{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:45:33Z","timestamp":1785545133529,"version":"3.56.0"},"reference-count":35,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Chronic kidney disease (CKD) is a common comorbidity of type 2 diabetes mellitus (T2DM). Data on the determination of CKD-related biomarkers among patients with T2DM in a real-life setting within Germany are limited.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n We aimed to determine the prevalence of CKD and risk factors, availability of urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) values, treatment satisfaction, and quality of life among patients with T2DM in Germany.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n SMART-Finder is a retrospective and prospective, observational, digital, patient-centered cohort study being performed as part of the routine use of an adherence-supporting app. This baseline analysis\u2019 observation period was from August to November 2023. Patients with T2DM in Germany who actively used the MyTherapy app; allowed push notifications; and documented use of diabetes medications, renin-angiotensin system inhibitors, finerenone, and\/or blood glucose test strips were eligible for inclusion. Study materials (background information, electronic consent form, and laboratory and electronic questionnaires) were provided to eligible patients via app push notifications. Participants completed an electronic case report form that included questions on their blood pressure; their most recent UACR, eGFR, and glycated hemoglobin (HbA\n 1c<\/jats:sub>\n ) values in the past 12 months; the EQ-5D-5L; and the Diabetes Treatment Satisfaction Questionnaire. The primary outcome was the proportion of patients with a UACR of \u226530 mg\/g.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Of 9527 invited eligible patients, 101 completed the electronic case report form (male: n=61; female: n=40; age: mean 54.2, SD 11.4 y). Of these, 1 female patient and 5 male patients reported their UACR values; 3 (all male) had a UACR of \u226530 mg\/g. The remaining 95 patients reported that their health care professionals had not provided UACR measurements. Only 9 (8.9%) patients were aware of their latest eGFR values (3 patients: 15\u201044 mL\/min\/1.73 m\n 2<\/jats:sup>\n ; 6 patients: 45\u201089 mL\/min\/1.73 m\n 2<\/jats:sup>\n ), 90 provided HbA\n 1c<\/jats:sub>\n values (80 patients: \u22656.0%), 46 had a systolic blood pressure of \u2265130 mm Hg, and 83 reported former or current nephrotoxic medication intake. The mean EQ-5D-5L index score was 0.7 (SD 0.3; range \u20130.1 to 1.0; 50 patients). The mean Diabetes Treatment Satisfaction Questionnaire score was 28.8 (SD 6.8; range 9.0-36.0; 49 patients).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n Patients with T2DM who were using an adherence-supporting app in Germany lacked awareness of CKD-related biomarkers but had high knowledge of self-manageable biomarkers (eg, blood pressure, serum fasting glucose, and HbA\n 1c<\/jats:sub>\n values). Our results suggest that treating physicians either do not test for UACRs and eGFRs or do not inform patients about the results. Nonadherence to diagnostic testing guidelines and a lack of physician-patient communication put patients at risk. Another reason for this health literacy imbalance may be the focus on HbA\n 1c<\/jats:sub>\n instead of kidney comorbidity in patient education material. Future goals for diabetes management must include guideline-compliant testing of CKD-related biomarkers and open physician-patient communication.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/60246","type":"journal-article","created":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:07:22Z","timestamp":1736381242000},"page":"e60246-e60246","source":"Crossref","is-referenced-by-count":0,"title":["Disease Awareness in Patients With Type 2 Diabetes: Analysis of Baseline Data From the SMART-Finder Observational 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