METHODS: The index prescriptions were those that when the annual blood tests were reviewed. Prescriptions of medication were verified, compared to the preceding prescriptions and classified as 1) no change, 2) stepping up and 3) stepping down. The treatment targets were HbA1c
OBJECTIVE: This study aims to evaluate the effects of remote telemonitoring with team-based management on people with uncontrolled type 2 diabetes.
DESIGN: This was a pragmatic 52-week cluster-randomized controlled study among 11 primary care government practices in Malaysia.
PARTICIPANTS: People with type 2 diabetes aged 18 and above, who had hemoglobin A1c ≥ 7.5% but less than 11.0% within the past 3 months and resided in the state of Selangor.
INTERVENTION: The intervention group received home gluco-telemonitors and transmitted glucose data to a care team who could adjust therapy accordingly. The team also facilitated self-management by supporting participants to improve medication adherence, and encourage healthier lifestyle and use of resources to reduce risk factors. Usual care group received routine healthcare service.
MAIN MEASURE: The primary outcome was the change in HbA1c at 24 weeks and 52 weeks. Secondary outcomes included change in fasting plasma glucose, blood pressure, lipid levels, health-related quality of life, and diabetes self-efficacy.
RESULTS: A total of 240 participants were recruited in this study. The telemonitoring group reported larger improvements in glycemic control compared with control at the end of study (week 24, - 0.05%; 95% CI - 0.10 to 0.00%) and at follow-up (week 52, - 0.03%; - 0.07 to 0.02%, p = 0.226). Similarly, no differences in other secondary outcomes were observed, including the number of adverse events and health-related quality of life.
CONCLUSION: This study indicates that there is limited benefit of replacing telemedicine with the current practice of self-monitoring of blood glucose. Further innovative methods to improve patient engagement in diabetes care are needed.
TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02466880.
METHODS: This was a quasi-experimental controlled study conducted in 20 intervention and 20 control public primary care clinics in Malaysia from November 2016 to June 2019. Type 2 diabetes patients aged 30 years and above were selected via systematic random sampling. Outcomes include process of care and intermediate clinical outcomes. Difference-in-differences analyses was conducted.
RESULTS: We reviewed 12,017 medical records of patients with type 2 diabetes. Seven process of care measures improved: HbA1c tests (odds ratio (OR) 3.31, 95% CI 2.13, 5.13); lipid test (OR 4.59, 95% CI 2.64, 7.97), LDL (OR 4.33, 95% CI 2.16, 8.70), and urine albumin (OR 1.99, 95% CI 1.12, 3.55) tests; BMI measured (OR 15.80, 95% CI 4.78, 52.24); cardiovascular risk assessment (OR 174.65, 95% CI 16.84, 1810.80); and exercise counselling (OR 1.18, 95% CI 1.04, 1.33). We found no statistically significant changes in intermediate clinical outcomes (i.e. HbA1c, LDL, HDL and BP control).
CONCLUSIONS: EnPHC interventions was successful in enhancing the quality of care, in terms of process of care, by changing healthcare providers behaviour.
METHODS: Five fresh-pooled blood samples were sent to participating laboratories twice each year. The results were evaluated against target values assigned by the National Glycohemoglobin Standardization Program network laboratories; a passing criterion of +/-7% of the target value was used. Measurement uncertainty at Hb A(1c) concentrations of 7.0% and 8.0% were determined.
RESULTS: A total of 276 laboratories from 11 countries took part in the Hb A(1c) survey. At the Hb A(1c) concentrations tested method-specific interlaboratory imprecision (CVs) were 1.1%-13.9% in 2005, 1.3%-10.1% in 2006, 1.2%-8.2% in 2007, and 1.1%-6.1% in 2008. Differences between target values and median values from the commonly used methods ranged from -0.24% to 0.22% Hb A(1c) in 2008. In 2005 83% of laboratories passed the survey, and in 2008 93% passed. At 7.0% Hb A(1c), measurement uncertainty was on average 0.49% Hb A(1c).
CONCLUSIONS: The use of accuracy-based proficiency testing with stringent quality criteria has improved the performance of Hb A(1c) testing in the Asian and Pacific laboratories during the 4 years of assessment.
METHODS: Haemoglobin variants were identified by HbA1c analysis in 93 of 3522 samples sent to our laboratory in a period of 1 month. Haemoglobin analysis identified HbE trait in 81 of 93 samples. To determine the influence of HbE trait on HbA1c analysis by Variant II Tubo 2.0, boronate affinity high performance liquid chromatography (HPLC) method (Primus PDQ) was used as the comparison method. Two stage linear regression analysis, Bland Altman plot and Deming regression analysis were performed to analyse whether the presence of HbE trait produced a statistically significant difference in the results. The total allowable error for HbA1c by the Royal Australasian College of Pathologists (RCPA) external quality assurance is 5%. Hence clinically significant difference is more than 5% at the medical decision level of 6% and 9%.
RESULTS: Statistically and clinically significant higher results were observed in Variant II Turbo 2.0 due to the presence of HbE trait. A positive bias of ∼10% was observed at the medical decision levels.
CONCLUSION: Laboratories should be cautious when evaluating HbA1c results in the presence of haemoglobin variants.
METHODS: Demographic and clinical variables were assessed at baseline, after three and six months in 73 type 2 diabetes patients. Regression analysis, using SPSS, evaluated the concurrent and longitudinal association of medication adherence and glycemic control. Potential confounders of variables were identified using bi-variate correlation analyses.
RESULTS: Concurrent Medication adherence and HbA1c association were significant after adjusting for ethnicity (P = 0.005). For longitudinal observation at 3 months, the association was significant after adjusting for ethnicity (P = 0.016); however, it became non-significant when baseline glycemic control was included in the model (P = 0.28).
CONCLUSION: Easy to administer MALMAS significantly predicted concurrent glycemic control independent of potential confounders. This association persisted in longitudinal observation after 3 months when adjusted for confounders and became non-significant after adjusting for baseline glycemic control.
METHODS: In this cross-sectional study, interviews and a standardised questionnaire comparing lifestyle changes before and during the lockdown were performed in follow-up clinic visits after the lockdown. Anthropometry measurements and glycated haemoglobin (HbA1c) values were compared 3 months prior and after the lockdown.
RESULTS: Participants were 93 patients with T1DM (11.08 ± 3.47 years) and 30 patients with T2DM (13.81 ± 2.03 years). Male gender, T2DM and pubertal adolescents were found to have a significant deterioration in glycaemic control. A significant increment of HbA1c was observed in patients with T2DM (8.5 ± 0.40 vs 9.9 ± 0.46%), but not in patients with T1DM (8.6 ± 0.28 vs 8.7 ± 0.33%). Contrarily, there was an improved glycaemic control in pre-pubertal T1DM children likely due to parental supervision during home confinement. Weight and BMI SDS increased in T1DM patients but surprisingly reduced in T2DM patients possibly due to worsening diabetes control. Reduced meal frequency mainly due to skipping breakfast, reduced physical activity level scores, increased screen time and sleep duration were observed in both groups.
CONCLUSIONS: Adverse impact on glycaemic control and lifestyle were seen mostly in patients with T2DM and pubertal adolescent boys.
METHODS: A randomized, double-blind, placebo-controlled trial was performed in a university hospital. Women with GDMA1 were recruited at 16-30 weeks of pregnancy and randomized to oral metformin 500 mg twice daily or identical placebo tablets to delivery. Level of HbA1c was taken at recruitment and at 36 weeks of pregnancy. The primary outcome was the change in level of HbA1c at recruitment and 36 weeks of pregnancy.
RESULTS: Data from 106 participants were analyzed. The level of HbA1c during pregnancy increased significantly with a mean increase of 0.20% ± 0.31% (P
PARTICIPANTS: Between 2020 and 2021, 383 children and young people with T1D who were active in the A4D supported programmes were reviewed including information on health coverage, multidisciplinary team management, diabetic ketoacidosis (DKA) on admission and insulin regimen.
RESULTS: Mean HbA1c between 2020 and 2021 for patients in these LMICs arereported for the first time. The average glycaemic index in the five SEAcountries reviewed between 2020 and 2021 were high at 83 mmol/mol (9.7%).
CONCLUSIONS: Government partnership working with non-government organisationsto support T1D from diagnosis to adulthood are the first steps to closing thegaps in many LMICs. Further epidemiological studies are needed to identify the glycaemic outcomes and DKA rates on admission for many of these countries.
METHODS: A cross-sectional study involving 20 primary healthcare clinics in the North East Region of Peninsular Malaysia and people with T2DM as the sampling unit was conducted from February to May 2019. The pro forma checklist, interview-guided Skala Kepuasan Interaksi Perubatan-11, and Patient Assessment of Chronic Illness Care (Malay version; PACIC-M) questionnaire were used for data collection. Univariate analysis and linear regression were used to determine the status of perceived quality of care and the factors associated with the perceived quality of care, respectively.
RESULTS: Overall, data from 772 participants were analyzed. The majority was from the Malay ethnic group (95.6%) with a mean (standard deviation [SD]) glycated hemoglobin A1c (HbA1c) level of 8.91% (2.30). The median (interquartile range [IQR]) of the number of medical officers available at each clinic was 6 (7), with Family Doctor Concept (FDC) clinics having a higher number of medical officers than non-FDC clinics (p = 0.001). The overall mean (SD) PACIC-M score was 2.65 (0.54) with no significant difference between scores of patients treated in the two clinic types (p = 0.806). Higher perceived quality of care was associated with lower number of medical officers (adjusted regression coefficient [Adj.β], - 0.021; p-value [p], 0.001), and greater doctor-patient interaction in all domains: distress relief (Adj.β, 0.033; p,
MATERIAL AND METHODS: We performed a questionnaire-based cross-sectional study at Hospital Canselor Tuanku Muhriz (HCTM) from a period of 15 months. A total of 133 T1DM patients who fulfilled our study's criteria were subjected to otoscopy examination, tuning fork test and free field voice test. The mini-Tinnitus Questionnaire (TQ) was used to assess the severity of tinnitus. We were careful to categorize the perceived duration of tinnitus.
RESULTS: The prevalence of tinnitus among T1DM patients was 24.1% (32/133 patients). Out of 32 patients, approximately 78.1% (25 patients) had a compensated level of tinnitus distress and the remaining 21.9% (7/32) had moderate tinnitus. The duration of tinnitus ranged from 2 seconds to 2 minutes, whıch was ringing and intermittent in nature. The HbA1c and estimated Glomerular Filtration Rate (eGFR) were higher in tinnitus compared to the non-tinnitus group. There was no significant correlation between the severity of tinnitus and HbA1c level or eGFR.
CONCLUSIONS: Our study concluded that tinnitus amongst T1DM patients was likely to be non-pathological in view of its short duration with minimal to no distress to the sufferers. An elevated HbA1c may increase the risk of developıng tinnitus.
MATERIALS AND METHODS: A cross-sectional study was conducted in Luyang Health Clinic from 1st June 2020 to 3rd September 2020. A self-interviewed questionnaire comprises of three sections; sociodemographic, Wake Forest Physician Trust Scale (WFS) and Adherence to Refills and Medications Scale (ARMS) was completed by 281 respondents. Glycaemic control is based on the latest Hba1c profile of the respondents. Descriptive and nonparametric bivariate analysis were performed using IBM SPSS version 26.
RESULTS: The median (IQR) level of trust in physician was 43(8) out of a possible score range of 10 to 50. Trust in physician was correlated with treatment adherence (r=-0.12, p=0.048). There was no significant association between trust in physician with sociodemographic factors, which include age (p=0.33), gender (p=0.46), ethnicity (p=0.70), education level (p=0.50), and household income (p=0.37). Similarly, there was no significant association between the level of trust in physician with glycaemic control (p=0.709).
CONCLUSION: In conclusion, trust in physician was associated with treatment adherence but not with glycaemic control. In our local context, the glycaemic control could be due to other factors. Further studies should include a multicentre population to assess other potential factors that could contribute to glycaemic control.
OBJECTIVES: To assess the effects of interventions for people with type 2 diabetes fasting during Ramadan.
SEARCH METHODS: We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, WHO ICTRP and ClinicalTrials.gov (29 June 2022) without language restrictions.
SELECTION CRITERIA: Randomised controlled trials (RCTs) conducted during Ramadan that evaluated all pharmacological or behavioural interventions in Muslims with T2DM.
DATA COLLECTION AND ANALYSIS: Two authors screened and selected records, assessed risk of bias and extracted data independently. Discrepancies were resolved by a third author. For meta-analyses we used a random-effects model, with risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes with their associated 95% confidence intervals (CIs). We assessed the certainty of evidence using the GRADE approach.
MAIN RESULTS: We included 17 RCTs with 5359 participants, with a four-week study duration and at least four weeks of follow-up. All studies had at least one high-risk domain in the risk of bias assessment. Four trials compared dipeptidyl-peptidase-4 (DPP-4) inhibitors with sulphonylurea. DPP-4 inhibitors may reduce hypoglycaemia compared to sulphonylureas (85/1237 versus 165/1258, RR 0.53, 95% CI 0.41 to 0.68; low-certainty evidence). Serious hypoglycaemia was similar between groups (no events were reported in two trials; 6/279 in the DPP-4 versus 4/278 in the sulphonylurea group was reported in one trial, RR 1.49, 95% CI 0.43 to 5.24; very low-certainty evidence). The evidence was very uncertain about the effects of DPP-4 inhibitors on adverse events other than hypoglycaemia (141/1207 versus 157/1219, RR 0.90, 95% CI 0.52 to 1.54) and HbA1c changes (MD -0.11%, 95% CI -0.57 to 0.36) (very low-certainty evidence for both outcomes). No deaths were reported (moderate-certainty evidence). Health-related quality of life (HRQoL) and treatment satisfaction were not evaluated. Two trials compared meglitinides with sulphonylurea. The evidence is very uncertain about the effect on hypoglycaemia (14/133 versus 21/140, RR 0.72, 95% CI 0.40 to 1.28) and HbA1c changes (MD 0.38%, 95% CI 0.35% to 0.41%) (very low-certainty evidence for both outcomes). Death, serious hypoglycaemic events, adverse events, treatment satisfaction and HRQoL were not evaluated. One trial compared sodium-glucose co-transporter-2 (SGLT-2) inhibitors with sulphonylurea. SGLT-2 may reduce hypoglycaemia compared to sulphonylurea (4/58 versus 13/52, RR 0.28, 95% CI 0.10 to 0.79; low-certainty evidence). The evidence was very uncertain for serious hypoglycaemia (one event reported in both groups, RR 0.90, 95% CI 0.06 to 13.97) and adverse events other than hypoglycaemia (20/58 versus 18/52, RR 1.00, 95% CI 0.60 to 1.67) (very low-certainty evidence for both outcomes). SGLT-2 inhibitors result in little or no difference in HbA1c (MD 0.27%, 95% CI -0.04 to 0.58; 1 trial, 110 participants; low-certainty evidence). Death, treatment satisfaction and HRQoL were not evaluated. Three trials compared glucagon-like peptide 1 (GLP-1) analogues with sulphonylurea. GLP-1 analogues may reduce hypoglycaemia compared to sulphonylurea (20/291 versus 48/305, RR 0.45, 95% CI 0.28 to 0.74; low-certainty evidence). The evidence was very uncertain for serious hypoglycaemia (0/91 versus 1/91, RR 0.33, 95% CI 0.01 to 7.99; very low-certainty evidence). The evidence suggests that GLP-1 analogues result in little to no difference in adverse events other than hypoglycaemia (78/244 versus 55/255, RR 1.50, 95% CI 0.86 to 2.61; very low-certainty evidence), treatment satisfaction (MD -0.18, 95% CI -3.18 to 2.82; very low-certainty evidence) or change in HbA1c (MD -0.04%, 95% CI -0.45% to 0.36%; 2 trials, 246 participants; low-certainty evidence). Death and HRQoL were not evaluated. Two trials compared insulin analogues with biphasic insulin. The evidence was very uncertain about the effects of insulin analogues on hypoglycaemia (47/256 versus 81/244, RR 0.43, 95% CI 0.13 to 1.40) and serious hypoglycaemia (4/131 versus 3/132, RR 1.34, 95% CI 0.31 to 5.89) (very low-certainty evidence for both outcomes). The evidence was very uncertain for the effect of insulin analogues on adverse effects other than hypoglycaemia (109/256 versus 114/244, RR 0.83, 95% CI 0.44 to 1.56; very low-certainty evidence), all-cause mortality (1/131 versus 0/132, RR 3.02, 95% CI 0.12 to 73.53; very low-certainty evidence) and HbA1c changes (MD 0.03%, 95% CI -0.17% to 0.23%; 1 trial, 245 participants; very low-certainty evidence). Treatment satisfaction and HRQoL were not evaluated. Two trials compared telemedicine with usual care. The evidence was very uncertain about the effect of telemedicine on hypoglycaemia compared with usual care (9/63 versus 23/58, RR 0.42, 95% CI 0.24 to 0.74; very low-certainty evidence), HRQoL (MD 0.06, 95% CI -0.03 to 0.15; very low-certainty evidence) and HbA1c change (MD -0.84%, 95% CI -1.51% to -0.17%; very low-certainty evidence). Death, serious hypoglycaemia, AEs other than hypoglycaemia and treatment satisfaction were not evaluated. Two trials compared Ramadan-focused patient education with usual care. The evidence was very uncertain about the effect of Ramadan-focused patient education on hypoglycaemia (49/213 versus 42/209, RR 1.17, 95% CI 0.82 to 1.66; very low-certainty evidence) and HbA1c change (MD -0.40%, 95% CI -0.73% to -0.06%; very low-certainty evidence). Death, serious hypoglycaemia, adverse events other than hypoglycaemia, treatment satisfaction and HRQoL were not evaluated. One trial compared drug dosage reduction with usual care. The evidence is very uncertain about the effect of drug dosage reduction on hypoglycaemia (19/452 versus 52/226, RR 0.18, 95% CI 0.11 to 0.30; very low-certainty evidence). No participants experienced adverse events other than hypoglycaemia during the study (very low-certainty evidence). Death, serious hypoglycaemia, treatment satisfaction, HbA1c change and HRQoL were not evaluated.
AUTHORS' CONCLUSIONS: There is no clear evidence of the benefits or harms of interventions for individuals with T2DM who fast during Ramadan. All results should be interpreted with caution due to concerns about risk of bias, imprecision and inconsistency between studies, which give rise to low- to very low-certainty evidence. Major outcomes, such as mortality, health-related quality of life and severe hypoglycaemia, were rarely evaluated. Sufficiently powered studies that examine the effects of various interventions on these outcomes are needed.
RECENT FINDINGS: Twelve studies were included in this review. A team of multidisciplinary healthcare professionals coordinated most interventions, half of which lasted for 6 months, and used a combination of videos, texts, images or audio to deliver the educational materials. The glycosylated hemoglobin (HbA1c) level improved in most of the studies, followed by diabetes self-care and fasting plasma glucose. The dietary intakes were only assessed in two interventions among the individuals with prediabetes and showed promising improvements. This scoping review provides a holistic overview of the recent designs of lifestyle interventions for diabetes management and prevention on social media. This is essential for various healthcare professionals and stakeholders to formulate and implement population-based, cost-effective interventions in combating diabetes using social media.