects of colesevelam for type 2 diabetes mellitus.
SEARCH METHODS: Several electronic databases were searched, among these The Cochrane Library (Issue 1, 2012), MEDLINE, EMBASE, CINAHL, LILACS, OpenGrey and Proquest Dissertations and Theses database (all up to January 2012), combined with handsearches. No language restriction was used.
SELECTION CRITERIA: We included randomised controlled trials (RCTs) that compared colesevelam with or without other oral hypoglycaemic agents with a placebo or a control intervention with or without oral hypoglycaemic agents.
DATA COLLECTION AND ANALYSIS: Two review authors independently selected the trials and extracted the data. We evaluated risk of bias of trials using the parameters of randomisation, allocation concealment, blinding, completeness of outcome data, selective reporting and other potential sources of bias.
MAIN RESULTS: Six RCTs ranging from 8 to 26 weeks investigating 1450 participants met the inclusion criteria. Overall, the risk of bias of these trials was unclear or high. All RCTs compared the effects of colesevelam with or without other antidiabetic drug treatments with placebo only (one study) or combined with antidiabetic drug treatments. Colesevelam with add-on antidiabetic agents demonstrated a statistically significant reduction in fasting blood glucose with a mean difference (MD) of -15 mg/dL (95% confidence interval (CI) -22 to - 8), P < 0.0001; 1075 participants, 4 trials, no trial with low risk of bias in all domains. There was also a reduction in glycosylated haemoglobin A1c (HbA1c) in favour of colesevelam (MD -0.5% (95% CI -0.6 to -0.4), P < 0.00001; 1315 participants, 5 trials, no trial with low risk of bias in all domains. However, the single trial comparing colesevelam to placebo only (33 participants) did not reveal a statistically significant difference between the two arms - in fact, in both arms HbA1c increased. Colesevelam with add-on antidiabetic agents demonstrated a statistical significant reduction in low-density lipoprotein (LDL)-cholesterol with a MD of -13 mg/dL (95% CI -17 to - 9), P < 0.00001; 886 participants, 4 trials, no trial with low risk of bias in all domains. Non-severe hypoglycaemic episodes were infrequently observed. No other serious adverse effects were reported. There was no documentation of complications of the disease, morbidity, mortality, health-related quality of life and costs.
AUTHORS' CONCLUSIONS: Colesevelam added on to antidiabetic agents showed significant effects on glycaemic control. However, there is a limited number of studies with the different colesevelam/antidiabetic agent combinations. More information on the benefit-risk ratio of colesevelam treatment is necessary to assess the long-term effects, particularly in the management of cardiovascular risks as well as the reduction in micro- and macrovascular complications of type 2 diabetes mellitus. Furthermore, long-term data on health-related quality of life and all-cause mortality also need to be investigated.