Diagnosed duration of type-2 diabetes mellitus and periodontitis

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Assessing self-efficacy behaviour of type 2 diabetes mellitus in primary care

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Confirmatory factor analysis on traditional Chinese version of 26-item Diabetes Self-Efficacy Scale (C-DSES) in Chinese patients with type 2 diabetes mellitus

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Effect of oral health care on Chinese diabetic patients

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Simple non-laboratory-based and laboratory-based risk assessment algorithms and nomogram for detecting undiagnosed diabetes mellitus

This journal suppl. entitled: Abstracts of the 10th International Diabetes Federation–Western Pacific Region Congress and the 6th AASD Scientific MeetingBACKGROUND: Early detection for undiagnosed diabetes mellitus (DM), through routine screening periodically, is critical to prevent or delay severe diabetes-related complications. In order to classify high-risk subjects for DM screening, risk algorithms for undiagnosed DM detection have been richly developed and validated in diverse populations and health care settings. However, the majority of risk algorithms developed within Chinese population were developed and validated in low income setting. Furthermore, there are no nomograms for the use in detecting undiagnosed DM, of which are simple-to-use graphical tool to guide decision-making in both routine clinical practice and community setting. The purpose of this study was to develop simple a nomogram to predict the risk of undiagnosed DM for use in asymptomatic general population, based on non-laboratory-based ...postprin

One-stage debridement versus conventional therapy in type-2 diabetic periodontitis patients

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The pregnant woman with heart disease: management of pregnancy and delivery

Women with heart disease are at risk of cardiac complications during pregnancy and delivery. Risk assessment should be performed in these women, and the management of pregnancy and delivery should be planned accordingly. Depending on the risk, women should be cared for in specialised centres, regional centres or a combination of both. Multidisciplinary teams must be involved in the care of these women. Adequate organisation of care and communication between the team members is important to prevent complications

Simple Non-laboratory- and Laboratory-based Risk Assessment Algorithms and Nomogram for Detecting Undiagnosed Diabetes Mellitus

Background: To develop a simple nomogram which can be used to predict the risk of diabetes mellitus (DM) in asymptomatic non-diabetic general population based on non-laboratory-based and laboratory-based risk algorithms. Methods: Anthropometric data, plasma fasting glucose, full lipid profile, exercise habit and family history of DM were collected from Chinese non-diabetic subjects aged 18-70. Logistic regression analysis was performed on the data of a random sample of 2518 subjects to construct non-laboratory-based and laboratory-based risk assessment algorithms for the detection of undiagnosed DM; both algorithms were validated on the data of the remaining sample (n=839). Hosmer-Lemeshow χ2 statistic and area under the receiver-operating characteristic curve (AUC) were employed to assess the calibration and discrimination of the different DM risk algorithms. Results: Of 3357 subjects recruited, 271 (8.1%) had undiagnosed DM defined by fasting glucose≥7.0mmol/L or 2-hour post-load plasma glucose≥11.1mmol/L after oral glucose tolerance test. The non-laboratory-based risk algorithm, with score ranging from 0 to 33, included age, body mass index, family history of DM, regular exercise and uncontrolled blood pressure; the laboratory-based risk algorithm, with score ranging from 0 to 37, added triglyceride level to the risk factors. Both algorithms demonstrated acceptable calibration (Hosmer-Lemeshow test: P=0.229 and P=0.483, respectively) and discrimination (AUC: 0.709 and 0.711, respectively) for the detection of undiagnosed DM. The optimal cutoff point on the receiver-operating characteristic curve was 18 for the detection of undiagnosed DM in both algorithms. Conclusions: Simple-to-use nomogram for detecting undiagnosed DM has been developed using the validated non-laboratory-based and laboratory-based risk algorithms.postprin

Cost-Effectiveness of a Short Message Service Intervention to Prevent Type 2 Diabetes from Impaired Glucose Tolerance

Aims. To investigate the costs and cost-effectiveness of a short message service (SMS) intervention to prevent the onset of type 2 diabetes mellitus (T2DM) in subjects with impaired glucose tolerance (IGT). Methods. A Markov model was developed to simulate the cost and effectiveness outcomes of the SMS intervention and usual clinical practice from the health provider’s perspective. The direct programme costs and the two-year SMS intervention costs were evaluated in subjects with IGT. All costs were expressed in 2011 US dollars. The incremental cost-effectiveness ratio was calculated as cost per T2DM onset prevented, cost per life year gained, and cost per quality adjusted life year (QALY) gained. Results. Within the two-year trial period, the net intervention cost of the SMS group was $42.03 per subject. The SMS intervention managed to reduce 5.05$118.39 per subject over two years. In the lifetime model, the SMS intervention dominated the control by gaining an additional 0.071 QALY and saving $1020.35 per person. The SMS intervention remained dominant in all sensitivity analyses. Conclusions. The SMS intervention for IGT subjects had the superiority of lower monetary cost and a considerable improvement in preventing or delaying the T2DM onset. This trial is registered with ClinicalTrials.gov NCT01556880.published_or_final_versio