Population-Based Study of Hypoglycemia in Patients with Type 1 Diabetes Mellitus Requiring Emergency Medical Services

ObjectiveTo report the population burden of hypo glycemia necessitating emergency medical services (EMS) and the long-term outcomes in patients with type 1 diabetes mellitus (T1DM) receiving different insulin treatments.MethodsWe retrieved all EMS calls because of hypoglycemia in patients with T1DM in Olmsted County, Minnesota, between January 1, 2003, and December 31, 2009, and reviewed the related medical records.ResultsDuring the 7-year study period, 531 EMS calls were made involving 208 patients with T1DM (112 men, 96 women; mean age 47 ± 13 years). Of the 208 patients, 137 (66%) were receiving multiple daily insulin (MDI) injections, 50 (24%) were receiving continuous sub cutaneous insulin infusion, 15 (7%) were receiving simple insulin (SI), 4 (2%) were treated with metformin + MDI, and 2 (1%) were not receiving treatment for diabetes (after pancreas transplantation). The last 2 groups were excluded from further analysis because of small sample size. The remaining 3 treatment groups differed by age (P < .02), with the oldest patients receiving SI. Repeated calls, emergency department transportation (EDT), and hospitalization had a 33%, 49%, and 18% frequency, respectively, and did not differ among the treatment groups. In a multivariate model, mortality was significantly associated with treatment type (the SI group had a higher risk for mortality than did the MDI group [P = .03] after exclusion of 27 patients who changed treatment during follow-up), age (P < .0001), and EDT (P = .04).ConclusionThe population burden of EMS-requiring hypoglycemia in patients with T1DM is high. Medical resource utilization was similar among the 3 treatment groups. Mortality was higher in the SI group (limited by small sample size) and among patients requiring EDT and increased with advancing age. Further research could be directed toward understanding the effect of expert evaluation of high-risk patients on long-term outcomes. (EndocrPract. 2012;18:834-841)     

Reduced Risk of Hypoglycemia with Insulin Degludec Versus Insulin Glargine in Patients with Type 2 Diabetes Requiring High Doses of Basal Insulin: A Meta-Analysis of 5 Randomized Begin Trials

ObjectiveThis meta-analysis of 5 trials from the Phase 3a insulin degludec (IDeg) clinical trial program evaluated the risk of hypoglycemia in a subset of subjects with type 2 diabetes (T2D) who required high basal insulin doses at the end of the trials.MethodsThis meta-analysis compared glycated hemoglobin (HbA_1c), fasting plasma glucose (FPG), basal insulin dose, body weight, and rates of overall and nocturnal confirmed hypoglycemia in a pooled population of T2D subjects using > 60 U basal insulin at trial completion. Five Phase 3a, open-label, randomized, treat-to-target, confirmatory 26-or 52-week trials with IDeg (n = 2,262) versus insulin glargine (IGlar) (n = 1,110) administered once daily were included. Overall confirmed hypoglycemia was defined as self-measured blood glucose < 56 mg/dL or any episode requiring assistance; nocturnal confirmed hypoglycemia had an onset between 00:01 and 05:59 am.ResultsMore than one-third of IDeg-(35%) and IGlar-(34%) treated T2D subjects required > 60 U of basal insulin daily at the ends of the trial. Patients achieved similar mean HbA_1c values (estimated treatment difference [ETD] IDeg - IGlar: 0.05%, P = .44) while mean FPG values were lower with IDeg than IGlar (ETD: - 5.9 mg/ dL, P = .04) at end-of-trial. There was a 21% lower rate of overall confirmed hypoglycemic episodes for IDeg (estimated rate ratio [RR] IDeg/IGlar: 0.79, P = .02) and a 52% lower rate of nocturnal confirmed hypoglycemic episodes for IDeg (RR: 0.48, P < .01).ConclusionIn this post hoc meta-analysis, more than 30% of subjects with T2D required > 60 U/day of basal insulin at the end of the trials. In these individuals, IDeg achieves similar HbA_1c reduction with significantly less overall and nocturnal confirmed hypoglycemia compared with IGlar. (Endocr Pract. 2014;20:285-292)     

Identifying Risk Factors for Severe Hypoglycemia in Hospitalized Patients with Diabetes

ObjectiveSome of the deleterious effects of hypoglycemia in hospitalized patients include increased rates of mortality and longer length of stay. Our primary objective was to identify the risk factors associated with severe hypoglycemia to identify those patients at highest risk.MethodsThe medical records of 5,026 patients with diabetes mellitus (DM) admitted in 2010 were reviewed to identify those patients that developed severe hypoglycemia (blood glucose [BG] < 40 mg/dL). We performed c2 tests to assess statistical significance. Adjusted logical regression was used to determine the risk factors for hypoglycemia in the hospital.ResultsOut of 5,026 DM patients included in our review, 81 experienced severe hypoglycemia (1.6%). Statistically higher proportions of chronic kidney disease (CKD; 69.1% vs. 46.9%, P < .001), congestive heart failure (CHF; 48.1% vs. 28.5%, P < .001), sepsis (49.4% vs. 12.5%, P < .001), insulin use (45.7% vs. 26.04%, P = .000), type 1 DM (21% vs. 5.1%, P = .000), and cirrhosis (14.8% vs. 7.2%, P = .009) were seen in the severe hypoglycemic group compared to the nonsevere hypoglycemic group. Overall, 84% of patients who experienced an episode of severe hypoglycemia in the hospital (BG < 40 mg/dL) had a previous episode of hypoglycemia (BG < 70 mg/dL). The odds ratios (ORs) for type 1 DM, sepsis, previous hypoglycemia, and insulin use were 3.43 (95% confidence interval [CI] 1.81, 6.49), 2.64 (95% CI 1.6, 4.35), 46.1 (95% CI 24.76, 85.74), and 1.66 (95% CI 1.02, 2.69), respectively.ConclusionPrior episodes of hypoglycemia in the hospital, the presence of type 1 DM, insulin use, and sepsis were identified as independent risk factors for the development of severe hypoglycemia in the hospital. (Endocr Pract. 2014;20:1051-1056)     

Impaired Awareness of Hypoglycemia Continues to be a Risk Factor for Severe Hypoglycemia Despite the Use of Continuous Glucose Monitoring System in Type 1 Diabetes

Objective: Impaired awareness of hypoglycemia (IAH) is a risk factor for severe hypoglycemia in patients with type 1 diabetes (T1D) not using a continuous glucose monitoring (CGM) system. The current study investigated the prevalence of IAH and its relationship with severe hypoglycemia in T1D patients using CGM systems.Methods: This cross-sectional observational study enrolled 135 patients with T1D and ongoing real-time CGM use. A survey was conducted to assess hypoglycemia awareness with the Gold, Clarke, and Pedersen-Bjergaard questionnaires and the 6-month history of severe hypoglycemia. Other diabetes histories and the CGM glucose data were collected.Results: The Gold, Clarke, and Pedersen-Bjergaard questionnaires demonstrated the overall prevalence of IAH/abnormal awareness to be 33.3%, 43.7%, and 77.0%, respectively. Participant age and duration of T1D were consistently related to IAH or hypoglycemia unawareness with all three questionnaires (P<.05). Amongst the patients using CGM for >6 months, 24.5% were found to have at least one episode of severe hypoglycemia in the preceding 6 months. IAH identified by the Gold and Clarke questionnaires and hypoglycemia unawareness identified by the Pedersen-Bjergaard questionnaire were related to 6-, 4.63-, and 5.83-fold increased risk of severe hypoglycemia (P = .001, .004, and .013), respectively. IAH identified by the Gold/Clarke questionnaires was associated with a longer duration of CGM glucose <54 mg/dL and higher glucose coefficients of variation (P<.05).Conclusion: IAH is highly prevalent and related to a higher risk for severe hypoglycemia in T1D patients using CGM.Abbreviations: CGM = continuous glucose monitoring; CI = confidence interval; HAAF = hypoglycemia-associated autonomic failure; HbA1c = hemoglobin A1C; IAH = impaired awareness of hypoglycemia; T1D = type 1 diabetes     

Efficacy and Safety of Insulin Lispro in Obese Patients with Type 2 Diabetes: A Retrospective Meta-Analysis of 7 Randomized Controlled Trials

ObjectiveTo evaluate the efficacy and safety of insulin lispro in the treatment of patients with type 2 diabetes (T2DM) who had a body mass index (BMI) ≥ 30 kg/m² (obese) compared with patients with BMIs < 30 kg/m² (nonobese).MethodsA retrospective analysis of predefined endpoints from 7 randomized clinical trials of T2DM patients treated with insulin lispro was performed. The primary efficacy measure was to assess the noninferiority of insulin lispro in obese patients versus nonobese patients as measured by the change in hemoglobin A1C (HbA_1c) from baseline to Month 3 (n = 1,518), using a noninferiority margin of 0.4%. The secondary measures included overall hypoglycemia incidence and event rates and relative change in body weight.ResultsMean changes in HbA_1c from baseline (9.06% for obese and 8.92% for nonobese) to Month 3 were similar for obese patients (–1.03%) and nonobese (–1.02%), with a least squares (LS) mean difference (95% confidence interval [CI]) of –0.05% (–0.17%, 0.07%; P = .384). The overall incidence of hypoglycemia (53% vs. 63%; P < .001) and rate of hypoglycemia (0.93 vs. 1.76 events per 30 days; P < .001) was significantly lower in obese patients compared with nonobese patients. The 2 BMI cohorts did not demonstrate a significant difference in mean percent changes in body weights (LS mean difference = 0.4% [–0.2%, 0.9%]; P = .202).ConclusionObese patients with T2DM treated with insulin lispro were able to achieve the same level of glycemic control as their nonobese counterparts, with some evidence supporting a reduced risk of hypoglycemia. (Endocr Pract. 2014;20:389-398)     

Adding Rapid-Acting Insulin or Glp-1 Receptor Agonist to Basal Insulin: Outcomes in A Community Setting

ObjectiveTo evaluate real-world outcomes in patients with type 2 diabetes mellitus (T2DM) receiving basal insulin who initiate add-on therapy with a rapid-acting insulin (RAI) or a glucagon-like peptide 1 (GLP-1) receptor agonist.MethodsData were extracted retrospectively from a U.S. health claims database. Adults with T2DM on basal insulin who added an RAI (basal + RAI) or GLP-1 receptor agonist (basal + GLP-1) were included. Propensity score matching (with a 1 up to 3 ratio) was used to control for differences in baseline demographics, clinical characteristics, and health resource utilization. Endpoints included prevalence of hypoglycemia, pancreatic events, all-cause and diabetes-related resource utilization, and costs at 1-year follow-up.ResultsOverall, 6,718 matched patients were included: 5,013 basal + RAI and 1,705 basal + GLP1. Patients in both groups experienced a similar proportion of any hypoglycemic event (P = .4079). Hypoglycemic events leading to hospitalization were higher in the basal + RAI cohort (2.7% vs. 1.8%; P = .0444). The basal + GLP-1 cohort experienced fewer all-cause (13.55% vs. 18.61%; P < .0001) and diabetes-related hospitalizations (11.79% vs. 15.68%; P < .0001). The basal + GLP-1 cohort had lower total all-cause health care costs ($18,413 vs. $20,821; P = .0002) but similar diabetes-related costs ($9,134 vs. $8,985; P < .0001) compared with the basal + RAI cohort.ConclusionsAdd-on therapy with a GLP-1 receptor agonist in T2DM patients receiving basal insulin was associated with fewer hospitalizations and lower total all-cause costs compared with add-on therapy using an RAI and could be considered as an alternative to an RAI in certain patients with T2DM who do not achieve effective glycemic control with basal insulin. (Endocr Pract. 2015; 21:68-76)     

子宫内膜容受性检测技术在反复种植失败患者冻融胚胎移植中的应用价值及其临床妊娠的影响因素分析

摘要 目的：探讨子宫内膜容受性检测（ERT）技术在反复种植失败患者冻融胚胎移植（FET）中的应用价值,并分析其临床妊娠的影响因素。方法：回顾性分析2019年10月~2022年4月期间海南省妇女儿童医学中心收治的150例反复种植失败患者的临床资料,根据是否接受ERT技术分为ERT组（n=78,接受ERT技术）和无ERT组（n=72,未接受ERT技术）。按照反复种植失败患者是否临床妊娠分为临床妊娠组和未临床妊娠组。采用单因素和多因素Logistic回归模型分析临床妊娠的影响因素。结果：两组异位妊娠率组间对比未见统计学差异（P>0.05）。ERT组临床妊娠率、活产率高于无ERT组,移植日内膜厚度大于无ERT组,移植胚胎数少于无ERT组,流产率低于无ERT组（P<0.05）。所有患者按照是否临床妊娠分为临床妊娠组（n=85）和未临床妊娠组（n=65）。单因素分析结果显示：临床妊娠与年龄、移植胚胎类别、移植胚胎数量、总周期数、FSH、子宫内膜厚度、子宫内膜类型有关（P<0.05）,而与体质量指数（BMI）、不孕年限、不孕类型、胚胎冷冻保存时间无关（P>0.05）。多因素Logistic回归分析结果显示：年龄偏大、FSH偏高是临床妊娠的危险因素,而移植胚胎类别为囊胚、移植胚胎数量偏多是临床妊娠的保护因素（P<0.05）。结论：ERT技术用于反复种植失败患者FET中,可有效改善患者的临床妊娠。年龄、FSH、移植胚胎类别、移植胚胎数量是临床妊娠的影响因素。     

Diabetes Duration and the Efficacy and Safety of Insulin Glargine Versus Comparator Treatment in Patients with Type 2 Diabetes Mellitus

ObjectiveTo evaluate the effect of diabetes duration on efficacy and safety in patients with type 2 diabetes mellitus (T2DM) using insulin glargine versus comparator (oral antidiabetic drugs [OADs], dietary changes, or other insulins).MethodsData were pooled from randomized controlled clinical trials conducted in adults with T2DM with at least 24-week treatment with insulin glargine or a comparator, where predefined insulin titration algorithms were utilized to achieve fasting plasma glucose (FPG) concentrations of ≤ 100 mg/dL. Glycated hemoglobin A1C (A1C), FPG, and insulin dose and safety (hypoglycemia) outcomes were analyzed.ResultsNine studies were included in the analysis of 2,930 patients. Patients with shorter duration of diabetes were more likely to have greater reductions in A1C compared with those who had longer-duration disease (P < .0001). Disease duration did not affect change in FPG concentrations (P = .9017), but lower weight-adjusted insulin dose was correlated with longer-duration disease (P < .0001). Patients with longer-duration diabetes had increased risks of symptomatic hypoglycemia, confirmed hypoglycemia (self-monitored blood glucose < 50 mg/dL and < 70 mg/dL), and nocturnal hypoglycemia (all P < .001). No significant relationship was found between severe hypoglycemia and duration of diabetes. However, treatment with insulin glargine lowered A1C values more effectively than comparator treatments with fewer hypoglycemic episodes.ConclusionPatients with shorter-duration T2DM better achieved target A1C levels and had less hypoglycemia than those with longer disease duration. Insulin glargine was associated with reduced A1C and fewer hypoglycemic events than comparators, regardless of disease duration. (Endocr Pract. 2014;20:120-128)     

Association of Glycemic Control Parameters with Clinical Outcomes in Chronic Critical Illness

ObjectiveChronic critical illness (CCI) is a term used to designate patients requiring prolonged mechanical ventilation and tracheostomy with associated poor outcomes. The present study assessed the impact of glycemic parameters on outcomes in a CCI population.MethodsA retrospective case series was performed including 148 patients in The Mount Sinai Hospital Respiratory Care Unit (2009-2010). Utilizing a semi-parametric mixture model, trajectories for the daily mean blood glucose (BG), BG range, and hypoglycemia rate over time identified low- (n = 87) and high-risk (n = 61) hyperglycemia groups and low- (n = 90) and high-risk (n = 58) hypoglycemia groups. The cohort was also classified into diabetes (DM, n = 48), stress hyperglycemia (SH, n = 85), and normal glucose (n = 15) groups.ResultsHospital- (28% vs. 13%, P = .0199) and 1-year mortality (66% vs. 46%, P = .0185) rates were significantly greater in the high- versus low-risk hyperglycemia groups, respectively. The hypoglycemia rate (< 70 mg/dL) was lower among ventilator-liberated patients compared to those who failed to liberate (0.092 vs. 0.130, P < .0001). In the SH group, both hospital mortality (high-risk hyperglycemia 48% and low-risk hyperglycemia 15%, P = .0013) and 1-year mortality (high-risk 74% and low-risk 50%, P = .0482) remained significantly different, while no significant difference in the diabetes group was observed. There were lower hypoglycemia rates with SH compared to diabetes (< 70 mg/dL: 0.086 vs. 0.182, P < .0001; < 40 mg/dL: 0.012 vs. 0.022, P = .0118, respectively).ConclusionTighter glycemic control was associated with improved outcomes in CCI patients with SH but not in CCI patients with diabetes. Confirmation of these findings may lead to stratified glycemic control protocols in CCI patients based on the presence or absence of diabetes. (Endocr Pract. 2014;20:884-893)     

Liraglutide Achieves A1C Targets More often than Sitagliptin or Exenatide when Added to Metformin in Patients with Type 2 Diabetes and a Baseline A1C <8.0%

ObjectiveCompare the safety and efficacy of liraglutide to that of sitagliptin or exenatide as add-on to metformin in patients with type 2 diabetes (T2D) and glycated hemoglobin (A1C) <8.0%.MethodsPost hoc analysis of 26-week data from liraglutide 1.8 mg once daily (OD) versus exenatide 10 μg twice daily (LEAD-6) and liraglutide 1.8 mg OD versus sitagliptin 100 mg OD (LIRA-DPP-4); only patients treated as add-on to metformin with baseline A1C <8.0% were included. Efficacy analysis was performed on the intention-to-treat population with missing values imputed by last observation carried forward.ResultsMore patients achieved A1C targets (<7.0% and ≤6.5%) with liraglutide versus exenatide or sitagliptin; the difference was greatest for A1C ≤6.5% (LEAD-6: 65% versus 35%; odds ratio [OR]=3.37, 95% confidence interval [CI]: 1.31-8.63; P = .01 or LIRA-DPP-4: 53% versus 19%; OR = 4.78, 95% CI 2.10 to 10.87; P = .0002). Significantly more patients achieved a composite endpoint of A1C <7.0% with no weight gain or hypoglycemia with liraglutide compared with exenatide (78% versus 42%; OR = 4.99, 95% CI: 1.77 to 14.04; P = .0023) or sitagliptin (61% versus 21%; OR = 5.95, 95% CI: 2.66 to 13.29; P<.0001). All treatments were well tolerated, there was no major hypoglycemia and few patients (8 to 10%) experienced minor hypoglycemia.ConclusionWhen added to metformin in patients with an A1C <8.0%, more patients using liraglutide 1.8 mg reached A1C targets than with exenatide or sitagliptin. Sitagliptin had particularly low efficacy in this analysis. These data support the use of liraglutide 1.8 mg as a safe and effective alternative to sitagliptin or exenatide following metformin failure in patients with an A1C <8.0%. (Endocr Pract. 2013;19:64-72)     

Correlation of Body Mass Index and Age with Osteoporosis Probability in Patients with Primary Hyperparathyroidism

ObjectiveCurrently, there are limited markers to predict the osteoporosis probability in patients with primary hyperparathyroidism. We studied the relationship between various parameters and results of DXAs at various skeletal sites.MethodsRetrospective review of data for 218 patients with primary hyperparathyroidism was performed. Age, BMI, bone mineral density, serum total calcium, ionized calcium, intact parathyroid hormone, albumin, alkaline phosphatase, phosphate, 25-hydroxy vitamin D, 1,25-dihydroxy vitamin D, 24-hour urinary calcium levels and parathyroid tumor weight were analyzed. Two different statistical models- linear regression and multivariate logistic regression were performed.ResultsAt the lumbar spine, with the linear model, BMI (P < .001), alkaline phosphatase (P < .001), and ionized calcium (P < .001) significantly correlated with T scores; whereas with the logistic model, BMI was the only variable predicting osteoporosis probability.At the femoral neck, BMI (P < .022), 25-hydroxy vitamin D (P < .001), 1,25-dihydroxy vitamin D (P < .034) correlated with T scores; whereas both BMI (P < .029) and age (P < .051) were the significant variables that predicted osteoporosis.At the total hip, BMI (P < .001) and age (P < .001) correlated with T scores; whereas with the logistic model, only BMI (P < .016) predicted osteoporosis. At the forearm, a model could not be generated due to limited number.ConclusionIn patients with primary hyperparathyroidism, BMI strongly correlated with T scores and probability of osteoporosis.     

Feasibility,Acceptability, and Preliminary Efficacy of an Intensive Clinic-Based Intervention for Children With Poorly Controlled Type 1 Diabetes

ObjectiveTo evaluate the feasibility, acceptability, and preliminary efficacy of a team-based intervention for youth with type 1 diabetes (T1D) with suboptimal glycemia, as detected based on the measurement of hemoglobin A1C (HbA1C).MethodsForty participants with T1D for >1 year and an HbA1C level of ≥9.5% (80 mmol/mol) enrolled for a multidisciplinary intervention that included pediatric endocrinologists, pediatric psychologists, and a certified diabetes care and education specialist (CDCES). The CDCES-integrated medical management, while reinforcing physical, emotional, and behavioral health, connected with families to set and monitor goals and reviewed medication adjustments. The feasibility was assessed based on enrollment targets; acceptability based on retention rates; and preliminary efficacy based on changes in HbA1C levels, quality of life, diabetes-related strengths and resilience, hospital admissions, emergency room visits, and missed school days.ResultsOf 43 patients and families approached, 40 agreed to participate, 36 completed the 4-month intervention, and 31 completed full 8 months of follow-up data collection. The CDCES coach averaged 6.8 contacts per participant during the 8-month study period. The HbA1C level reduced significantly from baseline to 4 months (12.1% ± 1.6% to 11.0% ± 1.9%, P = .001) and was sustained at 8 months (10.7% ± 1.9%, P < .001). The participants reported significant increases in diabetes-specific quality of life (P < .05) and diabetes-related strength and resilience (P = .003). The missed school days reduced from 7.23 ± 7.5 days to 1.55 ± 1.9 days (P < .001), and the diabetes-related hospitalizations decreased from 0.4 ± 0.6 to 0.1 ± 0.3 (P = .009).ConclusionPreliminary data suggest that a multidisciplinary intervention leveraging a team-based approach with a physician, psychologist, and CDCES can support improvements in glycemic control and psychosocial outcomes among youth with T1D with an HbA1C level above the target.     

Risk for Coexistent Autoimmune Diseases in Familial and Sporadic Type 1 Diabetes is Related to Age at Diabetes Onset

ObjectiveType 1 diabetes (T1D) is frequently associated with other autoimmune diseases (AIDs). Although most of T1D patients are sporadic cases (S-T1D), 10% to 15% have a familial form (F-T1D) involving 2 or more first-degree relatives. This study evaluated the effect of T1D family aggregation and age onset on AIDs occurrence.MethodsIn this observational, cross-sectional, case-control, single center study, we enrolled 115 F-T1D and 115 S-T1D patients matched for gender, age, T1D age onset, and duration. With respect to T1D age onset (before or after 18 years), both groups were further subdivided into young- or adult-onset F-T1D and young- or adult-onset S-T1D. The presence of organ-specific antibodies and/or overt AIDs was evaluated.ResultsThe F-T1D group had a higher percentage of AIDs (29.8% vs 18.4%, P = .04) and a significant earlier onset of AIDs at Cox regression analysis (P = .04) than the S-T1D group. Based on multivariate analysis, the adult-onset F-T1D subgroup had the highest prevalence of both additional organ-specific antibodies (60.5%) and overt AIDs (34.9%), whereas the adult S-T1D subgroup was the least frequently involved (29.1% and 12.7%, respectively). In F-T1D patients, offsprings develop T1D and AIDs earlier than their parents do.ConclusionsIn T1D patients, familial aggregation and adult-onset of T1D increase the risk for coexistent AIDs. These clinical predictors could guide clinicians to address T1D patients for the screening of T1D-related AIDs.     

Economic and Clinical Impact of Inpatient Diabetic Hypoglycemia

ObjectiveTo assess the clinical and economic impact of hypoglycemia that develops during hospitalization of patients with diabetes.MethodsIn this retrospective cohort study, data from 70 hospitals were used to identify the first inpatient encounter for adult patients with diabetes. Patients were included if all blood glucose measurements were 70 mg/dL or higher during the first 24 hours and their primary discharge diagnosis was for a condition other than hypoglycemia. Those who developed laboratory evidence of hypoglycemia (blood glucose < 70 mg/dL after 24 hours) were compared with patients whose blood glucose values were all 70 mg/dL or higher. An alternative definition of hypoglycemia (blood glucose < 50 mg/dL after 24 hours) was also evaluated. We adjusted for potential confounders with multivariate models.ResultsHypoglycemia had an adverse effect on all outcomes among more than 100 000 diabetic patients. After adjustment, patients with diabetes who developed hypoglycemia had higher charges (38.9%), longer lengths of stay (3.0 days), higher mortality (odds ratio, 1.07; 95% confidence interval, 1.02-1.11), and higher odds of being discharged to a skilled nursing facility (odds ratio, 1.58; 95% confidence interval, 1.48-1.69) than diabetic patients without hypoglycemia (P < .01 for all). In all cases, using the lower threshold (< 50 mg/dL) to define hypoglycemia resulted in similar findings with a larger magnitude of differences.ConclusionsAlthough a direct causal relationship cannot be inferred, these study findings suggest the importance of carefully maintaining euglycemia during hospitalizations. Whether the observed worse outcomes were due to hypoglycemia itself or whether they were a marker of worse outcomes due to other causes requires further research. (Endocr Pract. 2009;15:302-312)     

The Added and Interpretative Value of CGM-Derived Parameters in Type 1 Diabetes Depends on the Level of Glycemic Control

ObjectiveIn type 1 diabetes mellitus (T1DM) management, continuous glucose monitoring (CGM)-derived parameters can provide additional insights, with time in range (TIR) and other parameters reflecting glycemic control and variability being put forward. This study aimed to examine the added and interpretative value of the CGM-derived indices TIR and coefficient of variation (CV%) in T1DM patients stratified according to their level of glycemic control by means of HbA1C.MethodsT1DM patients with a minimum disease duration of 10 years and without known macrovascular disease were enrolled. Patients were equipped with a blinded CGM device for 7 days. TIR and time spent in hypoglycemia and hyperglycemia were determined, and CV% was used as a parameter for glycemic variability. Pearson (r) and Spearman correlations (r_s) and a regression analysis were used to examine associations.ResultsNinety-five patients (age: 45 ± 10 years; HbA1C level: 7.7% ± 0.8% [61 ± 7 mmol/mol]) were included (mean blood glucose [MBG]: 159 ± 31 mg/dL; TIR: 55.8% ± 14.9%; CV%: 43.5% ± 7.8%) and labeled as having good (HbA1C level ≤7% [≤53 mmol/mol]; n = 20), moderate (7%-8%; n = 44), or poor (>8% [>64 mmol/mol]; n = 31) glycemic control. HbA1C was significantly associated with MBG (r_s = 0.48, P < .001) and time spent in hyperglycemia (total: r_s = 0.52; level 2: r = 0.46; P < .001) but not with time spent in hypoglycemia and CV%, even after an analysis of the HbA1C subgroups. Similarly, TIR was negatively associated with HbA1C (r = −0.53; P < .001), MBG (r_s = −0.81; P < .001), and time spent in hyperglycemia (total: r_s = −0.90; level 2: r_s = −0.84; P < .001) but not with time in hypoglycemia. The subgroup analyses, however, showed that TIR was associated with shorter time spent in level-2 hypoglycemia in patients with good (r_s = −0.60; P = .007) and moderate (r_s = −0.25; P = .047) glycemic control. In contrast, CV% was strongly positively associated with time in hypoglycemia (total: r_s = 0.78; level 2: r_s = 0.76; P < .001) but not with TIR or time in hyperglycemia in the entire cohort, although the subgroup analyses showed that TIR was negatively associated with CV% in patients with good glycemic control (r = −0.81, P < .001) and positively associated in patients with poor glycemic control (r = +0.47; P < .01).ConclusionThe CGM-derived metrics TIR and CV% are related to clinically important situations, TIR being strongly dependent on hyperglycemia and CV% being reflective of hypoglycemic risk. However, the interpretation and applicability of TIR and CV% and their relationship depends on the level of glycemic control of the individual patient, with CV% generally adding less clinically relevant information in those with poor control. This illustrates the need for further research and evaluation of composite measures of glycemic control in T1DM.     

Improved Glycemic Control with Insulin Glargine Versus Pioglitazone as Add-On Therapy to Sulfonylurea or Metformin in Patients with Uncontrolled Type 2 Diabetes Mellitus

ObjectiveTo compare glycemic control with add-on insulin glargine versus pioglitazone treatment in patients with type 2 diabetes.MethodsThis 48-week, multicenter, parallel-group, open-label study randomized 389 adults with poorly controlled type 2 diabetes (glycated hemoglobin A1c [A1C], 8.0% to 12.0%), despite ≥ 3 months of sulfonylurea or metformin monotherapy, to receive add-on therapy with insulin glargine or pioglitazone. Outcomes included A1C change from baseline to end point (primary), percentage of patients achieving A1C levels ≤ 7.0%, and changes from baseline in fasting plasma glucose, body mass index, weight, and serum lipids. The safety analysis included incidence of adverse events and rates of hypoglycemia.ResultsAt end point, insulin glargine yielded a significantly greater reduction in A1C in comparison with pioglitazone (-2.48% versus -1.86%, respectively; 95% confidence interval, -0.93 to -0.31; P = .0001, 48-week modified intent-to-treat population). Insulin glargine also yielded significantly greater reductions in fasting plasma glucose at all time points (end point difference, -34.9 mg/ dL; 95% confidence interval, -47.6 to -22.2; P < .0001). In comparison with pioglitazone, insulin glargine resulted in a lower overall incidence of possibly related treatmentemergent adverse events (12.0% versus 20.7%) and fewer study discontinuations (2.2% versus 9.1%), but a higher rate (per patient-year) of confirmed clinically relevant hypoglycemic episodes (blood glucose < 70 mg/dL and all severe hypoglycemia) (4.97 versus 1.04; P <.0001) and severe hypoglycemia (0.07 versus 0.01; P = .0309). Weight and body mass index changes were similar between the 2 treatment groups.ConclusionThe addition of insulin glargine early in the diabetes treatment paradigm in patients for whom sulfonylurea or metformin monotherapy had failed resulted in significantly greater improvements in glycemic control in comparison with the addition of pioglitazone. Although severe hypoglycemia was more frequent in patients with insulin glargine therapy, hypoglycemic events occurred in < 5% of patients in the insulin glargine treatment group. (Endocr Pract. 2010;16:588-599)     

The Emerging Role Of Adjunctive Noninsulin Antihyperglycemic Therapy In The Management Of Type 1 Diabetes

Objective: Review available data on adjunctive therapies for type 1 diabetes (T1D), with a special focus on newer antihyperglycemic agents.Methods: Published data on hypoglycemia, obesity, mortality, and goal attainment in T1D were reviewed to determine unmet therapeutic needs. PubMed databases and abstracts from recent diabetes meetings were searched using the term “type 1 diabetes” and the available and investigational sodium-glucose cotransporter (SGLT) inhibitors, glucagon-like peptide 1 (GLP-1) receptor agonists, dipeptidyl peptidase 4 inhibitors, and metformin.Results: The majority of patients with T1D do not meet glycated hemoglobin (A1C) goals established by major diabetes organizations. Hypoglycemia risks and a rising incidence of obesity and metabolic syndrome featured in the T1D population limit optimal use of intensive insulin therapy. Noninsulin antihyperglycemic agents may enable T1D patients to achieve target A1C levels using lower insulin doses, which may reduce the risk of hypoglycemia. In pilot studies, the SGLT2 inhibitor dapagliflozin and the GLP-1 receptor agonist liraglutide reduced blood glucose, weight, and insulin dose in patients with T1D. Phase 2 studies with the SGLT2 inhibitor empagliflozin and the dual SGLT1 and SGLT2 inhibitor sotagliflozin, which acts in the gut and the kidney, have demonstrated reductions in A1C, weight, and glucose variability without an increased incidence of hypoglycemia.Conclusion: Newer antihyperglycemic agents, particularly GLP-1 agonists, SGLT2 inhibitors, and dual SGLT1 and SGLT2 inhibitors, show promise as adjunctive treatment for T1D that may help patients achieve better glucose control without weight gain or increased hypoglycemia.Abbreviations:A1C = glycated hemoglobinBMI = body mass indexCI = confidence intervalDKA = diabetic ketoacidosisDPP-4 = dipeptidyl peptidase 4GLP-1 = glucagonlike peptide 1PYY = polypeptide tyrosine tyrosineSGLT = sodium-glucose cotransporterSGLT1 = sodium-glucose cotransporter 1SGLT2 = sodium-glucose cotransporter 2T1D = type 1 diabetesT2D = type 2 diabetesTDD = total daily dosage