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T2D Complications Associated with Objective Measure of Poor Medication Adherence

Article

Robust analyses of urine metabolites detects poor adherence with prescribed treatment in T2D and is associated with prevalence of micro- and macrovascular complications.

In persons with type 2 diabetes (T2D), poor adherence to medications, as measured using biochemical urine testing, is associated with a significantly higher prevalence of micro- and macrovascular complications compared with taking medications as prescribed, a new study finds.

©Ronstick/stock.adobe.com

©Ronstick/stock.adobe.com

Researchers in the Netherlands assessed real-world adherence to 3 main drug classes in patients with T2D to determine the association of poor treatment adherence with complications, treatment targets, and baseline demographics. Results appear in the April issue of Diabetes Care.

Investigators, led by Jelle Beernink, of Ziekenhuis Groep Twente, Almelo, the Netherlands, analyzed study entry data on 457 patients in the observational prospective cohort DIAbetes and LifEstyle Cohort Twente (DIALECT) study. Baseline urine samples were analyzed using liquid chromatography–tandem mass spectrometry to determine participant adherence to oral antidiabetic drugs, antihypertensive agents, and statins.

The primary outcomes of interest were microvascular and macrovascular complications and treatment targets of LDL-C, A1c, and blood pressure. Cross sectional analysis was performed at baseline.

Average age of study participants was 64 years and average duration of diabetes was 11 years.

The majority of participants were identified as adherent, with 89.3% having detectable levels of all prespecified metabolites on evaluation of 24-hour urine samples. Medication adherence overall, based on urinalysis, was 95.7% for OADs, 92.0% for antihypertensive medications, and 95.5% for statins.

Prevalence of microvascular complications was significantly higher among nonadherent vs adherent patients (81.6 v. 66.2%; P = 0.029) and the same was true for macrovascular complications (55.1 vs. 37.0%; P = 0.014). The percentage of patients reaching an LDL-C target of ≤2.5 mmol/L also was lower (67.4 vs 81.1%; P = 0.029) in nonadherent patients.

Baseline demographics and clinical variables were comparable between those who were and were not adherent with treatments. There were some notable differences, however, with smoking being more prevalent among those poorly adherent (28.6% vs 15.0%); number of medications being taken higher in that group (median 8 vs 7); and A1c and LDL-C levels also being higher.

Based on binary logistic regression analysis, higher BMI, current smoking, elevated serum LDL-C, higher A1c, presence of diabetic kidney disease, and presence of macrovascular disease all were associated with nonadherence.

It is possible, the authors suggest, that lack of adherence to prescribed regimens was not recognized by the treating physicians, which in turn, they conclude, "emphasizes the importance of objective detection and tailored interventions to improve adherence."

The authors note that the relatively high baseline adherence with medication (89.3%) may be a characteristic of the study cohort given it was drawn from specialty outpatient clinics of 2 hospitals, participants having been referred from primary care after being unable to reach A1c targets or for the presence of cardiovascular complications.

Beernink et al write that people “treated in specialist care may feel more urgency to adhere to their treatment in comparison with patients treated in primary care."

However, among poorly adherent participants in this group micro- and macrovascular disease were significantly higher and important cardiometabolic treatment targets were not met. It is possible, the authors suggest, that lack of adherence to prescribed regimens was not recognized by the treating physicians, which in turn, they conclude, "emphasizes the importance of objective detection and tailored interventions to improve adherence."


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