Our model provides an estimate of benefit that may balance the risks associated with use of SGLT2 inhibition in T1D. Using the Steno T1 CVD and renal risk engine we estimated the risk of CVD and ESKD in persons with T1D with and without treatment with SGLT2i and found a substantial CVD and ESKD risk reduction, especially in the subgroup with albuminuria. To estimate the 5-year cumulative risk of ESKD in the total study population, and the 5- and 10-year cumulative risk of CVD among the 3284 (89.7) patients without previous CVD at baseline. For the estimated 5-year risk of ESKD, we found an overall relative risk reduction of 5.3% (5.1,5.4) with up to 7.6% (6.9,8.4) in the subgroup with albuminuria. Similar results were seen for the 10-year risk of CVD. The SGLT2i induced change in the risk variables translated into an overall 5-year CVD relative risk reduction of 6.1% (95%CI 5.9,6.3), with up to 11.1% (10.0,12.2) in the subgroup with albuminuria. The recorded eGFR and albuminuria were changed in accordance with results from the Tandem studies no change in eGFR and mean (SD) %-change in albuminuria of -23.7 (12.9). Among these, a recently published CVD prediction modelthe Steno Type 1 Risk Engine (ST1RE)has shown a high performance in predicting 10-year CVD events in a cohort of 4996 T1D adults without previous CVD events 23, and also in identifying T1D patients with preclinical atherosclerosis 27, 28. Individual absolute change in HbA 1c and SBP was simulated as randomly drawn numbers from a normal distribution with mean (standard deviation (SD)) of -3.6 (0.9) mmol/mmol and -1.12 (2.8) mmHg. The effect of SGLT2i was simulated by changing the recorded HbA 1c and systolic blood pressure (SBP) values in accordance with results from the DEPICT studies. The Steno Type 1 Risk Engine was used to calculate 5-year cumulative risks of ESKD and in the subset of 3,284 (89.7%) without previous CVD at baseline, 5- and 10-year cumulative risk of CVD were estimated.

The study is based on 3,660 adults with T1D treated from 2001-2016 who fulfilled the inclusion criteria of age 30-75 years and an eGFR >45 ml/min/1.73 m 2. We aimed to estimate the risk of cardiovascular disease (CVD) and end-stage kidney disease (ESKD) in persons with T1D with and without treatment with SGLT2i. Even though credit-builder loans are essentially risk-free for the bank. We recognize that these cutoffs need to be validated in larger prospective cohorts of patients with T1D.Sodium–glucose cotransporter 2 inhibitors (SGLT2i) have beneficial cardiovascular and renal effects in persons with type 2 diabetes but no studies have shown whether this can be demonstrated in type 1 diabetes (T1D). 1 Pay Your Other Bills Heres one you may have heard before: If you have any. Our data were used to calculate the 10-year probability of CVD according to the ST1RE. The model with the higher C-statistic-the Steno Type 1 Risk Engine (ST1RE) ( 3)-includes 10 factors (age, sex, smoking, exercise, diabetes duration, systolic blood pressure, LDL cholesterol, HbA 1c, estimated glomerular filtration rate, and micro/macroalbuminuria) and classifies patients with T1D and no previous cardiovascular disease according to their 5- and 10-year cardiovascular risk into low (7.3 m/s for moderate/high risk (C-statistic 0.91, 95% CI 0.87–0.95) and aPWV >8.7 m/s for high-risk (C-statistic 0.88, 95% CI 0.81–0.95). The Steno Type 1 Risk Engine Dorte Vistisen, Gregers Stig Andersen, Christian Stevns Hansen, Adam Hulman, Jan Erik Henriksen, Henning Bech-Nielsen and Marit Eika Jrgensen Circulation.

Risk scores are usually compared with the C-statistic, which quantifies the probability that a randomly selected patient who experienced a cardiovascular event had a higher risk score than a patient who had not experienced the event, and ranges from 0.5 (random prediction) to 1.0 (perfect prediction). Current models for predicting cardiovascular risk in T1D have not gained wide acceptance, likely because they include too many factors ( 2, 3). Cardiovascular disease is the leading cause of death in T1D, and simple models are urgently needed to guide its prediction in routine clinical practice.

Steno type 1 risk engine