scholarly journals Factors associated with the degree of glycemic deterioration among patients with type 2 diabetes who dropped out of diabetes care: a longitudinal analysis using medical claims and health checkup data in Japan

2021 ◽  
Author(s):  
Noriko Ihana‐Sugiyama ◽  
Takehiro Sugiyama ◽  
Kenjiro Imai ◽  
Ayako Yanagisawa‐Sugita ◽  
Hirokazu Tanaka ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Longitudinal Analysis ◽  
Diabetes Care ◽  
Health Checkup ◽  
Medical Claims ◽  
Factors Associated

scholarly journals Response to Comment on Balkau et al. Factors Associated With Weight Gain in People With Type 2 Diabetes Starting on Insulin. Diabetes Care 2014;37:2108–2113

Diabetes Care ◽  
2014 ◽  
Vol 37 (12) ◽  
pp. e266-e266
Author(s):  
Beverley Balkau ◽  
Philip D. Home ◽  
Maya Vincent ◽  
Michel Marre ◽  
Nick Freemantle
Keyword(s):  
Type 2 Diabetes ◽  
Weight Gain ◽  
Diabetes Care ◽  
Factors Associated

scholarly journals Guideline Adherence and the Factors Associated with Better Care for Type 2 Diabetes Mellitus Patients in Lithuanian PHC: Diabetes Mellitus Guideline Adherence in Lithuania PHC

2019 ◽  
Vol 6 (1) ◽  
pp. 50-57
Author(s):  
Raila Gediminas ◽  
Liseckienė Ida ◽  
Jarusevičienė Lina ◽  
Leonas Valius
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Serum Creatinine ◽  
Guideline Adherence ◽  
Diabetes Care ◽  
Factors Associated ◽  
Positive Effect

Background: Type 2 diabetes mellitus is one of the most common chronic conditions, which requires appropriate management and care at PHC level, which is described in guidelines. However, guideline adherence at the international arena is insufficient and little is known about the reasons for guideline non-adherence. Objective: The aim of the survey was to analyse to what extent the Lithuanian family practitioners adhere to diabetes guidelines in order to compare to international data and to discover the factors associated with better diabetes care. Methods: The present study is a part of EUPRIMECARE Project, which sets out to develop a framework aiming at the analysis of PHC across Europe. The sample strategy was based on an unequal probability sampling design. An audit of 4 public and 6 private PHC medical records of the year 2011 was carried out in Kaunas region, clinical records of 382 diabetes type 2 patients were reviewed. Demography, diseases and diabetes performance indicators data were collected using a uniform template. Binary and multivariable logistic regression analyses were used in the investigation of the factors related to better diabetes guideline adherence. Results: Three guideline adherence levels were identified: high performance (performed in more than 90% cases) - BP measurement and HbA1c exam; good performance (performed in more than 50% cases) - ECG examination and serum creatinine check; insufficient performance (performed in less than 50% of cases) - annual endocrinologist consultation, eye fundus and foot examinations, LDL check and BMI calculation. Insufficient glycaemic control was positive associated with increased endocrinologist consultation and foot exam rates, elevated BP demonstrated the positive effect to creatinine check rate, multimorbidity had positive association to the annual eye, ECG, creatinine check rates; frequent FP attendance showed no positive effect on process indicators. Rural patients have a negative association to foot and ECG exam rates compared to urban patients. In a stepwise logistic regression model, 3 dependent variables had statistically significant impact on overall diabetes care indicator performance: negative - rural location of patients (OR 0.4, 95% CI 0.2-0.8), elevated mean BP (OR 0.6, 95% CI 0.4-0.9); positive - multimorbidity (OR 2.0, 95% CI 1.2-3.4). Conclusion: Guideline adherence for T2DM is not optimal in Lithuanian PHC. The best are BP and HbA1c checks. Suboptimal are BMI and LDL annual checks. The situation with these is almost the same as in other European countries. The better guideline adherence has been observed in urban (foot exam, ECG exam), multimorbidity (eye, ECG, creatinine exams), controlled by means of BP patients (serum creatinine test).

The Probability of A1C Goal Attainment in Patients with Uncontrolled Type-2 Diabetes in a Large Integrated Delivery System: A Prediction Model

2020 ◽  
Author(s):  
Kevin M Pantalone ◽  
Anita D Misra-Hebert ◽  
Todd M Hobbs ◽  
Sheldon X Kong ◽  
Xinge Ji ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Goal Attainment ◽  
Index Date ◽  
Cleveland Clinic ◽  
Patient Characteristics ◽  
Psychiatric Disease ◽  
Lower Probability ◽  
Factors Associated ◽  
One Year

<b>Objective:</b> To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of A1C goal attainment. <p><b>Research Design and Methods</b>: Retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C>9%) were identified on the index date of 12/31/2016 (n=6,973), grouped by attainment (n=1,653 [24.7%) or non-attainment (n=5,320 [76.3%]) of A1C<8% by 12/31/2017, and subgroups compared on a number of demographic and clinical variables. Based on these variables, a nomogram was created for predicting probability of A1C goal attainment. </p> <p><b>Results:</b> For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%) and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common anti-diabetes medications. Only 1,653 (24%) patients achieved an A1C <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, DPP-4i use, thiazolidinedione use, metformin use, GLP-1RA use, and fewer classes of anti-diabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). </p> <p><b>Conclusions:</b> A minority of patients with an A1C>9% achieved an A1C<8% at one year. While most identified predictive factors are non-modifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help improve A1C goal attainment. </p>

Risk Factors Associated With Hyperuricemia in Patients with Diabetes Type 2: About 190 Cases

2020 ◽  
Vol 2 (1) ◽  
pp. 12-16
Author(s):  
Fennoun H ◽  
Haraj NE ◽  
El Aziz S ◽  
Bensbaa S ◽  
Chadli A
Keyword(s):  
Type 2 Diabetes ◽  
Heart Disease ◽  
Glycemic Control ◽  
Ischemic Heart Disease ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Ischemic Heart ◽  
Factors Associated ◽  
Patients With Diabetes

Introduction: Hyperuricemia is common Type 2 diabetes at very high cardiovascular risk. Objective: Evaluate the relationship between hyperuricemia and diabetes type 2, and determine its predictive factors in this population. Patients and Methods: Retrospective study cross including 190 patients with diabetes type 2 hospitalized Service of Endocrinology of CHU Ibn Rushd Casablanca from January 2015 to December 2017. Hyperuricemia was defined as a serum uric acid concentration> 70 mg/L (men) and> 60 mg/L (women). The variables studied were the anthropometric measurements), cardiovascular factors (tobacco, hypertension, dyslipidemia), and degenerative complications (retinopathy, neuropathy, kidney failure, ischemic heart disease). The analyzes were performed by SPSS software. Results: Hyperuricemia was found in 26.5% of patients with a female predominance (76%), an average age of 55.9 years, and an average age of 12.4ans diabetes. The glycemic control was found in 84.6% of cases with mean glycated hemoglobin 8.6%. Factors associated al hyperuricemia were the blood pressure in 86% (p <0.05), dyslipidemia in 76.3% of cases (p <0.001) with hypertriglyceridemia in 48.3% of cases (p <0.02), and a hypoHDLémie 28% (p <0.001). The age, obesity, smoking, and glycemic control were associated significantly n al hyperuricemia. The research of degenerative complications of hyperuricemia has objectified renal impairment (GFR between 15 and 60ml / min) chez47% (p <0.001), it was kind of moderate in 35.8% (p <0.01) and severe in 5.1% (p <0.02), ischemic heart disease was found in 34% of cases (p <0.01). Conclusion: In our study, hyperuricemia in type 2 diabetes is common in female patients, especially with hypertension, dyslipidemia, and renal failure. Other factors such as age, obesity, smoking is not associated with hyperuricemia in type 2 diabetics.

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