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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.

Aims Current guidelines recommend beta‐blocker therapy in chronic heart failure with reduced ejection fraction (HFrEF) titrated according to tolerated target dose. The efficiency of this strategy to obtain adequate heart rate (HR) control remains unclear in clinical practice. The aim of this study was to determine, in a real‐world setting, the proportion of HFrEF patients who fail to achieve beta‐blocker target doses, whether target doses of beta‐blockers have a relationship with the adequacy in reducing resting HR over time. Methods and results Beta‐blocker dose and resting HR of consecutive ambulatory patients with a diagnosis of HFrEF (ejection fraction ≤ 35%) in sinus rhythm were reviewed at the first outpatient contact in the Cleveland Clinic Health System from the year 2000 to 2015. Patients who did not receive beta‐blocker therapy, have congenital heart disease and hypertrophic cardiomyopathy, were not in sinus rhythm, or have a history of heart transplant were excluded. Patients were followed up until their last known visit at the Cleveland Clinic. Median resting HR was 71 b.p.m. [inter‐quartile range (IQR) 60–84 b.p.m.] in 8041 patients (median age 65; 68% male) with 67% on carvedilol, 32% on metoprolol succinate, and 1% on bisoprolol. In 3674 subjects (56%), resting HR was ≥70 b.p.m. At final follow‐up after a median of 21 months (IQR 0.1–7.2 years), resting HR was 72 b.p.m. (IQR 60–84 b.p.m.) in the subset of patients with persistently low ejection fraction ≤ 35%. HR ≥ 70 b.p.m. was observed in 55% of this group. Beta‐blocker target dose was achieved in 19%, 5%, and 15% of those receiving carvedilol, metoprolol succinate, and bisoprolol, respectively. In the subset of patients who experienced beta‐blocker up‐titration, reduced mortality or hospitalization due to heart failure was observed in patients who experienced the lowest HR after titration. Conclusions In our single‐centre experience, the majority of patients with chronic HFrEF treated with beta‐blocker therapy did not achieve target doses over time, and a substantial proportion had inadequate control of resting HR. There was no relationship between achieved beta‐blocker target dose and resting HR control.

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

Hospital systems, payers, and regulators have focused on reducing length of stay (LOS) and early readmission, with uncertain benefit. Interpretable machine learning (ML) may assist in transparently identifying the risk of important outcomes. We conducted a retrospective cohort study of hospitalizations at a tertiary academic medical center and its branches from January 2011 to May 2018. A consecutive sample of all hospitalizations in the study period were included. Algorithms were trained on medical, sociodemographic, and institutional variables to predict readmission, length of stay (LOS), and death within 48–72 h. Prediction performance was measured by area under the receiver operator characteristic curve (AUC), Brier score loss (BSL), which measures how well predicted probability matches observed probability, and other metrics. Interpretations were generated using multiple feature extraction algorithms. The study cohort included 1,485,880 hospitalizations for 708,089 unique patients (median age of 59 years, first and third quartiles (QI) [39, 73]; 55.6% female; 71% white). There were 211,022 30-day readmissions for an overall readmission rate of 14% (for patients ≥65 years: 16%). Median LOS, including observation and labor and delivery patients, was 2.94 days (QI [1.67, 5.34]), or, if these patients are excluded, 3.71 days (QI [2.15, 6.51]). Predictive performance was as follows: 30-day readmission (AUC 0.76/BSL 0.11); LOS > 5 days (AUC 0.84/BSL 0.15); death within 48–72 h (AUC 0.91/BSL 0.001). Explanatory diagrams showed factors that impacted each prediction.

Summary Objective In shared medical appointments (SMAs), multiple patients with a similar clinical diagnosis are seen by a multidisciplinary team for interactive group sessions. Very few studies have specifically studied SMAs and weight loss in patients with obesity. This study compared weight loss outcomes and anti‐obesity medication (AOM) access between patients with obesity managed through (SMAs) versus individual appointments. Methods Retrospective study of adults seen for obesity between September 2014 and February 2017 at Cleveland Clinic Institute of Endocrinology and Metabolism. Percent weight loss from baseline was compared between two propensity score‐matched populations: patients who attended ≥1 SMA and patients managed with individual medical appointments. Results From all eligible patients identified (n=310 SMA, n=1,993 non‐SMA), 301 matched pairs were evaluated for weight loss. The SMA group (n=301) lost a mean of 4.2%, 5.2% and 3.8% of baseline weight over 6, 12 and 24 months; the non‐SMA group (n=301) lost significantly less weight (1.5%, 1.8% and 1.6%, respectively) (paired t‐test, P

Background Venous thromboembolism (VTE) prophylaxis is recommended for hospitalized medical patients at high risk for VTE. Multiple risk assessment models exist, but few have been compared in large datasets. Methods We constructed a derivation cohort using 6 years of data from 12 hospitals to identify risk factors associated with developing VTE within 14 days of admission. VTE was identified using a complex algorithm combining administrative codes and clinical data. We developed a multivariable prediction model and applied it to three validation cohorts: a temporal cohort, including two additional years, a cross-validation, in which we refit the model excluding one hospital each time, applying the refitted model to the holdout hospital, and an external cohort. Performance was evaluated using the C-statistic. Results The derivation cohort included 155,026 patients with a 14-day VTE rate of 0.68%. The final multivariable model contained 13 patient risk factors. The model had an optimism corrected C-statistic of 0.79 and good calibration. The temporal validation cohort included 53,210 patients, with a VTE rate of 0.64%; the external cohort had 23,413 patients and a rate of 0.49%. Based on the C-statistic, the Cleveland Clinic Model (CCM) outperformed both the Padua (0.76 vs. 0.72, p = 0.002) and IMPROVE (0.68, p Conclusion A new VTE risk assessment model outperformed recommended models.

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.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.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 (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.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.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.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;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.Traitement de substitution de la testostérone, Hypogonadisme masculin, Risque cardiovasculaire, Mortalité.

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 (

Background Left ventricular non‐compaction remains a poorly described entity, which has led to challenges of overdiagnosis. We aimed to evaluate if the presence of a thin compacted myocardial layer portends poorer outcomes in individuals meeting cardiac magnetic resonance criteria for left ventricular non‐compaction . Methods and Results This was an observational, retrospective cohort study involving individuals selected from the Cleveland Clinic Foundation cardiac magnetic resonance database (N=26 531). Between 2000 and 2018, 328 individuals ≥12 years, with left ventricular non‐compaction or excessive trabeculations based on the cardiac magnetic resonance Petersen criteria were included. The cohort comprised 42% women, mean age 43 years. We assessed the predictive ability of myocardial thinning for the primary composite end point of major adverse cardiac events (composite of all‐cause mortality, heart failure hospitalization, left ventricular assist device implantation/heart transplant, ventricular tachycardia, or ischemic stroke). At mean follow‐up of 3.1 years, major adverse cardiac events occurred in 102 (31%) patients. After adjusting for comorbidities, the risk of major adverse cardiac events was nearly doubled in the presence of significant compacted myocardial thinning (hazard ratio [HR], 1.88 [95% CI, 1.18‒3.00]; P =0.016), tripled in the presence of elevated plasma B‐type natriuretic peptide (HR, 3.29 [95% CI, 1.52‒7.11]; P =0.006), and increased by 5% for every 10‐unit increase in left ventricular end‐systolic volume (HR, 1.01 [95% CI, 1.00‒1.01]; P =0.041). Conclusions The risk of adverse clinical events is increased in the presence of significant compacted myocardial thinning, an elevated B‐type natriuretic peptide or increased left ventricular dimensions. The combination of these markers may enhance risk assessment to minimize left ventricular non‐compaction overdiagnosis whilst facilitating appropriate diagnoses in those with true disease.

Background: Functional mitral regurgitation (MR) grading by echocardiography is often challenging, and cardiac magnetic resonance (CMR) may provide more accurate and reproducible assessment, however optimal CMR thresholds have not been established. We aimed to determine clinically significant thresholds of MR-volume and MR-fraction by CMR in patients with non-ischemic cardiomyopathy (NICM). Methods: All patients having CMR with confirmed NICM between 2001/4/1-2019/3/31 were retrospectively studied. Time to death, heart transplant and/or left ventricular assist device is the primary endpoint, and receiver-operative (ROC) characteristics analyses were used to identify significant cut-points for MR-volume and MR-fraction. Results: Mean MR-volume was 11±12% and MR-fraction 14±13% in 840 NICM patients. C-statistics for the primary endpoint (141 events) were MR-volume 0.629 (95%CI: 0.577-0.691) and MR-fraction 0.594 (95%CI 0.542-0.647). Thresholds of MR-volume≥10mL and MR-fraction≥15% had the highest products of sensitivities and specificities (57.4%, 56.8%; and 54.6%, 63.4% respectively) reflecting elevated risk. MR-volume≥35mL and MR-fraction≥40% were associated the best combination of positive and negative predictive values (40.1%, 84.2%; and 38.4%, 84.6% respectively) representing severe risk. The figure illustrates Kaplan-Meier curves of the primary endpoint, categorized into three subgroups based on aforementioned MR-volume and MR-fraction thresholds. Conclusion: Adverse prognosis are observed when MR-volume≥10mL or MR-fraction≥15%, with increasing risk of adverse outcomes as functional MR severity increased in NICM. The proposed MR thresholds from this study for elevated and severe risk are lower than current valvular regurgitation guidelines, suggesting the need for separate classification schema for functional MR.

Background: Functional mitral regurgitation (MR) is associated with poor outcomes and the prognostic role of cardiac magnetic resonance imaging (CMR) quantification of secondary MR has rarely been studied. We evaluated the associations between CMR-derived MR-fraction and adverse outcomes in non-ischemic cardiomyopathy (NICM) patients. Methods: We retrospectively studied 840 consecutive NICM patients undergoing CMR during 2001/4/1-2019/3/31. Multivariable Cox proportional hazards regression was performed for MR-fraction and two composite endpoints: primary (time to death, heart transplant and/or left ventricular assist device) and secondary (primary endpoint plus heart failure hospitalizations). Results: The cohort had mean age of 53.0±15.9 years, 319 (38.0) were female, and mean MR-fraction of 14±13% by CMR. There were 141 (16.8%) primary and 223 (26.5%) secondary endpoints over a mean follow-up of 3.6±3.0 years. Multivariable analyses results are shown in the Table. MR-fraction was independently associated with the primary and secondary endpoints with hazards ratios of 1.13 (95%CI 1.07-1.20) and 1.13 (95%CI 1.07-1.19) respectively per 5% increase in MR-fraction. MR-fraction provided stronger prognostic power compared to late gadolinium enhancement (LGE) in both models. Older age and diabetes were independently associated with both composite endpoints, while lower LVEF was independently associated with the secondary endpoint only. Conclusion: CMR quantification of functional MR is a powerful predictor of adverse outcomes and demonstrated stronger associations with poor prognosis compared to LGE and left ventricular remodeling in a large cohort of patients with NICM.

Introduction Sleep disordered breathing (SDB), including obstructive sleep apnea (OSA) and obesity-associated sleep hypoventilation (OASH), has well-characterized adverse effects on the cardiovascular system and increases morbidity and mortality. Long-term impact on cardiovascular outcomes post-bariatric surgery, however, remains unclear. We hypothesize that patients with SDB have increased frequency of major adverse cardiovascular events (MACE) post-bariatric surgery than those without. Methods Patients undergoing polysomnography (PSG) prior to bariatric surgery at The Cleveland Clinic from 2011–2018 were retrospectively examined and followed up from date of last surgery to 2019, including the perioperative period. Primary predictors include moderate-severe OSA, i.e. apnea hypopnea index(AHI)>15, and OASH, i.e. body mass index (BMI)≥30kg/m2 and either end-tidal CO2≥45mmHg or serum bicarbonate≥27mEq/L. MACE (coronary artery events, cerebrovascular events, heart failure or atrial fibrillation)-free probability was compared using hazard ratios estimated from Cox proportional hazards models on four groups: OASH with moderate-severe OSA (N=492), OASH-only (N=442), moderate-severe OSA-only (N=203), and a reference group without OASH or moderate-severe OSA (N=243). Multivariable Cox proportional hazards models adjusting for age, sex, BMI were fit on MACE survival. Analysis was performed based on an overall significance level of 0.05, using SAS software (version 9.4, Cary, NC). Results The sample comprised 1380 patients: age: 43.5±12 years, BMI: 49±9 kg/m2, 17.7% male, 63.7% White. Risk of MACE across the groups bordered significance (p=0.051). Compared to the reference group, the OASH with moderate-severe OSA group had higher risk of MACE (HR2.53, 95%CI:1.07–6.00,p=0.035). Patients with moderate-severe OSA had higher risk of MACE than those with AHI Conclusion Preliminary data from this largest-to-date sample of systematically phenotyped patients with SDB undergoing bariatric surgery show significant differences in risk of MACE and MACE-free survival mitigated after consideration of obesity. Further investigation to elucidate effect modification by obesity and metabolic factors is needed. Support (if any) Cleveland Clinic Transformative Resource Neuroscience Award

Introduction Obesity and obstructive sleep apnea (OSA) are associated with left ventricular hypertrophy and increased cardiovascular risk. Alternatively, the “obesity paradox” describes an improved prognosis from heart failure in obesity, though potentially attributable to confounding/bias. We sought to determine the contributions of obesity and sleep-disordered breathing (SDB) to left ventricular function and morphology in bariatric surgery candidates. Methods Patients undergoing polysomnography prior to bariatric surgery from 2011–2018 had demographic (age, gender, race), anthropometric (body mass index [BMI], neck circumference), comorbidities (atrial fibrillation, coronary artery disease, diabetes, hypertension, hyperlipidemia), echocardiographic and sleep-disordered breathing (apnea-hypopnea index [AHI], peak end-tidal CO2 [etCO2]) variables retrospectively examined. The echocardiographic visit closest to polysomnogram within two years was selected with missing values filled by available values within 6 months. Linear regression assessed the relationship of BMI, AHI, and etCO2 with left ventricular mass index (LVMI) after adjustment of demographics and comorbidities. Echocardiographic measures were logarithm transformed before regression analysis. Coefficients and 95% confidence intervals (CI) were calculated by exponential transformation. The analysis was performed based on an overall significance level of 0.05 using SAS software (version 9.4, Cary, NC). Results The total of 832 patients had 24% males, mean age 48.8±12, 60% white, and BMI:49.4±9.5kg/m2. Ejection fraction (%) was 60.0±7.0, and LVMI (g/m2): 80.9±23.7. In adjusted models, LVMI decreased by 2.1% for each 5kg/m2 increase in BMI (coefficient=0.979, 95%CI 0.961–0.997, p=0.022) and increased by 4.3% for each 5 mmHg increase in etCO2 (coefficient=1.043, 95%CI 1.013–1.073, p=0.005). Without adjustment, patients with AHI ≥ 5 had 15.3% higher LVMI than non-OSA group (coefficient=1.153, 95%CI 1.034–1.286, p=0.011) and moderate/severe OSA was associated with a 7.6% higher LVMI than those with AHI Conclusion In obese patients, nocturnal hypoventilation rather than obesity may have adverse influences on left ventricular morphology. Future studies should focus on clarifying whether obesity is truly protective in terms of LV mass, i.e. reflective of paradox versus a product of bias. The potential benefit of identifying/treating SDB in bariatric surgery candidates to mitigate cardiovascular risk also deserves further investigation. Support (if any) Cleveland Clinic Transformative Resource Neuroscience Award

Introduction There is lack of clarity of sleep disordered breathing (SDB)--including the role of nocturnal hypoxia and confounding influence of obesity--on the clinical course of human coronavirus disease 2019 (COVID-19). We postulate that SDB portends increased risk of adverse COVID-19 clinical outcomes even after accounting for confounding factors. Methods A retrospective cohort analysis of COVID-19 and sleep laboratory observational registries March-November 2020 within the Cleveland Clinic health system was performed. Ordinal logistic regression assessed the association of SDB indices and World Health Organization (WHO)-7 COVID-19 clinical outcome (hospitalization, use of supplemental oxygen, non-invasive ventilation, mechanical ventilation/ECMO and death) in an unadjusted model and adjusted for age, sex, race, body mass index(BMI,kg/m2),diabetes mellitus, hypertension, coronary artery disease, heart failure, asthma, chronic obstructive pulmonary disease (COPD), cancer and smoking using SAS software. Results Of 19,449 (32%) patients positive for SARS-CoV-2,2,290 (6%) had an available sleep study. The analytic sample included 1788 of which 1,484(64%) had an apnea hypopnea index (AHI, 3–4% hypopnea oxygen desaturation)≥5. The median duration from sleep study to COVID test was 5.8 years (IQR:3.3–9.0). Age was 56.5±14.4 years,50.4% female,28% African American with BMI=35.9±8.9kg/m2. Nine percent of patients were hospitalized,10% with supplemental oxygen,6% used non-invasive ventilation,2% required ECMO or mechanical ventilation and 2% died. For every AHI increase of 5, the odds of a higher WHO-7 level increased 2% (OR=1.02,95%CI1.01-1.04,p=0.005),but the association was mitigated in the adjusted model (OR=1.00,95%CI:0.98,1.02,p=0.80). Per 5% increase in time spent with SaO2 Conclusion Even after adjustment for obesity, underlying cardiopulmonary disease and smoking, sleep-related hypoxemia was a potential key pathophysiologic mechanism associated with increased morbidity and mortality in COVID-19. Elucidation of sleep-related hypoxemia as a risk stratification measure, particularly given the silent hypoxia inherent to early COVID-19, is critical for future investigation, as is the role of sleep-related hypoxia reversal as a target to improve COVID-19 outcomes. Support (if any) Cleveland Clinic Neurologic Institute Resource Development Award

Background Coronavirus disease 2019 (COVID-19) is sweeping the globe. Despite multiple case-series, actionable knowledge to tailor decision-making proactively is missing. Research Question Can a statistical model accurately predict infection with COVID-19? Study Design and Methods We developed a prospective registry of all patients tested for COVID-19 in Cleveland Clinic to create individualized risk prediction models. We focus here on the likelihood of a positive nasal or oropharyngeal COVID-19 test. A least absolute shrinkage and selection operator logistic regression algorithm was constructed that removed variables that were not contributing to the model’s cross-validated concordance index. After external validation in a temporally and geographically distinct cohort, the statistical prediction model was illustrated as a nomogram and deployed in an online risk calculator. Results In the development cohort, 11,672 patients fulfilled study criteria, including 818 patients (7.0%) who tested positive for COVID-19; in the validation cohort, 2295 patients fulfilled criteria, including 290 patients who tested positive for COVID-19. Male, African American, older patients, and those with known COVID-19 exposure were at higher risk of being positive for COVID-19. Risk was reduced in those who had pneumococcal polysaccharide or influenza vaccine or who were on melatonin, paroxetine, or carvedilol. Our model had favorable discrimination (c-statistic = 0.863 in the development cohort and 0.840 in the validation cohort) and calibration. We present sensitivity, specificity, negative predictive value, and positive predictive value at different prediction cutoff points. The calculator is freely available at https://riskcalc.org/COVID19 . Interpretation Prediction of a COVID-19 positive test is possible and could help direct health-care resources. We demonstrate relevance of age, race, sex, and socioeconomic characteristics in COVID-19 susceptibility and suggest a potential modifying role of certain common vaccinations and drugs that have been identified in drug-repurposing studies.

Background: Understanding the impact of the COVID-19 pandemic on healthcare workers (HCW) is crucial.Objective: Utilizing a health system COVID-19 research registry, we assessed HCW risk for COVID-19 infection, hospitalization and intensive care unit (ICU) admission.Design: Retrospective cohort study with overlap propensity score weighting.Participants: Individuals tested for SARS-CoV-2 infection in a large academic healthcare system (N=72,909) from March 8-June 9 2020 stratified by HCW and patient-facing status. Main Measures: SARS-CoV-2 test result, hospitalization, and ICU admission for COVID-19 infection. Key Results: Of 72,909 individuals tested, 9.0% (551) of 6,145 HCW tested positive for SARS-CoV-2 compared to 6.5% (4353) of 66,764 non-HCW. The HCW were younger than non-HCW (median age 39.7 vs. 57.5, pConclusions: In a large healthcare system, HCW had similar odds for testing SARS-CoV-2 positive, but lower odds of hospitalization compared to non-HCW. Patient-facing HCW had higher odds of a positive test. These results are key to understanding HCW risk mitigation during the COVID-19 pandemic.

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.

BackgroundCoronavirus Disease 2019 is a pandemic that is straining healthcare resources, mainly hospital beds. Multiple risk factors of disease progression requiring hospitalization have been identified, but medical decision-making remains complex.ObjectiveTo characterize a large cohort of patients hospitalized with COVID-19, their outcomes, develop and validate a statistical model that allows individualized prediction of future hospitalization risk for a patient newly diagnosed with COVID-19.DesignRetrospective cohort study of patients with COVID-19 applying a least absolute shrinkage and selection operator (LASSO) logistic regression algorithm to retain the most predictive features for hospitalization risk, followed by validation in a temporally distinct patient cohort. The final model was displayed as a nomogram and programmed into an online risk calculator.SettingOne healthcare system in Ohio and Florida.ParticipantsAll patients infected with SARS-CoV-2 between March 8, 2020 and June 5, 2020. Those tested before May 1 were included in the development cohort, while those tested May 1 and later comprised the validation cohort.MeasurementsDemographic, clinical, social influencers of health, exposure risk, medical co-morbidities, vaccination history, presenting symptoms, medications, and laboratory values were collected on all patients, and considered in our model development.Results4,536 patients tested positive for SARS-CoV-2 during the study period. Of those, 958 (21.1%) required hospitalization. By day 3 of hospitalization, 24% of patients were transferred to the intensive care unit, and around half of the remaining patients were discharged home. Ten patients died. Hospitalization risk was increased with older age, black race, male sex, former smoking history, diabetes, hypertension, chronic lung disease, poor socioeconomic status, shortness of breath, diarrhea, and certain medications (NSAIDs, immunosuppressive treatment). Hospitalization risk was reduced with prior flu vaccination. Model discrimination was excellent with an area under the curve of 0.900 (95% confidence interval of 0.886-0.914) in the development cohort, and 0.813 (0.786, 0.839) in the validation cohort. The scaled Brier score was 42.6% (95% CI 37.8%, 47.4%) in the development cohort and 25.6% (19.9%, 31.3%) in the validation cohort. Calibration was very good. The online risk calculator is freely available and found at https://riskcalc.org/COVID19Hospitalization/.LimitationRetrospective cohort design.ConclusionOur study crystallizes published risk factors of COVID-19 progression, but also provides new data on the role of social influencers of health, race, and influenza vaccination. In a context of a pandemic and limited healthcare resources, individualized outcome prediction through this nomogram or online risk calculator can facilitate complex medical decision-making.

Purpose Type 2 diabetes–related polyneuropathy (DPN) is associated with increased vascular events and mortality, but determinants and outcomes of pain in DPN are poorly understood. We sought to examine the effect of neuropathic pain on vascular events and mortality in patients without DPN, DPN with pain (DPN + P), and DPN without pain (DPN-P). Methods A retrospective cohort study was conducted within a large health system of adult patients with type 2 diabetes from January 1, 2009 through December 31, 2016. Using an electronic algorithm, patients were classified as no DPN, DPN + P, or DPN-P. Primary outcomes included number of vascular events and time to mortality. Independent associations with DPN + P were evaluated using multivariable negative binomial and Cox proportional hazards regression models, adjusting for demographics, socioeconomic characteristics, and comorbidities. Results Of 43 945 patients with type 2 diabetes (age 64.6 ± 14.0 years; 52.1% female), 13 910 (31.7%) had DPN: 9104 DPN + P (65.4%) vs 4806 DPN-P (34.6%). Vascular events occurred in 4538 (15.1%) of no DPN patients, 2401 (26.4%) DPN + P, and 1006 (20.9%) DPN-P. After adjustment, DPN + P remained a significant predictor of number of vascular events (incidence rate ratio [IRR] = 1.55, 95% CI, 1.29-1.85), whereas no DPN was protective (IRR = 0.70, 95% CI, 0.60-0.82), as compared to DPN-P. Compared to DPN-P, DPN + P was also a significant predictor of mortality (hazard ratio = 1.42, 95% CI, 1.25-1.61). Conclusions Our study found a significant association between pain in DPN and an increased risk of vascular events and mortality. This observation warrants longitudinal study of the risk factors and natural history of pain in DPN.

Background The clinical impact of addressing potential germline alterations from tumor-only next-generation sequencing (NGS) is not well characterized. Current guidelines for cancer genetic testing may miss clinically actionable germline changes, which may have important implications for cancer screening, treatment, and prevention. We examined whether increasing involvement of the clinical genetics service during somatic tumor-only NGS review at Molecular Tumor Board (MTB) increases the detection of germline findings. Methods In a retrospective evaluation of patients who underwent tumor-only NGS and were reviewed at MTB, we quantified genetic counseling (GC) referrals as well as germline testing uptake and results across three cohorts: before (C1) and after (C2) the addition of tumor-only NGS review and after (C3) instituting a formal process to coordinate NGS-based genetics referrals to preexisting oncology appointments. All statistical tests were two-sided. Results From 2013 to 2017, 907 tumor-only NGS reports were reviewed at MTB (nC1 = 281, nC2 = 493, nC3 = 133); gastrointestinal (22.5%), lung (19.7%), genitourinary (14.8%), and breast (14.1%) were the most common index cancers. GC visits due to MTB increased with each successive cohort (C1 = 1.1%, C2 = 6.9%, C3 = 13.5%; P for trend [Ptrend] < .001), as did germline testing (C1 = 0.7%, C2 = 3.2%, C3 = 11.3%; Ptrend < .001). Diagnosis of germline pathogenic variants increased with each successive cohort (C1 = 1.4%, C2 = 2.0%, C3 = 7.5%; Ptrend = .003) and with germline pathogenic variants found by MTB review (C1 = 0.4%, C2 = 0.4%, C3 = 2.3%; Ptrend = .12). Conclusions Both review of tumor-only NGS by genetics and the institution of a process coordinating GC with oncology appointments increased the discovery of germline pathogenic variants from tumor-only NGS testing. Furthermore, this process identified germline pathogenic variant carriers who would not have otherwise met standard criteria for germline testing.

Background and Aims Crohn’s disease (CD) is a chronic illness that affects both the pediatric and adult populations with an increasing worldwide prevalence. We aim to identify a large, single-center cohort of patients with CD using natural language processing (NLP) in combination with codified data and extract surgical rates and medication usage from the electronic medical record (EMR). Methods Patients with CD were identified from the entire Cleveland Clinic EMR using ICD codes and CD-specific terms identified by NLP to fit a logistic regression model. Cohorts were developed for pediatric-onset (younger than 18 years) and adult-onset (18 years and older) CD. Surgeries were identified using current procedural terminology (CPT) codes and NLP. Crohn’s disease–related medications were extracted using physician orders in the EMR. Results Patients with pediatric-onset (n = 2060) and adult-onset (n = 4973) CD were identified from 2000 to 2017 with a positive predictive value of 98.5%. Rate of CD-related abdominal surgery over time was significantly higher in adult-onset compared with pediatric-onset CD (10-year surgery rate 49.9% vs 37.7%, respectively; P < 0.001). Treatment with biologics was significantly higher in pediatric vs adult-onset CD cohorts (63.6% vs 49.2%; P < 0.001). The overall rate of CD-related abdominal surgery was significantly higher in those who received Conclusion We used a combination of codified and NLP data to establish the largest, North American, single-center EMR cohort of pediatric- and adult-onset CD patients and determined that biologics are associated with lower rates of surgery over time, potentially altering the natural history of the disease.

Key Points Question Are sleep-disordered breathing and sleep-related hypoxia associated with SARS-CoV-2 infection and COVID-19 outcomes? Findings In this case-control study of 5402 patients in a large integrated health system, sleep-disordered breathing and sleep-related hypoxia were not associated with an increased likelihood of contracting SARS-CoV-2. After accounting for confounding factors including cardiopulmonary disease, cancer, and smoking exposure, sleep-related hypoxia indices were associated with more severe COVID-19 clinical outcomes, including hospitalization and mortality, in time-to-event analyses. Meaning These results suggest that baseline sleep-related hypoxia may portend worse clinical prognosis in COVID-19., This case-control study investigates the association of sleep-disordered breathing and sleep-related hypoxia with SARS-CoV-2 infection and COVID-19 outcomes., Importance The influence of sleep-disordered breathing (SDB) and sleep-related hypoxemia in SARS-CoV-2 viral infection and COVID-19 outcomes remains unknown. Controversy exists regarding whether to continue treatment for SDB with positive airway pressure given concern for aerosolization with limited data to inform professional society recommendations. Objective To investigate the association of SDB (identified via polysomnogram) and sleep-related hypoxia with (1) SARS-CoV-2 positivity and (2) World Health Organization (WHO)-designated COVID-19 clinical outcomes while accounting for confounding including obesity, underlying cardiopulmonary disease, cancer, and smoking history. Design, Setting, and Participants This case-control study was conducted within the Cleveland Clinic Health System (Ohio and Florida) and included all patients who were tested for COVID-19 between March 8 and November 30, 2020, and who had an available sleep study record. Sleep indices and SARS-CoV-2 positivity were assessed with overlap propensity score weighting, and COVID-19 clinical outcomes were assessed using the institutional registry. Exposures Sleep study–identified SDB (defined by frequency of apneas and hypopneas using the Apnea-Hypopnea Index [AHI]) and sleep-related hypoxemia (percentage of total sleep time at

Background Sites of entry for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are highly expressed in nasal epithelial cells; however, little is known about the impact of intranasal corticosteroids (INCS) on coronavirus disease 2019 (COVID-19)-related outcomes. Objective To determine the association between baseline INCS use and COVID-19-related outcomes. Methods Using the Cleveland Clinic COVID-19 Research Registry, we performed a propensity score matching for treatment with INCS before SARS-CoV-2 infection (April 1, 2020, to March 31, 2021). Of the 82,096 individuals who tested positive, 72,147 met inclusion criteria. Our endpoints included the need for hospitalization, admission to the intensive care unit (ICU), or in-hospital mortality. Results Of the 12,608 (17.5%) who were hospitalized, 2935 (4.1%) required ICU admission and 1880 (2.6%) died during hospitalization. A significant proportion (n = 10,187; 14.1%) were using INCS before SARS-CoV-2 infection. Compared with nonusers, INCS users demonstrated lower risk for hospitalization (adjusted odds ratio [OR] [95% confidence interval (CI)]: 0.78 [0.72; 0.85]), ICU admission (adjusted OR [95% CI]: 0.77 [0.65; 0.92]), and in-hospital mortality (adjusted OR [95% CI]: 0.76 [0.61; 0.94]). These findings were replicated in sensitivity analyses where patients on inhaled corticosteroids and those with allergic rhinitis were excluded. The beneficial effect of INCS was significant after adjustment for baseline blood eosinophil count (measured before SARS-CoV-2 testing) in a subset of 30,289 individuals. Conclusion INCS therapy is associated with a lower risk for COVID-19-related hospitalization, ICU admission, or death. Future randomized control trials are needed to determine if INCS reduces the risk for severe outcomes related to COVID-19.

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 (

ObjectivesTo describe variation in and drivers of contemporary preoperative cardiac stress testing.SettingA dedicated preoperative risk assessment and optimisation clinic at a large integrated medical centre from 2008 through 2018.ParticipantsA cohort of 118 552 adult patients seen by 104 physicians across 159 795 visits to a preoperative risk assessment and optimisation clinic.Main outcomeReferral for stress testing before major surgery, including nuclear, echocardiographic or electrocardiographic-only stress testing, within 30 days after a clinic visit.ResultsA total of 8303 visits (5.2%) resulted in referral for preoperative stress testing. Key patient factors associated with preoperative stress testing included predicted surgical risk, patient functional status, a previous diagnosis of ischaemic heart disease, tobacco use and body mass index. Patients living in either the most-deprived or least-deprived census block groups were more likely to be tested. Patients were tested more frequently before aortic, peripheral vascular or urologic interventions than before other surgical subcategories. Even after fully adjusting for patient and surgical factors, provider effects remained important: marginal testing rates differed by a factor-of-three in relative terms and around 2.5% in absolute terms between the 5th and 95th percentile physicians. Stress testing frequency decreased over the time period; controlling for patient and physician predictors, a visit in 2008 would have resulted in stress testing approximately 3.5% of the time, while a visit in 2018 would have resulted in stress testing approximately 1.3% of the time.ConclusionsIn this large cohort of patients seen for preoperative risk assessment at a single health system, decisions to refer patients for preoperative stress testing are influenced by various factors other than estimated perioperative risk and functional status, the key considerations in current guidelines. The frequency of preoperative stress testing has decreased over time, but remains highly provider-dependent.

Introduction The relationship of OSA and human coronavirus (COVID-19) in the pediatric population is unknown. We postulate that OSA is associated with SARS-CoV-2 positivity and with adverse COVID-19 outcomes in children. Methods A retrospective review of 120 consecutive patients ( Results Cases (n=36) were 11.8±4.4 years, 61% male, 27.8% black and 88.9% with OSA, while 85.7% of controls (n=84) had OSA. OSA was not associated with increased SARS-CoV-2 positivity: OR=1.33(0.40, 4.45,p=0.64). No significant difference between cases and controls for mean AHI 3.7(1.5,6.0) vs 3.5(1.5,7.1),p=0.91,SpO2 nadir 88.6±5.4 vs 89.1±4.4,p=0.58,%time SpO2 Conclusion In this first report of which we are aware focused on COVID-19 in pediatric OSA, we use a case control design leveraging COVID-19 and sleep laboratory registries. Albeit not statistically significant, pediatric patients with OSA had a higher percentage of worse clinical outcomes. Larger network studies are needed to clarify whether poorer COVID-19 outcomes may be attributable to OSA or modulated via high risk health conditions. Support (if any)

BACKGROUND: The pneumonia 30-d readmission rate has been endorsed by the National Quality Forum as a quality metric. Hospital readmissions can potentially be lowered by improving in-hospital care, transitions of care, and post-discharge disease management programs. The purpose of this study was to create an accurate prediction model for determining the risk of 30-d readmission at the point of discharge. METHODS: The model was created using a data set of 1,295 hospitalizations at the Cleveland Clinic Main Campus with pneumonia over 3 y. Candidate variables were limited to structured variables available in the electronic health record. The final model was compared with the Centers for Medicare and Medicaid Services (CMS) model among subjects 65 y of age and older (n = 628) and was externally validated. RESULTS: Three hundred thirty subjects (25%) were readmitted within 30 d. The final model contained 13 variables and had a bias-corrected C statistic of 0.74 (95% CI 0.71–0.77). Number of admissions in the prior 6 months, opioid prescription, serum albumin during the first 24 h, international normalized ratio and blood urea nitrogen during the last 24 h were the predictor variables with the greatest weight in the model. In terms of discriminative performance, the Cleveland Clinic model outperformed the CMS model on the validation cohort (C statistic 0.69 vs 0.60, P = .042). CONCLUSIONS: The proposed risk prediction model performed better than the CMS model. Accurate readmission risk prediction at the point of discharge is feasible and can potentially be used to focus post-acute care interventions in a high-risk group of patients.

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

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.

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.

Importance The role of angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor blockers (ARB) in the setting of the coronavirus disease 2019 (COVID-19) pandemic is hotly debated. There have been recommendations to discontinue these medications, which are essential in the treatment of several chronic disease conditions, while, in the absence of clinical evidence, professional societies have advocated their continued use. Objective To study the association between use of ACEIs/ARBs with the likelihood of testing positive for COVID-19 and to study outcome data in subsets of patients taking ACEIs/ARBs who tested positive with severity of clinical outcomes of COVID-19 (eg, hospitalization, intensive care unit admission, and requirement for mechanical ventilation). Design, Setting, and Participants Retrospective cohort study with overlap propensity score weighting was conducted at the Cleveland Clinic Health System in Ohio and Florida. All patients tested for COVID-19 between March 8 and April 12, 2020, were included. Exposures History of taking ACEIs or ARBs at the time of COVID-19 testing. Main Outcomes and Measures Results of COVID-19 testing in the entire cohort, number of patients requiring hospitalizations, intensive care unit admissions, and mechanical ventilation among those who tested positive. Results A total of 18 472 patients tested for COVID-19. The mean (SD) age was 49 (21) years, 7384 (40%) were male, and 12 725 (69%) were white. Of 18 472 patients who underwent COVID-19 testing, 2285 (12.4%) were taking either ACEIs or ARBs. A positive COVID-19 test result was observed in 1735 of 18 472 patients (9.4%). Among patients who tested positive, 421 (24.3%) were admitted to the hospital, 161 (9.3%) were admitted to an intensive care unit, and 111 (6.4%) required mechanical ventilation. Overlap propensity score weighting showed no significant association of ACEI and/or ARB use with COVID-19 test positivity (overlap propensity score–weighted odds ratio, 0.97; 95% CI, 0.81-1.15). Conclusions and Relevance This study found no association between ACEI or ARB use and COVID-19 test positivity. These clinical data support current professional society guidelines to not discontinue ACEIs or ARBs in the setting of the COVID-19 pandemic. However, further study in larger numbers of hospitalized patients receiving ACEI and ARB therapy is needed to determine the association with clinical measures of COVID-19 severity.

Modern cancer care has seen an increase in the use of targeted therapies and the number of FDA-approved biomarkers. To take advantage of these options, many have turned to commercially available comprehensive genome profiling (CGP) services, like Foundation Medicine's FoundationOne assay. FoundationOne (FO) offers a list of clinically relevant genomic alterations and biomarkers, as well as a list of clinical trials, on-label and off-label therapies that may benefit the patient, that is, therapeutic associations. We performed a retrospective cohort study to assess the clinical benefit of therapy associations from FO reports. We collected demographics, therapy records, and clinical outcomes for 1004 patients who had a history of advanced cancer in the Cleveland Clinic system and had received a FO report between 2012 and 2017. FO therapy associations were considered as “applied” if a patient received an order for said therapy for the first time after their report date. We classified patients as follows: No Associated Therapy (NAT) if the patient did not receive any recommendations, Therapy Applied (TA) if at least one associated therapy was ordered after report date, and Therapy Not Applied (TNA) if none of the associated therapies were applied. We evaluated differences in demographic and clinical features among the 3 groups using Chi-squared and Kruskal-Wallis tests where appropriate. We performed survival analysis using univariate and multivariate COX Proportional Hazards regression models, and Log-Rank tests on Kaplan Meier Curves with overall survival (OS) as our metric. Our cohort demographics were 55% male, 85% white, 92% non-Hispanic, and a median age at report of 60 (IQR: 51-69). The most common diagnoses were Lung Adenocarcinoma (14%), Glioblastoma (8%), Colon Adenocarcinoma (8%), and Breast Cancer NOS (4%). Most of our patients belonged to the TNA class (64%), 21% were NAT, and 15% were TA. There was no statistical significance in the demographic distribution among the therapy classes. In the pan-cancer analysis, we found no statistically significant difference in OS among the therapy groups or any of the adjusted covariates except for metastasis status. Similarly, when evaluating the top cancer diagnoses individually, we found no significant differences in OS. The data in our study indicates that the application of FO therapy associations is not correlated with a statistically significant difference in OS for advanced cancer patients. This suggests that larger studies should be performed to better understand how CGP services provide clinical benefits to patients, and how we can maximize these benefits in the real-world community setting. Citation Format: Jean Rene Clemenceau, Sung Hak Lee, Alex Milinovich, Jian Jin, Nathan Pennell, Davendra Sohal, Tae Hyun Hwang. Analysis of the clinical benefit of comprehensive genome profiling derived therapeutic associations in advanced cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3638.

Left ventricular non-compaction (LVNC) is a poorly defined entity which encompasses both physiological adaption and pathological disease. We sought to determine the prognostic impact of plasma B-Type Natriuretic Peptide (BNP) in identifying patients at high risk of long-term complications. Patients

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.

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.

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 …

To assess changes in the clinical characteristics and treatment patterns of patients with newly diagnosed type 2 diabetes (T2D), the electronic health record system at Cleveland Clinic was used to create cross-sectional summaries of all patients with new-onset T2D in 2008 and 2013. Differences between the 2008 and 2013 data sets were assessed after adjusting for age, gender, race, and income. Approximately one-third of patients with newly diagnosed T2D in 2008 and 2013 had an A1C ≤8%, suggesting the continued presence of a delayed recognition of the disease. Patients with newly diagnosed T2D in 2008 were older than those in 2013. Hypertension, cardiovascular disease, and neuropathy were highly prevalent among patients diagnosed with T2D. The prevalence of neuropathy, cerebrovascular disease, and peripheral vascular disease increased from 2008 to 2013. Metformin was the most commonly prescribed antidiabetic medication. Sulfonylurea usage remained unchanged, while use of thiazolidinediones decreased considerably.

ObjectiveTo 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.DesignThe 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.SettingA large US integrated health system.ResultsA 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 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.ConclusionsThis 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.

BACKGROUND Few studies have examined the general correlation between socioeconomic status and imaging. This study is the first to analyze this relationship in the spine patient population. OBJECTIVE To assess the effect of socioeconomic status on the frequency with which imaging studies of the lumbar spine are ordered and completed. METHODS Patients that were diagnosed with lumbar radiculopathy and/or myelopathy and had at least 1 subsequent lumbar magnetic resonance imaging (MRI), computed tomography (CT), or X-ray ordered were retrospectively identified. Demographic information and the number of ordered and completed imaging studies were among the data collected. Patient insurance status and income level (estimated based on zip code) served as representations of socioeconomic status. RESULTS A total of 24,105 patients met the inclusion criteria for this study. Regression analyses demonstrated that uninsured patients were significantly less likely to have an MRI, CT, or X-ray study ordered (P < .001 for all modalities) and completed (P < .001 for MRI and X-ray, P = .03 for CT). Patients with lower income had higher rates of MRI, CT, and X-ray (P < .001 for all) imaging ordered but were less likely to have an ordered X-ray be completed (P = .009). There was no significant difference in the completion rate of ordered MRIs or CTs. CONCLUSION Disparities in image utilization based on socioeconomic characteristics such as insurance status and income level highlight a critical gap in access to health care. Physicians should work to mitigate the influence of such factors when deciding whether to order imaging studies, especially in light of the ongoing shift in health policy in the United States.