Effects of a Computerized Order Set on the Inpatient Management of Hyperglycemia: A Cluster-Randomized Controlled Trial

ObjectiveTo determine the effects of a computerized order set on the inpatient management of diabetes and hyperglycemia.MethodsWe conducted a cluster-randomized controlled trial on the general medical service of an academic medical center staffed by residents and hospitalists. Consecutively enrolled patients with diabetes mellitus or inpatient hyperglycemia were randomized on the basis of their medical team to usual care (control group) or an admission order set built into the hospital’s computer provider order entry (CPOE) system (intervention group). All teams received a detailed subcutaneous insulin protocol and case-based education. The primary outcome was the mean percent of glucose readings per patient between 60 and 180 mg/dL.ResultsBetween April 5 and June 22, 2006, we identified 179 eligible study subjects. The mean percent of glucose readings per patient between 60 and 180 mg/dL was 75% in the intervention group and 71% in the usual care group (adjusted relative risk, 1.36; 95% confidence interval, 1.03 to 1.80). In comparison with usual care, the intervention group also had a lower patient-day weighted mean glucose (148 mg/dL versus 158 mg/dL, P = .04), less use of sliding-scale insulin by itself (25% versus 58%, P = .01), and no significant difference in the rate of severe hypoglycemia (glucose < 40 mg/dL; 0.5% versus 0.3% of patient-days, P = .58).ConclusionThe use of an order set built into a hospital’s CPOE system led to improvements in glycemic control and insulin ordering without causing a significant increase in hypoglycemia. Other institutions with CPOE should consider adopting similar order sets as part of a comprehensive inpatient glycemic management program. (Endocr Pract. 2010;16:209-218)     

Computerized Physician Order Entry- Based Hyperglycemia Inpatient Protocol and Glycemic Outcomes: The CPOE-HIP Study

ObjectiveTo evaluate the impact of implementing a computerized physician order entry (CPOE)-based hyperglycemia inpatient protocol (HIP) on glycemic outcomes.MethodsThis retrospective, cross-sectional study compared blood glucose values, hemoglobin A_1c values, diabetes medication profiles, and demographic data of diabetic patients admitted to medicine services between March 15, 2006, and April 11, 2006 (before CPOE-HIP protocol was adopted), with data of diabetic patients admitted between October 3, 2007, and October 30, 2007 (1 year after CPOE-HIP protocol was implemented).ResultsA total of 241 diabetic patients comprised the pre-CPOE-HIP group and 197 patients comprised the post-CPOE-HIP group. After the protocol was adopted, there was a decrease of 10.8 mg/dL in the mean glucose concentration per patient-day (175.5 ± 81.2 mg/dL vs 164.7 ± 82 mg/dL, P < .001). Additional glycemic control improvements included a 5% increase in patient-days with serum glucose concentrations between 70 and 150 mg/ dL (41.1% vs 46.1%, P = .008) and a 3.1% decrease in patient-days with glucose concentrations above 299 mg/dL (16.9% vs 13.8%, P = .023). The percentage of patientdays with glucose concentrations less than or equal to 50 mg/dL was not significantly different (0.95% vs 1.27%, P = .15). Compliance with the American Diabetes Association recommendation for hemoglobin A_1c inpatient testing frequency increased from 37.3% to 64.5% (P < .001). The length of stay did not differ between the groups.ConclusionsImplementation of a hospital-wide, CPOE-based, hyperglycemia management protocol had a favorable impact onglucose targets, decreasing excessively high glucose levels without increasing clinically meaningful hypoglycemic events. Compliance with hemoglobin A_1c testing recommendations also improved. (Endocr Pract. 2010;16:389-397)     

Effect Of A Targeted Glycemic Management Program On Provider Response To Inpatient Hyperglycemia

ObjectiveTo report the results of implementation of a Targeted Glycemic Management (TGM) Service pilot, with the goals of improving clinician awareness of available inpatient glycemic management protocols and improving responsiveness to and frequency of severe hyperglycemia.MethodsPatients with a blood glucose (BG) level ≥ 300 mg/dL who were hospitalized on a general medicine unit during three 12-week periods before, during, and after the TGM pilot were compared for responsiveness by the primary team, percentage of subsequent BG measurements between 80 and 180 mg/dL, and frequency of subsequent severe hyperglycemia (BG levels ≥ 300 mg/dL) and hypoglycemia (BG values < 70 mg/dL).ResultsIn comparison with pre-TGM and post-TGM periods, more patients during the TGM pilot had a modification of their glycemic regimen in response to severe hyperglycemia (49% versus 73% versus 50%, before, during, and after TGM, respectively; P = .044), and the percentage of patients with ≥ 50% of subsequent BG measurements in the desired range (27% versus 53% versus 32%; P = .035) was greatest during the TGM period. The incidence of subsequent severe hyperglycemia (20% versus 9% versus 16%; P = .0004) was lowest during the TGM period; however, the incidence of hypoglycemia was similar in all 3 periods (3.9% versus 3.7% versus 3.7%).ConclusionThese results indicate that a TGM Service can favorably influence glycemic management practices and improve glycemic control, but ongoing intervention is necessary for maintenance of these results. (Endocr Pract. 2011;17:552-557)     

The Association of Diabetes and Hyperglycemia on Inpatient Readmissions

ObjectiveTo evaluate the association between inpatient glycemic control and readmission in individuals with diabetes and hyperglycemia (DM/HG).MethodsTwo data sets were analyzed from fiscal years 2011 to 2013: hospital data using the International Classification of Diseases, Ninth Revision (ICD-9) codes for DM/HG and point of care (POC) glucose monitoring. The variables analyzed included gender, age, mean, minimum and maximum glucose, along with 4 measures of glycemic variability (GV), standard deviation, coefficient of variation, mean amplitude of glucose excursions, and average daily risk range.ResultsOf 66 518 discharges in FY 2011-2013, 28.4% had DM/HG based on ICD-9 codes and 53% received POC monitoring. The overall readmission rate was 13.9%, although the rates for individuals with DM/HG were higher at 18.9% and 20.6% using ICD-9 codes and POC data, respectively. The readmitted group had higher mean glucose (169 ± 47 mg/dL vs 158 ± 46 mg/dL, P < .001). Individuals with severe hypoglycemia and hyperglycemia had the highest readmission rates. All 4 GV measures were consistent and higher in the readmitted group.ConclusionIndividuals with DM/HG have higher 30-day readmission rates than those without. Those readmitted had higher mean glucose, more extreme glucose values, and higher GV. To our knowledge, this is the first report of multiple metrics of inpatient glycemic control, including GV, and their associations with readmission.     

Daily Inpatient Glycemic Survey (DINGS): A Process to Remotely Identify and Assist in the Management of Hospitalized Patients with Diabetes and Hyperglycemia

Objective: Hyperglycemia, hypoglycemia, and glycemic variability have been associated with increased morbidity, mortality, and overall costs of care in hospitalized patients. At the Stratton VA Medical Center in Albany, New York, a process aimed to improve inpatient glycemic control by remotely assisting primary care teams in the management of hyperglycemia and diabetes was designed.Methods: An electronic query comprised of hospitalized patients with glucose values <70 mg/dL or >350 mg/dL is generated daily. Electronic medical records (EMRs) are individually reviewed by diabetes specialist providers, and management recommendations are sent to primary care teams when applicable. Glucose data was retrospectively examined before and after the establishment of the daily inpatient glycemic survey (DINGS) process, and rates of hyperglycemia and hypoglycemia were compared.Results: Patient-day mean glucose slightly but significantly decreased from 177.6 ± 64.4 to 173.2 ± 59.4 mg/dL (P<.001). The percentage of patient-days with any value >350 mg/dL also decreased from 9.69 to 7.36% (P<.001), while the percentage of patient-days with mean glucose values in the range of 90 to 180 mg/dL increased from 58.1 to 61.4% (P<.001). Glycemic variability, assessed by the SD of glucose, significantly decreased from 53.9 to 49.8 mg/dL (P<.001). Moreover, rates of hypoglycemia (<70 mg/dL) decreased significantly by 41% (P<.001).Conclusion: Quality metrics of inpatient glycemic control improved significantly after the establishment of the DINGS process within our facility. Prospective controlled studies are needed to confirm a causal association.Abbreviations: DINGS = daily inpatient glycemic survey EMR = electronic medical record HbA1c = glycated hemoglobin ICU = intensive care unit VA = Veterans Affairs     

A Retrospective Study Comparing Neutral Protamine Hagedorn Insulin With Glargine As Basal Therapy In Prednisone-Associated Diabetes Mellitus In Hospitalized Patients

ObjectiveTo compare glycemic outcomes in hospitalized patients with or without type 2 diabetes mellitus receiving neutral protamine Hagedorn insulin (NPH) vs glargine as basal insulin for management of glucocorticoid-associated hyperglycemia.MethodsWe conducted a retrospective review of electronic medical records in prednisone-treated adult patients with hyperglycemia in a university hospital. Consecutive patients were selected in both the NPH and glargine cohorts using inclusion and exclusion criteria. Baseline characteristics were assessed in each cohort. Glycemic outcomes were analyzed by comparing fasting blood glucose, mean daily blood glucose concentration, median daily blood glucose concentration, and the number of hypoglycemic episodes on a prespecified index day.ResultsOne hundred twenty patients were included: 60 patients in the NPH cohort and 60 patients in the glargine cohort. The weight-based insulin requirement was lower in the NPH cohort than in the glargine cohort (0.27 ± 0.2 units/kg vs 0.34 ± 0.2 units/kg [P = .04] for basal insulin and 0.26 ± 0.2 units/kg vs 0.36 ± 0.2 units/kg [P = .03] for bolus insulin). NPH and glargine cohorts were similar regarding age, sex, race, body mass index, hemoglobin A_1c, serum creatinine, and prednisone dosage. Glycemic outcomes in the NPH cohort compared with outcomes in the glargine cohort were similar regarding mean fasting blood glucose concentration (134 ± 49 mg/dL vs 139 ± 54 mg/dL [P = .63]), mean daily blood glucose (167 ± 46 mg/dL vs 165 ± 52 mg/dL [P = .79]), median blood glucose (160 ± 49 mg/dL vs 159 ± 57 mg/dL [P = .90]), and number of hypoglycemic episodes per day (0.12 ± 0.3 vs 0.10 ± 0.3 [P = .77]).ConclusionsNPH and glargine appear to be equally effective as basal insulin in the management of hyperglycemia in hospitalized patients receiving prednisone. However, the total daily insulin doses used were lower in the NPH cohort. (Endocr Pract. 2012;18:712-719)     

Reduction of Insulin Resistance and Plasma Glucose Level by Salsalate Treatment in Persons With Prediabetes

ObjectiveTo evaluate the effect of salsalate as an antiinflammatory agent on insulin resistance and glycemic control in persons with prediabetes.MethodsIn this double-blind, placebo-controlled clinical trial, 66 persons who had prediabetes on the basis of the American Diabetes Association criteria were enrolled. They were randomly assigned to receive salsalate (3 g daily) or placebo for 12 weeks. Fasting plasma glucose (FPG) and insulin, glucose 2 hours after oral administration of 75 g of glucose, hemoglobin A_1c, lipid profile, homeo stasis model assessment of insulin resistance (HOMA-IR), and homeostasis model assessment of beta-cell function were determined before and after treatment.ResultsSalsalate treatment reduced the FPG level from 5.86 ± 0.07 mmol/L to 5.20 ± 0.11 mmol/L and HOMA-IR from 4.2 ± 0.9 to 3.8 ± 0.3 (P = .01 for both changes). Homeostasis model assessment of beta-cell func tion increased in the salsalate-treatment group from 139.8 ± 11.0 to 189.4 ± 24.6 (P = .01). At the end of the study, FPG, HOMA-IR, and insulin levels were significantly different between salsalate and placebo groups (5.20 ± 0.11 mmol/L versus 5.53 ± 0.10 mmol/L, 3.8 ± 0.3 versus 4.4 ± 0.9, and 16.1 ± 1.9 μIU/mL versus 18.2 ± 2 μIU/mL, respectively; P < .05 for all). There were no persistent complications after salsalate therapy.ConclusionTreatment with salsalate can reduce insu lin resistance and the FPG level in subjects with predia betes. Determination of the long-term safety and efficacy of the use of salsalate necessitates further investigation. (Endocr Pract. 2012;18:826-833)     

Management of Hyperglycemia in Diabetic Patients with Hematologic Malignancies During Dexamethasone Therapy

ObjectiveTo compare the response to different insulin regimens for management of hyperglycemia in diabetic patients with hematologic malignancies who are receiving dexamethasone.MethodsA retrospective analysis was conducted to determine whether a basal bolus insulin (BBI) regimen with detemir and aspart is superior to a sliding scale regular insulin (SSI) regimen for management of hyperglycemia in hospitalized diabetic patients receiving dexamethasone.ResultsForty patients with hematologic malignancies were treated with intravenous (8 to 12 mg/day) or oral (40 mg/day) dexamethasone for 3 days. The average blood glucose (BG) level was 301 ± 57 mg/dL in the SSI group (n = 28) and 219 ± 51 mg/dL in the BBI group (n = 12) (P <.001). The BBI regimen resulted in an average BG reduction of 52 ± 82 mg/dL throughout the course of dexa-methasone therapy, while the SSI regimen produced an increase in the mean daily BG level of 128 ± 77 mg/dL (P <.001). On the last day of dexamethasone administration, the insulin requirement was 49 ± 29 units/day in the SSI group and 122 ± 39 units/day in the BBI group (P <.001). Three patients in the SSI group developed diabetic ketoacidosis or hyperosmolar hyperglycemia during steroid therapy. No hypoglycemia was observed in either group. The length of stay and infection rates were similar between groups.ConclusionBasal and bolus insulin regimen is an effective and safe approach for managing dexamethasone-induced hyperglycemia in hospitalized patients with hematologic malignancies. (Endocr Pract. 2013;19:231-235)     

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.     

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     

Patient Outcomes after Implementation of a Protocol for Inpatient Insulin Pump Therapy

ObjectiveTo determine the safety and the results of use of an inpatient insulin pump protocol (IIPP).MethodsIn this quality improvement initiative, review of medical records of bedside capillary blood glucose (CBG) levels and pump-related adverse events was performed on 50 consecutive inpatients admitted to the hospital with continuous subcutaneous insulin infusion (CSII) after implementation of our IIPP. Patients were categorized in 3 groups on the basis of evidence in the medical records for IIPP in combination with inpatient diabetes service consultation (group 1; n = 34), for IIPP alone (group 2; n = 12), or for usual care (group 3; n = 4). Patients identified during hospital admission as using CSII therapy were invited to complete a satisfaction questionnaire for inpatient CSII use.ResultsMean CBG levels were similar among the 3 groups (groups 1, 2, and 3: 173 ± 43 mg/dL versus 187 ± 62 mg/dL versus 218 ± 46 mg/dL, respectively). Although there were more patient-days with blood glucose > 300 mg/ dL in group 3 (P = .02), there were no significant group differences in the frequency of hypoglycemia (CBG < 70 mg/ dL). Only 1 pump malfunction and 1 infusion site problem were reported among all study patients. No serious adverse events related to CSII therapy occurred. The majority of patients (86%) reported satisfaction with their ability to continue CSII use in the hospital.ConclusionPatients using CSII as outpatients are candidates for inpatient diabetes self-management. Inexperience with these devices on the part of hospital personnel together with the limited studies of patient experience with CSII in the hospital contributes to inconsistencies in management of these patients. An IIPP provides a standardized and safe approach to the use of CSII in the hospital. (Endocr Pract. 2009;15:415-424)     

Standardized Glycemic Management and Perioperative Glycemic Outcomes in Patients with Diabetes Mellitus who Undergo Same-Day Surgery

ObjectiveTo assess the safety and effectiveness of a standardized glycemic management protocol in patients with diabetes mellitus who undergo same-day surgery.MethodsThe perioperative glycemic management protocol consisted of preoperative instructions and perioperative order sets for management of subcutaneous and intravenous insulin. Patients with known diabetes admitted to same-day surgery during a 10-month period were observed. Patient demographic information and all capillary blood glucose (CBG) values obtained during the sameday surgery visit were collected. Hyperglycemia, defined as a CBG concentration of 200 mg/dL or greater, prompted notification of the attending anesthesiologist. While use of the perioperative order sets was encouraged, the attending anesthesiologist retained the prerogative to treat according to these order sets or their usual care. Physician compliance with the standardized order sets was determined by chart review in the patients who had a documented blood glucose value of 200 mg/dL or greater.ResultsPatients managed with the standardized order sets had greater reductions in CBG values (percentage change, 35 ± 20.5% vs 18 ± 24%, P < .001) and lower postoperative CBG values (186 ± 53 mg/dL vs 208 ± 63 mg/dL, P < .05) than patients who received usual care. No cases of intraoperative or postoperative hypoglycemia (CBG < 70 mg/dL) were observed in either group.ConclusionsA systematic approach to glycemic management that includes instructions for preoperative adjustments to home diabetic medications and order sets for treatment of perioperative hyperglycemia is safe and can be more effective than usual care for ambulatory surgery patients with diabetes. (Endocr Pract. 2011;17:404-411)     

Knowledge,Attitudes, and Decision Making in Hospital Glycemic Management: are Faculty up to Speed?

Objective: Knowledge and confidence deficits in the management of hospital glucose abnormalities are prevalent among resident physicians. However, it is unclear whether such gaps prevail among faculty within different professional fields. In this study, we examined faculty knowledge and explored perceptions of challenges related to the management of inpatient hyperglycemia and diabetes.Methods: We conducted a survey that examined management decisions about inpatient hyperglycemia and diabetes among Medicine, Medicine/Pediatrics, Family and Community Medicine, Surgery, and Neurology faculty clinicians. All participating faculty had teaching and patient care responsibilities.Results: Responses from 69 faculty participants revealed gaps in several areas, including biomedical and contextual knowledge, familiarity with resources, clinical decision making, and self-efficacy. We identified important factors perceived as barriers to optimal glycemic management in the inpatient settings.Conclusion: The results of this study enhance our insight about the limitations existing among faculty related to the management of hyperglycemia and diabetes in hospitalized patients. We suggest that these barriers may impede optimization of patient care. Faculty play a crucial role in the clinical decision-making process and quality of care delivered by trainees. Therefore, attending physicians are likely to impact trainees' clinical performance and competency in the management of inpatient diabetes during training and beyond. Education in this subject should be a priority among trainees and faculty alike.Abbreviation: ICU = intensive care unit     

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)     

Effectiveness of a Spanish Language Clinic for Hispanic Youth with Type 1 Diabetes

ObjectiveA pilot study was undertaken to determine whether establishment of a Spanish Language Diabetes Clinic (SLDC) for Spanish-speaking families conducted by a team of Spanish-speaking, Hispanic and nonHispanic clinicians provides a means to improve control of type 1 diabetes (T1D).MethodsThe first 21 Hispanic pediatric patients with T1D who enrolled in the SLDC were matched to 21 Hispanic patients treated in the English Language Diabetes Clinic (ELDC) based on age and duration of diabetes. The two groups did not differ significantly with respect to gender, body mass index (BMI), or glycated hemoglobin (HbAlc). Patients in both groups were followed for 12 months.ResultsThe mean (± standard deviation) baseline glycated hemoglobin (HbA1c) level in the SLDC group (8.4 ± 1.0%) was similar to that in the ELDC group (8.6 ± 1.4%, P = .83). HbA1c levels fell by 0.5 ± 1.0% (P = .01) during the year following enrollment in the SLDC but did not change significantly from baseline during the year of follow-up in the ELDC group (decrease of 0.2 ± 0.9%, P = .1). At the start of the study, only 5 patients (23%) in the SLDC group and 7 patients (33%) in the ELDC group met the ≤7.5% target HbAlc level. After 1 year, 10 of the SLDC patients (48%) and 4 of ELDC patients (19%) had HbAlc levels ≤7.5% (P = .01).ConclusionOur preliminary findings support the hypothesis that overcoming language barriers by the establishment of a SLDC can be an effective means of improving metabolic control in youth with T1D in Hispanic families with limited English language skills. (Endocr Pract. 2013;19:800-804)     

Patient Understanding of Discharge Instructions for Home Diabetes Self-Management and Risk for Hospital Readmission and Emergency Department Visits

ObjectiveThe primary objective of this study was to examine the patient comprehension of diabetes self-management instructions provided at hospital discharge as an associated risk of readmission.MethodsNoncritically ill patients with diabetes completed patient comprehension questionnaires (PCQ) within 48 hours of discharge. PCQ scores were compared among patients with and without readmission or emergency department (ED) visits at 30 and 90 days. Glycemic measures 48 hours preceding discharge were investigated. Diabetes Early Readmission Risk Indicators (DERRIs) were calculated for each patient.ResultsOf 128 patients who completed the PCQ, scores were similar among those with 30-day (n = 31) and 90-day (n = 54) readmission compared with no readmission (n = 72) (79.9 ± 14.4 vs 80.4 ± 15.6 vs 82.3 ± 16.4, respectively) or ED visits. Clarification of discharge information was provided for 47 patients. PCQ scores of 100% were achieved in 14% of those with and 86% without readmission at 30 days (P = .108). Of predischarge glycemic measures, glycemic variability was negatively associated with PCQ scores (P = .035). DERRIs were significantly higher among patients readmitted at 90 days but not 30 days.ConclusionThese results demonstrate similar PCQ scores between patients with and those without readmission or ED visits despite the need for corrective information in many patients. Measures of glycemic variability were associated with PCQ scores but not readmission risk. This study validates DERRI as a predictor for readmission at 90 days.     

Effect of Sitagliptin on Post-Prandial Glucagon and GLP-1 Levels in Patients With Type 1 Diabetes: Investigator-Initiated,Double-Blind,Randomized, Placebo-Controlled Trial

ObjectivePeripheral insulin resistance in type 1 diabetes may be related to a paradoxical postprandial glucagon increase. This study evaluated the effects of sitagliptin (dipeptidyl peptidase-IV [DPP-IV] inhibitor, approved for patients with type 2 diabetes), in adults with type 1 diabetes to improve glycemic control through decreasing postprandial glucagon.MethodsThis investigator-initiated, double-blind, randomized-parallel 20-week study enrolled 141 subjects. Subjects received sitagliptin 100 mg/day or placebo for 16 weeks. A subset of 85 patients wore blinded continuous glucose monitors (CGM) for 5 separate 7-day periods. The primary outcome was post-meal (Boost™) reduction in 4-hour glucagon area under the curve (AUC). Secondary endpoints included changes in glycated hemoglobin (A1c), CGM data, insulin dose, glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic peptide (GIP), and C-peptide levels.ResultsThere were no differences at screening between groups; however, after a 4-week run-in phase, A1c was significantly lower in the sitagliptin vs. placebo group. Post-meal GLP-1 levels were higher (P<.001) and GIP levels lower (P = .03), with glucagon suppression at 30 minutes (LS means 23.2 ± 1.9 versus 16.0 ± 1.8; P = .006) in the sitagliptin group at 16 weeks. There were no differences between the groups in change in A1c, insulin dose, weight, or C-peptide after 16 weeks of treatment. However, C-peptide positive patients randomized to sitagliplin had a non-significant trend toward decrease in A1c, mean glucose, and time spent in hyperglycemia.ConclusionSitagliptin use in type 1 diabetes did not change glucagon AUC, A1c, insulin dose, or weight despite post-meal rise in GLP-1 levels. C-peptide positive subjects treated with sitagliptin had a nonsignificant trend in decreasing hyperglycemia, which needs further evaluation. (Endocr Pract. 2013;19:19-28)     

Care Directed by a Specialty-Trained Nurse Practioner or Physician Assistant can Overcome Clinical Inertia in Management of Inpatient Diabetes

ObjectiveThe study’s objective was to determine the impact of care directed by a specialty-trained nurse practitioner (NP) or physician assistant (PA) on use of basal-bolus insulin therapy and glycemic control in a population of noncritically ill patients with diabetes.MethodsA retrospective review of diabetes patients evaluated between July 1, 2011 and December 31, 2011 was conducted. Patients cotreated by a specialty-trained NP/PA were compared with patients who did not receive such care.ResultsIn total, 171 patients with 222 hospitalizations were cotreated by an NP/PA and 543 patients with 665 hospitalizations were not. Patients with NP/PA involvement were younger, and had more frequent hyperglycemia, and had greater corticosteroid use than patients without NP/PA involvement (P < .01 for all). Basal-bolus insulin therapy was administered to 80% of patients with NP/PA involvement and 34% of patients without it (P < .01). After adjustment for age, sex, hyperglycemia measures, and corticosteroid use, the odds of basal-bolus insulin therapy being administered were increased significantly through NP/PA care (odds ratio, 3.66; 95% confidence interval, 2.36-5.67; P < .01). After adjustment for these variables and insulin regimen, NP/PA care was significantly correlated with lower mean point-of-care glucose levels at 24 hours before discharge (P = .042).ConclusionDiabetes care assisted by an NP/PA trained in inpatient diabetes management results in greater use of recommended basal-bolus insulin therapy and is correlated with lower mean glucose levels before discharge. Adapting this model for use outside an endocrinology consult service needs to be explored so that the expertise can be brought to a broader inpatient population with diabetes. (Endocr Pract. 2014;20:112-119)     

Diabetes and Hyperglycemia Quality Improvement Efforts in Hospitals in the United States: Current Status,Practice Variation,and Barriers to Implementation

ObjectiveTo determine the status of diabetes and hyperglycemia quality improvement efforts in hospitals in the United States.MethodsWe designed and administered a survey to a convenience sample of hospitals, and the responses were analyzed statistically.ResultsWe received 269 responses from 1,151 requested surveys. The sample was similar to hospitals in the United States on the basis of hospital type and geographic region (P = no significant difference) but not on the basis of number of beds (P < .001). Among responding hospitals, 39%, 21%, and 15% had fully implemented inpatient diabetes and hyperglycemia quality improvement programs for critically ill, non-critically ill, and perioperative patients, respectively. Moreover, 77%, 44%, and 49% had fully implemented protocols for hypoglycemia, hyperglycemic crises, and diabetic ketoacidosis, respectively. Variations in glucose target ranges were noted. The responding hospitals had no standard biochemical definition of hypoglycemia; 47% defined hypoglycemia as a glucose level ≤ 70 mg/dL, but 29%, 8%, 6%, and 4% used < 60, ≤ce:hsp sp="0.10"/>50, < 40, and < 80 mg/dL, respectively. Almost a third of reporting hospitals had no metric to track the quality of inpatient diabetes and hyperglycemia care. More than half (59%) indicated that they did not have an automated capability to extract and analyze glucose data. The most frequent barrier to implementing a glycemic control program was concern regarding hypoglycemia (61%).ConclusionHospitals are addressing the issue of inpatient diabetes and glycemic control but face obstacles to implementation of quality improvement programs and vary in their approach to management. Improving the consistency of glucose control practices within hospitals in the United States should help enhance patient care and safety. Future efforts to help hospitals overcome barriers to introducing glucose control programs could include developing standardized glycemic control metrics, improving data collection and reporting methods, and providing improved tools that enable clinicians to control glucose safely. (Endocr Pract. 2010;16:219-230)