Factors that drive insulin-dosing decisions of diabetes care providers: a vignette-based study in the Netherlands.

AIM: To test how certain patient factors would influence the decision of Dutch care providers regarding insulin dose adjustments. We hypothesize that some of these decisions would diverge from recent evidence and consensus statements. METHODS: We developed narrative vignettes describing clinical scenarios of patients receiving basal insulin therapy. For each vignette, the respondents were asked to indicate whether they would advise a change in insulin dose. A total of 520 paper questionnaires were distributed among physicians and nurses in primary and secondary care in the Netherlands. Multivariate linear and logistic regression analyses were performed to identify factors associated with dosing decisions. RESULTS: A total of 190 (37%) questionnaires were returned. In cases of a severe rather than mild hypoglycaemic event, care providers were nearly five times more likely to decrease the dose (odds ratio 4.77, 95% CI 1.65-13.75). Care providers were six times more likely to increase the dose when the patient's current dose was low (30 units) rather than high (90 units) (odds ratio 6.38, 95% CI 3.04-13.37). The plasma glucose concentration during a hypoglycaemic event and a known history of cardiovascular disease did not influence the care providers' dosing decisions. CONCLUSION: Evidence regarding the optimum insulin titration is not always translated into clinical practice. When formulating guidelines, misconceptions should be identified and addressed.

Physical characteristics that predict final basal insulin dose in type 2 diabetes mellitus, with a special focus on BMI.

BACKGROUND AND AIMS: The possibility to predict final insulin dose based on patient's characteristics would allow for efficient titration for patients with higher dose needs. The primary aim of this post-hoc analysis of the L2T3 study was to determine predictors for final dose. Specifically, we focused on the relationship between BMI and dose. The secondary aims were to investigate (i) the predictive value of BMI and age on final dose and (ii) the possibility to tailor the starting dose of insulin based on BMI and age. METHODS AND RESULTS: We performed two stepwise regression analyses, one using all baseline characteristics, and one using physical characteristics and FPG which can be assessed "at the bedside" only. Furthermore, median [min, max] final doses of groups stratified according to BMI and age were calculated. BMI clearly correlated with final dose in IU (Pearson correlation 0.42 [0.37; 0.48], p < 0.001). Characteristics which can be assessed "at the bedside" that predict high final dose were allocation to detemir, absence or discontinuation of insulin secretagogues, high BMI, low age, male gender and high FPG. Final dose varied among strata (BMI ≥30 kg/m(2): 64 IU; BMI <30 kg/m(2): 38 IU, p < 0.001 and age <59 years: 52 IU; age ≥59 years: 44 IU, p < 0.001). All groups stratified for both BMI and age showed similarly low minimal final dose (5-17 IU). CONCLUSION: Our data showed a high predictive value of BMI on final dose. However, it does not seem possible to tailor starting dose based on BMI and age.

The incidence of mild and severe hypoglycaemia in patients with type 2 diabetes mellitus treated with sulfonylureas: a systematic review and meta-analysis.

Patients with type 2 diabetes mellitus using sulfonylurea derivatives or insulin may experience hypoglycaemia. However, recent data regarding the incidence of hypoglycaemia are scarce. We conducted a systematic review and meta-analysis to determine the proportion of patients with type 2 diabetes mellitus that experience hypoglycaemia when treated with sulfonylurea or insulin. We searched MEDLINE and EMBASE for randomized controlled trials that compared incretin-based drugs to sulfonylureas or insulin and assessed hypoglycaemia incidence in the latter therapies. Subgroup and meta-regression analyses were performed to study possible associations with potential risk factors for hypoglycaemia. Data of 25 studies were extracted, 22 for sulfonylurea and 3 for insulin. Hypoglycaemia with glucose ≤3.1 mmol/L or ≤2.8 mmol/L was experienced by 10.1% [95% confidence interval (CI) 7.3-13.8%] and 5.9% (95% CI 2.5-13.4%) of patients with any sulfonylurea treatment. Severe hypoglycaemia was experienced by 0.8% (95% CI 0.5-1.3%) of patients. Hypoglycaemia with glucose ≤3.1 mmol/L and severe hypoglycaemia occurred least frequently with gliclazide: in 1.4% (95% CI 0.8-2.4%) and 0.1% (95% CI 0-0.7%) of patients, respectively. None of the risk factors were significant in a stepwise multivariate meta-regression analysis. Too few studies had insulin as comparator, so these data could not be meta-analysed. The majority of patients with type 2 diabetes mellitus on sulfonylurea therapy in clinical trials remain free of any relevant hypoglycaemia. Gliclazide was associated with the lowest risk of hypoglycaemia. Because participants in randomized controlled trials differ from the general population, care should be taken when translating these data into clinical practice.

Safety of a web-based insulin titration system for patients with type 2 diabetes mellitus - pilot study.

The treatment of type 2 diabetes patients with insulin requires active dose titration to obtain optimal glycemic control. We developed a web-based decision support system to guide patients in performing the titration task autonomously, at their homes. The system is based on a clinically validated algorithm. The aim of this study was to test the safety of the system in a pilot implementation in clinical practice. Patients were blinded from the advice given by the system and instead received insulin dosing advice given by caregivers. At the end of the pilot, advice of the system were evaluated on safety by an expert panel. In this pilot study six patients used the web-based system at their home. In total, 48 advice were logged in the system resulting in eighteen deviating systems dosing advice as compared to the advice of the caregiver. Evaluation of the eighteen deviating systems advice lead to the detection of one unsafe advice indicating a need to extend the algorithm with an additional safety decision rule.

Development of a web-based decision support system for insulin self-titration.

Insulin is the most potent agent for the treatment of diabetes mellitus. However insulin treatment requires frequent evaluation of blood glucose levels and adjustment of the insulin dose. This process is called titration. To guide patients with type 2 diabetes using once-daily long-acting insulin, we have developed a web-based decision support system for insulin self-titration. The purpose of this paper is to provide an overview of the phases of development and the final design of the system. We reviewed the literature, consulted an expert panel, and conducted interviews with patients to elicit system requirements. This revealed four important aspects: the insulin titration algorithm, the handling of hypoglycemic events, telemedicine functionalities, and visiting frequency monitoring. We used these requirements to develop a fully functional system.