A method to predict the metabolic effects of changes in insulin treatment in subgroups of a large population based patient cohort.

This case-control study was designed to analyse predictors of the effects on HbA1c levels in 4001 type 1 and type 2 diabetic patients after changing their insulin treatment. Patients from 15 outpatient diabetic clinics were treated with basal insulin and multiple injections of short-acting insulin. The effects on HbA1c of changing from NPH insulin to insulin glargine as basal insulin were studied, compared to patients continuing with NPH insulin. The following possible predictors were examined with multiple regression analysis: age, sex, type and duration of diabetes, smoking, metformin use, insulin requirement, number of basal doses per day, BMI and HbA1c at baseline. The difference between the two regression functions yielded the effect of switching treatment to insulin glargine compared to continuing with NPH insulin. Male gender, low BMI and high baseline HbA1c levels were significant predictors for a greater decrease in HbA1c when changing to insulin glargine. For example, for men with a BMI of 25 and an HbA1c of 8.0%, there was a calculated mean benefit in HbA1c of 0.26 percentage points by changing to insulin glargine, whereas women with a BMI 30 had no benefit of such a change. Thus, changing to insulin glargine had best effect in male patients with low BMI. This is one of the first studies designed to find responders to insulin treatment. Analyses of predictors may prove useful in order to tailor insulin treatment in diabetic patients in clinical practice. The clinical effects need to be confirmed in other studies and randomised controlled trials

The relationship between the exposure time of insulin glargine and risk of breast and prostate cancer: An observational study of the time-dependent effects of antidiabetic treatments in patients with diabetes.

AIMS: To elucidate methodological questions in assessing the relationship between insulin treatment and cancer, since the risk of tumour growth generally increases with longer exposure time and higher dose of a growth promoting substance. METHODS: Continuous hazard functions for risk of breast and prostate cancer were estimated in relation to exposure of insulin glargine among diabetic patients included in the record system, Diab-Base, as well as in the general population in Sweden. RESULTS: In 7942 female diabetic patients, mean follow-up 7.0 years, 2014 patients initiated insulin glargine with a mean follow-up of 3.5 years. Among 11,613 men, mean follow-up 6.9 years, 2760 had a mean follow-up with glargine of 3.4 years. Risk of prostate cancer decreased significantly with longer exposure to insulin glargine (p=0.032), although average risk versus non-glargine was non-significantly higher (HR 1.37, 95% CI 0.78-2.39). The breast cancer risk did not change with longer exposure to insulin glargine (p=0.35) and the mean risk was similar for glargine and non-glargine (p=0.12). With higher dose of insulin glargine, there was an increase in risk of prostate (p=0.037) and breast cancer (p=0.019). In diabetics, the mean risk of prostate cancer was decreased (HR 0.68, 95% CI 0.59-0.79) but similar for breast cancer (HR 0.95, 95% CI 0.78-1.14) compared to the general population and did not change with longer diabetes duration (p=0.68 and p=0.53 respectively). CONCLUSIONS: Analysing continuous hazard functions for cancer risk in relation to exposure time to an antidiabetic agent is an important complementary tool in diabetes and cancer research

Automatic blood glucose prediction with confidence using recurrent neural networks

Low-cost sensors continuously measuring blood glucose levels in intervals of a few minutes and mobile platforms combined with machine-learning (ML) solutions enable personalized precision health and disease management. ML solutions must be adapted to different sensor technologies, analysis tasks and individuals. This raises the issue of scale for creating such adapted ML solutions. We present an approach for predicting blood glucose levels for diabetics up to one hour into the future. The approach is based on recurrent neural networks trained in an end-to-end fashion, requiring nothing but the glucose level history for the patient. The model outputs the prediction along with an estimate of its certainty, helping users to interpret the predicted levels. The approach needs no feature engineering or data pre-processing, and is computationally inexpensive

Variability of INR and its relationship with mortality, stroke, bleeding and hospitalisations in patients with atrial fibrillation.

BACKGROUND - RATIONALE FOR STUDY: Atrial fibrillation is associated with an increased risk of stroke and mortality which is reduced by treatment with Warfarin. The most commonly used tool to assess the effectiveness of warfarin therapy is the time in therapeutic Range (TTR) of International Normalised Ratio (INR) 2.0-3.0. Our aim was to study whether INR variability, as assessed by the standard deviation of transformed INR (SDT(INR)) is more prognostically important than the TTR. METHODS AND RESULTS: We studied 19,180 patients with atrial fibrillation on warfarin therapy to evaluate the association of TTR and that of SDT(INR) with all-cause mortality, stroke, bleeding and hospitalisation. The SDT(INR) was more prognostically important than the TTR. One standard deviation (SD) higher of SDT(INR) had a hazard ratio (HR) of 1.59 (95% CI 1.52-1.66) of mortality compared with 1.18 (95% CI 1.13-1.24) for one SD lower of TTR. For the other 3 events the HR was also higher for the SDT(INR) than for the TTR (stroke 1.30 (95% CI 1.22-1.39) vs. 1.06 (95% CI 1.00-1.13), bleeding 1.27 (95% CI 1.20-1.35) vs. 1.07 (95% CI 1.01-1.14) , hospitalisation 1.47 (95% CI 1.45-1.49) vs. 1.13 (95% CI 1.10-1.15). When both metrics were included in the same analysis only the SDT(INR) was of significant predictive value. CONCLUSIONS: The SDT(INR) is a better predictor of mortality, stroke, bleeding and hospitalisation than the TTR in patients with atrial fibrillation receiving warfarin therapy

Variability of INR and its relationship with mortality, stroke, bleeding and hospitalisations in patients with atrial fibrillation.

BACKGROUND - RATIONALE FOR STUDY: Atrial fibrillation is associated with an increased risk of stroke and mortality which is reduced by treatment with Warfarin. The most commonly used tool to assess the effectiveness of warfarin therapy is the time in therapeutic Range (TTR) of International Normalised Ratio (INR) 2.0-3.0. Our aim was to study whether INR variability, as assessed by the standard deviation of transformed INR (SDT(INR)) is more prognostically important than the TTR. METHODS AND RESULTS: We studied 19,180 patients with atrial fibrillation on warfarin therapy to evaluate the association of TTR and that of SDT(INR) with all-cause mortality, stroke, bleeding and hospitalisation. The SDT(INR) was more prognostically important than the TTR. One standard deviation (SD) higher of SDT(INR) had a hazard ratio (HR) of 1.59 (95% CI 1.52-1.66) of mortality compared with 1.18 (95% CI 1.13-1.24) for one SD lower of TTR. For the other 3 events the HR was also higher for the SDT(INR) than for the TTR (stroke 1.30 (95% CI 1.22-1.39) vs. 1.06 (95% CI 1.00-1.13), bleeding 1.27 (95% CI 1.20-1.35) vs. 1.07 (95% CI 1.01-1.14) , hospitalisation 1.47 (95% CI 1.45-1.49) vs. 1.13 (95% CI 1.10-1.15). When both metrics were included in the same analysis only the SDT(INR) was of significant predictive value. CONCLUSIONS: The SDT(INR) is a better predictor of mortality, stroke, bleeding and hospitalisation than the TTR in patients with atrial fibrillation receiving warfarin therapy

Prevalence of primary aldosteronism among patients with type 2 diabetes

Context: Diabetes and hypertension coexist in 40%-60% of individuals with type 2 diabetes. The coexistence of these two conditions is associated with increased risk of retinopathy, nephropathy and cardiovascular disease. Objective: To investigate the prevalence of primary aldosteronism (PA) in a general cohort of persons with type 2 diabetes. Design: Cross-sectional study involving six diabetes outpatient clinics in Sweden. Patients: were enrolled individuals with type 2 diabetes between February 2008 and December 2013. Measurements: Plasma aldosterone concentrations (PAC pmol/L) and direct renin concentrations (DRC mIU/L) were measured. Patients with increased aldosterone renin ratios (ARR) > 65 were further evaluated for PA. Results: Of 578 consecutively screened patients with type 2 diabetes, 27 were treated with mineralocorticoid receptor antagonists (MRA) and potassium-sparing diuretics not further evaluated. Among the remaining 551 patients, 38 had increased ARR, including 22 who were clinically indicated for PA tests and 16 who were not further evaluated due to severe comorbidities and old age. There were five (0.93%) patients with confirmed PA after computerized tomography and adrenal venous sampling. Patients with PA had higher systolic blood pressure (P=.032) and lower potassium levels (P=.027) than those without PA. No significant association was found between plasma aldosterone and diabetic complications. Conclusions: The prevalence of PA in an unselected cohort of patients with type 2 diabetes is relatively low, and measures of plasma aldosterone are not strong risk factors for micro-and macrovascular diabetic complications