OBJECTIVES: To (1) assess the factor structure of the Malay Audit of Diabetes Dependent Quality of Life-18 (ADDQoL-18) questionnaire; (2) determine the impact of DM on QoL; and (3) identify areas of concern to patients with type 2 DM from three major ethnic groups in Malaysia.
METHODS: Data was obtained from a cross sectional study involving 256 patients with type 2 DM attending the diabetes clinic of the National University of Malaysia Medical Centre. The Malay version of ADDQoL-18 survey was translated from its English version according to standard guidelines and administered by a trained research assistant. Exploratory Factor Analysis (EFA) with oblimin rotation was used to determine factor structure of the data. Confirmatory Factor Analysis (CFA) was used to confirm the factor structure. Hierarchical liner regression was used to determine factors associated with QoL.
RESULTS: Unforced factor solution yielded two factors for the whole sample. Forced one factor solution was ascertained for the whole sample and for each ethnic group. Loadings ranged between 0.588 and 0.949. Reliability coefficients were all higher than 0.955. CFA showed that the two factor model had better fit statistics. QoL was associated with the use of insulin and desired glycaemic control, longer diabetes duration, worry about diabetes, and diabetes complications.
CONCLUSIONS: The Malay ADDQoL-18 is a valid tool to be used among patients with diabetes from different ethnic groups in Malaysia. The use of insulin to achieve desired glycaemic control had more negative impact on QoL than the use of tablets and/or dietary changes.
SETTING: The study was conducted at a tertiary hospital in the northern region of Peninsular Malaysia. Methods Action research methodology was used.
MAIN OUTCOME MEASURE: Pharmaceutical care issues.
RESULTS: The prevalence of diabetes mellitus among newly diagnosed tuberculosis patients was 15% (53/352). Out of 53 patients identified, 35 participated in the study. Patients' ages ranged between 29 and 73 years (mean of 52 ± 10 years). The male: female ratio was 1.7:1. Pharmaceutical care issues identified by pharmacists were nonadherence, uncontrolled diabetes mellitus, adverse drug reactions and individual patient's medication related problems. Pharmacists were able to intervene and resolve some of the pharmaceutical care issues.
CONCLUSION: Pharmacists played an important role in integrating the provision of care for tuberculosis and diabetes mellitus by providing individualised pharmaceutical care management. There still remains a need to address logistic barriers that impinged on the ability to conduct the pharmaceutical care service to its full potential.
METHODS: Data on demography, diabetes status, management and complications were collected via medical records, interview and laboratory assessments. HbA(1c) was analysed by a central laboratory prospectively.
RESULTS: Patient profile was similar in the 1998 (N = 21,838) and 2003 cohorts (N = 15,549): 95% were diagnosed as type 2 diabetes mellitus and were obese (BMI approximately 25 kg/m(2)). Glycaemic control was unsatisfactory in many patients (mean HbA(1c) approximately 8%; fasting glucose approximately 9 mmol/L). Lipids were well-controlled but hypertension was not. The incidence of neuropathy ( approximately 33%) and cataract ( approximately 27%) were high. The majority ( approximately 71%) of patients in both cohorts were treated with oral antidiabetic drug (OAD) monotherapy; approximately 24% were on insulin therapy. Approximately half of the 2003 cohort reported a healthy state of well-being. Quality of life did not appear to have suffered as a result of having diabetes. However, many patients were worried about hypoglycaemic risk (53.9%) or worsening of diabetes (45.8%) and insulin initiation (64.5%).
CONCLUSIONS: Although both cohorts were separate cross-sectional studies of diabetes management status in Asia, the results showed that the demography profile, glycaemic control and cardiovascular risk factors were remarkably similar in both cohorts 5 years after the first survey. More concerted efforts are needed to increase diabetes awareness and education.
METHODS: We assessed sCD26/DPP-IV levels, active GLP-1 levels, body mass index (BMI), glucose, insulin, A1c, glucose homeostasis indices, and lipid profiles in 549 Malaysian subjects (including 257 T2DM patients with MetS, 57 T2DM patients without MetS, 71 non-diabetics with MetS, and 164 control subjects without diabetes or metabolic syndrome).
RESULTS: Fasting serum levels of sCD26/DPP-IV were significantly higher in T2DM patients with and without MetS than in normal subjects. Likewise, sCD26/DPP-IV levels were significantly higher in patients with T2DM and MetS than in non-diabetic patients with MetS. However, active GLP-1 levels were significantly lower in T2DM patients both with and without MetS than in normal subjects. In T2DM subjects, sCD26/DPP-IV levels were associated with significantly higher A1c levels, but were significantly lower in patients using monotherapy with metformin. In addition, no significant differences in sCD26/DPP-IV levels were found between diabetic subjects with and without MetS. Furthermore, sCD26/DPP-IV levels were negatively correlated with active GLP-1 levels in T2DM patients both with and without MetS. In normal subjects, sCD26/DPP-IV levels were associated with increased BMI, cholesterol, and LDL-cholesterol (LDL-c) levels.
CONCLUSION: Serum sCD26/DPP-IV levels increased in T2DM subjects with and without MetS. Active GLP-1 levels decreased in T2DM patients both with and without MetS. In addition, sCD26/DPP-IV levels were associated with Alc levels and negatively correlated with active GLP-1 levels. Moreover, metformin monotherapy was associated with reduced sCD26/DPP-IV levels. In normal subjects, sCD26/DPP-IV levels were associated with increased BMI, cholesterol, and LDL-c.
PATIENTS & METHODS: DPP4, WFS1 and KCNJ11 gene polymorphisms were genotyped in a cohort study of 662 T2DM patients treated with DPP-4 inhibitors sitagliptin, vildagliptin or linagliptin. Genotyping was performed by Applied Biosystems TaqMan SNP genotyping assay.
RESULTS: Patients with triglyceride levels less than 1.7 mmol/l (odds ratio [OR]: 2.2.; 95% CI: 1.031-4.723), diastolic blood pressure (DBP) less than 90 mmHg (OR: 1.7; 95% CI: 1.009-2.892) and KCNJ11 rs2285676 (genotype CC) (OR: 2.0; 95% CI: 1.025-3.767) were more likely to response to DPP-4 inhibitor treatment compared with other patients, as measured by HbA1c levels.
CONCLUSION: Triglycerides, DBP and KCNJ11 rs2285676 are predictors of the DPP-4 inhibitor treatment response in T2DM patients.
METHODS: This open-label, parallel-group, 26-week, multicentre, treat-to-target trial, randomly allocated participants (1:1) to two titration arms. The Simple algorithm titrated IDegAsp twice weekly based on a single pre-breakfast self-monitored plasma glucose (SMPG) measurement. The Stepwise algorithm titrated IDegAsp once weekly based on the lowest of three consecutive pre-breakfast SMPG measurements. In both groups, IDegAsp once daily was titrated to pre-breakfast plasma glucose values of 4.0-5.0 mmol/l. Primary endpoint was change from baseline in HbA1c (%) after 26 weeks.
RESULTS: Change in HbA1c at Week 26 was IDegAspSimple -14.6 mmol/mol (-1.3%) (to 52.4 mmol/mol; 6.9%) and IDegAspStepwise -11.9 mmol/mol (-1.1%) (to 54.7 mmol/mol; 7.2%). The estimated between-group treatment difference was -1.97 mmol/mol [95% confidence interval (CI) -4.1, 0.2] (-0.2%, 95% CI -0.4, 0.02), confirming the non-inferiority of IDegAspSimple to IDegAspStepwise (non-inferiority limit of ≤ 0.4%). Mean reduction in fasting plasma glucose and 8-point SMPG profiles were similar between groups. Rates of confirmed hypoglycaemia were lower for IDegAspStepwise [2.1 per patient years of exposure (PYE)] vs. IDegAspSimple (3.3 PYE) (estimated rate ratio IDegAspSimple /IDegAspStepwise 1.8; 95% CI 1.1, 2.9). Nocturnal hypoglycaemia rates were similar between groups. No severe hypoglycaemic events were reported.
CONCLUSIONS: In participants with insulin-naïve Type 2 diabetes mellitus, the IDegAspSimple titration algorithm improved HbA1c levels as effectively as a Stepwise titration algorithm. Hypoglycaemia rates were lower in the Stepwise arm.