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Objective To assess whether an electronic health record (EHR)-based diabetes intensification tool can improve the rate of A1C goal attainment among patients with type 2 diabetes and an A1C ≥8%. Methods An EHR-based tool was developed and sequentially implemented in a large, integrated health system using a four-phase, stepped-wedge design (single pilot site [phase 1] and then three practice site clusters [phases 2–4]; 3 months/phase), with full implementation during phase 4. A1C outcomes, tool usage, and treatment intensification metrics were compared retrospectively at implementation (IMP) sites versus nonimplementation (non-IMP) sites with sites matched on patient population characteristics using overlap propensity score weighting. Results Overall, tool utilization was low among patient encounters at IMP sites (1,122 of 11,549 [9.7%]). During phases 1–3, the proportions of patients achieving the A1C goal ( Conclusion Utilization of a diabetes intensification tool was low and did not influence rates of A1C goal attainment or time to treatment intensification. The low level of tool adoption is itself an important finding highlighting the problem of therapeutic inertia in clinical practice. Testing additional strategies to better incorporate, increase acceptance of, and improve proficiency with EHR-based intensification tools is warranted.

Aims Little is known about the impact of weight loss on developing comorbidities in patients with obesity in real-world settings. Understanding health benefits and associated comorbidities with weight loss are critical to addressing the global obesity health epidemic. This study aimed to determine health outcomes associated with weight loss in individuals with obesity, and to better understand the relationship between disease burden (i.e., prior comorbidities, healthcare utilization) and weight loss in individuals with obesity. Electronic health records (EHRs) represent an important resource to investigate these impacts. Materials and methods We conducted a case-control study using deidentified EHR-derived information from 204,921 patients seen at the Cleveland Clinic between 2000-2018. Patients were ≥20 years of age with BMI ≥30 kg/m2 and ≥7 weight measurements, over ≥3 years. Thirty outcomes were investigated, including chronic and acute diseases, as well as psychological and metabolic disorders. Weight change was investigated three, five, and ten years prior to an event. Results Weight loss was associated with reduced incidence of many outcomes (e.g., type 2 diabetes, non-alcoholic steatohepatitis/non-alcoholic fatty liver disease, obstructive sleep apnea, hypertension) (P 10% was associated with increased incidence of certain outcomes including stroke and substance abuse. However, many outcomes that increased with weight loss were attenuated by disease burden adjustments. Conclusions This study provides the most comprehensive real-world evaluation of health impacts of weight change to date. After comorbidity burden and healthcare utilization adjustments, weight loss was associated with an overall reduction in risk of many adverse outcomes. This article is protected by copyright. All rights reserved.

Objective. To assess whether an electronic health record (EHR) based diabetes intensification tool can improve the rate of A1C goal attainment among patients with type 2 diabetes and an A1C ≥8%. Methods. An EHR-based tool was developed and sequentially implemented in a large, integrated health system using a four-phase, stepped-wedge design (single pilot site [phase 1] and then three practice site clusters [phases 2–4]; 3 months/phase), with full implementation during phase 4. A1C outcomes, tool usage, and treatment intensification metrics were compared retrospectively at implementation (IMP) sites versus nonimplementation (non-IMP) sites with sites matched on patient population characteristics using overlap propensity score weighting. Results. Overall, tool utilization was low among patient encounters at IMP sites (1,122 of 11,549 [9.7%]). During phases 1–3, the proportions of patients achieving the A1C goal (P = 0.02). Implementation was not associated with mean A1C improvement from baseline (range −0.88 to −1.08%, IMP sites vs. non-IMP sites P ≥0.093). Times to intensification were similar between IMP and non-IMP sites. Conclusion. Utilization of a diabetes intensification tool was low and did not influence rates of A1C goal attainment or time to treatment intensification. The low level of tool adoption is itself an important finding highlighting the problem of therapeutic inertia in clinical practice. Testing additional strategies to better incorporate, increase acceptance of, and improve proficiency with EHR-based intensification tools is warranted.

OBJECTIVE To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of hemoglobin A1c (A1C) goal attainment. RESEARCH DESIGN AND METHODS This was a retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C >9%) were identified on the index date of 31 December 2016 (n = 6,973) and grouped by attainment (n = 1,653 [23.7%]) or nonattainment (n = 5,320 [76.3%]) of A1C RESULTS For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%), and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common antidiabetes medications. Only 1,653 (23.7%) patients achieved an A1C CONCLUSIONS A minority of patients with an A1C >9% achieved an A1C

OBJECTIVE To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of future severe hypoglycemia (SH). RESEARCH DESIGN AND METHODS From 2005 to 2017, we identified NSH events by diagnosis codes and NLP. We then built an SH prediction model. RESULTS There were 204,517 patients with type 2 diabetes and no diagnosis codes for NSH. Evidence of NSH was found in 7,035 (3.4%) of patients using NLP. We reviewed 1,200 of the NLP-detected NSH notes and confirmed 93% to have NSH. The SH prediction model (C-statistic 0.806) showed increased risk with NSH (hazard ratio 4.44; P < 0.001). However, the model with NLP did not improve SH prediction compared with diagnosis code–only NSH. CONCLUSIONS Detection of NSH improved with NLP in patients with type 2 diabetes without improving SH prediction.

Type 2 diabetes (T2D) has a strong association with atrial fibrillation (AF) which increases risk of thromboembolic events, heart failure, and frequent hospitalizations. Metformin is the first-line medication for T2D with proposed anti-inflammatory, pro-metabolic, and cardio-protective benefits. Our objective was to investigate if initial therapy with metformin is associated with reduced incidence of AF in comparison to other non-insulin anti-hyperglycemic agents in patients with newly diagnosed T2D.This retrospective cohort analysis included adults with a new diagnosis of T2D who were started on monotherapy (except insulin) between 2007 and 2017, without prior anti-hyperglycemic agent use, history of arrhythmias, or estimated GFR (eGFR) ≤ 30 ml/min. A multivariate analysis was performed using a fine-gray regression competing risk analysis to control for confounding variables after which pooled hazard ratios and 95 % confidence intervals were reported. Patients were followed until the end of study date, development of AF, addition of more anti-hyperglycemic agents, or death, whichever occurred first.Among 4584 metformin initiators compared to 1080 non-metformin monotherapy initiators, 10-year cumulative incidence of AF in metformin group was 5.2 % as compared to 8.1 % with other agents which was not statistically significant. Competing risk analysis did not demonstrate reduced rates of AF with metformin use (HR 0.92, 95 % CI 0.69 to 1.21; P = 0.55). Increased age and the presence of congestive heart failure were associated with significantly higher risk of AF in both groups (HR: 1.29, 95 % CI: 1.21 to 1.37; P ≤ 0.001; HR: 2.73, 95 % CI: 1.62 to 4.61; P ≤ 0.001, respectively).Initiation of metformin as a first line monotherapy for T2D, when compared to other non-insulin monotherapies, was not associated with decreased risk of developing AF in this retrospective observational study.

Objective Current type 2 diabetes (T2D) management contraindicates intensive glycemia treatment in patients with high cardiovascular disease (CVD) risk, and is partially motivated by evidence of harms in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Heterogeneity in response to intensive glycemia treatment has been observed, suggesting potential benefit for some individuals. Research Design and Methods ACCORD was a randomized controlled trial that investigated whether intensively treating glycemia in individuals with T2D reduced CVD outcomes. Using a novel approach to cluster HbA1c trajectories, we identified groups in the intensive glycemia arm with modified CVD risk. Genome-wide analysis and polygenic score (PS) were developed to predict group membership. Mendelian randomization was performed to infer causality. Results We identified four clinical groupings in the intensive glycemia arm, and clinical group 4 (C4) displayed fewer CVD outcomes (HR=0.34, P=2.01x10-3) and microvascular outcomes (HR=0.86, P=.015) than standard treatment. A single nucleotide polymorphism, rs220721, in MAS1, reached suggestive significance with C4 (P=4.34x10-7). The PS predicted C4 with high accuracy (AUC=0.98), and predicted C4 displayed reduced CVD risk on intensive versus standard glycemia treatment (HR=0.53, P=4.02x10-6), but not for microvascular outcomes (PP Conclusions We found evidence of a T2D clinical group in ACCORD that benefited from intensive glycemia treatment, and membership of this group can be predicted using genetic variants. This study generates new hypotheses with implications for precision medicine in T2D and represents an important development for this landmark clinical trial warranting further investigation.

OBJECTIVE Current type 2 diabetes (T2D) management contraindicates intensive glycemia treatment in patients with high cardiovascular disease (CVD) risk and is partially motivated by evidence of harms in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Heterogeneity in response to intensive glycemia treatment has been observed, suggesting potential benefit for some individuals. RESEARCH DESIGN AND METHODS ACCORD was a randomized controlled trial that investigated whether intensively treating glycemia in individuals with T2D would reduce CVD outcomes. Using a novel approach to cluster HbA1c trajectories, we identified groups in the intensive glycemia arm with modified CVD risk. Genome-wide analysis and polygenic score (PS) were developed to predict group membership. Mendelian randomization was performed to infer causality. RESULTS We identified four clinical groupings in the intensive glycemia arm, and clinical group 4 (C4) displayed fewer CVD (hazard ratio [HR] 0.34; P = 2.01 × 10−3) and microvascular outcomes (HR 0.86; P = 0.015) than those receiving standard treatment. A single-nucleotide polymorphism, rs220721, in MAS1 reached suggestive significance in C4 (P = 4.34 × 10−7). PS predicted C4 with high accuracy (area under the receiver operating characteristic curve 0.98), and this predicted C4 displayed reduced CVD risk with intensive versus standard glycemia treatment (HR 0.53; P = 4.02 × 10−6), but not reduced risk of microvascular outcomes (P < 0.05). Mendelian randomization indicated causality between PS, on-trial HbA1c, and reduction in CVD outcomes (P < 0.05). CONCLUSIONS We found evidence of a T2D clinical group in ACCORD that benefited from intensive glycemia treatment, and membership in this group could be predicted using genetic variants. This study generates new hypotheses with implications for precision medicine in T2D and represents an important development in this landmark clinical trial warranting further investigation.

Diabetes risk increases with age due to changes in β-cell function and increased insulin resistance and is one of the most common chronic medical conditions in the elderly. Diabetes management in this population requires a multidisciplinary, patient-centric approach due to wide heterogeneity in patients' health and functional capacities. Meticulous assessment of each patient before formulating a regimen and thorough patient education are keys to success in achieving glycemic goals, which should be individualized. Lifestyle modification is recommended for every patient.

Objective: To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of A1C goal attainment. Research Design and Methods: Retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C>9%) were identified on the index date of 12/31/2016 (n=6,973), grouped by attainment (n=1,653 [24.7%) or non-attainment (n=5,320 [76.3%]) of A1C Results: For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%) and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common anti-diabetes medications. Only 1,653 (24%) patients achieved an A1C Conclusions: A minority of patients with an A1C>9% achieved an A1C

Guidelines recommend individualized treatment for patients with type 2 diabetes (T2D), avoidance of clinical inertia, and specific therapeutic choices for patients at risk for cardiovascular disease, congestive heart failure, or chronic kidney disease. However, a gap exists in translating these guidelines into practice. We created an electronic medical record (EMR) tool to improve evidence-based treatment intensification for T2D and studied its implementation in endocrinology and primary care (PC). The tool included a best practice alert (BPA) informing providers at an office visit of an A1C ≥ 8% and prompted providers, within the tool, to make therapeutic choices based upon five priority care goals- cardiovascular risk reduction, A1c lowering, low hypoglycemia risk, cost, or weight loss. After a 3-month pilot at one site, the tool was implemented using a stepped-wedge approach from March-November 2019 to all PC (N=52) and endocrinology (N=17) sites in our health system with 1903 eligible patient visits by November 2019. Within endocrinology, provider tool usage ranged from 94% of visits at the pilot site to 34% after full rollout; in PC, usage ranged from 52% during the pilot to just above 5%. Usage varied by practice site (range Uptake of a point of care EMR tool to promote treatment intensification for T2D in endocrinology and PC demonstrated variation at the specialty, practice site, and provider levels. Our findings also suggest that, given time pressures, provider focused point of care EMR-based interventions to improve T2D care may need to be supplemented with tools asynchronous to the office visit and should address patient factors in adherence. Further analyses will focus on tool effects on A1c control. Disclosure A.D. Misra-Hebert: Research Support; Self; Agency for Healthcare Research and Quality, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk Inc. K.M. Pantalone: Consultant; Self; Bayer Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. Speaker’s Bureau; Self; AstraZeneca, Merck & Co., Inc., Novo Nordisk Inc. S. Rajpathak: Employee; Self; Menarini Group. T. Weiss: Employee; Self; Merck & Co., Inc. M. Hamaty: Research Support; Self; Merck & Co., Inc. R.S. Zimmerman: Research Support; Self; Bayer U.S., Merck & Co., Inc., Novo Nordisk A/S. Speaker’s Bureau; Self; LifeScan, Inc., Merck & Co., Inc. Stock/Shareholder; Self; Baxter, Bristol-Myers Squibb, Pfizer Inc., Procter & Gamble Company.

Background: Atrial fibrillation (AF) is the most frequent cardiac arrhythmia and is associated with an increased risk of thromboembolic events, heart failure, and frequent hospitalizations. Type 2 diabetes mellitus (T2DM) has one of the strongest associations with AF with an overall 35% increased risk. Metformin is the first-line medication for T2DM and it has been proposed to have anti-inflammatory, pro-metabolic and cardioprotective benefits, but its effect on AF is not well studied. Our objective was to investigate whether the initial metformin monotherapy was associated with reduced AF rates compared to other non-insulin agents. Methods: This retrospective cohort analysis involved adults with newly diagnosed T2DM between 2007 and 2017, without any history of arrhythmias or contraindications to metformin use including GFR less than 30 ml/min who initiated a single antidiabetes therapy (except insulin). A multivariate analysis was performed to control for other variables that may have impacted the association between initial therapy with metformin and the outcomes of interest. Results: Out of 42384 cases with newly diagnosed diabetes, 5664 patients met the inclusion criteria. The majority of patients initiated monotherapy with metformin (81%), followed by sulfonylureas (13%) and thiazolidinediones (4%). The 10-year cumulative incidence of AF in the metformin group was 5.2% vs. 8.1% with others. Competing risk analysis did not demonstrate reduced rates of AF with metformin use (HR 0.92 95% CI 0.69 to 1.21; P = 0.55). Increased age and the presence of CHF were associated with significantly higher risk of AF (HR: 1.29, 95% CI: 1.21 to 1.37; P Conclusion: In this observational study following patients with newly diagnosed T2DM, first-line therapy with metformin, when compared to other non-insulin antidiabetes therapies, was not found to be associated with a decreased risk of developing AF. Disclosure Z. Tekin: None. A. Milinovich: Research Support; Self; Novartis AG, Novo Nordisk Inc. X. Ji: Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. J. Bauman: None. M. Kattan: Consultant; Self; GlaxoSmithKline plc. Research Support; Self; Boehringer Ingelheim (Canada) Ltd., Novo Nordisk Inc. K.M. Pantalone: Consultant; Self; Bayer Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. Speaker’s Bureau; Self; AstraZeneca, Merck & Co., Inc., Novo Nordisk Inc. R.S. Zimmerman: Research Support; Self; Bayer U.S., Merck & Co., Inc., Novo Nordisk A/S. Speaker’s Bureau; Self; LifeScan, Inc., Merck & Co., Inc. Stock/Shareholder; Self; Baxter, Bristol-Myers Squibb, Pfizer Inc., Procter & Gamble Company. M.K. Chung: None. S. Kashyap: Other Relationship; Self; GI Dynamics Inc.

AIMS To assess the effects of 'clinical' and 'intensification inertia' by evaluating the impact of different intensification interventions on the probability of HbA1c goal attainment using real-world data. METHODS Electronic health records (Cleveland Clinic, 2005-2016) were used to identify 7389 people with Type 2 diabetes mellitus and HbA1c ≥53 mmol/mol (≥7.0%), despite a stable regimen of two oral antihyperglycaemic drugs for ≥6 months. The participants were stratified by index HbA1c and analysed over a 6-month period for pharmacological intensification, and then for 12 additional months for HbA1c goal attainment (

Objective: To determine if natural language processing (NLP) improves detection of non-severe hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes, and to measure if NLP detection improves the prediction of future severe hypoglycemia (SH). Research Design and Methods: From 2005-2017, we identified NSH events by diagnosis codes and NLP. We then built an SH prediction model. Results: There were 204,517 patients with type 2 diabetes and no diagnosis codes for NSH. Evidence of of NSH was found in 7035 (3.4%) using NLP. We reviewed 1200 of the NLP-detected NSH notes and confirmed 93% to have NSH. The SH prediction model (C-statistic 0.806) showed increased risk with NSH (Hazard Ratio=4.44, p Conclusions: Detection of NSH improved with NLP in patients with type 2 diabetes without improving SH prediction.

Allgrove’s syndrome is an inherited condition caused by mutations in the AAAS gene (encoding the protein ALADIN) and is inherited in an autosomal recessive pattern (1). It classically is characterized by three specific features: achalasia, Addison’s disease, and alacrima (reduced or absent ability to secrete tears). This has led to the name “Triple A syndrome”, and some have suggested a 4th ‘A’ of autonomic disturbance (2). It is important to note that the phenotype of this condition is variable, and some patients may have all three (or four) of the manifestations at initial presentation, and that other patients may develop or have worsening of the ‘As’ over time. In this clinical vignette, we present a patient with Allgrove’s syndrome who developed clinical manifestations of the third ‘A’ of Addison’s disease later in life. A 46-year-old female patient presented to our tertiary referral center for follow-up of Allgrove’s disease after having been diagnosed with genetic testing as an adolescent. Prior to presentation, she underwent esophagectomy in 1995 and additionally had confirmed alacrima with ophthalmology. She was undergoing annual surveillance testing with 8 am cortisol and ACTH stimulation testing to monitor for the development of adrenal insufficiency. Prior to consultation, her baseline cortisol was 8.7 ug/dL. At presentation and the age of 46, her ACTH stimulation test (0.25 mg cosyntropin, 3 timepoints) was positive for adrenal insufficiency with a baseline cortisol of < 0.5 ug/dL (8 am), with 30-minute value of 4.4 ug/dL and 60-minute value of 6.3 ug/dL (peak). She was started on replacement dosing of hydrocortisone 20 mg at 8 am and 10 mg at 2 pm, in addition to calcium and vitamin D supplementation. Of note, her adrenal antibody (21-hydroxylase antibodies) were negative on two separate occasions. Allgrove’s syndrome is a rare condition described by the development of three, or at times four, characteristics with support of genetic testing. This case demonstrates that patients with Allgrove’s syndrome can present with two clinical manifestations of the condition (alicrima and achalasia) and develop the third (adrenal insufficiency) later in life. Therefore, regular screening for the missing clinical manifestation of this disease should be considered. References: 1. National Institute of Health: Genetic and Rare Disease Information Center. Triple A Syndrome. Genetics Home Reference. February 2010; http://ghr.nlm.nih.gov/condition/triple-a-syndrome. Accessed 2/1/2020. 2. Kimber J, McLean BN, Prevett M, Hammans SR. Allgrove or 4 “A” syndrome: an autosomal recessive syndrome causing multisystem neurological disease. J Neurol Neurosurg Psychiatry. 2003;74:654-657.

Background: Ring chromosome 13 is a rare genetic disorder in which the two ends of chromosome 13 are fused together to form a ring shape. Ring formation subsequently leads to gene deletions on both the long and short arms of the chromosome. Observed phenotypes among these patients are variable due to differences in the number of genetic deletions that occur with fusion. Common clinical features seen in ring chromosome 13 include micro- or anencephaly, severe mental retardation (MR), ambiguous genitalia, growth retardation, and facial dysmorphism. To our knowledge, diabetes mellitus (DM) has only been reported in two published case reports of patients with ring chromosome 13. It has been proposed that development of DM in this syndrome may be due to deletion of the IRS2 gene on the long arm of chromosome 13. This hypothesis is based on evidence from knockout mice studies and genetic comparisons of ring chromosome 13 patients with and without DM. Clinical Case: We present a case of a 23-year-old woman with a known history of mosaic ring chromosome 13 abnormality who was diagnosed with DM at age 21. Diagnosis was made incidentally based on laboratory data obtained at a routine outpatient visit. Hemoglobin A1c at that time was 13.1%. Glutamic acid decarboxylase and insulin antibodies were negative. She has been on a basal-bolus insulin regimen since diagnosis with overall good glycemic control (average hemoglobin A1c 6.5%). She has no known micro- or macrovascular complications of DM. She has no family history of chromosome 13 syndrome or DM. Other notable clinical features associated with her ring chromosome 13 disorder include MR, spastic encephalopathy, delayed puberty (menarche at age 18), scoliosis, facial dysmorphism, and deficiencies in clotting factors 7 and 10. Conclusion: DM is a common disorder that is typically multifactorial in etiology. In rare cases, DM can be the result of monogenic mutations or deletions. We present a case of a young woman with early-onset antibody-negative DM thought to be related to gene deletions resulting from her underlying ring chromosome 13 abnormality. There is some evidence from prior case reports and rodent studies to suggest that DM in patients with this disorder may be the result of IRS2 deletion from the long arm of chromosome 13. Although DM is a rare complication of ring chromosome 13 disorder, early screening should be considered in these patients to prevent development of downstream complications. References: 1. Babaya N, Noso S, Hiromine Y, Ito H, Taketomo Y, Yamamoto T, Kawabata Y, Ikegami H. Early-Onset Diabetes Mellitus in a Patient With a Chromosome 13q34qter Microdeletion Including IRS2. J Endocr Soc. 2018 Sep 11;2(10):1207-1213. 2. Lagergren M, Börjeson M, Mitelman F. Prophase analysis of ring chromosome 13--an attempt at phenotype-karyotype correlation. Hereditas. 1980;93(2):231-3.

Background: Glycogen storage disease type 1b (GSD1b) is caused by a deficiency of glucose 6 phosphatase leading to glycogen deposition. The hallmark findings of GSD1b are hypoglycemia and lactic acidosis. GSD1b can be associated with hepatomegaly, hypertriglyceridemia, hematologic abnormalities, hypothyroidism, inflammatory bowel disease, proteinuria, and hypoglycemic seizures. Main stay of therapy is to avoid fasting and to ingest frequent feeds high in complex CHO. Raw cornstarch (CS) has been used for the treatment of hypoglycemia in GSD1b since the early 1980s. CS is digested slowly, providing a steady release of glucose allowing for more stable glucose levels over a longer period of time as compared with other sources of CHO. Adults may require more CS to maintain BG >70 mg/dL and lactate Clinical Case: A 31 year old female with a history of GSD1b complicated by hypoglycemia, Crohn’s disease, chronic pancreatitis and neutropenia was admitted for abdominal pain, emesis and inability to tolerate CS. She was made NPO and was started on a dextrose drip to avoid hypoglycemia and hyperlactatemia. The rate of dextrose infusion was adjusted to maintain lactate levels Conclusion: We report a rare case of GSD1b and diabetes. The pathogenesis may be related to effects of chronic pancreatitis or metabolic syndrome. Treatment of hyperglycemia in patients with GSD1b is challenging given the heightened risk of fasting hypoglycemia. Treatment options are limited, and there are no data regarding the safe use of insulin in this patient population.

Objective: Titration of desmopressin can be challenging during complex, lengthy surgical procedures in patients with chronic central diabetes insipidus (DI). Arginine vasopressin (AVP) may be the preferred treatment modality in these settings. No data currently exist on the use of AVP during lengthy operations.Methods: We report a novel AVP infusion protocol for the management of chronic DI during a 27-hour total facial transplantation surgery.Results: A 21-year-old woman was admitted for a total facial transplantation surgery. Her medical history was significant for severe facial injuries and panhypopituitarism, both secondary to a ballistic trauma sustained 3 years prior. For the management of her chronic central DI during the complex surgery, a unique AVP infusion protocol was developed. Intraoperatively, the infusion was adjusted hourly following an internally developed algorithm with pre-specified goal parameters for urine output (50 to 200 mL/hour) and serum sodium levels (136 to 144 mmol/L; reference range: 136 to 144 mmol/L). The short half-life of AVP provided ease of dose titration. Under this protocol, the patient's hemodynamic values and serum sodium levels remained stable throughout the 27-hour transplantation surgery.Conclusion: We describe the successful use of a novel AVP infusion protocol for the management of DI during a 27-hour facial transplantation surgery. This protocol may also be effective in managing other patients with chronic central DI during lengthy intraoperative periods.Abbreviations: AVP = arginine vasopressin; DDAVP = 1-deamino-8-D-arginine vasopressin; DI = diabetes insipidus

BACKGROUND The aim of the present study was to assess the longitudinal accumulation of diabetes-related complications and the effect of glycemic control on the Diabetes Complications Severity Index (DCSI) score in people with newly diagnosed type 2 diabetes (T2D). METHODS A retrospective cohort study was conducted using electronic health records from a large integrated healthcare system. People with newly diagnosed T2D were identified between 2005 and 2016 and stratified by initial HbA1c category (

Aims To assess the potential impact of glucagon-like peptide-1 receptor agonist (GLP-1RA) exposure on cardiovascular disease (CVD) and mortality outcomes in patients with type 2 diabetes (T2D), using a large retrospective cohort. Research Design and Methods Patients who had T2D between 2005 and 2014 (N = 105 862) were identified from the electronic health record system at Cleveland Clinic using a validated electronic phenotype. A time-dependent, Cox, multiple regression analysis was used to assess the association between GLP-1RA exposure and risk of acute myocardial infarction (AMI), stroke/cerebrovascular accident (CVA), and overall mortality, as well as the composite of all three outcomes. The findings were further evaluated by assessing the effect of GLP-1RAs on the same variables in patients with and without prior CVD. The model adjusted for differences in demographic information, hypertension, laboratory/vital signs, history of outcomes, and T2D medications. Results There were significantly lower rates of AMI (hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.65 to 0.99; P = .045), CVA (HR 0.82, 95% CI 0.74 to 0.91, P

Objective: Clomiphene citrate-induced hypertriglyceridemia causing acute pancreatitis is rare. The aim of this case report is to alert physicians to the possibility of clomiphene citrate-induced hypertriglyceridemia that can lead to acute, and even chronic, pancreatitis.Methods: We describe a patient with known mild hypertriglyceridemia who presented with acute pancreatitis and severe hypertriglyceridemia after initiation of clomiphene citrate.Results: The patient had mid-epigastric tenderness with radiation around her bilateral flanks in a band-like distribution. Lab studies showed a triglyceride level greater than 4,425 mg/dL, a lipase level greater than 3,000 U/L, and computed tomography of the abdomen showed acute interstitial edematous pancreatitis. The patient's Naranjo Adverse Drug Reaction score was calculated to be a 7, and was therefore probable as clomiphene being the causative agent. The patient's triglyceride levels improved after initiation of fibrate therapy and discontinuation of clomiphene at first; however, she continued to develop acute episodes of pancreatitis that progressed to chronic pancreatitis despite stopping clomiphene citrate. This is the second report of recurrent pancreatitis with hypertriglyceridemia induced by clomiphene citrate and, in this case specifically, each episode of pancreatitis was associated with hypertriglyceridemia.Conclusion: Clomiphene citrate-induced hypertriglyceridemia rarely occurs and can progress to acute, and even chronic, pancreatitis with significant morbidity. Clomiphene citrate should be used with caution in patients with elevated triglycerides, and should be avoided in patients with triglyceride levels greater than 400 mg/dL.

Background/Aim Episodes of non-severe hypoglycemia can be captured through diagnoses documented in the electronic medical record. We aimed to create a clinically useful prediction model for a severe hypoglycemia event, requiring an emergency department visit or hospitalization, in patients with Type 2 diabetes with a history of non-severe hypoglycemia. Methods Using electronic medical record data from 50,439 patients with Type 2 diabetes in one health system, number of severe hypoglycemia events and associated patient characteristics from 2006 to 2015 were previously defined. Using the landmarking method, a dynamic prediction model was built using the subset of 1876 patients who had a documented non-severe hypoglycemia diagnosis code, using logistic regression to obtain landmark-specific odds of severe hypoglycemia in this group. For model performance, the bootstrap procedure was employed for internal validation and area under the curve (AUC) and index of prediction accuracy (IPA) were calculated. Results Glycosylated hemoglobin (HbA1c) less than 7% (53 mmol/mol) was associated with increased odds ratio (OR) of severe hypoglycemia at 3 months (OR 1.92 95% Confidence Interval (CI) 1.19–3.10 at HbA1c 5% (31 mmol/mol) and OR 1.21, CI 1.03–1.41 at HbA1c 6%(42 mmol/mol).) History of non-severe hypoglycemia within the past 3 months increased odds for severe hypoglycemia (OR 2.58 95% CI 1.80–3.70) as did Black race, insulin use with the past 3 months, and comorbidities. Metformin and sulfonlylurea use in the past 3 months, increasing age and body mass index had lower odds of a future severe hypoglycemia event. For the prediction model for 3 month risk of severe hypoglycemia, the AUC was 0.890 (CI 0.843–0.907) and the IPA was 10.8% (CI 4.4% - 12.4%). Conclusion In patients with a documented diagnosis of non-severe hypoglycemia, a dynamic prediction model identifies patients with Type 2 diabetes with 3-month increased risk of severe hypoglycemia, allowing for preventive efforts, such as medication changes, at the point of care.

An electronic health record (EHR)-based tool was developed for EPIC My Practice at Cleveland Clinic to aid treatment decisions and combat therapeutic inertia in patients with type 2 diabetes (T2D) and suboptimal glycemic control (A1C ≥8%). The tool consists of three separate components activated during an office visit: a best practice alert (BPA) if a patient had an A1C ≥ 8% within the past 6 months, a Smartform (patient summary and order entry form), and a Smartset for T2D medications to achieve patient-centered treatment goals, supplies, laboratory, and consult orders. The provider may acknowledge the BPA and pursue therapy intensification or defer. The tool was piloted for 3 months (primary care providers (PCP) n=12, endocrinology providers n=5). BPA acknowledgement and utilization practices were recorded by specialty. The CollaboRATE survey (3 items, scale 0-9) was used to assess patient perceptions of shared decision-making afforded by the tool. The BPA appeared for 420/1,766 T2D patients at an office-based encounter with a PCP or endocrinology provider. While the BPA was acknowledged at most endocrinology visits (95%) and approximately 50% of primary care visits, use of all three components of the tool only occurred in ∼10% of eligible encounters. The CollaboRATE survey was administered to a subset of 83 patients exposed to the tool. Most chose the highest rating for questions assessing if efforts were made to: 1. help them better understand their health issue (87%), 2. listen to what matters most to them about their health issue (93%) and 3. integrate what matters to them into next steps (92%). Use of an EHR-based tool to aid treatment decisions is variable by specialty, though appears to lead to a high perception of shared decision-making for T2D patients. Additional provider education and improved incorporation of the tool into PCP work-flow may help to address therapeutic inertia in routine clinical practice. Disclosure K.M. Pantalone: Consultant; Self; Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. Speaker's Bureau; Self; AstraZeneca, Merck & Co., Inc., Novo Nordisk Inc. A.D. Misra-Hebert: Research Support; Self; Agency for Healthcare Research and Quality, Merck & Co., Inc., Novo Nordisk Inc. S. Rajpathak: None. T. Weiss: Employee; Self; Merck & Co., Inc. M. Hamaty: Consultant; Self; Applied Clinical Intelligence, LLC. R.S. Zimmerman: Consultant; Self; Novo Nordisk Inc. Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. Speaker's Bureau; Self; Johnson & Johnson Diabetes Institute, Merck & Co., Inc.

Background: Comprehensive medication management (CMM) ensures an individualized plan for medication appropriateness, effectiveness, safety, and adherence. It is most often performed by pharmacists within a pharmacist-physician collaborative agreement. Published studies on CMM are few and mostly conducted in primary care settings. The aim of our study was to determine the impact of CMM on the proportion of patients that achieve ≥ 1% A1c reduction in an interprofessional specialty clinic. Methods: This is a retrospective study comparing 2 groups: group 1-without pharmacist collaboration, group 2-with pharmacist collaboration. Subjects were adults with diabetes and most recent A1c ≥ 8.5% with at least one visit in the interprofessional endocrinology clinic between 1/2016-12/2017. Exclusion criteria were pregnancy, no A1c within 6 weeks of initial visit, and no follow-up A1c. The 2 groups were matched for initial A1c, type of diabetes, age, and BMI. Results: A total of 162 participants were included. Baseline characteristics were similar between groups: Group 1: (mean age: 57.6 ± 15.8 years, BMI: 34.3 ± 8.1 kg/m2, A1c: 10.2 ± 1.2%, T1DM: 26%), Group 2 (mean age: 56.0 ±16.4 years, BMI: 32.6 ± 8.1 kg/m2, A1c: 10.1± 1.3%, T1DM: 26%). The percentage of subjects achieving ≥1% A1c reduction at 6 months was 58.0% in Group 2 compared to 40.7% in Group 1, p=0.041. More subjects achieved A1c < 8% in group 2 (32.1%) vs. Group 1 (18.5%), p=0.047. The frequency of endocrinologist visits was more in group 1 (2.37/patient) vs. group 2 (1.89/patient), p=0.01. Group 2 averaged 3.0 pharmacist visits per patient. Discussion: Physician-pharmacist collaboration led to greater A1c reduction compared to usual endocrinologist care in patients with uncontrolled A1c. However, frequency of total provider visits may account for some differences. Overall, utilizing pharmacists within diabetes health care models may reduce frequency of endocrinologist visits while improving glycemic control. Disclosure D. Isaacs: Advisory Panel; Self; BD, Sanofi-Aventis. R.S. Zimmerman: Consultant; Self; Novo Nordisk Inc. Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. Speaker's Bureau; Self; Johnson & Johnson Diabetes Institute, Merck & Co., Inc. M. Lansang: None.

Background: T2D management is shifting toward treating patients with therapies that align with their level of CV and end-organ risk. To this end, evidence-based guidelines now recommend glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for both glycemic and extraglycemic benefits. The great speed with which these recommendations change create immediate gaps in knowledge and competence, especially as they relate to managing patients with comorbid CV and/or renal disease. To help clinicians understand GLP-1 RA therapies and their novel characteristics in practice, we developed a decision support tool where choice of treatment among GLP-1 RAs is guided by a panel of experts. Methods: We developed a decision support tool with guidance from 5 experts who provided therapy recommendations for 48 unique patient case scenarios based on patient variables including CVD, CKD, retinopathy, A1C level, and need for weight loss. Clinician learners are prompted to specify a patient scenario using these variables before selecting an intended therapy. After all questions are completed for a patient scenario, the tool displays what the panel of experts recommend and then asks the learner if this information changed their intended choice. Results: From February through October 2020, 983 learners entered 1433 unique patient case scenarios. Of these, 365 were anonymous and 623 were authenticated, of which 70% (n = 437) were from the US; 50% (n = 310) were MDs; 22% (n = 135) were nurses, NPs, or PAs; and 19% (n = 121) were PharmDs. The intended therapy of learners differed from the experts in 34% (n = 489) of cases and were limited to 3 categories: cases in which learners chose to use exenatide (17%), cases in which they chose to use a GLP-1 RA in conjunction with insulin (12%), or cases in which they were unsure (71%). Of note, of the 93 cases in which learners chose exenatide, 68% (n = 63) were cases with CVD and/or CKD, where exenatide was not recommended by experts. Similarly, of the 89 cases in which learners chose insulin with a GLP-1 RA, 57% (n = 51) were cases with A1C < 9%, where insulin was not recommended by experts. Of cases in which learners’ intended therapy differed from the experts’ (and they indicated the impact of the tool), 52% indicated that they planned to change their treatment plan. Conclusion: This tool highlights continuing gaps in clinicians’ ability to select among GLP-1 RAs for T2D. Using a decision support tool can positively influence practice behaviors: Learners can see if their intended treatment choice is congruent with a panel of experts and change plans as appropriate.

OBJECTIVE “Clinical inertia” has been used to describe the delay in the intensification of type 2 diabetes treatment among patients with poor glycemic control. Previous studies may have exaggerated the prevalence of clinical inertia by failing to adequately monitor drug dose changes and nonmedication interventions. This project evaluated the intensification of diabetes therapy and hemoglobin A1c (A1C) goal attainment among patients with newly diagnosed type 2 diabetes when metformin monotherapy failed. RESEARCH DESIGN AND METHODS The electronic health record at Cleveland Clinic was used to identify patients with newly diagnosed type 2 diabetes between 2005 and 2013 who failed to reach the A1C goal after 3 months of metformin monotherapy. A time-dependent survival analysis was used to compare the time until A1C goal attainment in patients who received early intensification of therapy (within 6 months of metformin failure) or late intensification. The analysis was performed for A1C goals of 7% (n = 1,168), 7.5% (n = 679), and 8% (n = 429). RESULTS Treatment was intensified early in 62%, 69%, and 72% of patients when poor glycemic control was defined as an A1C >7%, >7.5%, and >8%, respectively. The probability of undergoing an early intensification was greater the higher the A1C category. Time until A1C goal attainment was shorter among patients who received early intensification regardless of the A1C goal (all P < 0.05). CONCLUSIONS A substantial number of patients with newly diagnosed type 2 diabetes fail to undergo intensification of therapy within 6 months of metformin monotherapy failure. Early intervention in patients when metformin monotherapy failed resulted in more rapid attainment of A1C goals.

Many employers offer worksite wellness programs, including financial incentives to achieve goals. Evidence supporting such programs is sparse.To assess whether diabetes and cardiovascular risk factor control in employees improved with financial incentives for participation in disease management and for attaining goals.Retrospective cohort study using insurance claims linked with electronic medical record data from January 2008-December 2012.Employee patients with diabetes covered by the organization's self-funded insurance and propensity-matched non-employee patient comparison group with diabetes and commercial insurance.Financial incentives for employer-sponsored disease management program participation and achieving goals.Change in glycosylated hemoglobin (HbA1c), low-density lipoprotein (LDL), systolic blood pressure (SBP), and weight.A total of 1092 employees with diabetes were matched to non-employee patients. With increasing incentives, employee program participation increased (7 % in 2009 to 50 % in 2012, p 0.001). Longitudinal mixed modeling demonstrated improved diabetes and cardiovascular risk factor control in employees vs. non-employees [HbA1c yearly change -0.05 employees vs. 0.00 non-employees, difference in change (DIC) p0.001]. In their first participation year, employees had larger declines in HbA1c and weight vs. non-employees (0.33 vs. 0.14, DIC p = 0.04) and (2.3 kg vs. 0.1 kg, DIC p 0.001), respectively. Analysis of employee cohorts corresponding with incentive offerings showed that fixed incentives (years 1 and 2) or incentives tied to goals (years 3 and 4) were not significantly associated with HbA1c reductions compared to non-employees. For each employee cohort offered incentives, SBP and LDL also did not significantly differ in employees compared with non-employees (DIC p 0.05).Financial incentives were associated with employee participation in disease management and improved cardiovascular risk factors over 5 years. Improvements occurred primarily in the first year of participation. The relative impact of specific incentives could not be discerned.

Background The aim of the present study was to assess the risk of overall mortality, coronary artery disease (CAD), and congestive heart failure (CHF) in patients with type 2 diabetes mellitus (T2DM) treated with metformin (MF) and an additional antidiabetic agent. Methods A retrospective cohort study was conducted using an academic health center enterprise-wide electronic health record (EHR) system to identify 13 185 adult patients (>18 years) with T2DM from January 2008 to June 2013 and received a prescription for MF in combination with a sulfonylurea (SU; n = 9419), thiazolidinedione (TZD; n = 1846), dipeptidyl peptidase-4 inhibitor (DPP-4i; n = 1487), or a glucagon-like peptide-1 receptor agonist (GLP-1a; n = 433). Multivariate Cox models with propensity analysis were used to compare cohorts, with MF+SU serving as the comparator group. Results The mean (±SD) age was 60.6 ± 12.6 years, with 54.6% male and 75.8% Caucasians. The median follow-up was 4 years. There were 1077 deaths, 1733 CAD events, and 528 CHF events in 55 100 person-years of follow-up. A higher risk of CHF was observed with MF+DPP-4i use (hazard ratio [HR] 1.104; 95% confidence interval [CI] 1.04–1.17; P = 0.001). A trend towards improved overall survival for users of MF+TZD (HR 0.86; 95% CI 0.74–1.0; P = 0.05) and MF+GLP-1a (HR 0.569; 95% CI 0.30–1.07; P = 0.08) was observed. No significant differences in the risk of CAD were identified. Conclusions Consistent with recent studies, our results raise concern for an increased risk of CHF with use of DPP-4i.

The American Association of Clinical Endocrinologists/American College of Endocrinology Medical Guidelines for Clinical Practice are systematically developed statements to assist healthcare professionals in medical decision making for specific clinical conditions. Most of the content herein is based on literature reviews. In areas of uncertainty, professional judgment was applied. These guidelines are a working document that reflects the state of the field at the time of publication. Because rapid changes in this area are expected, periodic revisions are inevitable. We encourage medical professionals to use this information in conjunction with their best clinical judgment. The presented recommendations may not be appropriate in all situations. Any decision by practitioners to apply these guidelines must be made in light of local resources and individual patient circumstances. Abbreviations: A1C = hemoglobin A1c AACE = American Association of Clinical Endocrinologists ACCORD = Action to Control Cardiovascu...

OBJECTIVE To identify severe hypoglycemia events, defined as emergency department visits or hospitalizations for hypoglycemia, in patients with type 2 diabetes receiving care in a large health system and to identify patient characteristics associated with severe hypoglycemia events. RESEARCH DESIGN AND METHODS This was a retrospective cohort study from January 2006 to December 2015 using the electronic medical record in the Cleveland Clinic Health System (CCHS). Participants included 50,439 patients with type 2 diabetes receiving care in the CCHS. Number of severe hypoglycemia events and associated patient characteristics were identified. RESULTS The incidence proportion of severe hypoglycemia increased from 0.12% in 2006 to 0.31% in 2015 (P = 0.01). Compared with patients who did not experience severe hypoglycemia, those with severe hypoglycemia had similar median glycosylated hemoglobin (HbA1c) levels. More patients with severe hypoglycemia versus those without had a prior diagnosis of nonsevere hypoglycemia (9% vs. 2%, P < 0.001). Logistic regression confirmed an increased odds for severe hypoglycemia with insulin, sulfonylureas, increased number of diabetes medications, history of nonsevere hypoglycemia (odds ratio [OR] 3.01, P < 0.001), HbA1c CONCLUSIONS In this retrospective study of patients with type 2 diabetes with severe hypoglycemia, patient characteristics were identified. Patients with severe hypoglycemia had previous nonsevere hypoglycemia diagnoses more frequently than those without. Identifying patients at high risk at the point of care can allow for change in modifiable risk factors and prevention of severe hypoglycemia events.

The aim of the present study was to assess the longitudinal accumulation of diabetes-related complications and the effect of glycemic control on the Diabetes Complications Severity Index (DCSI) score in people with newly diagnosed type 2 diabetes (T2D).A retrospective cohort study was conducted using electronic health records from a large integrated healthcare system. People with newly diagnosed T2D were identified between 2005 and 2016 and stratified by initial HbA1c category (7%,8%, ≥8%). The DCSI scores were determined for each study year, and the cumulative incidence of diabetes-related complications was assessed. A Cox proportional hazard model was used to evaluate the effect of baseline HbA1c and worsening glycemic (HbA1c) control on longitudinal changes in DCSI scores.Of 32 174 people identified as having newly diagnosed T2D, 14 016 (44%), 21 657 (67%), and 9983 (31%) had an initial or baseline HbA1c7%,8%, and ≥8%, respectively. Ten years after diabetes diagnosis, retinopathy, chronic kidney disease, coronary heart disease, and neuropathy were diagnosed in 22%, 29%, 24%, and 36% of people. Baseline HbA1c did not affect the observed trend in longitudinal changes in DCSI scores throughout the 11-year period. For people in each of the initial HbA1c groups (7%,8%, ≥8%), worsening or persistently poor glycemic control was significantly associated with a 10%, 19%, or 16% increase in the risk of experiencing an increased DCSI score, respectively (all P0.01).Baseline glycemic control had no apparent effect on longitudinal changes in DCSI score. Worsening or persistently poor glycemic control was associated with an increased risk of an increase in the DCSI score.

Inadequate glycemic control remains the leading cause of blindness, kidney failure, and nontraumatic lower-limb amputation.

Despite clinical practice guidelines that recommend frequent monitoring of HbA1c (every 3 months) and aggressive escalation of antihyperglycemic therapies until glycemic targets are reached (1,2), the intensification of therapy in patients with uncontrolled type 2 diabetes (T2D) is often inappropriately delayed. The failure of clinicians to intensify therapy when clinically indicated has been termed “clinical inertia.” A recently published systematic review found that the median time to treatment intensification after an HbA1c measurement above target was longer than 1 year (range 0.3 to >7.2 years) (3). We have previously reported a rather high rate of clinical inertia in patients uncontrolled on metformin monotherapy (4). Treatment was not intensified early (within 6 months of metformin monotherapy failure) in 38%, 31%, and 28% of patients when poor glycemic control was defined as an HbA1c >7% (>53 mmol/mol), >7.5% (>58 mmol/mol), and >8% (>64 mmol/mol), respectively. Using the electronic health record system at Cleveland Clinic (2005–2016), we identified a cohort of 7,389 patients with T2D who had an HbA1c value ≥7% (≥53 mmol/mol) (“index HbA1c”) despite having been on a stable regimen of two oral antihyperglycemic drugs (OADs) for at least 6 months prior to the …

Aims To analyse the association between cancer incidence and oral diabetes therapy (biguanide, sulphonylurea, thiazolidinedione and meglitinide) in men and women with type 2 diabetes mellitus. Methods A retrospective analysis of the electronic health record-based Cleveland Clinic Diabetes Registry (25 613 patients) was cross-indexed with the histology-based tumour registry (48 051 cancer occurrences) over an 8-year period (1998–2006). Multiple imputations were used to account for missing data. Cox regression with propensity scores was used to model time for the development of incident cancer in each of the imputed datasets and the results were pooled. Results During 51 994 person follow-up years, 892 incident cancer cases were identified; prostate (14.5%) and breast (11.7%) malignancies were most frequent. In women, thiazolidinedione use was associated with a 32% decreased cancer risk compared with sulphonylurea use [hazard ratio (HR) 0.68; 95% confidence interval (CI) 0.48–0.97, in the adjusted analysis]. Comparison of insulin secretagogues (sulphonylurea and meglitinide) versus insulin sensitizers (biguanide and thiazolidinedione) demonstrated a 21% decreased cancer risk in insulin sensitizers [HR 0.79 (95% CI 0.64–0.98) in the adjusted analysis]. Oral diabetes therapy showed no significant difference in men. Adjustments were made for age, body mass index (BMI), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, coronary heart disease (CHD), diabetes oral monotherapy, race, gender, haemoglobin A1c, statin use, income, insulin use, glomerular filtration rate (GFR), new diabetes status, prior cancer, prior cerebrovascular accident (stroke or transient ischaemic event), systolic/diastolic blood pressure, tobacco use (ever/never) and the propensity score for receiving a biguanide. Conclusions Oral insulin sensitizers, particularly thiazolidinedione, are associated with decreased malignancy risk in women with type 2 diabetes mellitus.

Objective This study retrospectively compared the effects of angiotensin-converting enzyme inhibitors (ACEIs) versus angiotensin receptor blockers (ARBs) as classes with respect to overall mortality and cardiovascular and renal events in patients with type 2 diabetes. Methods An electronic database of medical records was reviewed. A total of 16,489 patients with type 2 diabetes were enrolled and divided into ACEI (n = 12,351) or ARB (n = 4,138) groups. Baseline patient characteristics were compared using univariable analysis. A chi-square test was used for categorical outcomes, and the propensity class was calculated using multivariable logistic regression. Survival analysis was performed to evaluate the effect of ACEIs/ARBs on overall survival, coronary artery disease (CAD), and renal events via Cox regression analysis, adjusting for propensity class and baseline variables. All statistical analyses were conducted using R 2.15.1 software. Results No significant differences in overall survival (P = .16) and CAD (P = .81) events were observed between groups. With respect to renal events, ARBs increased the risk of creatinine doubling compared with ACEIs, but the difference was not significant (hazard ratio [HR], 1.207; 95% confidence interval [CI], 0.921-1.583; P = .173). Patients who received ARBs had a significantly higher rate of albuminuria than patients who received ACEIs (HR, 1.303; 95% CI, 1.053-1.612; P = .015). Conclusion The early effects of ACEIs and ARBs on albuminuria outcome seem to be different in type 2 diabetes, favoring the use of ACEIs. A well-designed prospective study is warranted to evaluate this finding. (Endocr Pract. 2013;19:579-586)

Diabet. Med. 29, 1029–1035 (2012) Abstract Aims Sulfonylureas have been shown to increase mortality when used in combination with metformin. This may not be a class effect of sulfonylureas, but rather secondary to differences in properties inherent to the individual sulfonylureas (hypoglycaemic risk, sulfonylurea receptor selectivity and effects on myocardial ischemic preconditioning). The purpose of this study was to assess the risk of overall mortality in patients with Type 2 diabetes treated with different combinations of sulfonylureas and metformin. Methods A retrospective cohort study was conducted using an academic health center enterprise-wide electronic health record system to identify 7320 patients with Type 2 diabetes (3768 initiators of glyburide (glibenclamide) and metformin, 2277 initiators of glipizide and metformin and 1275 initiators of glimepiride and metformin), ≥ 18 years of age and not on insulin or a non-insulin injectable at baseline. The patients were followed for mortality by documentation in the electronic health record and Social Security Death Index. Multivariable Cox models with propensity analysis were used to compare cohorts. Results No statistically significant difference in overall mortality risk was observed among the different combinations of sulfonylureas and metformin: glimepiride and metformin vs. glipizide and metformin (HR 1.03; 95% CI 0.89–1.20), glimepiride and metformin vs. glyburide (glibenclamide) and metformin (HR 1.08; 95% CI 0.90–1.30), or with glipizide and metformin vs. glyburide (glibenclamide) and metformin (HR 1.05; 95% CI 0.95–1.15). Conclusions Our results did not identify an increased mortality risk among the different combinations of sulfonylureas and metformin, suggesting that overall mortality is not substantially influenced by the choice of sulfonylurea.

Given that preoperative hyperglycemia is associated with poor outcomes and many non-diabetic patients have high plasma glucose (PG) levels, the purpose of our study was to estimate the prevalence of undiagnosed diabetes among non-cardiac surgery patients and to identify predictors of hyperglycemia in non-diabetics.We included all non-cardiac surgery patients with complete records in the Clinical Database of the Anesthesiology Institute at the Cleveland Clinic during January 2007 to April 2009, and we estimated the prevalence of undiagnosed diabetes and impaired fasting glucose (IFG) among the non-diabetic patients. The mean glucose levels for known diabetics and undiagnosed diabetics were compared using two-tailed Student's t tests, and we assessed the association between PG levels and demographic variables within the non-diabetics.Of the 39,434 patients analyzed, 5,511 (14%) were known diabetics. Of the 33,923 known non-diabetics, 3,426 (10 %) were undiagnosed diabetics and another 3,549 (11%) had IFG. Thus, 6,975 patients (21%) of the non-diabetic patients presented with abnormally high glucose. Previously undiagnosed diabetics had higher preoperative glucose levels compared with known diabetics, with a mean ± standard deviation (SD) of 161 ± 48 vs 146 ± 67 mg·dL⁻¹ (8.9 ± 2.7 vs 8.1 ± 3.7 mmoL·L⁻¹), respectively. The difference remained highly significant after adjusting for body mass index, age, sex, and American Society of Anesthesiologists (ASA) physical status (P0.001). Among non-diabetics, older age, obesity, male sex, and a higher ASA physical status were collectively significant predictors of hyperglycemia, with a c-statistic (95% confidence interval) of 0.67 (0.66-0.68).A significant proportion of non-cardiac surgery patients have previously undiagnosed diabetes and pre-diabetes. Previously undiagnosed patients have higher fasting glucose levels compared with diabetic patients. Further studies should be conducted to identify the implications of these findings on patient outcomes.

OBJECTIVE Sulfonylureas have historically been analyzed as a medication class, which may be inappropriate given the differences in properties inherent to the individual sulfonylureas (hypoglycemic risk, sulfonylurea receptor selectivity, and effects on myocardial ischemic preconditioning). The purpose of this study was to assess the relationship of individual sulfonylureas and the risk of overall mortality in a large cohort of patients with type 2 diabetes. RESEARCH DESIGN AND METHODS A retrospective cohort study was conducted using an academic health center enterprise-wide electronic health record (EHR) system to identify 11,141 patients with type 2 diabetes (4,279 initiators of monotherapy with glyburide, 4,325 initiators of monotherapy with glipizide, and 2,537 initiators of monotherapy with glimepiride), ≥18 years of age with and without a history of coronary artery disease (CAD) and not on insulin or a noninsulin injectable at baseline. The patients were followed for mortality by documentation in the EHR and Social Security Death Index. Multivariable Cox models were used to compare cohorts. RESULTS No statistically significant difference in the risk of overall mortality was observed among these agents in the entire cohort, but we did find evidence of a trend toward an increased overall mortality risk with glyburide versus glimepiride (hazard ratio 1.36 [95% CI 0.96–1.91]) and glipizide versus glimepiride (1.39 [0.99–1.96]) in those with documented CAD. CONCLUSIONS Our results did not identify an increased mortality risk among the individual sulfonylureas but did suggest that glimepiride may be the preferred sulfonylurea in those with underlying CAD.