scholarly journals Comorbidity in an Older Population with Type-2 Diabetes Mellitus: Identification of the Characteristics and Healthcare Utilization of High-Cost Patients

2020 ◽  
Vol 11 ◽  
Author(s):  
Inmaculada Guerrero-Fernández de Alba ◽  
Valentina Orlando ◽  
Valeria M. Monetti ◽  
Sara Mucherino ◽  
Antonio Gimeno-Miguel ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Healthcare Database ◽  
Campania Region ◽  
Total Cost ◽  
T2dm Patient ◽  
Logistic Regression Models ◽  
Cost Distribution

Objectives: Little is known about the specific comorbidities contributing to higher costs in patients with type-2 diabetes mellitus (T2DM), particularly in older cases. We aimed to evaluate the prevalence, type, and cost of comorbidities occurring in older T2DM patients versus older non-T2DM patients, and the factors associated with high cost (HC) T2DM patients.Methods: Retrospective cohort study using information from the Campania Region healthcare database. People aged ≥65 years who received ≥2 prescriptions for antidiabetic drugs were identified as “T2DM patients.” Comorbidities among T2DM and non-T2DM groups were assessed through the RxRiskV Index (modified version). T2DM individuals were classified according to the total cost distribution as HC or “non-high cost.” Two sub-cohorts of HC T2DM patients were assessed: above 90th and 80th percentile of the total cost. Age- and sex-adjusted logistic regression models were created.Results: Among the T2DM cohort, concordant and discordant comorbidities occurred significantly more frequently than in the non-T2DM cohort. Total mean annual cost per T2DM patient due to comorbidities was €7,627 versus €4,401 per non-T2DM patient. Among T2DM patients identified as being above 90th and 80th percentiles of cost distribution, the total annual costs were >€19,577 and >€2,563, respectively. The hospitalization cost was higher for T2DM cases. Strongest predictors of being a HC T2DM patient were having ≥5 comorbidities and renal impairment.Conclusion: HC patients accrued >80% of the total comorbidities cost in older T2DM patients. Integrated care models, with holistic and patient-tailored foci, could achieve more effective T2DM care.

scholarly journals Health Economic Evaluation of Type 2 Diabetes Mellitus: A Clinical Practice Focused Review

2015 ◽  
Vol 8 ◽  
pp. CMED.S20906 ◽  
Author(s):  
Andreas Liebl ◽  
Kamlesh Khunti ◽  
Domingo Orozco-Beltran ◽  
Jean-Francois Yale
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Health Economic ◽  
Type 2 Diabetes Mellitus ◽  
Drug Therapy ◽  
Glycemic Control ◽  
Cost Effective ◽  
Treatment Intensification ◽  
Total Cost

Type 2 diabetes mellitus (T2D) is a growing healthcare burden primarily due to long-term complications. Strict glycemic control helps in preventing complications, and early introduction of insulin may be more cost-effective than maintaining patients on multiple oral agents. This is an expert opinion review based on English peer-reviewed articles (2000–2012) to discuss the health economic consequences of T2D treatment intensification. T2D costs are driven by inpatient care for treatment of diabetes complications (40%–60% of total cost), with drug therapy for glycemic control representing 18% of the total cost. Insulin therapy provides the most improved glycemic control and reduction of complications, although hypoglycemia and weight gain may occur. Early treatment intensification with insulin analogs in patients with poor glycemic control appears to be cost-effective and improves clinical outcomes. Key Messages • Type 2 diabetes mellitus is a growing burden on healthcare services. • Despite the high cost of drug therapy versus diet and lifestyle interventions, treatment intensification with insulin analog therapy is a cost-effective strategy for improving clinical outcomes in patients with poor glycemic control.

scholarly journals Association Between Transcription Factor 7-Like-2 Polymorphisms and Type 2 Diabetes Mellitus in a Ghanaian Population

2021 ◽  
Author(s):  
Christian Obirikorang ◽  
Evans Asamoah Adu ◽  
Enoch Odame Odame ◽  
Emmanuel Acheampong ◽  
Lawrence Quaye ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Lipid Analysis ◽  
Nucleotide Polymorphisms ◽  
Logistic Regression Models ◽  
Allele Specific ◽  
Amplification Assay ◽  
Glucose Estimation

Type-2 diabetes mellitus (T2DM) have been strongly associated with single nucleotide polymorphisms (SNPs) in the TCF7L2 gene. This study investigated the association between rs12255372, rs7903146 and T2DM in a Ghanaian population. A case-control study design was used for this study. A total of 106 T2DM patients and 110 control participants were selected. Basic data collected included body mass index, blood pressure and socio-demographics. Fasting blood samples were collected and used for serum lipid analysis, HbA1c, plasma glucose estimation and DNA extraction. Common and allele-specific primers were designed for genotyping using the Modified Tetra-Primer Amplification assay. Associations were evaluated using logistic regression models. The rs7903146 risk variant was significantly associated with 2.16 vs 4.06 increased odds for T2DM in patients

scholarly journals Cost-of-Illness Analysis of Type 2 Diabetes Mellitus in the Russian Federation: Results from Russian multicenter observational pharmacoepidemiologic study of diabetes care for patients with type 2 diabetes mellitus (FORSIGHT-Т2DM)

2018 ◽  
Vol 20 (6) ◽  
pp. 403-419 ◽  
Author(s):  
Ivan I. Dedov ◽  
Marina F. Kalashnikova ◽  
Dmitriy Y. Belousov ◽  
Aleksey S. Kolbin ◽  
Vladimir V. Rafalskiy ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Russian Federation ◽  
Cost Of Illness ◽  
Indirect Costs ◽  
Medical Costs ◽  
Total Cost ◽  
The Russian Federation

Background: Cost-of-Illness Analysis (COI) constitutes the basis for the decision-making process on the budget and allocation in a modern health care system. Considering the wide prevalence of type 2 diabetes mellitus (Т2DM), it is important to perform COI in the Russian Federation (RF). Aim: The aim of the secondary objective FORSIGHT-Т2DM study was to conduct Cost-of-Illness Analysis (COI) of Т2DM in the Russian Federation in relation to taking into consideration the presence of complications and concomitant diseases. Materials and methods: COI of Т2DM was performed using the data obtained in Russian multicenter observational, pharmacoepidemiologic cross-sectional study of diabetes care for assessing routine healthcare pattern of T2DM in the Russian Federation (FORSIGHT-Т2DM). Information for each patient was collected from primary medical records and By asking patients to fill out a questionnaire. Total costs were calculated as the sum of direct medical costs (DCm), direct non-medical costs (DCn) and indirect costs (IC). Results: The final analysis included data from 2014 patients with T2DM residing in 45 cities of RF. Total direct medical costs (DCm) of treating Т2DM and its complications and comorbidities amounted to 105 337 rubles ($2742) per patient per year; direct non-medical costs (DCn) amounted to 24 518 rubles ($638) per patient per year; indirect costs (IC) amounted to 149 754 rubles ($3898) per patient per year. The total cost of T2DM in RF in 2014 year amounted to 279 609 rubles ($7278) per patient. The total cost of T2DM in RF in 2014 amounted to 279 609 rubles per patient. Conclusions: More than half (53,5%) of the total cost of T2DM is the loss of GDP due to patients disability. The DCm constitute 37,7% of the total cost of the disease, of which 57% is spent on treatment of T2DM complications and concomitant diseases, while only 10% is spent on glucose-lowering therapies.

scholarly journals Secondary metformin monotherapy failure in individuals with type 2 diabetes mellitus

2021 ◽  
Vol 9 (1) ◽  
pp. e002127
Author(s):  
Tracey Weiss ◽  
Kristy Iglay ◽  
Tania Gulati ◽  
Swapnil Rajpathak ◽  
Lingfeng Yang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Glycemic Control ◽  
Treatment Change ◽  
Logistic Regression Models ◽  
Multivariable Logistic Regression ◽  
Metformin Monotherapy

IntroductionTo assess secondary metformin monotherapy (MM) failure in a real-world type 2 diabetes mellitus (T2DM) cohort.Research design and methodsUsing the IQVIA Electronic Medical Record (formerly GE Centricity) database, adults with T2DM who initiated MM between January 1, 2012 and June 30, 2016 and achieved glycemic control (hemoglobin A1c (HbA1c) <7% (53 mmol/mol); index date) were analyzed. Secondary MM failure was defined in two ways: loss of glycemic control (HbA1c ≥7% (53 mmol/mol)) and treatment change (addition or switch of antihyperglycemic agent). Multivariable logistic regression models assessed the association between secondary MM failure and sociodemographic and clinical factors.ResultsThe analysis included 4775 patients initiating MM. 32.9% and 19.2% experienced secondary MM failure at 24 months measured as loss of glycemic control and treatment change, respectively. Multivariable logistic regression found that women (OR=1.3, 95% CI 1.1 to 1.5) compared with men, lower Charlson Comorbidity Index (CCI) (OR=0.89, 95% CI 0.86 to 0.93), and lower baseline HbA1c (OR=0.93, 95% CI 0.88 to 0.98) were associated with increased likelihood of loss of glycemic control. Lower CCI was associated with increased likelihood of treatment change (OR=0.78, 95% CI 0.75 to 0.82).ConclusionsThe observed frequency of secondary MM failure underscores the importance of the American Diabetes Association’s recommendation for glycemic monitoring of at least every 6 months so that timely therapeutic adjustments can be made.

scholarly journals Prevalence and characteristics of alcohol consumption and risk of type 2 diabetes mellitus in rural China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xueyan Wu ◽  
Xiaotian Liu ◽  
Wei Liao ◽  
Ning Kang ◽  
Xiaokang Dong ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cohort Study ◽  
Alcohol Consumption ◽  
Rural China ◽  
Logistic Regression Models ◽  
Alcohol Abstinence ◽  
Increased Risk

Abstract Background The study aimed to characterize the prevalence of alcohol consumption and further investigate the relationship between alcohol consumption and type 2 diabetes mellitus (T2DM). Methods We studied 39,259 participants aged 18 to 79 years of the Henan Rural Cohort study. The associations between alcohol consumption and T2DM were examined using the logistic regression models and restricted cubic spline. Results For men, alcohol abstinence was associated with an increased risk of T2DM (1.491(1.265, 1.758)), whereas current drinkers were not associated with T2DM (1.03(0.91, 1.15)). Further analysis of alcohol drinkers revealed that only high-risk drinkers of WHO drinking risk levels increased the risk of T2DM (1.289(1.061,1.566)) compared to never drinkers. The risk of T2DM increased as the age of starting to consume alcohol decreased and as the number of years of consuming alcohol and the alcohol intake increased only in men. We further found that the risk of T2DM decreased as the number of years of abstinence increases and no association between alcohol abstinence and T2DM was found after more than 10 years of abstinence among men. Conclusions Our results suggested that reducing the amount of alcohol consumed and adhering to abstinence from alcohol consumption are beneficial in reducing the risk of T2DM. Trial registration The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 2015-07-06. http://www.chictr.org.cn/showproj.aspx?proj=11375

scholarly journals Metabolomics Identifies Biomarker Signatures to Differentiate Pancreatic Cancer from Type 2 Diabetes Mellitus in Early Diagnosis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hongmin Xu ◽  
Lei Zhang ◽  
Hua Kang ◽  
Jie Liu ◽  
Jiandong Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Pancreatic Cancer ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Early Diagnosis ◽  
Regression Models ◽  
Pancreatic Tissue ◽  
Logistic Regression Models

Background and Purpose. Carbohydrate antigen 19-9 (CA19-9) based approaches differentiate less than 60% of cases of pancreatic cancer (PC) from those of pancreatic tissue damage caused by chronic pancreatitis and type 2 diabetes mellitus (DM). This study aims to identify potential blood-derived candidate biomarkers for improved diagnosis sensitivity. Methods. Plasma metabolic profiles in 26 PC patients, 27 DM patients, and 23 healthy volunteers were examined using an ultraperformance liquid chromatography coupled with tandem mass spectrometry platform. Differential metabolite ions were then identified using the principal component analysis (PCA) model and the orthogonal partial least-squares discrimination analysis (OPLS-DA) model. The diagnosis performance of metabolite biomarkers was validated by logistic regression models. Results. We established a PCA model (R2X = 23.5%, Q2 = 8.21%) and an OPLS-DA model (R2X = 70.0%, R2Y = 84.9%, Q2 = 69.7%). LysoPC (16 : 0), catelaidic acid, cerebronic acid, nonadecanetriol, and asparaginyl-histidine were found to identify PC, with a sensitivity of 89% and a specificity of 91%. Besides, lysoPC (16 : 0), lysoPC (16 : 1), lysoPC (22 : 6), and lysoPC (20 : 3) were found to differentiate PC from DM, with higher accuracy (68% versus 55%) and higher AUC values (72% versus 63%) than those of CA19-9. The diagnostic performance of metabolite biomarkers was finally validated by logistic regression models. Conclusion. We succeeded in screening differential metabolite ions among PC and DM patients and healthy individuals, thus providing a preliminary basis for screening the biomarkers for the early diagnosis of PC.

scholarly journals Associations of Midpoint of Sleep and Night Sleep Duration with Type 2 Diabetes Mellitus in Chinese Rural Population: The Henan Rural Cohort

2021 ◽  
Author(s):  
Zhihan Zhai ◽  
Xiaotian Liu ◽  
Haiqing Zhang ◽  
Xiaokang Dong ◽  
Yaling He ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Sleep Duration ◽  
Night Sleep ◽  
Potential Health ◽  
Logistic Regression Models ◽  
Intermediate Group ◽  
Clinical Trail

Abstract Background: The study aimed to explore the independent and combined associations of midpoint of sleep and night sleep duration with type 2 diabetes mellitus (T2DM) in areas with limited resources.Methods: A total of 37,276 participants (14,456 men and 22,820 women) were derived from the Henan Rural Cohort. Information on sleep were collected using the Pittsburgh Sleep Quality Index. Logistic regression models and restricted cubic splines were used to estimate the relationship of the midpoint of sleep and night sleep duration with T2DM.Results: Of the 37276 included participants, 3580 subjects suffered from T2DM. The mean midpoint of sleep among Early, Intermediate and Late groups were 1.09 ± 0.39, 1.93 ± 0.24 and 2.95 ± 0.56, respectively. Compared to Intermediate group, adjusted odd ratios (ORs) and 95% confidence interval (CI) of T2DM were 1.13 (1.04-1.22) and 1.16 (1.05-1.28) in Early group and Late group. Adjusted OR (95% CI) for T2DM compared with reference (7- h) was 1.27 (1.08-1.50) for longer (≥10 h) night sleep duration. The combination of late midpoint of sleep and night sleep duration (≥9 h) increased 39% (95% CI: 11%-75%) prevalence for T2DM. These associations were more obvious in women than men.Conclusions: Late and early midpoint of sleep and long night sleep duration were all associated with the higher odds of T2DM. Meanwhile, midpoint of sleep and night sleep duration might be jointly associated with a higher prevalence of T2DM. Sleep may be a modifiable behavior that has potential health implications for T2DM.Clinical Trail Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 2015-07-06.

scholarly journals Anthropometric indices as novel markers of risk in type 2 diabetes mellitus (T2DM) among Nigerian adults in Zamfara State

Bio-Research ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 1237-1245
Author(s):  
Ikenna Bruno Aguh ◽  
Zurmi Rabiu Sani ◽  
Lynda Chinanu Ohaleme ◽  
Andover Alfred Agba
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Anthropometric Measures ◽  
Logistic Regression Models ◽  
Arm Circumference ◽  
Increased Risk ◽  
Size Measure ◽  
Diabetes Mellitus Risk

Body mass index (BMI) has traditionally been used as an indicator of body size measure and composition. Although, other measures of adiposity of the abdomen such as waist circumference (WC), waist-hip ratio (WHR), neck circumference (NC) have been suggested as being superior to BMI in predicting disease outcome. This study was designed to compare different anthropometric variables in term of their ability to predict type 2 diabetes mellitus (T2DM). This was a case-control study in 240 participants involving 120 verified T2DM cases and 120 non-diabetics as control. Age, gender and anthropometric data were collected from each participant. Logistic regression models were used with areas under the receiver operating characteristic (AROC) curve to compare the variables predictive statistics. The AROC of WHR to identify T2DM patients was 0.678 (P<0.05), with sensitivity 62.5% of and specificity of 60.8%. The AROC for average arm circumference (AAC) model is 0.649 with sensitivity of 55.8% followed by BMI model (AROC 0.635) and WC model (AROC 0.600) (P<0.05). Hip circumference (HC) (AROC 0.508) and NC (AROC 0.492) models were not significant predictors of T2DM. Subjects of ≥60 years, AAC value ≥32.6 cm, BMI value ≥ 30 kg/m2, and WHR value ≥ 0.93 were at significantly (P<0.05) higher odds of developing T2DM than lower subjects with lower values. There were no significant differences (P>0.05) in the mean HC and NC values between the diabetic and non-diabetic subjects. The non-diabetic subjects have significantly (P>0.05) higher mean height value than the diabetic subjects. Measures of generalized and central obesity were significantly associated with increased risk of developing T2DM. This study revealed that WHR can predict type 2 diabetes mellitus risk more accurately than other anthropometric measures and can thus be helpful in predicting patients with future occurrence of diabetes and providing necessary interventions

scholarly journals Interplay of Transcription Factor 7-Like-2 Polymorphisms with Type 2 Diabetes Mellitus in a Ghanaian Population

2021 ◽  
Author(s):  
Christian Obirikorang ◽  
Evans Asamoah Adu ◽  
Emmanuel Acheampong ◽  
Enoch Odame Anto ◽  
Lawrence Quaye ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Family History ◽  
Lipid Analysis ◽  
Additive Model ◽  
Nucleotide Polymorphisms ◽  
Logistic Regression Models ◽  
Glucose Estimation

Abstract Background Type-2 diabetes mellitus (T2DM) have been strongly associated with single nucleotide polymorphisms (SNPs) in the TCF7L2 gene. This study investigated the interplay between rs12255372 and rs7903146 with T2DM in a Ghanaian population. Methods A case-control design was used for this study. A total of 106 T2DM patients and 110 apparently healthy control participants were selected. Basic data collected included body mass index, blood pressure and socio-demographics. Fasting blood samples were collected and used for serum lipid analysis, HbA1c, glucose estimation and DNA extraction. Common and allele-specific primers were designed for genotyping using the Modified Tetra-Primer Amplification assay. Associations were evaluated using logistic regression models. Results The rs7903146 risk variant was significantly associated with 2.16 vs 4.06 increased odds for T2DM in patients < 60 years vs ≥ 60 years. Both rs7903146 and rs12255372 were significantly associated with increased odds of T2DM in women, overweight/obese; negative T2DM family history and low-HDL-C. In a multivariate model, rs7903146 but not rs12255372 was significantly associated with 2.18, 5.01 and 2.25 increased odds of T2DM, under the codominant, recessive and additive model, respectively (p < 0.05). Haplotype analysis showed that rs7903146 and rs12255372 SNPs are weakly associated (D’=0.021; r2 = 0.0001). Conclusion The association between rs7903146 and rs12255372 with T2DM looks to be more highly associated in a subgroup- women and those without T2DM family history, yet have cardiometabolic risk.

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