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Patients on dialysis require caregiving and assistance in their daily lives from family members and/or others for hospital visitation and supervised administration. This places a considerable burden on caregivers, which can in turn influence caregivers' quality of life (QOL). We recruited dialysis patients and their caregivers to elucidate how the QOL of patients relates to that of their caregivers'. Patients completed the EuroQol 5-Dimension scale (EQ-5D) and Kidney Disease Quality of Life-Short Form. Caregivers completed the EQ-5D and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). We calculated utility index values for the EQ-5D, and physical, mental (MCS), and role-social component summary scores for the SF-36. Compared to national norms, the caregivers of dialysis patients tended to have poor physical health-related QOL but normal mental health-related QOL, as also found with patients. The multivariate analysis revealed that ≥ median dialysis period and ≥ average burden of kidney disease were significantly related to caregiver MCS score (odds ratios; 6.79 and 9.89, respectively). Caregivers tended to have lower physical health-related QOL if their patients had high social QOL, and lower mental health-related QOL during the early stage of the patient's dialysis treatment, and when patients experienced low disease-targeted QOL.

Dialysis treatment is known to lead to reduced quality of life (QOL) among patients. This decreased QOL is believed to influence medication compliance, although this effect has not yet been clarified. In this study, we investigated whether decreased QOL due to dialysis treatment does in fact influence medication compliance. Participants were 92 patients who self-managed their medication and were receiving dialysis treatment at Secomedic Hospital or Chiba Central Medical Center. We surveyed their age, sex, dialysis period, and medication management situation, and administered the EQ-5D and Kidney Disease Quality of Life Instrument-Short Form. A multiple logistic regression analysis with medication compliance as the dependent variable and QOL as the independent variable was conducted. The recovery rate and effective response rate were both 100%. The results indicated that patients with good sleep QOL (mean or above) had higher odds of medication compliance (odds ratio, 3.36; 95% confidence interval, 1.26-8.96; P = 0.016). Therefore, improving the quality of sleep of dialysis patients might help to improve their medication compliance.

Background: Adverse events (AEs) can be caused not only by one drug but also by the interaction between two or more drugs. Therefore, clarifying whether an AE is due to a specific suspect drug or drug-drug interaction (DDI) is useful information for proper use of drugs. Whereas previous reports on the search for drug-induced AEs with signal detection using spontaneous reporting systems (SRSs) are numerous, reports on drug interactions are limited. This is because in methods that use "a safety signal indicator" (signal), which is frequently used in pharmacovigilance, a huge number of combinations must be prepared when signal detection is performed, and each risk index must be calculated, which makes interaction search appear unrealistic. Objective: In this paper, we propose association rule mining (AR) using large dataset analysis as an alternative to the conventional methods (additive interaction model (AI) and multiplicative interaction model (MI)). Methods: The data source used was the Japanese Adverse Drug Event Report database. The combination of drugs for which the risk index is detected by the "combination risk ratio (CR)" as the target was assumed to be true data, and the accuracy of signal detection using the AR methods was evaluated in terms of sensitivity, specificity, Youden's index, F -score. Results: Our experimental results targeting Stevens-Johnson syndrome indicate that AR has a sensitivity of 99.05%, specificity of 92.60%, Youden's index of 0.917, F -score of 0.876, AI has a sensitivity of 95.62%, specificity of 96.92%, Youden's index of 0.925, and F -score of 0.924, and MI has a sensitivity of 65.46%, specificity of 98.78%, Youden's index of 0.642, and F -score of 0.771. This result was about the same level as or higher than the conventional method. Conclusions: If you use similar calculation methods to create combinations from the database, not only for SJS, but for all AEs, the number of combinations would be so enormous that it would be difficult to perform the calculations. However, in the AR method, the "Apriori algorithm" is used to reduce the number of calculations. Thus, the proposed method has the same detection power as the conventional methods, with the significant advantage that its calculation process is simple.

Diabetic nephropathy is one of three major complications of diabetes mellitus, often leading to chronic renal failure requiring dialysis. Recently developed dipeptidyl peptidase-4 (DPP-4) inhibitors may exhibit renoprotective effects in addition to antihyperglycemic effects. In this study, we retrospectively investigated temporal changes in the renal function index of patients with type 2 diabetes mellitus (DM) and examined the influence of DPP-4 inhibitors on renal function. Patients with type 2 DM (>18 years old) prescribed hypoglycemic agents at Gifu Municipal Hospital for ≥3 months between March 2010 and April 2014 were included in the study. Renal function was evaluated as estimated the decline in 12-month glomerular filtration rate from the baseline in patients receiving and not receiving DPP-4 inhibitors. Patient data from the DPP-4 inhibitor-treated (501 patients, 58.6%) and untreated (354, 41.4%) groups were analyzed using multiple logistic regression analysis, as well as Cox proportional-hazards regression analysis (616, 55.6% and 491, 44.4%, for DPP-4 inhibitors-treated and untreated groups). Multiple logistic regression analysis indicated that DPP-4 inhibitors significantly lowered the estimated glomerular filtration rate (eGFR) decline [20% over 12 months; odds ratio (OR), 0.626; 95% confidence interval [CI], 0.409-0.958; P = 0.031]. Similar results were obtained using Cox proportional-hazards regression analysis (hazard ratio [HR], 0.707; 95% CI, 0.572-0.874; P = 0.001). These findings suggest that DPP-4 inhibitors suppress the decrease of estimated glomerular filtration rate in patients with type 2 DM and show a renoprotective effect.