Association of anti-diabetic drugs and COVID-19 outcomes in patients with diabetes mellitus type 2 and cardiomyopathy.

There is a scarcity of information on the population with diabetes mellitus type 2 and cardiomyopathy (PDMC) in COVID-19, especially on the association between anti-diabetic medications and COVID-19 outcomes. Study is designed as a retrospective cohort analysis covering 2020 and 2021. Data from National Diabetes Registry (CroDiab) were linked to hospital data, primary healthcare data, the SARS-CoV-2 vaccination database, and the SARS-CoV-2 test results database. Study outcomes were cumulative incidence of SARS-CoV-2 positivity, COVID-19 hospitalizations, and COVID-19 deaths. For outcome predictors, logistic regression models were developed. Of 231 796 patients with diabetes mellitus type 2 in the database, 14 485 patients had cardiomyopathy. The two2-year cumulative incidence of all three studies' COVID-19 outcomes was higher in PDMC than in the general diabetes population (positivity 15.3% vs. 14.6%, p = 0.01; hospitalization 7.8% vs. 4.4%, p < 0.001; death 2.6% vs. 1.2%, p < 0.001). Sodium-Glucose Transporter 2 (SGLT-2) inhibitors therapy was found to be protective of SARS-CoV-2 infections [OR 0.722 (95% CI 0.610-0.856)] and COVID-19 hospitalizations [OR 0.555 (95% CI 0.418-0.737)], sulfonylureas to be risk factors for hospitalization [OR 1.184 (95% CI 1.029-1.362)] and insulin to be a risk factor for hospitalization [OR 1.261 (95% CI 1.046-1.520)] and death [OR 1.431 (95% CI 1.080-1.897)]. PDMC are at greater risk of acquiring SARS-CoV-2 infection and having worse outcomes than the general diabetic population. SGLT-2 inhibitors therapy was a protective factor against SARS-CoV-2 infection and against COVID-19 hospitalization, sulfonylurea was the COVID-19 hospitalization risk factor, while insulin was a risk factor for all outcomes. Further research is needed in this diabetes sub-population.

Adoption of sodium-glucose cotransporter-2 inhibitors among prescribers caring for nursing home residents.

BACKGROUND: Sodium-glucose cotransporter-2 inhibitor (SGLT2I) use has increased among community-dwelling populations, but little is known about how clinicians have prescribed them for US nursing home (NH) residents. We described the adoption of SGLT2Is by prescribers caring for long-stay NH residents by clinician specialty and over time, compared with sulfonylureas, an older diabetes medication class. METHODS: We conducted a retrospective cohort study of prescribers of SGLT2Is and sulfonylureas for all long-stay US NH residents aged 65 years or older (2017-2019). Using 100% of Medicare Part D claims linked to prescriber characteristics data, we identified all dispensings of SGLT2Is and sulfonylureas for long-stay NH residents and their associated prescribers. We described the distribution of prescriber specialties for each drug class over time as well as the number of NH residents prescribed SGLT2s versus sulfonylureas. We estimated the proportions of prescribers who prescribed both drug classes versus only sulfonylureas or only SGLT2Is. RESULTS: We identified 36,427 unique prescribers (SGLT2I: N = 5811; sulfonylureas: N = 35,443) for 117,667 NH residents between 2017 and 2019. For both classes, family medicine and internal medicine physicians accounted for most prescriptions (75%-81%). Most clinicians (87%) prescribed only sulfonylureas, 2% prescribed SGLT2Is only, and 11% prescribed both. Geriatricians were least likely to prescribe only SGLT2Is. We observed an increase in the number of residents with SGLT2I use from n = 2344 in 2017 to n = 5748 in 2019. CONCLUSIONS: Among NH residents, most clinicians have not incorporated SGLT2Is into their prescribing for diabetes, but the extent of use is increasing. Family medicine and internal medicine physicians prescribed the majority of diabetes medications for NH residents, and geriatricians were the least likely to prescribe only SGLT2Is. Future research should explore provider concerns regarding SGLT2I prescribing, particularly adverse events.

De novo HNF1A mutation of young maturity-onset diabetes 3 of a young girl-Case report.

Young maturity-onset diabetes of the young type3(MODY3) as a special type of diabetes, the probability of diagnosis is low. This article reports on a case and reviews the relevant knowledge of the disease. We report an 11-year-and-11-month-old girl whose grandmother died from diabetic complications while the rest of the families were non-diabetes. The proband was initially treated with insulin and metformin but the threatment proved inefficient. After an exome-targeted capture sequencing test, she was diagnosed with mature-onset diabetes of young type 3 (MODY3), and sulfonylureas make sense. The key to mody treatment is a correct and timely diagnosis, which contributes to helping patients overcome the problems of MODY3, especially for blood sugar control.

Comparative safety of sulfonylureas among U.S. nursing home residents.

BACKGROUND: The comparative safety of sulfonylureas (SUs) in nursing home (NH) residents remains understudied despite widespread use. We compared the effects of three SU medications and initial SU doses on adverse glycemic and cardiovascular events among NH residents. METHODS: This national retrospective cohort study linked Medicare claims with Minimum Data Set 2.0 assessments for long-stay NH residents aged ≥65 years between January 2008 and September 2010. Exposures were the SU medication initiated (glimepiride, glipizide, or glyburide) and doses (standard or reduced). One-year outcomes were hospitalizations or emergency department visits for severe hypoglycemia, heart failure (HF), stroke, and acute myocardial infarction (AMI). After the inverse probability of treatment and inverse probability of censoring by death weighting, we estimated hazard ratios (HR) using Cox regression models with robust 95% confidence intervals (CI). RESULTS: The cohort (N = 6821) included 3698 new glipizide, 1754 glimepiride, and 1369 glyburide users. Overall, the mean (standard deviation) age was 81.4 (8.2) years, 4816 (70.6%) were female, and 5164 (75.7%) were White non-Hispanic residents. The rates of severe hypoglycemia were 30.3 (95% CI 22.3-40.1), 49.0 (95% CI 34.5-67.5), and 35.9 (95% CI 22.2-54.9) events per 1000 person-years among new glipizide, glimepiride, and glyburide users, respectively (glimepiride versus glipizide HR 1.6, 95% CI 1.0-2.4, p = 0.04; glyburide versus glipizide HR 1.2, 95% CI 0.7-1.9, p = 0.59). The rates of severe hypoglycemia were 27.1 (95% CI 18.6-38.0) and 42.8 (95% CI 33.6-53.8) events per 1000 person-years among new users of reduced and standard SU doses, respectively (HR 2.2, 95% CI 1.4-3.5, p < 0.01). Rates of HF, stroke, and AMI were similar between medications and doses. CONCLUSIONS: Among long-stay NH residents, new use of glimepiride and standard SU doses resulted in higher rates of severe hypoglycemic events. Cardiovascular outcomes may not be affected by the choice of SU medication or dose.

Correction to: "Cardiovascular Outcomes Comparison of Dipeptidyl Peptidase-4 Inhibitors Versus Sulfonylurea as Add-on Therapy for Type 2 Diabetes Mellitus: A Meta-Analysis".

OBJECTIVE: Recent studies have raised concerns about the cardiovascular safety of dipeptidyl peptidase-4 (DPP4) inhibitors. We performed a systematic review and meta-analysis to compare the cardiovascular outcomes of sulfonylureas (SUs) versus DPP4 inhibitors in combination with metformin. METHODS: After searching for trials using combination therapy of metformin with an SU or DPP4 inhibitor in PubMed, Cochrane Library, and Embase, 1 prospective observational study and 15 randomized controlled studies were selected. RESULTS: Regarding the primary analysis endpoint, no significant differences were found in the risk of all-cause mortality between SUs and DPP4 inhibitors as add-on therapies to metformin (random-effect relative risk [RR], 1.14; 95% confidence interval [CI], 0.98-1.33; I2=0%; p=0.097). Cardiovascular death was also similar between SUs and DPP4 inhibitors in the 5 studies that reported outcomes (random-effect RR, 1.03; 95% CI, 0.83-1.27; I2=0%; p=0.817). Furthermore, there were no significant differences in major adverse cardiac events, coronary heart disease, myocardial infarction, and heart failure. However, the SU group showed a higher risk of ischemic stroke, more hypoglycemic events, and more weight gain than the DPP4 inhibitor group (ischemic stroke, random-effect RR, 2.78; 95% CI, 1.06-7.30; I2=51.9%; p=0.039; hypoglycemia, random-effect RR, 3.79; 95% CI, 1.53-9.39; I2=98.2; p=0.004; weight gain, weighted mean difference, 1.68; 95% CI, 1.07-2.29; I2=94.7; p<0.001). CONCLUSION: As add-on therapies to metformin, SUs and DPP4 inhibitors showed no significant differences in all-cause mortality and cardiovascular mortality. However, some of the favorable results of DPP4 inhibitors suggest good safety and feasibility of the drugs.

Association of vitamin B12 deficiency with metformin use in patients with type 2 diabetes treated in the largest tertiary care hospital in Qatar.

BACKGROUND: Data on the effect of metformin on serum vitamin B12 (VitB12) level in patients with type 2 diabetes mellitus (T2DM) in Qatar are limited; therefore, we aimed to assess the prevalence of VitB12 deficiency and its related factors among patients with tbl2DM treated with metformin at Hamad General Hospital in Doha, Qatar, from January 1, 2017, to December 31, 2017. METHODS: This cross-sectional analytical study involved patients with tbl2DM aged ≥ 18 years who used metformin for at least 3 months. The serum VitB12 was quantified on a chemiluminescent enzyme immunoassay analyzer using Cobas e 801 module, Roche, and VitB12 deficiency was defined as serum VitB12 level of ≤ 145 pmol/L. All data were obtained from the patients' electronic medical records. RESULTS: The study recruited 3124 eligible patients with tbl2DM. The overall prevalence of metformin-associated VitB12 deficiency was 30.7% [95% confidence of interval, 0.290-0.323]. A significant difference exists in the median VitB12 levels between the VitB12-normal and VitB12-deficient groups [129 vs. 286; p < 0.001]. Compared with the VitB12-normal group, the VitB12-deficient group had higher mean body mass index (BMI) (p < 0.001) and consumed higher doses of metformin (p = 0.001). They also more often used sulfonylurea (p = 0.004), dipeptidyl peptidase-4 inhibitor (p < 0.001), thiazolidinediones (p < 0.001), glucagon-like peptide 1 [GLP-1] receptor agonists (p < 0.001), alpha-glucosidase inhibitor (p < 0.001), and H2 blocker/proton pump inhibitors [PPI] (p < 0.001) than the VitB12-normal group. Moreover, the VitB12-normal group consumed more calcium supplements (p < 0.001) than the VitB12-deficient group. In the multivariate analysis, independent risk factors for metformin-associated VitB12 deficiency in patients with tbl2DM include high daily dose of metformin >2000 mg, male gender, high BMI, smoking, sulfonylurea, dipeptidyl peptidase-4 inhibitor, H2 blockers/PPI, low fasting blood glucose, and low hemoglobin. CONCLUSION: This study showed a high prevalence of VitB12 deficiency in patients with tbl2DM taking metformin and a significant negative correlation between the daily dose of metformin and serum VitB12 level. Therefore, regular screening for serum VitB12 is necessary in patients with tbl2DM on metformin treatment, especially those who have the abovementioned risk factors.

Comparative safety of dipeptidyl peptidase-4 inhibitors and sulfonylureas among frail older adults.

BACKGROUND: Studies comparing dipeptidyl peptidase-4 inhibitors (DPP4Is) to sulfonylureas (SUs) are unavailable for frail older adults, especially nursing home (NH) residents. We examined the effects of DPP4Is versus SUs on severe adverse glycemic events, cardiovascular events, and death among NH residents. METHODS: We conducted a national retrospective cohort study of long-stay NH residents aged ≥65 years using 2008-2010 national US Minimum Data Set clinical assessment data and linked Medicare claims. Exposure was new DPP4I versus new SU use assessed via Medicare Part D drug claims. One-year outcomes were severe hypoglycemia, severe hyperglycemia, acute myocardial infarction (AMI), heart failure (HF), major adverse cardiovascular events plus HF (MACE+HF), and death. We compared outcomes after propensity score matching using Cox proportional hazards regression models. RESULTS: The cohort (N = 2016) had a mean (SD) age of 81 (8.1) years and was 72% female. Compared with SU users, DPP4I users had a lower 1-year rate of severe hypoglycemic events (HR = 0.57, 95% CI 0.34-0.94), but statistically similar rates of severe hyperglycemic events (HR = 0.94, 95% CI 0.52-1.72), AMI (HR = 0.76, 95% CI 0.44-1.30), HF (HR = 1.01, 95% CI 0.79-1.30), MACE+HF (HR = 0.90, 95% CI 0.72-1.12), and death (HR = 0.97, 95% CI 0.86-1.10). CONCLUSIONS: DPP4Is should be a preferred treatment option over SUs for NH residents and other frail older adults given the importance of avoiding hypoglycemia.

Weight change and risk of cardiovascular disease among adults with type 2 diabetes: more than 14 years of follow-up in the Tehran Lipid and Glucose Study.

BACKGROUND: To examine the impact of weight change on incident cardiovascular disease and coronary heart disease (CVD/CHD) among an Iranian population with type 2 diabetes mellitus (T2DM). METHODS: The study population included 763 participants with T2DM aged ≥ 30 years without a history of CVD and cancer at baseline. Two weight measurements done at baseline and about 3 years later. Based on their weight change, they categorized into: > 5% loss, 3-5% loss, stable (± < 3%), 3-5% gain, > 5% gain. Participants were then followed for incident CVD/CHD annually up to 20 March 2018. Multivariable Cox proportional hazard models, adjusted for age, sex, body mass index, educational level, current smoking, glucose-lowering drug use, family history of CVD, hypertension, hypercholesterolemia, chronic kidney disease, and fasting plasma glucose (FPG) were applied to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of weight change categories for incident CVD/CHD, considering stable weight as reference. RESULTS: After the weight change measurement, during a median follow-up of 14.4 years, 258 CVD and 214 CHD occurred. Over 5% weight gain was associated with reduced risks of CVD and CHD development by the HRs of 0.70 [95% CI 0.48-1.01; P-value: 0.058] and 0.61 [0.40-0.93], respectively, in multivariable analysis. After further adjustment for FPG change, the HRs of weight gain > 5% were attenuated to 0.75 [0.51-1.10; P-value: 0.138] and 0.66 [043-1.01; P-value: 0.053] for incident CVD and CHD, respectively. The effect of weight loss > 5% was in opposite direction among those older versus younger than 60 years; with suggestive increased risk (not statistically significant) of incident CHD/CVD for the older group. Moreover, weight gain > 5% significantly reduced the risk of CHD only among those older than 60 years (P-value for interaction < 0.2). Furthermore, weight gain > 5% had an association with lower risk of CVD and CHD among sulfonylurea users (0.56 [0.32-0.98] for CVD and 0.54 [0.29-0.99] for CHD). CONCLUSIONS: Our results with a long-term follow-up showed that weight gain > 5% was associated with better CVD/CHD outcomes among Iranian participants with T2DM, especially older ones. Moreover, we did not find an unfavorable impact on incident CVD/CHD for sulfonylurea-induced weight gain.

Cardiovascular Outcomes Comparison of Dipeptidyl Peptidase-4 Inhibitors versus Sulfonylurea as Add-on Therapy for Type 2 Diabetes Mellitus: a Meta-Analysis.

OBJECTIVE: Recent studies have raised concern about the cardiovascular safety of dipeptidyl peptidase-4 (DPP4) inhibitors. We performed a systematic review through meta-analysis to compare cardiovascular outcomes of sulfonylurea (SU) versus DPP4 inhibitors when used in combination with metformin. METHODS: After searching for trials using combination therapy of metformin with DPP4 inhibitor or SU in PubMed, Cochrane Library, and Embase, one prospective observation study and 15 randomized controlled studies were selected. RESULTS: Regarding the primary analysis endpoint, there were no significant differences in the risk of all-cause mortality between SU and DPP4 inhibitors as an add-on therapy to metformin (random-effect relative risk [RR], 1.14; 95% confidence interval [CI], 0.98-1.33; p=0.811; I2=0%). Cardiovascular death was also similar between the two drug classes in the five studies which reported outcomes (random-effect RR, 1.03; 95% CI, 0.83-1.27; p=0.517; I2=0%). Furthermore, there were no significant differences in major adverse cardiac events (MACE), coronary heart disease, myocardial infarction, ischemic stroke and heart failure. However, there were less hypoglycemic events and weight gain in the DPP4 inhibitor group as compared with the SU group (random-effect RR, 3.79; 95% CI, 1.53-9.39; p<0.001; I2=98.2 and weighted mean difference, 1.68; 95% CI, 1.07-2.29; p<0.001; I2=94.7, respectively). CONCLUSION: As add-on therapy to metformin, there were no significant differences in all-cause mortality and cardiovascular mortality between DPP4 inhibitors and SUs.

Effects of Co-administration of Sulfonylureas and Antimicrobial Drugs on Hypoglycemia in Patients with Type 2 Diabetes Using a Case-Crossover Design.

OBJECTIVES: The purpose of this study was to investigate the effect of sulfonylureas (SUs) and antimicrobial co-administration on hypoglycemia in patients with type 2 diabetes mellitus (T2DM). METHODS: We conducted a case-crossover study using the Korean Health Insurance Review and Assessment Service-National Inpatient Sample database, using data from 2014 to 2016. Hospitalized adult patients with T2DM who were diagnosed with hypoglycemia and prescribed SUs for at least 120 days were included. Different risk ratings of severity of drug-drug interactions were considered, including "level X, D, or C" in Lexi-Interact online and "contraindicated, major, or moderate" in Micromedex. Exposure to antimicrobials in the 30-day period before the first hypoglycemia diagnosis was assessed. Two control periods (61-90 and 91-120 days) were matched before the diagnosis date. Conditional logistic regression analysis was conducted to compare the odds of antimicrobial exposure. RESULTS: A total of 9339 patients were included. The mean age of the patients was 71.3 ± 10.6 years, and 4818 (51.6%) were women. An increased risk of hypoglycemia was associated with co-administration of SUs and certain antimicrobials (adjusted odds ratio [aOR] 2.56, 95% confidence interval [CI] 2.34-2.80). The antimicrobial agents that were associated with an increased risk of hypoglycemia, when co-administered with SUs, were sulfonamides (aOR 2.99, 95% CI 1.99-4.52), fluoroquinolones (aOR 2.62, 95% CI 2.38-2.89), macrolides (aOR 2.48, 95% CI 1.88-3.27), and tetracyclines (aOR 1.56, 95% CI 1.05-2.33). CONCLUSIONS: Co-administration with SUs and certain antimicrobials increased the risk of hypoglycemia. Thus, clinically relevant interactions in patients concurrently using SUs and antimicrobials should be monitored, especially within 30 days after co-administration.

Sulfonylurea-Induced Hypoglycemia in a Patient With Cirrhosis.

Type 2 diabetes mellitus is highly prevalent among patients with cirrhosis. The pharmacological management of this disease in patients with chronic liver disease remains controversial, however. Insulin secretagogues such as sulfonylureas are associated with a high risk of hypoglycemia among diabetics. In patients with cirrhosis, this risk is more pronounced due to decreased hepatic clearance, concurrent alcoholism, hypoalbuminemia, and acute liver decompensation. In this case report, we present a case of severe refractory hypoglycemia secondary to glipizide in a patient with alcoholic cirrhosis. We believe that the use of sulfonylureas in this patient population should be contraindicated to avoid debilitating neurologic damage and death following hypoglycemia.

A randomized study on the usefulness of an electronic outpatient hypoglycemia risk calculator for clinicians of patients with diabetes in a safety-net institution.

Objective: Hypoglycemia (HG) occurs in up to 60% of patients with diabetes mellitus (DM) each year. We assessed a HG alert tool in an electronic health record system, and determined its effect on clinical practice and outcomes.Methods: The tool applied a statistical model, yielding patient-specific information about HG risk. We randomized outpatient primary-care providers (PCPs) to see or not see the alerts. Patients were assigned to study group according to the first PCP seen during four months. We assessed prescriptions, testing, and HG. Variables were compared by multinomial, logistic, or linear model. ClinicalTrials.gov ID: NCT04177147 (registered on 22 November 2019).Results: Patients (N = 3350) visited 123 intervention PCPs; 3395 patients visited 220 control PCPs. Intervention PCPs were shown 18,645 alerts (mean of 152 per PCP). Patients' mean age was 55 years, with 61% female, 49% black, and 49% Medicaid recipients. Mean baseline A1c and body mass index were similar between groups. During follow-up, the number of A1c and glucose tests, and number of new, refilled, changed, or discontinued insulin prescriptions, were highest for patients with highest risk. Per 100 patients on average, the intervention group had fewer sulfonylurea refills (6 vs. 8; p < .05) and outpatient encounters (470 vs. 502; p < .05), though the change in encounters was not significant. Frequency of HG events was unchanged.Conclusions: Informing PCPs about risk of HG led to fewer sulfonylurea refills and visits. Longer-term studies are needed to assess potential for long-term benefits.

Efficacy and Safety of Pioglitazone versus Glimepiride after Metformin and Alogliptin Combination Therapy: A Randomized, Open-Label, Multicenter, Parallel-Controlled Study.

BACKGROUND: There is limited information regarding the optimal third-line therapy for managing type 2 diabetes mellitus (T2DM) that is inadequately controlled using dual combination therapy. This study assessed the efficacy and safety of pioglitazone or glimepiride when added to metformin plus alogliptin treatment for T2DM. METHODS: This multicenter, randomized, active-controlled trial (ClinicalTrials.gov: NCT02426294) recruited 135 Korean patients with T2DM that was inadequately controlled using metformin plus alogliptin. The patients were then randomized to also receive pioglitazone (15 mg/day) or glimepiride (2 mg/day) for a 26-week period, with dose titration was permitted based on the investigator's judgement. RESULTS: Glycosylated hemoglobin levels exhibited similar significant decreases in both groups during the treatment period (pioglitazone: -0.81%, P<0.001; glimepiride: -1.05%, P<0.001). However, the pioglitazone-treated group exhibited significantly higher high density lipoprotein cholesterol levels (P<0.001) and significantly lower homeostatic model assessment of insulin resistance values (P<0.001). Relative to pioglitazone, adding glimepiride to metformin plus alogliptin markedly increased the risk of hypoglycemia (pioglitazone: 1/69 cases [1.45%], glimepiride: 14/66 cases [21.21%]; P<0.001). CONCLUSION: Among patients with T2DM inadequately controlled using metformin plus alogliptin, the addition of pioglitazone provided comparable glycemic control and various benefits (improvements in lipid profiles, insulin resistance, and hypoglycemia risk) relative to the addition of glimepiride.

Efficacy and Safety of Pioglitazone versus Glimepiride after Metformin and Alogliptin Combination Therapy: A Randomized, Open-Label, Multicenter, Parallel-Controlled Study

BACKGROUND: There is limited information regarding the optimal third-line therapy for managing type 2 diabetes mellitus (T2DM) that is inadequately controlled using dual combination therapy. This study assessed the efficacy and safety of pioglitazone or glimepiride when added to metformin plus alogliptin treatment for T2DM.METHODS: This multicenter, randomized, active-controlled trial (ClinicalTrials.gov: NCT02426294) recruited 135 Korean patients with T2DM that was inadequately controlled using metformin plus alogliptin. The patients were then randomized to also receive pioglitazone (15 mg/day) or glimepiride (2 mg/day) for a 26-week period, with dose titration was permitted based on the investigator's judgement.RESULTS: Glycosylated hemoglobin levels exhibited similar significant decreases in both groups during the treatment period (pioglitazone: −0.81%, P<0.001; glimepiride: −1.05%, P<0.001). However, the pioglitazone-treated group exhibited significantly higher high density lipoprotein cholesterol levels (P<0.001) and significantly lower homeostatic model assessment of insulin resistance values (P<0.001). Relative to pioglitazone, adding glimepiride to metformin plus alogliptin markedly increased the risk of hypoglycemia (pioglitazone: 1/69 cases [1.45%], glimepiride: 14/66 cases [21.21%]; P<0.001).CONCLUSION: Among patients with T2DM inadequately controlled using metformin plus alogliptin, the addition of pioglitazone provided comparable glycemic control and various benefits (improvements in lipid profiles, insulin resistance, and hypoglycemia risk) relative to the addition of glimepiride.

A comparison study on efficacy, insulin sensitivity and safety of Glimepiride/Metformin fixed dose combination versus glimepiride single therapy on type 2 diabetes mellitus patients with basal insulin therapy.

AIM: The aim of this study was to analyze the efficacy, insulin sensitivity and safety in the event of administering sulfonylurea-based drugs and metformin in combination with basal insulin. METHODS: A randomized, open-label, parallel, 16-week trial was conducted across four study centers. The 97 type 2 diabetic patients were selected and randomized into two groups, the insulin glargine plus fixed-dose combination glimepiride 1 mg and metformin 500 mg twice daily group (the G/M group) and the insulin glargine plus glimepiride 4 mg once daily group (the G group). The primary endpoint evaluated was change in HbA1c. The secondary endpoints evaluated were changes in fasting blood glucose (FPG), 2-h post prandial glucose (PPG 2 h), insulin, and C-peptide levels. RESULTS: The G/M group was found to have experienced a significantly greater decrease in HbA1c, as well as PPG 2 h compared to the G group. While no significant intergroup difference was found regarding FPG in the ITT, the G/M group in the PP set experienced a significantly greater decrease in FPG. CONCLUSION: Comparison of combined therapy consisting of either the G/M group or the G group indicated that both forms of therapy are relatively safe but that the former more effectively decreases blood glucose levels.

Additional Effect of Dietary Fiber in Patients with Type 2 Diabetes Mellitus Using Metformin and Sulfonylurea: An Open-Label, Pilot Trial.

BACKGROUND: Metformin, sulfonylurea, and dietary fiber are known to affect gut microbiota in patients with type 2 diabetes mellitus (T2DM). This open and single-arm pilot trial investigated the effects of the additional use of fiber on glycemic parameters, insulin, incretins, and microbiota in patients with T2DM who had been treated with metformin and sulfonylurea. METHODS: Participants took fiber for 4 weeks and stopped for the next 4 weeks. Glycemic parameters, insulin, incretins during mixed-meal tolerance test (MMTT), lipopolysaccharide (LPS) level, and fecal microbiota were analyzed at weeks 0, 4, and 8. The first tertile of difference in glucose area under the curve during MMTT between weeks 0 and 4 was defined as 'responders' and the third as 'nonresponders,' respectively. RESULTS: In all 10 participants, the peak incretin levels during MMTT were higher and LPS were lower at week 4 as compared with at baseline. While the insulin sensitivity of the 'responders' increased at week 4, that of the 'nonresponders' showed opposite results. However, the results were not statistically significant. In all participants, metabolically unfavorable microbiota decreased at week 4 and were restored at week 8. At baseline, metabolically hostile bacteria were more abundant in the 'nonresponders.' In 'responders,' Roseburia intestinalis increased at week 4. CONCLUSION: While dietary fiber did not induce additional changes in glycemic parameters, it showed a trend of improvement in insulin sensitivity in 'responders.' Even if patients are already receiving diabetes treatment, the additional administration of fiber can lead to additional benefits in the treatment of diabetes.

Hypoglycemia in People with Type 2 Diabetes and CKD.

BACKGROUND AND OBJECTIVES: Among people with diabetes mellitus, CKD may promote hypoglycemia through altered clearance of glucose-lowering medications, decreased kidney gluconeogenesis, and blunted counter-regulatory response. We conducted a prospective observational study of hypoglycemia among 105 individuals with type 2 diabetes treated with insulin or a sulfonylurea using continuous glucose monitors. DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS: We enrolled 81 participants with CKD, defined as eGFR<60 ml/min per 1.73 m2, and 24 control participants with eGFR≥60 ml/min per 1.73 m2 frequency-matched on age, duration of diabetes, hemoglobin A1c, and glucose-lowering medications. Each participant wore a continuous glucose monitor for two 6-day periods. We examined rates of sustained level 1 hypoglycemia (<70 mg/dl) and level 2 hypoglycemia (<54 mg/dl) among participants with CKD. We then tested differences compared with control participants as well as a second control population (n=73) using Poisson and linear regression, adjusting for age, sex, and race. RESULTS: Over 890 total days of continuous glucose monitoring, participants with CKD were observed to have 255 episodes of level 1 hypoglycemia, of which 68 episodes reached level 2 hypoglycemia. Median rate of hypoglycemic episodes was 5.3 (interquartile range, 0.0-11.7) per 30 days and mean time spent in hypoglycemia was 28 (SD 37) minutes per day. Hemoglobin A1c and the glucose management indicator were the main clinical correlates of time in hypoglycemia (adjusted differences 6 [95% confidence interval, 2 to 10] and 13 [95% confidence interval, 7 to 20] fewer minutes per day per 1% higher hemoglobin A1c or glucose management indicator, respectively). Compared with control populations, participants with CKD were not observed to have significant differences in time in hypoglycemia (adjusted differences 4 [95% confidence interval, -12 to 20] and -12 [95% confidence interval, -29 to 5] minutes per day). CONCLUSIONS: Among people with type 2 diabetes and moderate to severe CKD, hypoglycemia was common, particularly with tighter glycemic control, but not significantly different from groups with similar clinical characteristics and preserved eGFR.

Maturity Onset Diabetes of the Young: case report / Diabetes del adulto de inicio juvenil: reporte de un caso

Background: Maturity Onset Diabetes of the Young (MODY) is a type of diabetes that results from mutations in 13 known genes that play a role in the development and maturation of pancreatic beta cells. It represents 5% of all individuals diagnosed with diabetes before the age of 45 years and it is misdiagnosed as type 1 or type 2 diabetes in 80% of the cases. Clinical case: We present the case of a 21-year old female, initially diagnosed with type 1 diabetes when she was 19 years, and glycemic dyscontrol despite adequate use of long-acting insulin. She had family history of diabetes and persisting glycosuria. Due to high suspicions of MODY diabetes we requested an oral glucose tolerance test (basal 130 mg/dL, 2 hours post-glucose load 240 mg/dL) and serum concentrations of C-peptide (1.83 ng/mL) that confirmed our diagnosis. The patient improved after treatment with sulfonylurea with discontinuation of insulin treatment. Conclusion: Prompt identification of MODY allows patients to have effective and safe treatments and prevent the development of premature complications; in addition, its identification allows genetic counseling and can guide the management of other first-degree relatives who also suffer from it.

Introducción: la diabetes del adulto de inicio juvenil (MODY, por sus siglas en inglés: maturity onset diabetes of the young) es un tipo de diabetes que resulta de mutaciones en 13 genes conocidos que desempeñan un papel en el desarrollo y la maduración de las células beta pancreáticas. Representa el 5% de todas las personas diagnosticadas con diabetes antes de los 45 años y se diagnostica erróneamente como diabetes tipo 1 o tipo 2 hasta en el 80% de los casos. Caso clínico: presentamos el caso de una mujer de 21 años, inicialmente diagnosticada con diabetes tipo 1 a los 19 años y con descontrol glucémico a pesar del uso adecuado de insulina de acción prolongada. Tenía antecedentes familiares de diabetes y glucosuria persistente. Debido a la alta sospecha de diabetes MODY, solicitamos una prueba oral de tolerancia a la glucosa (basal 130 mg/dL y dos horas después de la carga de glucosa: 240 mg/dL) y de concentraciones séricas de péptido C (1.83 ng/mL), que confirmaron el diagnóstico. La paciente mejoró después del tratamiento con sulfonilurea y se logró la interrupción del tratamiento con insulina. Conclusiones: la identificación temprana de la diabetes tipo MODY permite a los pacientes tener tratamientos efectivos y seguros, y prevenir el desarrollo de complicaciones prematuras; además, su identificación permite el asesoramiento genético y puede orientar el manejo de otros parientes de primer grado que también la padecen.

Additional Effect of Dietary Fiber in Patients with Type 2 Diabetes Mellitus Using Metformin and Sulfonylurea: An Open-Label, Pilot Trial

BACKGROUND: Metformin, sulfonylurea, and dietary fiber are known to affect gut microbiota in patients with type 2 diabetes mellitus (T2DM). This open and single-arm pilot trial investigated the effects of the additional use of fiber on glycemic parameters, insulin, incretins, and microbiota in patients with T2DM who had been treated with metformin and sulfonylurea. METHODS: Participants took fiber for 4 weeks and stopped for the next 4 weeks. Glycemic parameters, insulin, incretins during mixed-meal tolerance test (MMTT), lipopolysaccharide (LPS) level, and fecal microbiota were analyzed at weeks 0, 4, and 8. The first tertile of difference in glucose area under the curve during MMTT between weeks 0 and 4 was defined as ‘responders’ and the third as ‘nonresponders,’ respectively. RESULTS: In all 10 participants, the peak incretin levels during MMTT were higher and LPS were lower at week 4 as compared with at baseline. While the insulin sensitivity of the ‘responders’ increased at week 4, that of the ‘nonresponders’ showed opposite results. However, the results were not statistically significant. In all participants, metabolically unfavorable microbiota decreased at week 4 and were restored at week 8. At baseline, metabolically hostile bacteria were more abundant in the ‘nonresponders.’ In ‘responders,’ Roseburia intestinalis increased at week 4. CONCLUSION: While dietary fiber did not induce additional changes in glycemic parameters, it showed a trend of improvement in insulin sensitivity in ‘responders.’ Even if patients are already receiving diabetes treatment, the additional administration of fiber can lead to additional benefits in the treatment of diabetes.

Evaluating associations between the benefits and risks of drug therapy in type 2 diabetes: a joint modeling approach.

OBJECTIVE: Precision medicine drug therapy seeks to maximize efficacy and minimize harm for individual patients. This will be difficult if drug response and side effects are positively associated, meaning that patients likely to respond best are at increased risk of side effects. We applied joint longitudinal-survival models to evaluate associations between drug response (longitudinal outcome) and the risk of side effects (survival outcome) for patients initiating type 2 diabetes therapy. STUDY DESIGN AND SETTING: Participants were randomized to metformin (MFN), sulfonylurea (SU), or thiazolidinedione (TZD) therapy in the A Diabetes Outcome Progression Trial (ADOPT) drug efficacy trial (n=4,351). Joint models were parameterized for 1) current HbA1c response (change from baseline in HbA1c) and 2) cumulative HbA1c response (total HbA1c change). RESULTS: With MFN, greater HbA1c response did not increase the risk of gastrointestinal events (HR per 1% absolute greater current response 0.82 [95% CI 0.67, 1.01]; HR per 1% higher cumulative response 0.90 [95% CI 0.81, 1.00]). With SU, greater current response was associated with an increased risk of hypoglycemia (HR 1.41 [95% CI 1.04, 1.91]). With TZD, greater response was associated with an increased risk of edema (current HR 1.45 [95% CI 1.05, 2.01]; cumulative 1.22 [95% CI 1.07, 1.38]) but not fracture. CONCLUSION: Joint modeling provides a useful framework to evaluate the association between response to a drug and the risk of developing side effects. There may be great potential for widespread application of joint modeling to evaluate the risks and benefits of both new and established medications.