Improved Glycemic Control through Robot-Assisted Remote Interview for Outpatients with Type 2 Diabetes: A Pilot Study.

Background and Objectives: Our research group developed a robot-assisted diabetes self-management monitoring system to support Certified Diabetes Care and Education Specialists (CDCESs) in tracking the health status of patients with type 2 diabetes (T2D). This study aimed to evaluate the impact of this system on glycemic control and to identify suitable candidates for its use. Materials and Methods: After obtaining written informed consent from all participants with T2D, the CDCESs conducted remote interviews with the patients using RoBoHoN. All participants completed a questionnaire immediately after the experiment. HbA1c was assessed at the time of the interview and two months later, and glycemic control status was categorized as either "Adequate" or "Inadequate" based on the target HbA1c levels outlined in the guidelines for adult and elderly patients with type 2 diabetes by the Japan Diabetes Society. Patients who changed their medication regimens within the two months following the interview were excluded from the study. Results: The clinical characteristics of the 28 eligible patients were as follows: 67.9 ± 14.8 years old, 23 men (69%), body mass index (24.7 ± 4.9 kg/m2), and HbA1c levels 7.16 ± 1.11% at interview and two months later. Glycemic control status (GCS) was Adequate (A) to Inadequate (I): 1 case; I to A: 7 cases; A to A good: 14 cases; I to I: 6 cases (p-value = 0.02862 by Chi-square test). Multiple regression analyses showed that Q1 (Did RoBoHoN speak clearly?) and Q7 (Was RoBoHoN's response natural?) significantly contributed to GCS, indicating that the naturalness of the responses did not impair the robot-assisted interviews. The results suggest that to improve the system in the future, it is more beneficial to focus on the content of the conversation rather than pursuing superficial naturalness in the responses. Conclusions: This study demonstrated the efficacy of a robot-assisted diabetes management system that can contribute to improved glycemic control.

A common variant of MAF/c-MAF, transcriptional factor gene in the kidney, is associated with gout susceptibility.

Gout is a multifactorial disease characterized by acute inflammatory arthritis, and it is caused as a consequence of hyperuricemia. A recent meta-analysis of genome-wide association studies has newly identified the relationship between serum uric acid (SUA) levels and rs889472, a single nucleotide polymorphism of musculoaponeurotic fibrosarcoma oncogene (MAF/c-MAF). However, it remained unclear whether rs889472 is associated with gout susceptibility. In the present study, we investigate the association between c-MAF rs889472 and gout in Japanese male population. We genotyped 625 male patients who were clinically diagnosed as gout and 1221 male control subjects without hyperuricemia or a history of gout by TaqMan method. As a result, the major allele (C), which reportedly increases SUA levels, had a higher frequency in the gout cases (58.8%) than in the controls (55.0%). A logistic regression analysis showed a significant association between rs889472 and gout (p = 0.029, odds ratio = 1.17; 95% confidence interval 1.02-1.34). C-MAF is reported as a pivotal transcriptional factor in the development and differentiation of renal proximal tubular cells. Because urate is mainly regulated in renal proximal tubular cells, c-MAF may have an important role in urate regulation in the kidney and influence not only SUA but also gout susceptibility. Our finding shows that rs889472 of c-MAF is associated with gout susceptibility.