The hidden diabetic kidney disease in a university hospital-based population: a real-world data analysis

BACKGROUND: Correct identification of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients is crucial to implement therapeutic interventions that may prevent disease progression. METHODS: We compared the real prevalence of DKD in T2DM patients according to actual serum and urine laboratory data with the presence of the diagnostic terms DKD and/or CKD on the electronic medical records (EMRs) using a natural language processing tool (SAVANA Manager). All patients ˃18 years of age and diagnosed with T2DM were selected. DKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m(2) or a urinary albumin:creatinine ratio (UACR) >30 mg/g or a urinary protein:creatinine ratio (UPCR) >0.3 g/g after excluding acute kidney injury. RESULTS: A total of 15 304 T2DM patients identified on EMRs were eligible to enter the study. A total of 4526 (29.6%) T2DM patients had DKD according to lab criteria. However, the terms CKD or DKD were only present in 33.1% and 7.5%, representing a hidden prevalence of CKD and DKD of 66.9% and 92.5%, respectively. Less severe kidney disease (lower UACR or UPCR, higher eGFR values), female sex and lack of insulin prescription were associated with the absence of DKD or CKD terms in the EMRs (P < .001) CONCLUSIONS: The prevalence of DKD among T2DM patients defined by lab data is significantly higher than that reported on hospital EMRs. This could imply underdiagnosis of DKD, especially in patients with the least severe disease who may benefit the most from optimized therapy.