Erratum: Addressing Therapeutic Inertia: Development and Implementation of an Electronic Health Record-Based Diabetes Intensification Tool. Diabetes Spectrum 2023;36:161-170 (https://doi.org/10.2337/ds22-0031).

[This corrects the article DOI: 10.2337/ds22-0031.].

Addressing Therapeutic Inertia: Development and Implementation of an Electronic Health Record-Based Diabetes Intensification Tool.

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 (<8%) were not significantly improved between IMP and non-IMP sites at 6 months (range 42.9-46.5%) or 12 months (range 46.5-53.1%). In phase 3, fewer patients at IMP sites versus non-IMP sites achieved the goal at 12 months (46.7 vs. 52.3%, P = 0.02). In phases 1-3, mean changes in A1C from baseline to 6 and 12 months (range -0.88 to -1.08%) were not significantly different between IMP and non-IMP sites. 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.

Unmet needs and opportunities for optimal management of patients with type 2 diabetes and chronic kidney disease.

This brief report utilizes EHR data from a large US health system to summarize unmet needs in patients with type 2 diabetes and chronic kidney disease and identifies areas of opportunity to optimize management within this patient population from treatment, screening and monitoring, and health care resource use perspectives.

Association between first-line monotherapy with metformin and the risk of atrial fibrillation (AMRAF) in patients with type 2 diabetes.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSION: 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.

Associations of weight loss with obesity-related comorbidities in a large integrated health system.

AIMS: To determine the health outcomes associated with weight loss in individuals with obesity, and to better understand the relationship between disease burden (disease burden; ie, prior comorbidities, healthcare utilization) and weight loss in individuals with obesity by analysing electronic health records (EHRs). 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 and 2018. Patients were aged ≥20 years with body mass index ≥30 kg/m2 and had ≥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 3, 5 and 10 years prior to an event. RESULTS: Weight loss was associated with reduced incidence of many outcomes (eg, type 2 diabetes, nonalcoholic steatohepatitis/nonalcoholic fatty liver disease, obstructive sleep apnoea, hypertension; P < 0.05). Weight loss >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 the 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.

A Type 2 Diabetes Subtype Responsive to ACCORD Intensive Glycemia Treatment.

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.

The Probability of A1C Goal Attainment in Patients With Uncontrolled Type 2 Diabetes in a Large Integrated Delivery System: A Prediction Model.

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 <8% by 31 December 2017, and subgroups were compared on a number of demographic and clinical variables. On the basis of these variables, a nomogram was created for predicting probability of A1C goal attainment. 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 <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, dipeptidyl peptidase 4 inhibitor use, thiazolidinedione use, metformin use, glucagon-like peptide 1 receptor agonist use, and fewer classes of antidiabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). CONCLUSIONS: A minority of patients with an A1C >9% achieved an A1C <8% at 1 year. While most identified predictive factors are nonmodifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help to improve A1C goal attainment.

Noninsulin Diabetes Therapies in Older Adults.

Diabetes risk increases with age due to changes in ß-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.

Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

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.

Risk prediction for severe hypoglycemia in a type 2 diabetes population with previous non-severe hypoglycemia.

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.

Testosterone replacement therapy and the risk of adverse cardiovascular outcomes and mortality.

BACKGROUND: The risk of adverse cardiovascular events and mortality associated with testosterone replacement therapy is controversial. The purpose of this report was to evaluate the effect of testosterone replacement therapy (TRT) in men with secondary hypogonadism on the risk of myocardial infarction (MI), stroke (CVA) or all-cause mortality. METHODS: A retrospective cohort study was conducted using the Cleveland Clinic's electronic health record. Men ≥40 years of age, with at least two testosterone levels < 220 ng/dL, with one level obtained between 7 am and 10 am, were identified. Men with primary hypogonadism, secondary hypogonadism related to overt hypothalamic pituitary pathology, human immunodeficiency virus infection, metastatic cancer, and select contraindications to TRT, were excluded. Men exposed to TRT were matched to controls that were not exposed. A survival analysis was performed on the composite outcome of MI, CVA, or all-cause mortality. RESULTS: One hundred sixty-five patients exposed to TRT (treatment group) were matched with 210 not exposed to TRT (comparison group). The prevalence of established cardiovascular disease (CVD) was 20.0% in the treatment group vs. 17.1% in the comparison group (P = 0.478). The median [interquartile range (IQR)] age (years) and BMI (kg/m2) were 55 (49, 62) and 35.6 (32.1, 40.1) in the treatment group, and 55 (49, 61.7) and 36.3 (32.1, 40.8) in the comparison group, respectively. There were 12 (7.3%) events observed in the treatment group, and 16 (7.6%) in the comparison group. The median time (years) to the composite event was 2.1 (IQR 0.9, 4.6) and 1.8 (IQR 0.6, 3.4) for treatment and comparison groups, respectively. No difference in the risk of the combined cardiovascular endpoint was observed between the treatment group vs the comparison group, hazard ratio (HR) 0.81 (95% Confidence Interval [CI]: 0.38-1.71; P = 0.57). CONCLUSION: In hypogonadal men with a modest prevalence of established CVD, TRT was not observed to confer a protective or adverse effect on the risk of MI, CVA or all-cause mortality.

CONTEXTE: Le risque d'événements cardiovasculaires indésirables et de mortalité associé au traitement de substitution de la testostérone est controversé. Le but du présent article est d'évaluer chez les hommes qui présentent un hypogonadisme secondaire l'effet du traitement de substitution de la testostérone (TST) sur le risque d'infarctus du myocarde (IM), d'accident cérébrovasculaire (ACV) ou de mortalité toutes causes confondues. PATIENTS ET MÉTHODES: Une étude de cohorte rétrospective a été menée en utilisant les dossiers de santé électroniques de la Clinique Cleveland. Ont été identifiés les hommes âgés de plus de 40 ans qui avaient au moins deux dosages de testostérone inférieurs à 220ng/dl, dont l'un obtenu le matin entre 7 et 10 heures. Ont été exclus les hommes qui présentaient un hypogonadisme primaire, un hypogonadisme secondaire lié à une pathologie hypothalamo-hypophysaire évidente, une infection par le virus de l'immunodéficience humaine, un cancer métastatique, et ceux qui présentaient des contrindications déterminées au TST. Les hommes exposés au TST ont été appariés à des témoins non exposés au TST. Une analyse de survie a été réalisée sur le paramètre composite incluant l'IM, l'AVC et la mortalité toutes causes confondues. RÉSULTATS: 165 patients exposés au TST (groupe traité) ont été appariés à 210 hommes non exposés au TST (groupe de référence). La prévalence de maladie cardiovasculaire (MCV) établie était de 20.0% dans le groupe traité versus 17.1% dans le groupe de référence (P=0.478). La médiane (écart interquartile (EI)) de l'âge et de l'indice de masse corporelle (IMC) était respectivement de 55 (49, 62) ans et de 35.6 (32.1, 40.1) kg/m2 dans le groupe traité, et respectivement de 55 (49, 61.7) ans et 36.3 (32.1, 40.8) kg/m2 dans le groupe de référence. Il y eut 12 événements indésirables (7.3%) dans le groupe traité, et 16 (7.6%) dans le groupe de référence. La médiane du temps (en années) des événements composites était de 2.1 (EI 0.9, 4.6) et de 1.8 (EI 0.6, 3.4) respectivement pour les groupes traité et de référence. Aucune différence n'a été observée en ce qui concerne le risque cardiovasculaire entre le groupe traité et le groupe de référence, rapport de risque (RR) 0.81 (Intervalle de Confiance à 95% [IC]: 0.38-1.71; P = 0.57). CONCLUSION: Chez les hommes qui présentent un hypogonadisme et une faible prévalence de maladie cardiovasculaire (MCV) établie, le TST n'apparait pas conférer un effet protecteur ou défavorable sur le risque de d'infarctus du myocarde (IM), d'accident cérébrovasculaire (ACV) ou de mortalité toutes causes confondues. MOTS-CLÉS: Traitement de substitution de la testostérone, Hypogonadisme masculin, Risque cardiovasculaire, Mortalité.

Antidiabetic treatment patterns and specialty care utilization among patients with type 2 diabetes and cardiovascular disease.

BACKGROUND: To evaluate real-world patient characteristics, medication use, and health care utilization patterns in patients with type 2 diabetes with established cardiovascular disease (CVD). METHODS: Cross-sectional analysis of patients with type 2 diabetes seen at Cleveland Clinic from 2005 to 2016, divided into two cohorts: with-CVD and without-CVD. Patient demographics and antidiabetic medications were recorded in December 2016; department encounters included all visits from 1/1/2016 to 12/31/2016. Comorbidity burden was assessed by the diabetes complications severity index (DCSI) score. RESULTS: Of 95,569 patients with type 2 diabetes, 40,910 (42.8%) were identified as having established CVD. Patients with CVD vs. those without were older (median age 69.1 vs. 58.2 years), predominantly male (53.8% vs. 42.6%), and more likely to have Medicare insurance (69.4% vs. 35.3%). The with-CVD cohort had a higher proportion of patients with a DCSI score ≥ 3 than the without-CVD cohort (65.0% vs. 10.3%). Utilization rates of glucagon-like peptide-1 receptor agonists and sodium-glucose co-transporter-2 inhibitors were low in both with-CVD (4.1 and 2.5%) and without-CVD cohorts (5.4 and 4.1%), respectively. The majority of patient visits (75%) were seen by a primary care provider. During the 1-year observation period, 81.9 and 62.0% of patients with type 2 diabetes and CVD were not seen by endocrinology or cardiology, respectively. CONCLUSIONS: These data indicated underutilization of specialists and antidiabetic medications reported to confer CV benefit in patients with type 2 diabetes and CVD. The impact of recently updated guidelines and cardiovascular outcome trial results on management patterns in such patients remains to be seen.

Patient Characteristics Associated With Severe Hypoglycemia in a Type 2 Diabetes Cohort in a Large, Integrated Health Care System From 2006 to 2015.

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 <6% (42 mmol/mol) (OR 1.95, P < 0.001), black race, and increased Charlson comorbidity index. Lower odds of severe hypoglycemia were noted with higher BMI and use of metformin, dipeptidyl peptidase 4 inhibitors, and glucagon-like peptide 1 agonists. 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.

Effect of glycemic control on the Diabetes Complications Severity Index score and development of complications in people with newly diagnosed type 2 diabetes.

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 (<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. RESULTS: Of 32 174 people identified as having newly diagnosed T2D, 14 016 (44%), 21 657 (67%), and 9983 (31%) had an initial or baseline HbA1c <7%, <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 P < 0.01). CONCLUSIONS: 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.

Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system.

OBJECTIVE: To determine the prevalence of obesity and its related comorbidities among patients being actively managed at a US academic medical centre, and to examine the frequency of a formal diagnosis of obesity, via International Classification of Diseases, Ninth Revision (ICD-9) documentation among patients with body mass index (BMI) ≥30 kg/m2. DESIGN: The electronic health record system at Cleveland Clinic was used to create a cross-sectional summary of actively managed patients meeting minimum primary care physician visit frequency requirements. Eligible patients were stratified by BMI categories, based on most recent weight and median of all recorded heights obtained on or before the index date of 1July 2015. Relationships between patient characteristics and BMI categories were tested. SETTING: A large US integrated health system. RESULTS: A total of 324 199 active patients with a recorded BMI were identified. There were 121 287 (37.4%) patients found to be overweight (BMI ≥25 and <29.9), 75 199 (23.2%) had BMI 30-34.9, 34 152 (10.5%) had BMI 35-39.9 and 25 137 (7.8%) had BMI ≥40. There was a higher prevalence of type 2 diabetes, pre-diabetes, hypertension and cardiovascular disease (P value<0.0001) within higher BMI compared with lower BMI categories. In patients with a BMI >30 (n=134 488), only 48% (64 056) had documentation of an obesity ICD-9 code. In those patients with a BMI >40, only 75% had an obesity ICD-9 code. CONCLUSIONS: This cross-sectional summary from a large US integrated health system found that three out of every four patients had overweight or obesity based on BMI. Patients within higher BMI categories had a higher prevalence of comorbidities. Less than half of patients who were identified as having obesity according to BMI received a formal diagnosis via ICD-9 documentation. The disease of obesity is very prevalent yet underdiagnosed in our clinics. The under diagnosing of obesity may serve as an important barrier to treatment initiation.

Association of glucagon-like peptide-1 receptor agonist use and rates of acute myocardial infarction, stroke and overall mortality in patients with type 2 diabetes mellitus in a large integrated health system.

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 < .001), overall mortality (HR 0.48, 95% CI 0.41 to 0.57; P < .001), and the composite outcome (HR 0.82, 95% CI 0.74 to 0.91; P < .002) during the consolidated time that patients were exposed to GLP-1RAs compared to corresponding rates during intervals without GLP-1RA exposure. GLP-1RA treatment was associated with a significant decrease in CVA, mortality, and the composite outcome in patients with and without established CVD, not significantly affecting AMI in these subgroups. CONCLUSIONS: GLP-1RA exposure was found to be associated with a reduction in the risk of cardiovascular events observed and overall mortality among patients with T2D with and without established CVD, after adjusting for potential confounders.

Intensification of Diabetes Therapy and Time Until A1C Goal Attainment Among Patients With Newly Diagnosed Type 2 Diabetes Who Fail Metformin Monotherapy Within a Large Integrated Health System.

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.