Differences in Achieving Hba1C Goals Among Patients Seen by Endocrinologists and Primary Care Providers

Objective: This study evaluated whether there is a difference in the proportion of patients with type 2 diabetes who achieve a hemoglobin A1c (HbA1c) <7% within one year following treatment by an endocrinologist or primary care physician (PCP).Methods: We conducted a retrospective, propensity-matched study of patients with type 2 diabetes that were not optimally controlled and seen within our health system from 2007–2016. We assessed differences in short term health outcomes for patients following an endocrinologist visit compared to a PCP visit.Results: Patients seen by endocrinologists obtained HbA1c control at a faster rate (hazard ratio = 1.226; 95% confidence interval = 1.01 to 1.488) than those seen by a PCP. Furthermore, 34.5% and 29.5% of those treated by endocrinologists and PCPs, respectively, obtained HbA1c control by one year. Endocrinologists were more likely to prescribe a new medication class within 90 days than PCPs (14.1% versus 10.3%, respectively, P = .043). There was no difference in the risk of hospitalization between groups; 24.4% and 24.1% of those treated by endocrinologists and PCPs, respectively, were hospitalized within one year.Conclusion: Patients treated by endocrinology specialists were more likely to achieve a target HbA1c of <7% (53 mmol/mol) than those treated by PCPs in our health-care system. The performance difference may be partially explained by a higher rate of adding new classes of diabetes medications to the patient's pharmacologic regimens within 90 days by endocrinologists compared with PCPs. The long-term impact of these differences is unknown but has the potential to have an unfavorable impact on the health of the population.Abbreviations: ACP = American College of Physicians; CI = confidence interval; DUHS = Duke University Health System; HbA1c = hemoglobin A1c; HR = hazard ratio; PCP = primary care physician; SMD = standard mean difference     

Endo Echo Improves Primary Care Provider And Community Health Worker Self-Efficacy In Complex Diabetes Management In Medically Underserved Communities

Objective: To determine whether participation in a multidisciplinary telementorship model of healthcare delivery improves primary care provider (PCP) and community health worker (CHW) confidence in managing patients with complex diabetes in medically underserved regions.Methods: We applied a well-established healthcare delivery model, Project ECHO (Extension for Community Healthcare Outcomes), to the management of complex diabetes (Endo ECHO) in medically underserved communities. A multidisciplinary team at Project ECHO connected with PCPs and CHWs at 10 health centers across New Mexico for weekly videoconferencing virtual clinics. Participating PCPs and CHWs presented de-identified patients and received best practice guidance and mentor-ship from Project ECHO specialists and network peers. A robust curriculum was developed around clinical practice guidelines and presented by weekly didactics over the ECHO network. After 2 years of participation in Endo ECHO, PCPs and CHWs completed self-efficacy surveys comparing confidence in complex diabetes management to baseline.Results: PCPs and CHWs in rural New Mexico reported significant improvement in self-efficacy in all measures of complex diabetes management, including PCP ability to serve as a local resource for other healthcare providers seeking assistance in diabetes care. Overall self-efficacy improved by 130% in CHWs (P<.0001) and by 60% in PCPs (P<.0001), with an overall large Cohen's effect size.Conclusion: Among PCPs and CHWS in rural, medically underserved communities, participation in Endo ECHO for 2 years significantly improved confidence in complex diabetes management. Application of the ECHO model to complex diabetes care may be useful in resource-poor communities with limited access to diabetes specialist services.Abbreviations: CHW = community health worker; CME = Continuing Medical Education; ECHO = Extension for Community Healthcare Outcomes; FQHC = federally qualified health center; PCP = primary care provider     

Utility of Psychological Screening of Young Adults with Type 1 Diabetes Transitioning to Adult Providers

Objective: Screening for depression, diabetes distress, and disordered eating in youth with type 1 diabetes (T1D) is recommended, as these comorbidities contribute to poor glycemic control. No consensus exists on which measures are optimal, and most previous studies have used nondisease-specific measures. We examined the utility of screening for these disorders using two disease-specific and one general measure at the time of transition from pediatric to adult care.Methods: Forty-three young adults from a T1D transition clinic completed the Patient Health Questionnaire, the Diabetes Distress Scale, and the Diabetes Eating Problem Survey–Revised. Chart review determined if clinicians noted similar symptoms during the year prior to transition. Metabolic data were also recorded.Results: Chart review identified 5 patients with depressive symptoms and 8 patients with diabetes distress. Screening identified 2 additional patients with depressive symptoms and 1 additional patient with diabetes distress. Of those noted to have symptomatic depression or diabetes distress on chart review, several subsequently screened negative on transition. Disordered eating was not detected by chart review, but 23.5% screened positive on transition. While depression, diabetes distress, and disordered eating positively correlated with glycated hemoglobin (HbA1c) (r = 0.31, P = .05; r = 0.40, P = .009; r = 0.63, P<.001, respectively), disordered eating accounted for the majority of observed variance (df = 1; F = 18.6; P<.001). Even though HbA1c was higher in patients with versus without disordered eating (P<.001), body mass index did not differ between the 2 groups (P = .51).Conclusion: In young adults with T1D, formal screening provides an opportunity to detect psychological problems, which, when treated, may help optimize metabolic control during the transition process.Abbreviations:T1D = type 1 diabetesHbA1C = hemoglobin A1cYCDP = Yale Children's Diabetes ProgramPHQ-8 = Patient Health Questionnaire–8DDS = Diabetes Distress ScaleDEPS-R = Diabetes Eating Problem Survey–Revised     

Implementation of an Electronic Dashboard with A Remote Management System to Improve Glycemic Management Among Hospitalized Adults

Objective: Better glycemic control for hospitalized diabetic patients significantly reduces health expenditures and improves disease outcomes. We developed a dynamic dashboard with a remote management system and evaluated its impact on inpatient glycemic control.Methods: This was an observational institution-wide study; study participants were enrolled from a 1,500-bed public medical center from 2016 to 2018. We evaluated the impact of a dynamic dashboard system, which analyzed and monitored all glucose data with virtual glycemic management recommendation by a team of endocrinologists, over 3 × 1-year periods: 2016 (pre-implementation), 2017 (development), and 2018 (implementation).Results: A total of 51,641 discharges with 878,159 blood glucose measurements were obtained during the 3-year period. After implementation of the dashboard system, the proportion of patients with poor glycemic control (hyperglycemia or hypoglycemia) was reduced by 31% (from 10.2 to 7.0 per day per 100 patients with glucose monitoring; P<.001); hyperglycemia decreased by 25% (from 6.1 to 4.6 per day per 100 patients with glucose monitoring; P<.001), and hypoglycemia decreased by 45% (from 4.2 to 2.3 per day per 100 patients with glucose monitoring; P<.001). Furthermore, the trend in the proportion of patients within the treat-to-target range showed significant improvement (P<.001) during the development period, with effectiveness maintained throughout the implementation period.Conclusion: We successfully installed a dynamic, electronic medical records-based dashboard monitoring system to improve inpatient glycemic control. The system, supported by a team of endocrinologists via remote recommendations, could efficiently fill an important need for improved glycemic management among hospitalized adults.Abbreviations: CDE = certified diabetes educator; DM = diabetes mellitus; EMR = electronic medical record; POC = point-of-care; TCVGH = Taichung Veterans General Hospital; UCSF = University of California, San Francisco; U.S. = United States; vGMS = virtual glucose management service     

Econsults to Endocrinologists Improve Access and Change Primary Care Provider Behavior

Objective: To describe the impact of an eConsult service on access to endocrinologists along with its influence on changing primary care provider (PCP) course of action and referral behaviors.Methods: Established in 2011, the Champlain BASE (Building Access to Specialist Care via eConsult) service allows PCPs to access specialist care in lieu of traditional face-to-face referrals. We conducted a cross-sectional study of eConsult cases submitted to endocrinologists by PCPs between April 15, 2011 and January 31, 2015. Usage data and PCP responses to a mandatory closeout survey were analyzed to determine eConsult response times, PCP practice behavior, referral outcomes, and provider satisfaction. Each eConsult was coded according to clinical topic and question type based on established taxonomies.Results: A total of 180 PCPs submitted 464 eConsults to endocrinology during the study period. Specialist median response time was 7 hours, with 90% of responses occurring within 3 days. PCPs received a new or additional course of action in 62% of submitted cases. An unnecessary face-to-face referral was avoided in 44% of all eConsults and in 67% of cases where the PCP initially contemplated requesting a referral. Over 95% of cases were rated at least 4 out of 5 in value for PCPs and their patients.Conclusion: The use of eConsult improves access to endocrinologists by providing timely, highly rated practice-changing clinical advice while reducing the need for patients to attend face-to-face office visits.Abbreviations:BASE = Building Access to Specialist Advice through eConsultPCP = primary care physicianUCSF = University of California San Francisco     

Improvements in Metabolic Control in Adults with Type 2 Diabetes Following Referral to a Diabetes Center, 2005–2010

Objective: We aimed to compare metabolic control in adults with diabetes in the general population to those newly referred to a diabetes center and after 1 year of specialty care.Methods: We performed a retrospective comparison of adults with diabetes aged ≥20 years data from the National Health and Nutrition Examination Survey (NHANES, n = 1,674) and a diabetes center (n = 3,128) from 2005–2010. NHANES participants represented the civilian, non-institutionalized U.S. population. Diabetes center referrals lived primarily around eastern Massachusetts. The proportion attaining targets for glycated hemoglobin A1c (A1c), blood pressure (BP), low-density lipoprotein (LDL) cholesterol, or all 3 (ABC control) and the proportion prescribed medications to lower A1c, BP, or cholesterol were evaluated.Results: Compared to the general sample, a smaller proportion of new diabetes center referrals had A1c <7% (<53 mmol/mol, 24% vs. 53%, P<.001), BP <130/80 mm Hg (38% vs. 50%, P<.001), and ABC control (5.6% vs. 17%, P<.001) but not LDL<100 mg/dL (<2.6 mmol/L, 54% vs. 53%, P = .65). After 1 year, more diabetes center referrals attained targets for A1c (40%), BP (38%), LDL (67%), and ABC control (15%) (P<.001 for all versus baseline). ABC control was not different between the general sample and diabetes center referrals at 1 year (P = .16). After 1 year, a greater percentage of diabetes center referrals compared to the general sample were prescribed medications to lower glucose (95% vs. 72%), BP (79% vs. 64%), and cholesterol (77% vs. 54%)(all P<.001).Conclusion: Compared to the general population, glycemic control was significantly worse for adults newly referred to the diabetes center. Within 1 year of specialty care, ABC control increased 270% in the setting of significant therapy escalation.Abbreviations:A1c = glycated hemoglobin A1cABC = composite of A1c, blood pressure, and cholesterolACEi = angiotensin-converting enzyme inhibitorARB = angiotensin receptor blockerBMI = body mass indexBP = blood pressureEHR = electronic health recordLDL = low-density lipoproteinNCHS = National Center for Health StatisticsNHANES = National Health and Nutrition Examination SurveyPCP = primary care provider     

The Synergy to Enable Glycemic Control Following Emergency Department Discharge Program for Adults with Type 2 Diabetes: Step-Diabetes

Objective: To evaluate a diabetes (DM) care delivery model among hyperglycemic adults with type 2 DM being discharged from the emergency department (ED) to home. The primary hypothesis was that a focused education and medication management intervention would lead to a greater short-term improvement in glycemic control compared to controls.Methods: A 4-week, randomized controlled trial provided antihyperglycemic medications management using an evidence-based algorithm plus survival skills diabetes self-management education (DSME) for ED patients with blood glucose (BG) levels ≥200 mg/dL. The intervention was delivered by endocrinologist-supervised certified diabetes educators. Controls received usual ED care.Results: Among 101 participants (96% Black, 54% female, 62.3% Medicaid and/or Medicare insurance), 77% completed the week 4 visit. Glycated hemoglobin A1C (A1C) went from 11.8 ± 2.4 to 10.5 ± 1.9% (P<.001) and 11.5 ± 2.0 to 11.1 ± 2.1% in the intervention and control groups, respectively (P = .012). At 4 weeks, the difference in A1C reduction between groups was 0.9% (P = .01). Mean BG decreased for both groups (P<.001), with a higher percentage of intervention patients (65%) reaching a BG <180 mg/dL compared to 29% of controls (P = .002). Hypoglycemia rates did not differ by group, and no severe hypoglycemia was reported. Medication adherence (Modified Morisky Score©) improved from low to medium (P<.001) among intervention patients and did not improve among controls.Conclusions: This study provides evidence that a focused diabetes care delivery intervention can be initiated in the ED among adults with type 2 diabetes and hyperglycemia and safely and effectively completed in the ambulatory setting. Improvement in short-term glycemic outcomes and medication adherence were observed.Abbreviations: A1C = glycated hemoglobin A1C BG = blood glucose BMI = body mass index CDE = certified diabetes educator CI = confidence interval DM = diabetes mellitus DSME = diabetes self-management education ED = emergency departmentMMAS-8 = Modified Morisky Medication Scale PCP = primary care provider POC = point of care SQ = subcutaneous     

Cheiroarthropathy: A Common Disorder in Patients in the T1D Exchange

Objective: Diabetic cheiroarthropathy is a long-term complication of diabetes that causes significant morbidity and can impair functional abilities. It has not been well studied in individuals with type 1 diabetes (T1D). The T1D Exchange registry provided an opportunity to assess the frequency of cheiroarthropathy and related characteristics.Methods: An internet-based survey was sent to 6,199 registry participants ≥18 years old, with 1,911 (31%) responding (62% female, 90% non-Hispanic White, mean age 40 years, median diabetes duration 20 years, mean glycated hemoglobin &lsqb;HbA1c] 7.7% &lsqb;61 mmol/mol]).Results: A total of 586 (31%) adults reported a diagnosis of ≥1 upper extremity disorder: 293 (15%) reported frozen shoulder, 293 (15%) trigger finger, 261 (14%) carpal tunnel, and 92 (5%) Dupuytren contracture, with 281 (15%) reporting ≥2 disorders. Those with upper extremity joint disorders were more likely older (P<.001) and had longer duration of diabetes (P<.001) than those without. HbA1c levels at the time of survey completion were 7.6% in participants with cheiroarthropathy versus 7.8% (62 mmol/mol) in participants without cheiroarthropathy.Conclusion: Cheiroarthropathy is common in adults with T1D. Additional research is needed to understand the pathogenesis and risk factors for this disorder. Standards of care for early recognition and treatment of diabetic cheiroarthropathy are also needed, particularly for adults with long-term diabetes. Improved awareness of cheiroarthropathy signs and symptoms of is needed so that patients can be identified and seek treatment before the condition causes disability.Abbreviations: BMI = body mass index; CGM = continuous glucose monitor; DCCT/EDIC = Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications; HbA1C = glycated hemoglobin; T1D = type 1 diabetes; T2D = type 2 diabetes     

An Italian Survey of Compliance With Major Guidelines for L-Thyroxine of Primary Hypothyroidism

Objective: The adherence by endocrinologists to guideline regarding levothyroxine (LT4) therapy and the compliance of patients may impact the management of hypothyroidism. The aim of this study was to compare the adherence of Italian endocrinologists to the ATA/AACE and ETA guidelines on the management of newly diagnosed primary hypothyroidism and to validate the Italian version of the Morisky-Green Medical Adherence Scale-8 (MMAS-8) questionnaire as applied to the evaluation of the adherence of patients with hypothyroidism to LT4 treatment.Methods: This was an observational, longitudinal, multicenter, cohort study, involving 12 Italian Units of Endocrinology.Results: The study enrolled 1,039 consecutive outpatients (mean age 48 years; 855 women, 184 men). The concordance of Italian endocrinologists with American Association of Clinical Endocrinologists/American Thyroid Association (AACE/ATA) and European Thyroid Association (ETA) recommendations was comparable (77.1% and 71.7%) and increased (86.7 and 88.6%) after the recommendations on LT4 dose were excluded, considering only the remaining recommendations on diagnosis, therapy, and follow-up. The MMAS-8 was filled out by 293 patients. The mean score was 6.71 with 23.9% low (score <6), 38.6% medium (6 to <8), 37.5% highly (= 8) adherers; the internal validation coefficient was 0.613. Highly adherent patients were not more likely to have good control of hypothyroidism compared with either medium (69% versus 72%, P = .878) or low (69% versus 43%, P = .861) adherers.Conclusion: Clinical management of hypothyroidism in Italy demonstrated an observance of international guidelines by Italian endocrinologists. Validation of the Italian version of the MMAS-8 questionnaire provides clinicians with a reliable and simple tool for assessing the adherence of patients to LT4 treatment.Abbreviations: AACE = American Association of Clinical Endocrinologists; ATA = American Thyroid Association; EDIPO = Endotrial SIE: DIagnosis and clinical management of Primitive hypothyrOidism in Italy; eCRF = electronic case report form; ETA = European Thyroid Association; fT3 = free triiodothyronine; fT4 = free thyroxine; LT4 = levothyroxine; MMAS-8 = Morisky-Green Medical Adherence Scale-8; PH = primary hypothyroidism; T3 = triiodothyronine; T4 = thyroxine; TSH = thyroid-stimulating hormone; US = ultrasonography     

Serum Levels of Carcinoembryonic Antigen in Patients with Type 2 Diabetes

Objective: To investigate whether serum carcinoembryonic antigen (CEA) levels are associated with type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c).Methods: A comparative, cross-sectional, observational study was conducted at Jordan University Hospital, Amman, Jordan, on 282 adult subjects from March 2012 to June 2015. Subjects were classified into 2 groups: T2DM subjects (n = 168) and a healthy comparison group (n = 114). Subjects with any condition known to be associated with elevated CEA levels were excluded. HbA1c and serum CEA levels were measured, and body mass index (BMI) was determined.Results: Subjects with T2DM had significantly higher mean serum CEA than controls (2.4 ± 1.5 vs. 1.5 ± 1.2 ng/mL, P<.0001). Sex did not correlate with CEA levels, while age (Spearman's rho [ρ] = 0.18, P =.002) and HbA1c (ρ = 0.56, P<.0001) did; however, age no longer correlated after correcting for diabetic status. HbA1c was the only variable shown to correlate with CEA in a stepwise linear regression (r = 0.37, P<.001).Conclusion: We observed a statistically significant association between elevated CEA and T2DM, despite average CEA values for both groups being within the reference range. In addition, serum CEA levels correlated positively with HbA1c values.Abbreviations:ADA = American Diabetes AssociationBMI = body mass indexCA 19-9 = carbohydrate antigen 19-9CEA = carcinoembryonic antigenCRP = C-reactive proteinDM = diabetes mellitusHbA1c = glycated hemoglobinJUH = Jordan University HospitalT2DM = type 2 diabetes mellitusρ = Spearman's correlation coefficient     

Predictors of Nonattendance at an Endocrinology Outpatient Clinic

Objective: To identify predictors potentially contributing to patients' nonattendance or to same-day cancellation of scheduled appointments at an adult endocrinology office practice.Methods: A retrospective, records-based, cross-sectional study was conducted using data from 9,305 electronic medical records of patients presenting at a U.S. metropolitan adult endocrinology clinic in 2013. Statistical analyses included multivariate regression, calculated odds ratios, and posttest probabilities.Results: Of 29,178 total patient visits analyzed, 68% were attended by patients. Of total scheduled appointments, 7% resulted in nonattendance and 5% in same-day cancellation. The most significant predictors of nonatten-dance were a previous history of nonattendance (P<.001), uncontrolled diabetes (P<.001), and new patients to the practice (P<.001). Long lead-time to appointment (P = .001), younger age (P<.001), and certain insurance carriers (P<.001) also were significant predictors.Conclusion: Specific predictors of nonattendance at scheduled appointments were identified using statistical analysis of electronic medical record data. Previous history of nonattendance and having uncontrolled diabetes (especially in patients newly referred to the practice) are among these significant predictors. Identifying specific predictors for nonattendance enables targeted strategies to be developed.Abbreviations:APRN = Advanced Practice Registered NurseCI = confidence intervalDM = diabetes mellitusEMR = electronic medical recordHbA1c = glycated hemoglobinNS = no-showOR = odds ratioSDC = same-day cancellation     

1,5-Anhydroglucitol and Neonatal Complications in Pregnancy Complicated by Diabetes

Objective: To determine the association of 1,5-anhydroglucitol (1,5-AG) with neonatal birth weight (NBW) and neonatal hypoglycemia (+NH) in pregnancies complicated by diabetes.Methods: We assessed a retrospective cohort of 102 females, 17 with gestational diabetes (GDM), 48 with type 1 diabetes mellitus (T1DM), and 37 with type 2 diabetes mellitus (T2DM). 1,5-AG and glycated hemoglobin A1C (A1C) values throughout pregnancy were extracted. Linear regression was used to assess their association with NBWs z-scores adjusting for maternal age, ethnicity and body mass index (BMI). +NH was defined by a note in the infant record, glucose <1.7 mmol/L in the first 24 h, or <2.5 mmol/L in the first 48 h after birth. A t test or Welch's approximate t test was used to compare the mean 1,5-AG and A1C of mothers with +NH versus those without (-NH), adjusted for gestational age and analyzed by diabetes type and across trimesters.Results: Mean 1,5-AG significantly differed across groups: T1DM 3.77 ± 2.82 μg/mL, T2DM 5.73 ± 4.38 μg/mL, GDM 8.89 ± 4.39 μg/mL (P<.0001), suggesting less glucose exposure in GDM relative to T1DM or T2DM. A negative linear association was found between mean 1,5-AG and z-scores (R= -0.28, P = .005. In contrast, the association between mean A1C and z-scores was weaker (R = 0.15, P = .14). The mean 1,5-AG tended to be lower in the +NH cohort versus -NH (P = .08), and this was statistically significant (P = .01) among subjects with GDM.Conclusion: The association of 1,5-AG with complications related to glycemic exposure supports the notion of its utility as an adjunct glycemic biomarker in pregnancies complicated by diabetes and across trimesters.Abbreviations: 1,5-AG = 1,5-anhydroglucitol A1C = glycated hemoglobin A1C BMI = body mass index CGM = continuous glucose monitoring GDM = gestational diabetes mellitus LGA = large for gestational age MICC = maternal and infant care unit NBW = neonatal birth weight NH = neonatal hypoglycemia PPH = postprandial hyperglycemia SMBG = self-monitoring of blood glucose T1DM = type 1 diabetes mellitus T2DM = type 2 diabetes mellitus     

Outcome Of Implementation Of A Multidisciplinary Team Approach To The Care Of Patients After Transsphenoidal Surgery

Objective: Transsphenoidal surgery (TS) for sellar lesions is an established and safe procedure, but complications can occur, particularly involving the neuroendocrine system. We hypothesized that postoperative care of TS patients would be optimized when performed by a coordinated team including a pituitary neurosurgeon, endocrinologists, and a specialty nurse.Methods: We implemented a formalized, multidisciplinary team approach and standardized postoperative protocols for the care of adult patients undergoing TS by a single surgeon (J.N.B.) at our institution beginning in July 2009. We retrospectively compared the outcomes of 214 consecutive TS-treated cases: 113 cases prior to and 101 following the initiation of the team approach and protocol implementation. Outcomes assessed included the incidence of neurosurgical and endocrine complications, length of stay (LOS), and rates of hospital readmission and unscheduled clinical visits.Results: The median LOS decreased from 3 days preteam to 2 days postteam (P<.01). Discharge occurred on postoperative day 2 in 46% of the preteam group patients compared to 69% of the postteam group (P<.01). Rates of early postoperative diabetes insipidus (DI) and readmissions within 30 days for syndrome of inappropriate antidiuretic hormone (SIADH) or other complications did not differ between groups.Conclusion: Implementation of a multidisciplinary team approach was associated with a reduction of LOS. Despite earlier discharge, postoperative outcomes were not compromised. The endocrinologist is central to the success of this team approach, which could be successfully applied to care of patients undergoing TS, as well as other types of endocrine surgery at other centers.Abbreviations:CSF = cerebrospinal fluidDDAVP = desmopressinDI = diabetes insipidusLOS = length of stayPOD = postoperative daySIADH = syndrome of inappropriate antidiuretic hormoneTS = transsphenoidal surgery     

The Guided Transfer of Care Improves Adult Clinic Show Rate

Objective: Every year, 500,000 youths in the U.S. with chronic disease turn 18 years of age and eventually require transfer to adult subspecialty care. Evidence-based interventions on the organization of transfer of care are limited, although engagement and retention in adult clinic are considered appropriate outcomes. Sustained continuity of care improves patient satisfaction and reduces hospitalization.Methods: We conducted a prospective, nonrandomized cohort study of patients with pediatric endocrine conditions, age 16 to 26 years, enrolled upon referral to the adult endocrine clinic of a physician trained in both adult and pediatric endocrinology (Med+Peds endocrinologist). Patients differed based on whether their referral originated from another pediatric endocrinologist (traditional transfer) or if the Med+Peds endocrinologist previously saw the patient in his pediatric endocrine clinic (guided transfer). Rather than relying on arbitrary age criteria, guided transfer to adult clinic occurred when physician and patient considered it appropriate. The primary outcome was show rate at the first and second adult visits.Results: Of 36 patients, 21 were referred by another pediatric endocrinologist and 15 underwent guided transfer. For traditional transfer, show rate to the first and second visit was 38%, compared to 100% in the guided transfer group (P = .0001). Subgroup analysis of 27 patients with diabetes revealed that both groups had similar initial hemoglobin A1c (P = .38), and the guided transfer group maintained hemoglobin A1c.Conclusion: Most traditional transfers were unsuccessful. Guided transfer was significantly more effective, with every patient successfully transferring, and could be implemented with adult endocrinologists willing to see patients in the pediatric clinic.Abbreviations: DKA = diabetic ketoacidosis; HbA1c = hemoglobin A1c; Med+Peds = Internal Medicine and Pediatrics     

Impact of Switching Youth With Diabetes to Insulin Degludec in Clinical Practice

Objective: Many youth with diabetes struggle to meet glycemic targets. The new ultralong duration of action of insulin degludec (iDeg) holds potential to ameliorate missed doses of basal insulin and improve glycemic control in youth with diabetes.Methods: A retrospective chart review was undertaken of youth age 13 to <24 years in our practice with type 1 diabetes (T1D) or type 2 diabetes (T2D) who had been switched from glargine or detemir to iDeg to evaluate the impact of this transition on glycemic control.Results: Glycated hemoglobin A1c (HbA1c) in youth with T1D (n = 82) remained stable during 6 months of treatment with iDeg (10.1 ± 2.11% &lsqb;87 ± 23 mmol/mol] at start of iDeg compared to 10.1 ± 2.12% &lsqb;87 ± 23 mmol/mol] at 6 months of treatment), whereas in youth with T2D (n = 16), HbA1c significantly declined from 10.6 ± 2.3% (92 ± 25 mmol/mol) to 8.3 ± 2.2% (67 ± 24 mmol/mol) (P = .0024).Conclusion: In youth switched to iDeg, which in our practice is commonly due to ineffectiveness of the patient's current regimen, the outcome differences we saw may be due to preserved beta-cell function in youth with T2D. It remains to be seen whether there are benefits of transition to iDeg in youth with T1D beyond glycemic outcomes, such as reduction in ketosis and episodes of diabetic ketoacidosis.Abbreviations: DKA = diabetic ketoacidosis; DPV = Diabetes-Patienten-Verlaufsdokumentation (German/Austrian Prospective Diabetes Follow-Up Registry); HbA1c = glycated hemoglobin A1c; iDeg = insulin degludec; T1D = type 1 diabetes; T2D = type 2 diabetes     

Performance of A1C Versus Ogtt for the Diagnosis of Prediabetes in a Community-Based Screening

Objective: Reliable identification of individuals at risk for developing diabetes is critical to instituting preventative strategies. Studies suggest that the accuracy of using hemoglobin A1c as a sole diagnostic criterion for diabetes may be variable across different ethnic groups. We postulate that there will be lack of concordance between A1c and the oral glucose tolerance test (OGTT) for diagnosing prediabetes across Hispanic and non-Hispanic white (NHW) populations.Methods: A total of 218 asymptomatic adults at risk for type 2 diabetes (T2D) were assessed with A1c and OGTT for the diagnosis of prediabetes. Glucose homeostasis status was assigned as no diabetes (A1c <5.7% [39 mmol/mol]), prediabetes (A1c 5.7 to 6.4% [46 mmol/mol]), and T2D (A1c >6.4% [46 mmol/mol]). Inclusion criteria were age >18 years and at least one of the following: a family history of diabetes, a history of gestational diabetes, Hispanic ethnicity, non-Caucasian race, or obesity. Subjects received a fasting 75-g OGTT and A1c on the same day. Bowker's test of symmetry was employed to determine agreement between the tests.Results: Data from 99 Hispanic patients and 79 NHW patients were analyzed. There was no concordance between A1c and OGTT for Hispanic (P =.002) or NHW individuals (P =.003) with prediabetes.Conclusion: A1c is discordant with OGTT among Hispanic and NHW subjects for the diagnosis of prediabetes. Sole use of A1c to designate glycemic status will result in a greater prevalence of prediabetes among Hispanic and NHW New Mexicans.Abbreviations:A1c = hemoglobin A1cBMI = body mass indexCDC = Centers for Disease ControlCI = confidence intervalFPG = fasting plasma glucoseNHW = non-Hispanic whiteOGTT = oral glucose tolerance testT2D = type 2 diabetesWHO = World Health Organization     

Guidelines to Improve Perioperative Management of Diabetes Mellitus: Assessment of the Impact of Change Across Time

Objective: Assess the impact of guidelines on the care of patients with diabetes undergoing elective surgery.Methods: A multidisciplinary team developed perioperative guidelines. Overall changes in key measures were evaluated after guidelines were introduced and compared with a historical cohort.Results: The historical cohort included 254 surgical procedures, and the post–guidelines implementation cohort comprised 1,387. Glucose monitoring was performed preoperatively in 93% of cases in the post–guidelines implementation cohort and in 88% in the historical cohort (P<.01), but the percentage of cases with measurements decreased over 12 months (from 95% to 91%, P = .044). Glucose was intraoperatively monitored in 67% of cases after guidelines were introduced and in 29% historically (P<.01); the post–guidelines implementation percentage decreased over 12 months from 67% to 55% (P<.01). The performance of glucose monitoring in the postanesthesia care unit (PACU) did not differ (86% vs. 87%, P = .57), but it decreased over 12 months, from 91% to 84% (P<.01). After introduction of the guidelines, insulin use increased in the preoperative, intraoperative, and PACU areas (all P≤.01) but decreased by the end of 12 months (all P<.01). Mean preoperative and PACU glucose levels in the post– guidelines implementation cohort were significantly lower than in the historical cohort (P<.01).Conclusion: Multidisciplinary management guidelines for diabetes patients undergoing surgery can improve the performance of key measures of care. Although adherence to recommendations generally remained higher after guideline implementation than in the historical period, the improvement in several measures began to decline over time.Abbreviations: DM = diabetes mellitus HbA_1c = hemoglobin A_1c PACU = postanesthesia care unit POC-BG = pointof-care blood glucose POME = preoperative medical evaluation     

Self Blood Glucose Monitoring Underestimates Hyperglycemia And Hypoglycemia As Compared To Continuous Glucose Monitoring In Type 1 And Type 2 Diabetes

Objective: When glucose records from self blood glucose monitoring (SBGM) do not reflect estimated average glucose from glycosylated hemoglobin (HgBA1) or when patients' clinical symptoms are not explained by their SBGM records, clinical management of diabetes becomes a challenge. Our objective was to determine the magnitude of differences in glucose values reported by SBGM versus those documented by continuous glucose monitoring (CGM).Methods: The CGM was conducted by a clinical diabetes educator (CDE)/registered nurse by the clinic protocol, using the Medtronic iPRO2™ system. Patients continued SBGM and managed their diabetes without any change. Data from 4 full days were obtained, and relevant clinical information was recorded. De-identified data sets were provided to the investigators.Results: Data from 61 patients, 27 with type 1 diabetes (T1DM) and 34 with T2DM were analyzed. The lowest, highest, and average glucose recorded by SBGM were compared to the corresponding values from CGM. The lowest glucose values reported by SBGM were approximately 25 mg/dL higher in both T1DM (P = .0232) and T2DM (P = .0003). The highest glucose values by SBGM were approximately 30 mg/dL lower in T1DM (P = .0005) and 55 mg/dL lower in T2DM (P<.0001). HgBA1c correlated with the highest and average glucose by SBGM and CGM. The lowest glucose values were seen most frequently during sleep and before breakfast; the highest were seen during the evening and postprandially.Conclusion: SBGM accurately estimates the average glucose but underestimates glucose excursions. CGM uncovers glucose patterns that common SBGM patterns cannot.Abbreviations: CDE = certified diabetes educator; CGM = continuous glucose monitoring; HgBA1c = glycosylated hemoglobin; MAD = mean absolute difference; SBGM = self blood glucose monitoring; T1DM = type 1 diabetes; T2DM = type 2 diabetes     

Relationship of Adipokines and Proinflammatory Cytokines Among Asian Indians With Obesity and Youth Onset Type 2 Diabetes

Objective: It is well known that inflammation is associated with diabetes, but it is unclear whether obesity mediates this association in individuals with youth-onset type 2 diabetes mellitus (T2DM-Y).Methods: We recruited individuals with T2DM-Y (age at onset <25 years) and age-matched normal glucose tolerance (NGT) subjects. Participants were further classified using Asia-Pacific body mass index cut-points for obesity and categorized as: nonobese NGT (n = 100), Obese NGT (n = 50), nonobese T2DM-Y (n = 50), and obese T2DM-Y (n = 50). We compared adipokines (adiponectin and leptin) and proinflammatory cytokines (tumor necrosis factor alpha &lsqb;TNF-α] and monocyte chemotactic protein-1 &lsqb;MCP-1]) across groups.Results: Compared to nonobese NGT, the other 3 groups (obese NGT, nonobese T2DM-Y, and obese T2DM-Y) were found to have lower adiponectin (7.7 vs. 5.7, 4.2, 3.8 μg/mL, P<.01), and higher leptin (3.6 vs. 5.4, 5.7, 7.9 μg/mL, P<.001) and MCP 1 (186 vs. 272, 340, 473 pg/mL, P<.001) respectively. However, TNF-α levels were higher only among nonobese T2DM-Y (112 pg/mL) and obese T2DM-Y (141 pg/mL, P<.01 for each). After adjusting for age, sex, waist, hypertension, homeostatic model assessment of insulin resistance (HOMA-IR), serum cholesterol, triglycerides, and family history of diabetes, adiponectin was associated with 33% and 41% lower odds of being nonobese T2DM and obese T2DM, respectively. However, adjusted for same factors, leptin, TNF-α, and MCP-1 were associated with markedly higher odds (5- to 14-fold) of nonobese and obese T2DM.Conclusion: In young Asian Indians, leptin and proinflammatory cytokines are positively, and adiponectin negatively, associated with both nonobese and obese T2DM-Y compared to nonobese NGT individuals.Abbreviations: BMI = body mass index CI = confidence interval FPG = fasting plasma glucose HOMA-IR = homeostatic model assessment of insulin resistance IGT = impaired glucose tolerance MCP-1 = monocyte chemotactic protein-1 NGT = normal glucose tolerance OGTT = oral glucose tolerance test OR = odds ratio T2DM-Y = youth-onset type 2 diabetes TNF-α = tumor necrosis factor-α     

Changing to Basal-Bolus Insulin Therapy for the Inpatient Management of Hyperglycemia—A Natural Experiment

Objective: Most acute-care hospitals have transitioned from sliding-scale to basal-bolus insulin therapy to manage hyperglycemia during hospitalization, but there is limited scientific evidence demonstrating better short-term clinical outcomes using the latter approach. The present study sought to determine if using basal-bolus insulin therapy favorably affects these outcomes in noncritical care settings and, if so, whether the magnitude of benefit differs in patients with known versus newly diagnosed type 2 diabetes.Methods: This natural experiment compared outcomes in 10,120 non–critically ill adults with type 2 diabetes admitted to an academic teaching hospital before and after hospital-wide implementation of a basal-bolus insulin therapy protocol. A group of 30,271 inpatients without diabetes (type 1 or 2) served as controls. Binomial models were used to compare percentages of patients with type 2 diabetes who were transferred to intensive care, experienced complications, or died in the hospital before and after implementation of the protocol, controlling for changes in the control group. The analysis also evaluated before-after changes in length of stay and glucometric indicators.Results: Implementation of basal-bolus therapy did not reduce intensive care use (the primary outcome), complications, mortality, or median length of stay, except in patients with newly diagnosed diabetes (n = 234), who experienced a statistically significant decline in the incidence of complications (P<.01). The absence of effect in previously diagnosed patients was observed in spite of a 32% decline (from 3.7% to 2.5%) in the proportion of inpatient days with hypoglycemia <70 mg/dL (P<.01) and a 16% decline (from 13.5% to 11.3%) in the proportion of days with hyperglycemia >300 mg/dL (P<.01).Conclusion: Despite achieving significant reductions in both hyperglycemia and hypoglycemia, use of basal-bolus insulin therapy to manage hyperglycemia in non–critically ill hospitalized patients did not improve short-term clinical outcomes, except in the small minority of patients with newly diagnosed diabetes. The optimal management of hyperglycemia for improving these outcomes has yet to be determined.Abbreviation: ICD-9 = International Classification of Diseases–Ninth Revision