BackgroundThere are few observational studies evaluating the risk of AKI in people with type 2 diabetes, and even fewer simultaneously investigating AKI and CKD in this population. This limits understanding of the interplay between AKI and CKD in people with type 2 diabetes compared with the nondiabetic population.MethodsIn this retrospective, cohort study of participants with or without type 2 diabetes, we used electronic healthcare records to evaluate rates of AKI and various statistical methods to determine their relationship to CKD status and further renal function decline.ResultsWe followed the cohort of 16,700 participants (9417 with type 2 diabetes and 7283 controls without diabetes) for a median of 8.2 years. Those with diabetes were more likely than controls to develop AKI (48.6% versus 17.2%, respectively) and have preexisting CKD or CKD that developed during follow-up (46.3% versus 17.2%, respectively). In the absence of CKD, the AKI rate among people with diabetes was nearly five times that of controls (121.5 versus 24.6 per 1000 person-years). Among participants with CKD, AKI rate in people with diabetes was more than twice that of controls (384.8 versus 180.0 per 1000 person-years after CKD diagnostic date, and 109.3 versus 47.4 per 1000 person-years before CKD onset in those developing CKD after recruitment). Decline in eGFR slope before AKI episodes was steeper in people with diabetes versus controls. After AKI episodes, decline in eGFR slope became steeper in people without diabetes, but not among those with diabetes and preexisting CKD.ConclusionsPatients with diabetes have significantly higher rates of AKI compared with patients without diabetes, and this remains true for individuals with preexisting CKD.

When all key oral anticoagulant value criteria and their relative importance are investigated in an MCDA, dabigatran appears to rank the highest and warfarin the lowest.

A349performing treatment, as demonstrated in clinical trials, or based on variation of health-related costs (both acute and follow-up for one year). These rankings were used to compute centroid weights. An additive model was used to combine treatment performance with centroid weights to estimate the overall value of each OAC. Probabilistic and structural sensitivity analyses were conducted. Results: Dabigatran was the best treatment in centroid weight analyses with 7% / 8% higher overall value than the second best performing treatment, apixaban. Dabigatran also had the highest first rank probability (72% / 70%) in probabilistic sensitivity analyses, with apixaban being second (22% / 24% first rank probability). Rivaroxaban performed worse than other non-VKA OACs, but better than VKA (both with 0% first rank probability). The results were largely insensitive to changes in model structure, although changing availability of reversal agent to be the least important criterion increased apixaban to have approximately the same overall value as dabigatran. ConClusions: Despite using only rank-based preference data, we were able to demonstrate dabigatran to be the most and warfarin the least preferred treatment with an MCDA incorporating all factors relevant for distinguishing OACs. CV2Using sUbpopUlation treatment effeCt pattern plot to identify more effiCient resoUrCe alloCation poliCies