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AIMS: To determine the associations between combined urinary protein (UP) and a reduced estimated glomerular filtration rate (eGFR) and the risk of starting dialysis with or without diabetes mellitus (DM). METHODS: A nationwide database with claims data on 335,778 people with and without DM aged 19-72 years in Japan was used to elucidate the impact of the severities of UP and eGFR on starting dialysis. Initiation of dialysis was determined from claims using ICD-10 codes and medical procedures. Using multivariate Cox modeling, we investigated the severities of UP and eGFR to predict the initiation of dialysis with and without DM. RESULTS: Both eGFR < 60 and UP(+) were independent predictors for starting dialysis with and without DM, and their values exhibited a synergistic risk of dialysis. eGFR < 60 presented a nearly twofold risk for starting dialysis compared to UP(+) regardless of DM. Risk of starting dialysis was increased with UP(+) and eGFR ≥ 60 accompanied by DM although this association was not observed without DM. Those who had UP(-) and eGFR < 60 had a high risk of starting dialysis regardless of DM. Compared with DM(-)UP(-)eGFR ≥ 60, HRs for starting dialysis for DM(+)UP(+)eGFR ≥ 60, DM(+)UP(-)eGFR < 60 and DM(+)UP(+)eGFR < 60 significantly increased 17.7 (10.6-29.7), 25.5 (13.8-47.1) and 358.1 (239.1-536.5) times, respectively. CONCLUSIONS: eGFR < 60 and UP(+) together presented an extremely high risk of dialysis especially with DM. UP( +) increased the risk of starting dialysis regardless of the eGFR with DM. Both patient education and a treatment strategy by physicians might be helpful to avoid the progression of renal failure.

DOI： 10.1007/s13340-022-00603-z

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BACKGROUND: Obesity is an established risk factor for non-communicable diseases such as type 2 diabetes mellitus, hypertension and cardiovascular disease. Thus, weight control is a key factor in the prevention of non-communicable diseases. A simple and quick method to predict weight change over a few years could be helpful for weight management in clinical settings. METHODS: We examined the ability of a machine learning model that we constructed to predict changes in future body weight over 3 years using big data. Input in the machine learning model were three-year data on 50,000 Japanese persons (32,977 men) aged 19-91 years who underwent annual health examinations. The predictive formulas that used heterogeneous mixture learning technology (HMLT) to predict body weight in the subsequent 3 years were validated for 5,000 persons. The root mean square error (RMSE) was used to evaluate accuracy compared with multiple regression. RESULTS: The machine learning model utilizing HMLT automatically generated five predictive formulas. The influence of lifestyle on body weight was found to be large in people with a high body mass index (BMI) at baseline (BMI ≥29.93 kg/m2) and in young people (<24 years) with a low BMI (BMI <23.44 kg/m2). The RMSE was 1.914 in the validation set which reflects ability comparable to that of the multiple regression model of 1.890 (p = 0.323). CONCLUSION: The HMLT-based machine learning model could successfully predict weight change over 3 years. Our model could automatically identify groups whose lifestyle profoundly impacted weight loss and factors the influenced body weight change in individuals. Although this model must be validated in other populations, including other ethnic groups, before being widely implemented in global clinical settings, results suggested that this machine learning model could contribute to individualized weight management.

DOI： 10.3389/fpubh.2023.1090146

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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BACKGROUND AND OBJECTIVES: To clarify whether the presence or absence of fast walking and habitual physical activity are independently associated with the incidence of functional disability. METHODS: This historical cohort study was comprised of 9,652 (4,412 men, mean age 65 years) individuals aged 39-98 years without functional disability at baseline. Functional disability was determined based on the Japanese long-term care insurance system, which specified requirements for assistance in the activities of daily living. The impact of fast walking and habitual physical activity on the incidence of functional disability was analysed by Cox proportional hazards models. RESULTS: The follow-up period was a median of 3.7 years during which 165 patients were newly certified as having functional disability. In the multivariate analysis, baseline age in 5-year increments (hazard ratio 2.42 [95% confidence interval 2.18-2.69]), no habitual physical activity (1.56 [1.07-2.27]), and not fast walking (1.89 [1.32-2.69]) significantly increased the risk of functional disability after adjustment for covariates. The stratified analysis showed that compared with physical activity (+), the impact of physical activity (-) on the incidence of functional disability was observed in those aged ≥75 years regardless of fast walking (+). Fast walking (-) significantly increased the risk of disability compared with fast walking (+) in those aged <75 years regardless of a physical activity habit. CONCLUSION: In Japanese, slow walking speed and lack of a physical activity habit were shown to be independent risk factors for incident functional disability, with their impact differing according to age.

DOI： 10.1093/fampra/cmac087

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Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

Abstract

Background

To determine the impact of metabolic syndrome (MetS) and/or metabolic dysfunction-associated fatty liver disease (MAFLD), which are pathophysiologically similar and include insulin resistance, on the development of new-onset cardiovascular disease with and without type 2 diabetes and according to sex.

Methods

This study included 570,426 individuals without a history of cardiovascular disease who were enrolled in a nationwide claims database from 2008 to 2016 and were classified by the presence or absence of MetS and/or MAFLD stratified by the presence or absence of type 2 diabetes and sex. The fatty liver index was used to determine the presence or absence of fatty liver that required a diagnosis of MAFLD. Risks of developing coronary artery disease (CAD) and cerebrovascular disease (CVD) in each category were analyzed using a multivariate Cox proportional hazard model.

Results

During a median follow-up of 5.2 years, 2252 CAD and 3128 CVD events occurred. Without type 2 diabetes the hazard ratio (HR) (95% CI) for CAD/CVD compared with neither MAFLD nor MetS was 1.32 (1.17–1.50)/1.41(1.28–1.57) for MAFLD only (without MetS), 1.78 (1.22–2.58)/1.66 (1.34–2.06) for MetS only (without MAFLD), and 2.10 (1.84–2.39)/1.73 (1.54–1.95) for MAFLD + MetS. For those with type 2 diabetes, the HR for CAD for MAFLD only (compared with neither MAFLD nor MetS) was 1.29 (1.06–1.58), for MetS only 1.34 (0.84–2.13), and for MAFLD + MetS 1.22 (1.02–1.47). For CVD, there was a significant increase in HR only in MAFLD + MetS [1.44 (1.18–1.76)]. The results of the analysis stratified by sex showed that MAFLD had a greater impact in men, and MetS had a greater impact in women regarding the development of CAD.

Conclusions

Distinguishing between MetS and/or MAFLD in the presence or absence of type 2 diabetes and according to sex may aid in accurately identifying patients at high risk of cardiovascular disease.

DOI： 10.1186/s12933-022-01518-4

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Other Link： https://link.springer.com/article/10.1186/s12933-022-01518-4/fulltext.html

Language：Japanese   Publisher：(一社)日本内分泌学会  

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Language：Japanese   Publisher：(一社)日本内分泌学会  

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Language：Japanese   Publisher：(一社)日本内分泌学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本疫学会  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

<title>Abstract</title><sec>
<title>Background</title>
Although both a history of cerebrovascular disease (CVD) and glucose abnormality are risk factors for CVD, few large studies have examined their association with subsequent CVD in the same cohort. Thus, we compared the impact of prior CVD, glucose status, and their combinations on subsequent CVD using real-world data.


</sec><sec>
<title>Methods</title>
This is a retrospective cohort study including 363,627 men aged 18–72 years followed for ≥ 3 years between 2008 and 2016. Participants were classified as normoglycemia, borderline glycemia, or diabetes defined by fasting plasma glucose, HbA1c, and antidiabetic drug prescription. Prior and subsequent CVD (i.e. ischemic stroke, transient ischemic attack, and non-traumatic intracerebral hemorrhage) were identified according to claims using ICD-10 codes, medical procedures, and questionnaires.


</sec><sec>
<title>Results</title>
Participants’ mean age was 46.1 ± 9.3, and median follow up was 5.2 (4.2, 6.7) years. Cox regression analysis showed that prior CVD + conferred excess risk for CVD regardless of glucose status (normoglycemia: hazard ratio (HR), 8.77; 95% CI 6.96–11.05; borderline glycemia: HR, 7.40, 95% CI 5.97–9.17; diabetes: HR, 5.73, 95% CI 4.52–7.25). Compared with normoglycemia, borderline glycemia did not influence risk of CVD, whereas diabetes affected subsequent CVD in those with CVD- (HR, 1.50, 95% CI 1.34–1.68). In CVD-/diabetes, age, current smoking, systolic blood pressure, high-density lipoprotein cholesterol, and HbA1c were associated with risk of CVD, but only systolic blood pressure was related to CVD risk in CVD + /diabetes.


</sec><sec>
<title>Conclusions</title>
Prior CVD had a greater impact on the risk of CVD than glucose tolerance and glycemic control. In participants with diabetes and prior CVD, systolic blood pressure was a stronger risk factor than HbA1c. Individualized treatment strategies should consider glucose tolerance status and prior CVD.


</sec>

DOI： 10.1186/s12933-021-01367-7

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Other Link： https://link.springer.com/article/10.1186/s12933-021-01367-7/fulltext.html

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PURPOSE: Our purpose in the research was to clarify the impact of medication adherence to oral hypoglycemic agents during a 1-year period and subsequent glycemic control on the risk of micro- and macrovascular diseases. METHODS: Examined was a nationwide claims database on 13,256 individuals with diabetic eye disease without requiring prior treatment, 7,862 without prior initiation of dialysis, 15,556 without prior coronary artery disease, 16,243 without prior cerebrovascular disease, and 19,386 without prior heart failure from 2008 to 2016 in Japan. Medication adherence was evaluated by the proportion of days covered. Patients were considered to have poor adherence if the proportion of days covered was <80%. Multivariate Cox regression model identified risks of micro- and macrovascular diseases. RESULTS: In each group, mean age was 53 to 54 years, HbA1c was 7.1% to 7.2%, and median follow-up period was 4.6 to 5.1 years, and the percentage of poor adherence was approximately 30%. During the study period, 532 treatment-requiring diabetic eye disease, 75 dialysis, 389 coronary artery disease, 316 cerebrovascular disease, and 144 heart failure events occurred. Multivariate Cox regression model revealed that the hazard ratio (95% confidence interval) of dialysis in the poor adherence group was 2.04 (1.27-3.30) compared with the good adherence group. The hazard ratios in the poor adherence/poor glycemic control group were 3.34 (2.63-4.24) for treatment-requiring diabetic eye disease, 4.23 (2.17-8.26) for dialysis, 1.69 (1.23-2.31) for coronary artery disease, and 2.08 (1.25-3.48) for heart failure compared with the good adherence/good glycemic control group. CONCLUSIONS: Poor medication adherence was an independent risk factor for the initiation of dialysis, suggesting that clinicians must pay close attention to these patients.

DOI： 10.1016/j.amjmed.2021.10.018

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：American Diabetes Association  

OBJECTIVE: To determine associations of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with new-onset coronary artery disease (CAD) or cerebrovascular disease (CVD) according to glucose status. RESEARCH DESIGN AND METHODS: Examined was a nationwide claims database from 2008 to 2016 on 593,196 individuals. A Cox proportional hazards model identified risks of CAD and CVD events among five levels of SBP and DBP. RESULTS: During the study period 2,240 CAD and 3,207 CVD events occurred. Compared with SBP ≤119 mmHg, which was the lowest quintile of SBP, hazard ratios (95% CI) for CAD/CVD in the 4 higher quintiles (120-129, 130-139, 140-149, ≥150 mmHg) gradually increased from 2.10 (1.73-2.56)/1.46 (1.27-1.68) in quintile 2 to 3.21 (2.37-4.34)/4.76 (3.94-5.75) in quintile 5 for normoglycemia, from 1.39 (1.14-1.69)/1.70 (1.44-2.01) in quintile 2 to 2.52 (1.95-3.26)/4.12 (3.38-5.02) in quintile 5 for borderline glycemia, and from 1.50 (1.19-1.90)/1.72 (1.31-2.26) in quintile 2 to 2.52 (1.95-3.26)/3.54 (2.66-4.70) in quintile 5 for diabetes. A similar trend was observed for DBP across 4 quintiles (75-79, 80-84, 85-89, and ≥90 mmHg) compared with ≥74 mmHg, which was the lowest quintile. CONCLUSIONS: Results indicated that cardiovascular risks gradually increased with increases in SBP and DBP regardless of the presence of and degree of a glucose abnormality. Further interventional trials are required to apply findings from this cohort study to clinical practice.

DOI： 10.2337/dc20-2252

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PURPOSE: To evaluate the accuracy of various claims-based definitions of diabetes-related complications (coronary artery disease [CAD], heart failure, cerebrovascular disease and dialysis). METHODS: We evaluated data on 1379 inpatients who received care at the Niigata University Medical & Dental Hospital in September 2018. Manual electronic medical chart reviews were conducted for all patients with regard to diabetes-related complications and were used as the gold standard. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each claims-based definition associated with diabetes-related complications based on Diagnosis Procedure Combination (DPC), International Classification of Diseases, Tenth Revision (ICD-10) codes, procedure codes and medication codes were calculated. RESULTS: DPC-based definitions had higher sensitivity, specificity, and PPV than ICD-10 code definitions for CAD and cerebrovascular disease, with sensitivity of 0.963-1.000 and 0.905-0.952, specificity of 1.000 and 1.000, and PPV of 1.000 and 1.000, respectively. Sensitivity, specificity, and PPV were high using procedure codes for CAD and dialysis, with sensitivity of 0.963 and 1.000, specificity of 1.000 and 1.000, and PPV of 1.000 and 1.000, respectively. DPC and/or ICD-10 codes + medication were better for heart failure than the ICD-10 code definition, with sensitivity of 0.933, specificity of 1.000, and PPV of 1.000. The PPVs were lower than 60% for all diabetes-related complications using ICD-10 codes only. CONCLUSION: The DPC-based definitions for CAD and cerebrovascular disease, procedure codes for CAD and dialysis, and DPC or ICD-10 codes with medication codes for heart failure could accurately identify these diabetes-related complications from claims databases.

DOI： 10.1002/pds.5213

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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BACKGROUND: The prevalence of diabetes is rising, and diabetes develops at a younger age in East Asia. Although lower limb amputation negatively affects quality of life and increases the risk of cardiovascular events, little is known about the rates and predictors of amputation among persons with diabetes from young adults to those in the "young-old" category (50-72 y). METHODS: We analyzed data from a nationwide claims database in Japan accumulated from 2008 to 2016 involving 17,288 people with diabetes aged 18-72 y (mean age 50.2 y, HbA1c 7.2%). Amputation occurrence was determined according to information from the claims database. Cox regression model identified variables related to lower limb amputation. RESULTS: The mean follow-up time was 5.3 years, during which time 16 amputations occurred (0.17/1000 person-years). Multivariate Cox regression analysis showed that age (hazard ratio [HR] 1.09 [95% confidence intervals] 1.02-1.16, p = 0.01) and HbA1c (HR 1.46 [1.17-1.81], p < 0.01) were independently associated with amputations. Compared with those aged < 60 years with HbA1c < 8.0%, the HR for amputation was 27.81 (6.54-118.23) in those aged ≥60 years and HbA1c ≥8.0%. CONCLUSIONS: Age and HbA1c were associated with amputations among diabetic individuals, and the rates of amputation were significantly greater in those ≥60 years old and with HbA1c ≥8.0%.

DOI： 10.1186/s13047-021-00474-8

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Language：Japanese   Publisher：(一社)日本内分泌学会  

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AIM: To compare the long-term efficacy of sodium-glucose co-transporter-2 inhibitors and dipeptidyl peptidase-4 inhibitors as second-line drugs after metformin for patients not at high risk of atherosclerotic cardiovascular disease (ASCVD). MATERIALS AND METHODS: In a 52-week randomized open-label trial, we compared ipragliflozin and sitagliptin in Japanese patients diagnosed with type 2 diabetes, without prior ASCVD and treated with metformin. The primary endpoint was a glycated haemoglobin (HbA1c) reduction of ≥0.5% (5.5 mmol/mol) without weight gain at 52 weeks. RESULTS: Of a total of 111 patients (mean age 59.2 years, mean body mass index [BMI] 26.6 kg/m2 , 61.3% men), 54 patients received ipragliflozin and 57 received sitagliptin. After 52 weeks, achievement of the primary endpoint was not significantly different (37.0% and 40.3%; P = 0.72). HbA1c reduction rate at 24 weeks was greater for sitagliptin (56.1%) than for ipragliflozin (31.5%; P = 0.01). From 24 to 52 weeks, the HbA1c reduction with sitagliptin was attenuated, with no significant difference in HbA1c reduction after 52 weeks between sitagliptin (54.4%) and ipragliflozin (38.9%; P = 0.10). Improvements in BMI, C-peptide and high-density lipoprotein cholesterol were greater with ipragliflozin than with sitagliptin. Adverse events occurred in 17 patients with ipragliflozin and in 10 patients with sitagliptin (P = 0.11). CONCLUSION: The HbA1c-lowering effect at 24 weeks was greater with sitagliptin than with ipragliflozin, but with no difference in efficacy related to HbA1c and body weight at 52 weeks. However, some ASCVD risk factors improved with ipragliflozin.

DOI： 10.1111/dom.14288

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To determine associations between severity of hypertension and risk of starting dialysis in the presence or absence of diabetes mellitus (DM). A nationwide database with claims data on 258 874 people with and without DM aged 19-72 years in Japan was used to elucidate the impact of severity of hypertension on starting dialysis. Initiation of dialysis was determined from claims using International Classification of Diseases-10 codes and medical procedures. Using multivariate Cox modeling, we investigated the severity of hypertension to predict the initiation of dialysis with and without DM. Hypertension was significantly associated with the initiation of dialysis regardless of DM. The incidence of starting dialysis in those with systolic blood pressure (SBP) ≤119 mm Hg and DM (DM+) was almost the same as in those with SBP ≥150 mm Hg and absence of DM (DM-). In comparison with SBP ≤119 mm Hg, SBP ≥150 mm Hg significantly increased the risk of the initiation of dialysis about 2.5 times regardless of DM+ or DM-. Compared with DM- and SBP ≤119 mm Hg, the HR for DM+ and SBP ≥150 mm Hg was 6.88 (95% CI 3.66 to 12.9). Although the risks of hypertension differed only slightly regardless of the presence or absence of DM, risks for starting dialysis with DM+ and SBP ≤119 mm Hg were equivalent to DM- and SBP ≥150 mm Hg, indicating more strict blood pressure interventions in DM+ are needed to avoid dialysis. Future studies are required to clarify the cut-off SBP level to avoid initiation of dialysis considering the risks of strict control of blood pressure.

DOI： 10.1136/jim-2020-001489

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BACKGROUND: Machine learning (ML) algorithms have been widely introduced to diabetes research including those for the identification of hypoglycemia. OBJECTIVE: The objective of this meta-analysis is to assess the current ability of ML algorithms to detect hypoglycemia (ie, alert to hypoglycemia coinciding with its symptoms) or predict hypoglycemia (ie, alert to hypoglycemia before its symptoms have occurred). METHODS: Electronic literature searches (from January 1, 1950, to September 14, 2020) were conducted using the Dialog platform that covers 96 databases of peer-reviewed literature. Included studies had to train the ML algorithm in order to build a model to detect or predict hypoglycemia and test its performance. The set of 2 × 2 data (ie, number of true positives, false positives, true negatives, and false negatives) was pooled with a hierarchical summary receiver operating characteristic model. RESULTS: A total of 33 studies (14 studies for detecting hypoglycemia and 19 studies for predicting hypoglycemia) were eligible. For detection of hypoglycemia, pooled estimates (95% CI) of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 0.79 (0.75-0.83), 0.80 (0.64-0.91), 8.05 (4.79-13.51), and 0.18 (0.12-0.27), respectively. For prediction of hypoglycemia, pooled estimates (95% CI) were 0.80 (0.72-0.86) for sensitivity, 0.92 (0.87-0.96) for specificity, 10.42 (5.82-18.65) for PLR, and 0.22 (0.15-0.31) for NLR. CONCLUSIONS: Current ML algorithms have insufficient ability to detect ongoing hypoglycemia and considerate ability to predict impeding hypoglycemia in patients with diabetes mellitus using hypoglycemic drugs with regard to diagnostic tests in accordance with the Users' Guide to Medical Literature (PLR should be ≥5 and NLR should be ≤0.2 for moderate reliability). However, it should be emphasized that the clinical applicability of these ML algorithms should be evaluated according to patients' risk profiles such as for hypoglycemia and its associated complications (eg, arrhythmia, neuroglycopenia) as well as the average ability of the ML algorithms. Continued research is required to develop more accurate ML algorithms than those that currently exist and to enhance the feasibility of applying ML in clinical settings. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020163682; http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020163682.

DOI： 10.2196/22458

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BACKGROUND: Applications of machine learning for the early detection of diseases for which a clear-cut diagnostic gold standard exists have been evaluated. However, little is known about the usefulness of machine learning approaches in the decision-making process for decisions such as insulin initiation by diabetes specialists for which no absolute standards exist in clinical settings. OBJECTIVE: The objectives of this study were to examine the ability of machine learning models to predict insulin initiation by specialists and whether the machine learning approach could support decision making by general physicians for insulin initiation in patients with type 2 diabetes. METHODS: Data from patients prescribed hypoglycemic agents from December 2009 to March 2015 were extracted from diabetes specialists' registries, resulting in a sample size of 4860 patients who had received initial monotherapy with either insulin (n=293) or noninsulin (n=4567). Neural network output was insulin initiation ranging from 0 to 1 with a cutoff of >0.5 for the dichotomous classification. Accuracy, recall, and area under the receiver operating characteristic curve (AUC) were calculated to compare the ability of machine learning models to make decisions regarding insulin initiation to the decision-making ability of logistic regression and general physicians. By comparing the decision-making ability of machine learning and logistic regression to that of general physicians, 7 cases were chosen based on patient information as the gold standard based on the agreement of 8 of the 9 specialists. RESULTS: The AUCs, accuracy, and recall of logistic regression were higher than those of machine learning (AUCs of 0.89-0.90 for logistic regression versus 0.67-0.74 for machine learning). When the examination was limited to cases receiving insulin, discrimination by machine learning was similar to that of logistic regression analysis (recall of 0.05-0.68 for logistic regression versus 0.11-0.52 for machine learning). Accuracies of logistic regression, a machine learning model (downsampling ratio of 1:8), and general physicians were 0.80, 0.70, and 0.66, respectively, for 43 randomly selected cases. For the 7 gold standard cases, the accuracies of logistic regression and the machine learning model were 1.00 and 0.86, respectively, with a downsampling ratio of 1:8, which were higher than the accuracy of general physicians (ie, 0.43). CONCLUSIONS: Although we found no superior performance of machine learning over logistic regression, machine learning had higher accuracy in prediction of insulin initiation than general physicians, defined by diabetes specialists' choice of the gold standard. Further study is needed before the use of machine learning-based decision support systems for insulin initiation can be incorporated into clinical practice.

DOI： 10.2196/22148

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Language：Japanese   Publisher：(一社)日本疫学会  

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AIMS: Little is known about the relationship between medication adherence for oral hypoglycemic agents (OHAs) and glycemic control after adjusting healthy adherer effect in large scale study. Thus, adjusting for health-related behaviors, we investigated the clinical variables associated with medication adherence and the relationship between medication adherence and glycemic control using a large claims database. METHODS: Analyzed were 8805 patients with diabetes whose medication records for OHA were available for at least 1year. Medication adherence was evaluated by the proportion of days covered (PDC). Multivariate logistic regression model was used to identify clinical variables significantly associated with non-adherence. Multiple regression analysis evaluated the relationship between PDC and HbA1c after adjusting for health-related behaviors. RESULTS: Mean PDC was 80.1% and 32.8% of patients were non-adherence. Logistic analysis indicated that older age and taking concomitant medications were significantly associated with adherence while skipping breakfast (odds ratio 0.66 [95% CI 0.57-0.76]), late-night eating (0.86 [0.75-0.98]), and current smoking (0.89 [0.80-0.99]) were significantly associated with non-adherence. CONCLUSIONS: Skipping breakfast, late-night eating and current smoking were significantly associated with medication adherence, suggesting that clinicians pay attention to those health-related behaviors to achieve good medication adherence.

DOI： 10.1016/j.pcd.2020.05.002

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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PURPOSE: This network meta-analysis aimed to assess the current efficacy of decreasing the uric acid (UA) level with drugs to reduce mortality in patients with heart failure (HF). METHODS: Electronic literature searches using EMBASE and MEDLINE of studies published from 1 Jan 1950 to 26 Dec 2019 were conducted for randomized controlled trials or non-randomized cohort studies that included at least one group of patients who took UA-lowering drugs and with a study outcome of all-cause mortality. A random-effects network meta-analysis was performed within a frequentist framework. Hierarchy of treatments was expressed as the surface under the cumulative ranking curve (SUCRA) value, which is in proportion to mean rank (best is 100%). RESULTS: Nine studies, which included seven different types of groups, were eligible for analysis. The "untreated uricemia" group in which patients had hyperuricemia but without treatment had a significantly higher risk of mortality than the "no uricemia" group in which patients had no hyperuricemia (relative risk (RR)(95% confidence interval (CI), 1.43 (1.08-1.89)). The "start-allo" group wherein patients started to take allopurinol did not have a significantly lower risk of mortality than the "untreated uricemia" group (RR (95% CI), 0.68 (0.45-1.01)). However, in the "start-allo" group the SUCRA value was comparable to that in the "no uricemia" group (SUCRA: 65.4% for "start-allo"; 64.1% for "no uricemia"). CONCLUSIONS: Results suggested that allopurinol therapy was not associated with a significantly improved prognosis in terms of mortality but could potentially counteract the adverse effects associated with longstanding hyperuricemia in HF patients.

DOI： 10.1007/s10557-020-07097-4

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AIM: To examine the association between treatment-achieved HbA1c values and incidence of both coronary artery disease (CAD) and severe eye disease with different diabetes treatments. METHODS: Associations of treatment-achieved HbA1c were investigated in various treatment groups [diet only; insulin; sulphonylurea (SU) alone; SU with glinides; and antihyperglycaemic agents other than glinides, SU or insulin] taken from a nationwide claims database of 14,633 Japanese diabetes patients. Cox's regression analysis examined risks over a 5.1-year follow-up. RESULTS: A significant linear trend was associated with HbA1c levels and CAD events in the diet-only group, and CAD risks were significantly higher in insulin and SU groups with HbA1c ≤ 7.0% and > 8.0% than in the diet-only group with HbA1c ≤ 7.0%. In contrast to CAD, a linear association was observed regardless of treatment modality between achieved HbA1c levels and risk of severe diabetic eye disease, but with no significant difference in eye disease risk between groups with HbA1c ≤ 7.0% and 7.1-8.0% in those treated with either SU alone, SU with glinides, or insulin. CONCLUSION: These findings suggest that the relationship between treatment-achieved HbA1c and incidence of both CAD and severe diabetic eye disease differed according to treatment, based on a large-scale real-life database. More research is now needed to confirm these findings and to further investigate the underlying mechanisms.

DOI： 10.1016/j.diabet.2018.08.009

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.diabet.2018.08.009

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

researchmap

Language：Japanese   Publisher：(一社)日本糖尿病学会  

researchmap

Language：Japanese   Publisher：(一社)日本糖尿病学会  

researchmap

Language：Japanese   Publisher：(一社)日本糖尿病学会  

researchmap

Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Language：Japanese   Publisher：(一社)日本糖尿病学会  

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Publishing type：Research paper (scientific journal)   Publisher：American Diabetes Association  

Low serum AMY values were previously reported to be associated with incident T2DM. We further investigated that association in detail by showing the combined effects of chronological changes in AMY and baseline AMY as well as results of stratified analyses of baseline age and HbA1c.

Analyzed were 5306 individuals who had health examinations yearly for 7 y. We monitored changes in AMY values between baseline1 (first visit) and baseline2 (2 y later). Multivariate Cox analysis was conducted to evaluate the impacts of baseline2 AMY and change in AMY on incident T2DM in consideration of age and HbA1c. During the 5-y follow-up, T2DM occurred in 716 patients. Both low baseline2 AMY and decrease in AMY were independently associated with the development of T2DM. Compared with those whose baseline2 AMY ≥57 (Quintiles (Q) 2-5) and changes in AMY ≥90.4 (Q 2-5), those whose baseline2 AMY ≤56 (Q1) and changes in AMY ≤90.3 (Q1) had a significantly increased risk for T2DM (HR 1.60 [1.22-2.09]). Stratified analyses by age and baseline HbA1c levels showed that the increased risk for T2DM due to low baseline2 AMY or its change occurred only among those &amp;lt;50 y old or with HbA1c levels &amp;lt;5.6%.

These findings imply the clinical relevance of using AMY values and their chronological changes over time for evaluation of T2DM risk among individuals who are relatively young or have low HbA1c.

<p></p> Disclosure

I. Ikeda: None. K. Fujihara: None. I. Risa: None. M.H. Yamada: None. R. Nedachi: None. M. Hatta: None. S. Kodama: None. Y. Mori: None. Y. Matsubayashi: None. Y. Arase: None. H. Sone: Research Support; Self; Kyowa Hakko Kirin Co., Ltd., Novartis AG, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co. R. Yamamoto-Honda: None.

DOI： 10.2337/db20-1903-p

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Publishing type：Research paper (scientific journal)   Publisher：American Diabetes Association  

An increase in screen time (ST) is reportedly associated with insulin resistance and obesity in children. However, most studies are of TV viewing but not smartphone use. Also, little is known of the relationship between ST and diet. In this study, we clarified the relationships among ST including smartphone use, lifestyle factors including dietary content, and obesity. Cross-sectionally analyzed were 1393 children between 11-15 years of age. ST (min/day) was classified into 4 groups: &amp;lt;120, 120-179, 180-239, ≥240. The associations of each group with dietary content and obesity were investigated. Smartphone usage time significantly increase and sleep duration significantly decreased as ST increased, which was not the case for physical activity. There was no significant difference in energy intake between the 4 groups of ST either for boys or girls, but intake of protein, vegetables green and yellow, other vegetables, and fish and shellfish decreased significantly as ST increased, as did increase in beverage intake. In addition, the association with obesity was significantly increased in the ≥240 ST group compared to the &amp;lt;120 ST group (1.93[1.14-3.28]).

In conclusion, the increase in ST including smartphone usage was suggested to be associated with various unfavorable lifestyles including dietary habits that could be connected to obesity.

<p></p> Disclosure

I. Ikeda: None. K. Fujihara: None. R. Nedachi: None. S.Y. Morikawa: None. H. Ishiguro: None. M.H. Yamada: None. Y. Matsubayashi: None. T. Yamada: None. H. Sone: Research Support; Self; Kyowa Hakko Kirin Co., Ltd., Novartis AG, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co.

DOI： 10.2337/db20-1988-p

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Language：English   Publishing type：Research paper (scientific journal)  

OBJECTIVE: Declining healthy life expectancy due to functional disability is relevant and urgent because of its association with decreased quality of life and also for its enormous socioeconomic impact. The aim of this study is to examine the impact of diabetes, hypertension, dyslipidemia and physical activity habits on functional disability among community-dwelling Japanese adults. RESEARCH DESIGN AND METHODS: This is a population-based retrospective cohort study including 9673 people aged 39-98 years in Japan (4420, men). Functional disability was defined as a condition meeting Japan's new long-term care insurance certification requirements for the need of assistance in the activities of daily living whether by caregivers or assistive devices. Cox proportional-hazards regression model identified variables related to functional disability. RESULTS: Median follow-up was 3.7 years. During the study period, 165 disabilities occurred in the overall study population. Multivariate analysis showed that diabetes (HR 1.74 (95% CI 1.12 to 2.68)) and no physical activity habit (HR 1.83 (1.27 to 2.65)) presented increased risks for disability. HR for disability increased with the number of risk factors (HR of individuals with four conditions, 3.96 (1.59 to 9.99) vs individuals with none of those conditions as a reference). HR for disability among patients with diabetes with and without a physical activity habit was 1.68 (0.70 to 4.04) and 3.19 (1.79 to 5.70), respectively, compared with individuals without diabetes with a physical activity habit. CONCLUSIONS: The combination of diabetes and lack of habitual physical activity is predictive of functional disability in Japanese. Habitual physical activity attenuates the risk of functional disability in patients with diabetes.

DOI： 10.1136/bmjdrc-2019-000901

PubMed

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Language：English   Publishing type：Research paper (scientific journal)  

OBJECTIVE: Although glucose abnormality status (GAS), prior coronary artery disease (CAD), and other traditional risk factors affect the incidence of subsequent CAD, their impact in the same cohort has been scantly studied. RESEARCH DESIGN AND METHODS: We analyzed data from a nationwide claims database in Japan that was accumulated during 2008-2016 involving 138,162 men aged 18-72 years. Participants were classified as having normoglycemia, borderline glycemia, or diabetes mellitus (DM) with prior CAD (CAD+) or without prior CAD (CAD-). Cox regression model identified variables related to the incidence of CAD. RESULTS: Among CAD-, management of traditional risks differed from those with and without subsequent CAD events. On the other hand, such differences were weaker in borderline glycemia and DM CAD+, and the influence of traditional risk factors on subsequent CAD was not observed. Cox regression model showed that borderline glycemia and DM confer approximately 1.2- and 2.8-fold excess risks of CAD, respectively, compared with CAD- with normoglycemia. CAD+ confers approximately a 5- to 8-fold increased risk. The impacts of DM and prior CAD additively reached a hazard ratio (HR) of 15.74 (95% confidence interval [CI]: 11.82-21.00). However, the HR in those with borderline glycemia and CAD+ was 7.20 (95% CI: 5.01-10.34), which was not different from those with normoglycemia and CAD+. CONCLUSION: Control status of traditional risk factors and impact on subsequent CAD differ among categories of glycemic status with and without prior CAD. Individualizing treatment strategies is needed in consideration of risk factors, such as GAS and CAD+.

DOI： 10.1016/j.metabol.2019.153991

PubMed

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Language：English   Publishing type：Research paper (scientific journal)  

PURPOSE: To determine the degree of control of multiple risk factors under real-world conditions for coronary artery disease (CAD) according to the presence or absence of diabetes mellitus (DM) and to determine whether reaching multifactorial targets for blood pressure (BP), low-density lipoprotein-cholesterol (LDL-C), HbA1c, and current smoking is associated with lower risks for CAD. METHODS: We investigated the effects on subsequent CAD of the number of controlled risk factors among BP, LDL-C, HbA1c, and current smoking in a prospective cohort study using a nationwide claims database of 220,894 individuals in Japan. Cox regression examined risks over a 4.8-year follow-up. RESULTS: The largest percentage of participants had two risk factors at target in patients with DM (39.6%) and subjects without DM (36.4%). Compared with those who had two targets achieved, the risks of CAD among those who had any one and no target achieved were two and four times greater, respectively, regardless of the presence of DM. The effect of composite control was sufficient to bring CAD risk in patients with DM below that for subjects without DM with any two targets achieved, whereas the risk of CAD in the DM group with all four risk factors uncontrolled was 9.4 times more than in the non-DM group who had achieved two targets. CONCLUSIONS: These findings show that composite control of modifiable risk factors has a large effect in patients with and without DM. The effect was sufficient to bring CAD risk in patients with DM below that in the non-DM group who had two targets achieved.

DOI： 10.1210/jc.2019-00168

PubMed

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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Language：Japanese   Publisher：(一社)日本糖尿病合併症学会  

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Publishing type：Research paper (scientific journal)   Publisher：American Diabetes Association  

DOI： 10.2337/db19-450-p

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Language：English   Publishing type：Research paper (scientific journal)  

AIMS: To determine incidence and predictors of starting dialysis in patients with diabetes emphasizing blood pressure variables. METHODS: A nationwide database with claim data on 18 935 people (15 789 men and 3146 women) with diabetes mellitus aged 19 to 72 years in Japan was used to elucidate predictors for starting dialysis. Initiation of dialysis was determined from claims using ICD-10 codes and medical procedures. Using multivariate Cox modelling, interactions between glycaemic and blood pressure values were determined. RESULTS: During a median follow-up of 5.3 years, incidence of dialysis was 0.81 per 1000 person-years. Multivariate analysis of a model involving systolic and diastolic blood pressure (SBP and DBP) simultaneously as covariates showed that hazard ratios (HRs) for starting dialysis for each 1-SD elevation in SBP and DBP were 2.05 (95% confidence interval 1.58-2.64) and 0.66 (0.50-0.88), respectively, implying that pulse pressure (PP) was a promising predictor. For confirmation, a model involving SBP and PP simultaneously as covariates demonstrated that HRs for each 1-SD elevation in SBP and PP were 1.09 (0.81-1.48) and 1.54 (1.14-2.08), respectively, with PP the more potent predictor. Compared with HbA1c <8% and PP <60 mmHg, the HR for those with HbA1c ≥8% and PP ≥60 mmHg was 6.32 (3.42-11.7). CONCLUSIONS: In our historical cohort analysis, SBP and PP were independent predictors for starting dialysis. PP was the more potent, suggesting the contribution of increased arterial stiffness to the incidence of dialysis. Future studies are needed to conclude the independent influence of PP and HbA1c on dialysis considering other risk factors.

DOI： 10.1002/dmrr.3120

PubMed

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Publishing type：Research paper (scientific journal)   Publisher：ClinMed International Library  

DOI： 10.23937/2377-3634/1410065

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：AMER DIABETES ASSOC  

DOI： 10.2337/db18-444-P

Web of Science

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：AMER DIABETES ASSOC  

DOI： 10.2337/db18-637-P

Web of Science

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：AMER DIABETES ASSOC  

DOI： 10.2337/db18-594-P

Web of Science

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：AMER DIABETES ASSOC  

DOI： 10.2337/db18-2384-PUB

Web of Science

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：SPRINGER  

Web of Science

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：SPRINGER  

Web of Science

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