Novel Sleep Phenotypic Profiles Associated With Incident Atrial Fibrillation in a Large Clinical Cohort.

BACKGROUND: While sleep disorders are implicated in atrial fibrillation (AF), the interplay of physiologic alterations and symptoms remains unclear. Sleep-based phenotypes can account for this complexity and translate to actionable approaches to identify at-risk patients and therapeutic interventions. OBJECTIVES: This study hypothesized discrete phenotypes of symptoms and polysomnography (PSG)-based data differ in relation to incident AF. METHODS: Data from the STARLIT (sleep Signals, Testing, And Reports LInked to patient Traits) registry on Cleveland Clinic patients (≥18 years of age) who underwent PSG from November 27, 2004, to December 30,2015, were retrospectively examined. Phenotypes were identified using latent class analysis of symptoms and PSG-based measures of sleep-disordered breathing and sleep architecture. Phenotypes were included as the primary predictor in a multivariable-adjusted Cox proportional hazard models for incident AF. RESULTS: In our cohort (N = 43,433, age 51.8 ± 14.5 years, 51.9% male, 74.9% White), 7.3% (n = 3,166) had baseline AF. Over a 7.6- ± 3.4-year follow-up period, 8.9% (n = 3,595) developed incident AF. Five phenotypes were identified. The hypoxia subtype (n = 3,245) had 48% increased incident AF (HR: 1.48; 95% CI: 1.34-1.64), the apneas + arousals subtype (n = 4,592) had 22% increased incident AF (HR: 1.22; 95% CI: 1.10-1.35), and the short sleep + nonrapid eye movement subtype (n = 6,126) had 11% increased incident AF (HR: 1.11; 95% CI: 1.01-1.22) compared with long sleep + rapid eye movement (n = 26,809), the reference group. The hypopneas subtype (n = 2,661) did not differ from reference (HR: 0.89; 95% CI: 0.77-1.03). CONCLUSIONS: Consistent with prior evidence supporting hypoxia as an AF driver and cardiac risk of the sleepy phenotype, this constellation of symptoms and physiologic alterations illustrates vulnerability for AF development, providing potential value in enhancing our understanding of integrated sleep-specific symptoms and physiologic risk of atrial arrhythmogenesis.

Adverse Cardiovascular Outcomes in Patients With Obstructive Sleep Apnea and Obesity: Metabolic Surgery vs Usual Care.

BACKGROUND: No therapy has been shown to reduce the risk of major adverse cardiovascular events (MACE) and death in patients with obstructive sleep apnea (OSA). OBJECTIVES: The authors sought to investigate the long-term relationship between metabolic surgery and incident MACE in patients with OSA and obesity. METHODS: Adult patients with a body mass index 35 to 70 kg/m2 and moderate-to-severe OSA at a U.S. health system (2004-2018) were identified. Baseline characteristics of patients who underwent metabolic surgery were balanced with a nonsurgical control group using overlap-weighting methods. Multivariable Cox regression analysis estimated time-to-incident MACE. Follow-up ended in September 2022. RESULTS: A total of 13,657 patients (7,496 [54.9%] men; mean age 52.0 ± 12.4 years; median body mass index 41.0 kg/m2 [Q1-Q3: 37.6-46.2 kg/m2]), including 970 patients in the metabolic surgery group and 12,687 patients in the nonsurgical group, with a median follow-up of 5.3 years (Q1-Q3: 3.1-8.4 years) were analyzed. The mean between-group difference in body weight at 10 years was 26.6 kg (95% CI: 25.6-27.6 kg) or 19.3% (95% CI: 18.6%-19.9%). The 10-year cumulative incidence of MACE was 27.0% (95% CI: 21.6%-32.0%) in the metabolic surgery group and 35.6% (95% CI: 33.8%-37.4%) in the nonsurgical group (adjusted HR: 0.58 [95% CI: 0.48-0.71]; P < 0.001). The 10-year cumulative incidence of all-cause mortality was 9.1% (95% CI: 5.7%-12.4%) in the metabolic surgery group and 12.5% (95% CI: 11.2%-13.8%) in the nonsurgical group (adjusted HR: 0.63 [95% CI: 0.45-0.89]; P = 0.009). CONCLUSIONS: Among patients with moderate-to-severe OSA and obesity, metabolic surgery, compared with nonsurgical management, was associated with a significantly lower risk of incident MACE and death.

Proportion and predictors of FVC decline in patients with interstitial lung disease.

RATIONALE: The proportion of patients who develop progressive pulmonary fibrosis (PPF), along with risk factors for progression remain poorly understood. OBJECTIVES: To examine factors associated with an increased risk of developing PPF among patients at a referral center. METHODS: We identified patients with a diagnosis of interstitial lung disease (ILD) seen within the Cleveland Clinic Health System. Utilizing a retrospective observational approach we estimated the risk of developing progression by diagnosis group and identified key clinical predictors using the FVC component of both the original progressive fibrotic interstitial lung disease (PFILD) and the proposed PPF (ATS) criteria. RESULTS: We identified 5934 patients with a diagnosis of ILD. The cumulative incidence of progression over the 24 months was similar when assessed with the PFILD and PPF criteria (33.1 % and 37.9 % respectively). Of those who met the ATS criteria, 9.5 % did not meet the PFILD criteria. Conversely, 4.3 % of patients who met PFILD thresholds did not achieve the 5 % absolute FVC decline criteria. Significant differences in the rate of progression were seen based on underlying diagnosis. Steroid therapy (HR 1.46, CI 1.31-1.62) was associated with an increased risk of progressive fibrosis by both PFILD and PPF criteria. CONCLUSION: Regardless of the definition used, the cumulative incidence of progressive disease is high in patients with ILD in the 24 months following diagnosis. Some differences are seen in the risk of progression when assessed by PFILD and PPF criteria. Further work is needed to identify modifiable risk factors for the development of progressive fibrosis.

Explainable machine learning for predicting conversion to neurological disease: Results from 52,939 medical records.

Objective: This study assesses the application of interpretable machine learning modeling using electronic medical record data for the prediction of conversion to neurological disease. Methods: A retrospective dataset of Cleveland Clinic patients diagnosed with Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, or Parkinson's disease, and matched controls based on age, sex, race, and ethnicity was compiled. Individualized risk prediction models were created using eXtreme Gradient Boosting for each neurological disease at four timepoints in patient history. The prediction models were assessed for transparency and fairness. Results: At timepoints 0-months, 12-months, 24-months, and 60-months prior to diagnosis, Alzheimer's disease models achieved the area under the receiver operating characteristic curve on a holdout test dataset of 0.794, 0.742, 0.709, and 0.645; amyotrophic lateral sclerosis of 0.883, 0.710, 0.658, and 0.620; multiple sclerosis of 0.922, 0.877, 0.849, and 0.781; and Parkinson's disease of 0.809, 0.738, 0.700, and 0.651, respectively. Conclusions: The results demonstrate that electronic medical records contain latent information that can be used for risk stratification for neurological disorders. In particular, patient-reported outcomes, sleep assessments, falls data, additional disease diagnoses, and longitudinal changes in patient health, such as weight change, are important predictors.

Healthcare utilization and clinical characteristics of genetic epilepsy in electronic health records.

Understanding the clinical characteristics and medical treatment of individuals affected by genetic epilepsies is instrumental in guiding selection for genetic testing, defining the phenotype range of these rare disorders, optimizing patient care pathways and pinpointing unaddressed medical need by quantifying healthcare resource utilization. To date, a matched longitudinal cohort study encompassing the entire spectrum of clinical characteristics and medical treatment from childhood through adolescence has not been performed. We identified individuals with genetic and non-genetic epilepsies and onset at ages 0-5 years by linkage across the Cleveland Clinic Health System. We used natural language processing to extract medical terms and procedures from longitudinal electronic health records and tested for cross-sectional and temporal associations with genetic epilepsy. We implemented a two-stage design: in the discovery cohort, individuals were stratified as being 'likely genetic' or 'non-genetic' by a natural language processing algorithm, and controls did not receive genetic testing. The validation cohort consisted of cases with genetic epilepsy confirmed by manual chart review and an independent set of controls who received negative genetic testing. The discovery and validation cohorts consisted of 503 and 344 individuals with genetic epilepsy and matched controls, respectively. The median age at the first encounter was 0.1 years and 7.9 years at the last encounter, and the mean duration of follow-up was 8.2 years. We extracted 188,295 Unified Medical Language System annotations for statistical analysis across 9659 encounters. Individuals with genetic epilepsy received an earlier epilepsy diagnosis and had more frequent and complex encounters with the healthcare system. Notably, the highest enrichment of encounters compared with the non-genetic groups was found during the transition from paediatric to adult care. Our computational approach could validate established comorbidities of genetic epilepsies, such as behavioural abnormality and intellectual disability. We also revealed novel associations for genitourinary abnormalities (odds ratio 1.91, 95% confidence interval: 1.66-2.20, P = 6.16 × 10-19) linked to a spectrum of underrecognized epilepsy-associated genetic disorders. This case-control study leveraged real-world data to identify novel features associated with the likelihood of a genetic aetiology and quantified the healthcare utilization of genetic epilepsies compared with matched controls. Our results strongly recommend early genetic testing to stratify individuals into specialized care paths, thus improving the clinical management of people with genetic epilepsies.

Impact of Embedding a Venous Thromboembolism Risk Assessment Model in the Electronic Health Record Versus Usual Care: A Cluster-Randomized Trial.

BACKGROUND: There are multiple risk assessment models (RAMs) for venous thromboembolism prophylaxis, but it is unknown whether they increase appropriate prophylaxis. METHODS: To determine the impact of a RAM embedded in the electronic health record, we conducted a stepped-wedge hospital-level cluster-randomized trial conducted from October 1, 2017 to February 28, 2019 at 10 Cleveland Clinic hospitals. We included consecutive general medical patients aged 18 years or older. Patients were excluded if they had a contraindication to prophylaxis, including anticoagulation for another condition, acute bleeding, or comfort-only care. A RAM was embedded in the general admission order set and physicians were encouraged to use it. The decisions to use the RAM and act on the results were reserved to the treating physician. The primary outcome was the percentage of patients receiving appropriate prophylaxis (high-risk patients with pharmacological thromboprophylaxis plus low-risk patients without prophylaxis) within 48 hours of hospitalization. Secondary outcomes included total patients receiving prophylaxis, venous thromboembolism among high-risk patients at 14 and 45 days, major bleeding, heparin-induced thrombocytopenia, and length of stay. Mixed-effects models were used to analyze the study outcomes. RESULTS: A total of 26 506 patients (mean age, 61; 52% female; 73% White) were analyzed, including 11 134 before and 15 406 after implementation of the RAM. After implementation, the RAM was used for 24% of patients, and the percentage of patients receiving appropriate prophylaxis increased from 43.1% to 48.8% (adjusted odds ratio, 1.11 [1.00-1.23]), while overall prophylaxis use decreased from 73.5% to 65.2% (adjusted odds ratio, 0.87 [0.78-0.97]). Rates of venous thromboembolism among high-risk patients (adjusted odds ratio, 0.72 [0.38-1.36]), rates of bleeding and heparin-induced thrombocytopenia (adjusted odds ratio, 0.19 [0.02-1.47]), and length of stay were unchanged. CONCLUSIONS: Implementation of a RAM for venous thromboembolism increased appropriate prophylaxis use, but the RAM was used for a minority of patients. REGISTRATION: URL: https://www.clinicaltrials.gov/study/NCT03243708?term=nct03243708&rank=1; Unique identifier: NCT03243708.

Predicting disability and mortality in CV2/CRMP5-IgG associated paraneoplastic neurologic disorders.

BACKGROUND: We aimed to investigate the prognostic factors associated with clinical outcomes in CV2/Collapsin response-mediator protein 5 (CRMP5)-IgG paraneoplastic neurologic disorders (PND). METHODS: This is a retrospective study of patients with CV2/CRMP5-IgG PND evaluated between 2002-2022. We examined the association of clinical variables (including age, clinical phenotype [autoimmune encephalopathy, myelopathy, polyneuropathy/radiculopathy, MG, cerebellar ataxia, chorea, optic neuropathy], cancer) with three clinical outcomes (wheelchair dependence, modified Rankin Scale [mRS], mortality) using univariate logistic regression and Cox proportional hazards modeling. Kaplan-Meier estimates were used to determine the probability of survival. RESULTS: Twenty-seven patients (56% female) with CV2/CRMP5-IgG PND were identified with a median follow-up of 54 months (IQR = 11-102). An underlying tumor was identified in 15 patients (56%) including small cell lung cancer (SCLC) (8, [53%]), thymoma (4, [27%]), and other histologies (3, [20%]). At last follow-up, 10 patients (37%) needed a wheelchair for mobility and this outcome was associated with myelopathy (HR = 7.57, 95% CI = 1.87-30.64, P = 0.005). Moderate-severe mRS = 3-5 was associated with CNS involvement (encephalopathy, myelopathy, or cerebellar ataxia) (OR = 7.00, 95% CI = 1.18-41.36, P = 0.032). The probability of survival 4 years after symptom onset was 66%. Among cancer subtypes, SCLC (HR = 18.18, 95% CI = 3.55-93.04, P < 0.001) was significantly associated with mortality, while thymoma was not. INTERPRETATION: In this retrospective longitudinal study of CV2/CRMP5-IgG PND, patients with CNS involvement, particularly myelopathy, had higher probability of disability. SCLC was the main determinant of survival in this population.

Longitudinal Disability, Cognitive Impairment, and Mood Symptoms in Patients With Anti-NMDA Receptor Encephalitis.

BACKGROUND AND OBJECTIVES: Longitudinal outcomes in anti-NMDA receptor encephalitis (anti-NMDARe) are still not fully understood and may not be adequately captured with the modified Rankin Scale (mRS), often the sole reported outcome. We aim to characterize longitudinal outcomes in anti-NMDARe using multiple outcome measures. METHODS: This single-center, retrospective, observational study examined outcome measures (mRS and Clinical Assessment Scale in Autoimmune Encephalitis [CASE]) in adults with NMDA receptor-IgG in CSF at short- and long-term follow-ups using linear and logistic regression modeling. Patients with evaluations for cognitive impairment (Montreal Cognitive Assessment/Mini-Mental State Examination), depression (Patient Health Questionnaire-9), and anxiety (General Anxiety Disorder-7) >6 months from symptom onset were correlated with final CASE scores. RESULTS: Thirty-eight patients (76% female, median disease onset age = 28 years, range = 1-75 years) were included. The majority received first-line immunosuppressants (97%) at a median of 3.9 weeks (interquartile range [IQR] = 2.1-9.7) from symptom onset and 68% received second-line therapies. At baseline, median/mean mRS and CASE were 4 (IQR = 3-5) and 12.9 (SD = 7.2), respectively. At short-term follow-up (median = 10 weeks, IQR = 6-17), factors associated with higher CASE and mRS included dysautonomia, coma/lethargy, seizures/status epilepticus, and intensive care unit admission (p < 0.05). At long-term follow-up (median = 70 weeks, IQR = 51-174), median/mean mRS and CASE were 2 (IQR = 1-3) and 4.4 (SD = 4.2), respectively. Only weakness at symptom onset predicted higher mRS scores (odds ratio = 5.6, 95% confidence interval 1.02-30.9, p = 0.047). Despite both mRS and CASE improving from baseline (p < 0.001), only 9 patients (31%) returned to their premorbid function. Among patients with cognitive and mood evaluations >6 months from onset, moderate-severe cognitive impairment (42%), depression (28%), and anxiety (30%) were frequent. Cognitive and depression measures were associated with final CASE subscores (including memory, language, weakness, and psychiatric). DISCUSSION: Multiple clinical factors influenced short-term outcomes, but only onset weakness influenced long-term mRS, highlighting that mRS is predominantly affected by global motor function. Although mRS and CASE improved over time for most patients, these outcome measures did not capture the full extent of long-term functional impairment in terms of mood, cognition, and the ability to return to premorbid function. This emphasizes the need for increased utilization of more nuanced cognitive and mood outcome measures.

Analysis of the Larissa Heart Failure Risk Score: Predictive Value in 9207 Patients Hospitalized for Heart Failure from a Single Center.

Early risk stratification is of outmost clinical importance in hospitalized patients with heart failure (HHF). We examined the predictive value of the Larissa Heart Failure Risk Score (LHFRS) in a large population of HHF patients from the Cleveland Clinic. A total of 13,309 admissions for heart failure (HF) from 9207 unique patients were extracted from the Cleveland Clinic's electronic health record system. For each admission, components of the 3-variable simple LHFRS were obtained, including hypertension history, myocardial infarction history, and red blood cell distribution width (RDW) ≥ 15%. The primary outcome was a HF readmission and/or all-cause mortality at one year, and the secondary outcome was all-cause mortality at one year of discharge. For both outcomes, all variables were statistically significant, and the Kaplan-Meier curves were well-separated and in a consistent order (Log-rank test p-value < 0.001). Higher LHFRS values were found to be strongly related to patients experiencing an event, showing a clear association of LHFRS with this study outcomes. The bootstrapped-validated area under the curve (AUC) for the logistic regression model for each outcome revealed a C-index of 0.64 both for the primary and secondary outcomes, respectively. LHFRS is a simple risk model and can be utilized as a basis for risk stratification in patients hospitalized for HF.

Sleep-Disordered Breathing, Hypoxia, and Pulmonary Physiologic Influences in Atrial Fibrillation.

Background We leverage a large clinical cohort to elucidate sleep-disordered breathing and sleep-related hypoxia in incident atrial fibrillation (AF) development given the yet unclear contributions of sleep-related hypoxia and pulmonary physiology in sleep-disordered breathing and AF. Methods and Results Patients who underwent sleep studies at Cleveland Clinic January 2, 2000, to December 30, 2015, comprised this retrospective cohort. Cox proportional hazards models were used to examine apnea hypopnea index, percentage time oxygen saturation <90%, minimum and mean oxygen saturation, and maximum end-tidal carbon dioxide on incident AF adjusted for age, sex, race, body mass index, cardiopulmonary disease and risk factors, antiarrhythmic medications, and positive airway pressure. Those with spirometry were additionally adjusted for forced expiratory volume in 1 second, forced vital capacity, and forced expiratory volume in 1 second/forced vital capacity. This cohort (n=42 057) was 50.7±14.1 years, 51.3% men, 74.1% White individuals, had median body mass index 33.2 kg/m2, and 1947 (4.6%) developed AF over 5 years. A 10-unit apnea hypopnea index increase was associated with 2% higher AF risk (hazard ratio [HR], 1.02 [95% CI, 1.00-1.03]). A 10-unit increase in percentage time oxygen saturation <90% and 10-unit decreases in mean and minimum oxygen saturation were associated with 6% (HR, 1.06 [95% CI, 1.04-1.08]), 30% (HR, 1.30 [95% CI, 1.18-1.42]), and 9% (HR, 1.09 [95% CI, 1.03-1.15]) higher AF risk, respectively. After adjustment for spirometry (n=9683 with available data), only hypoxia remained significantly associated with incident AF, although all coefficients were stable. Conclusions Sleep-related hypoxia was associated with incident AF in this clinical cohort, consistent across 3 measures of hypoxia, persistent after adjustment for pulmonary physiologic impairment. Findings identify a strong role for sleep-related hypoxia in AF development without pulmonary physiologic interdependence.

Nirmatrelvir or Molnupiravir Use and Severe Outcomes From Omicron Infections.

Importance: Ritonavir-boosted nirmatrelvir and molnupiravir are currently used in the US and in other countries to treat nonhospitalized patients who have mild-to-moderate COVID-19 and who are at high risk for progression to severe disease. The associations of these 2 oral antiviral drugs with hospitalization and death resulting from infection with new SARS-CoV-2 Omicron subvariants, particularly BQ.1.1 and XBB.1.5, are unknown. Objective: To assess the association of nirmatrelvir or molnupiravir use with the risks of hospitalization and death among patients infected with new Omicron subvariants. Design, Setting, and Participants: This was a cohort study of patients who received a diagnosis of COVID-19 at Cleveland Clinic from April 1, 2022, to February 20, 2023 (during which the Omicron variant evolved from BA.2 to BA.4/BA.5, then to BQ.1/BQ.1.1, and finally to XBB/XBB.1.5) and who were at high risk of progressing to severe disease, with follow-up through 90 days after diagnosis. The final date for follow-up data collection was February 27, 2023. Exposures: Treatment with ritonavir-boosted nirmatrelvir or molnupiravir. Main Outcomes and Measures: The primary outcome was time to death. The secondary outcome was time to either hospitalization or death. The association of either nirmatrelvir or molnupiravir use with each outcome was measured by the hazard ratio (HR) adjusted for demographic factors, socioeconomic status, date of COVID-19 diagnosis, coexisting medical conditions, COVID-19 vaccination status, and previous SARS-CoV-2 infection. Results: There were 68 867 patients (29 386 [42.7%] aged ≥65 years; 26 755 [38.9%] male patients; 51 452 [74.7%] non-Hispanic White patients). Thirty of 22 594 patients treated with nirmatrelvir, 27 of 5311 patients treated with molnupiravir, and 588 of 40 962 patients who received no treatment died within 90 days of Omicron infection. The adjusted HRs of death were 0.16 (95% CI, 0.11-0.23) for nirmatrelvir and 0.23 (95% CI, 0.16-0.34) for molnupiravir. The adjusted HRs of hospitalization or death were 0.63 (95% CI, 0.59-0.68) for nirmatrelvir and 0.59 (95% CI, 0.53-0.66) for molnupiravir. The associations of both drugs with both outcomes were observed across subgroups defined by age, race and ethnicity, date of COVID-19 diagnosis, vaccination status, previous infection status, and coexisting conditions. Conclusions and Relevance: These findings suggest that the use of either nirmatrelvir or molnupiravir is associated with reductions in mortality and hospitalization in patients infected with Omicron, regardless of age, race and ethnicity, virus strain, vaccination status, previous infection status, or coexisting conditions. Both drugs can, therefore, be used to treat nonhospitalized patients who are at high risk of progressing to severe COVID-19.

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.

Thrombotic outcomes in patients in a large clinical enterprise following COVID-19 vaccination.

Vaccination against COVID-19 reduces infection-related mortality. Unfortunately, reports of vaccine-induced immune thrombotic thrombocytopenia (VITT) in individuals administered adenovirus-vector-based vaccines (ChAdOx1 nCoV-19 and Ad26.COV2.S) have spurred side effect concerns. To address vaccine hesitancy related to this, it is essential to determine the incidence of VITT (defined by a 50% decrease in platelet count and positive anti-PF4 immunoassay within 4-28 days after vaccination) among patients administered two doses of an mRNA-based COVID-19 vaccination. We identified a retrospective cohort of 223,345 patients in the Cleveland Clinic Enterprise administered a COVID-19 vaccine at any location in Northeast Ohio and Florida from 12/4/2020 to 6/6/2021. 97.3% of these patients received an mRNA-based vaccination. Patients with: (1) a serial complete blood count both before and after vaccination and (2) a decrease in platelet count of ≥ 50% were selected for chart review. The primary outcome was the incidence of thrombotic events, including venous thromboembolism (VTE) and arterial thrombosis, 4-28 days post vaccination. Of 74 cohort patients with acute thrombosis, 72 (97.3%) demonstrated clear etiologies, such as active malignancy. Of two patients with unprovoked thrombosis, only one had findings concerning for VITT, with a strongly positive anti-PF4 antibody assay. In this large, multi-state, retrospective cohort, of 223,345 patients (97.2% of whom received the mRNA-based mRNA-1273 or BNT162b2 vaccines), we detected a single case that was concerning for VITT in a patient who received an mRNA vaccine. The overwhelming majority of patients with a thrombotic event 4-28 days following vaccination demonstrated clear etiologies.

Impacts of COVID-19 on Glycemia and Risk of Diabetic Ketoacidosis.

Reports indicate that coronavirus disease 2019 (COVID-19) may impact pancreatic function and increase type 2 diabetes (T2D) risk, although real-world COVID-19 impacts on HbA1c and T2D are unknown. We tested whether COVID-19 increased HbA1c, risk of T2D, or diabetic ketoacidosis (DKA). We compared pre- and post-COVID-19 HbA1c and T2D risk in a large real-world clinical cohort of 8,755 COVID-19(+) patients and 11,998 COVID-19(-) matched control subjects. We investigated whether DKA risk was modified in COVID-19(+) patients with type 1 diabetes (T1D) (N = 701) or T2D (N = 21,830), or by race and sex. We observed a statistically significant, albeit clinically insignificant, HbA1c increase post-COVID-19 (all patients ΔHbA1c = 0.06%; with T2D ΔHbA1c = 0.1%) and no increase among COVID-19(-) patients. COVID-19(+) patients were 40% more likely to be diagnosed with T2D compared with COVID-19(-) patients and 28% more likely for the same HbA1c change as COVID-19(-) patients, indicating that COVID-19-attributed T2D risk may be due to increased recognition during COVID-19 management. DKA in COVID-19(+) patients with T1D was not increased. COVID-19(+) Black patients with T2D displayed disproportionately increased DKA risk (hazard ratio 2.46 [95% CI 1.48-6.09], P = 0.004) compared with White patients, suggesting a need for further clinical awareness and investigation.

Prognostic value of initial electrocardiography in predicting long-term all-cause mortality in COVID-19.

BACKGROUND: The electrocardiography (ECG) has short-term prognostic value in coronavirus disease 2019 (COVID-19), yet its ability to predict long-term mortality is unknown. This study aimed to elucidate the predictive role of initial ECG on long-term all-cause mortality in patients diagnosed with COVID-19. METHODS: In this prospective cohort study, adults with COVID-19 who underwent ECG testing within a 17-hospital health system in Northeast Ohio and Florida between 03/2020-06/2020 were identified. An expert ECG reader analyzed all studies blinded to patient status. The associations of ECG characteristics with long-term all-cause mortality and intensive care unit (ICU) admission were assessed using Cox proportional hazards regression model and multivariable logistic regression models, respectively. Status of long-term mortality was adjudicated on 01/07/2022. RESULTS: Of 837 patients (median age 65 years, 51% female, 44% Black), 683 (81.6%) were hospitalized, 281 (33.6%) required ICU admission, 67 (8.0%) died in-hospital, and 206 (24.6%) died at final follow-up after a median (IQR) of 21 (9-103) days after ECG. Overall, 179 (20.7%) patients presented with sinus tachycardia, 12 (1.4%) with atrial flutter, and 45 (5.4%) with atrial fibrillation (AF). After multivariable adjustment, sinus tachycardia (E-value for HR=3.09, lower CI=2.2) and AF (E-value for HR=3.13, lower CI=2.03) each independently predicted all-cause mortality. At final follow-up, patients with AF had 64.5% probability of death compared with 20.5% for those with normal sinus rhythm (P<.0001). CONCLUSIONS: Sinus tachycardia and AF on initial ECG strongly predict long-term all-cause mortality in COVID-19. The ECG can serve as a powerful long-term prognostic tool in COVID-19.

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.

Association of Bariatric Surgery With Cancer Risk and Mortality in Adults With Obesity.

Importance: Obesity increases the incidence and mortality from some types of cancer, but it remains uncertain whether intentional weight loss can decrease this risk. Objective: To investigate whether bariatric surgery is associated with lower cancer risk and mortality in patients with obesity. Design, Setting, and Participants: In the SPLENDID (Surgical Procedures and Long-term Effectiveness in Neoplastic Disease Incidence and Death) matched cohort study, adult patients with a body mass index of 35 or greater who underwent bariatric surgery at a US health system between 2004 and 2017 were included. Patients who underwent bariatric surgery were matched 1:5 to patients who did not undergo surgery for their obesity, resulting in a total of 30 318 patients. Follow-up ended in February 2021. Exposures: Bariatric surgery (n = 5053), including Roux-en-Y gastric bypass and sleeve gastrectomy, vs nonsurgical care (n = 25 265). Main Outcomes and Measures: Multivariable Cox regression analysis estimated time to incident obesity-associated cancer (a composite of 13 cancer types as the primary end point) and cancer-related mortality. Results: The study included 30 318 patients (median age, 46 years; median body mass index, 45; 77% female; and 73% White) with a median follow-up of 6.1 years (IQR, 3.8-8.9 years). The mean between-group difference in body weight at 10 years was 24.8 kg (95% CI, 24.6-25.1 kg) or a 19.2% (95% CI, 19.1%-19.4%) greater weight loss in the bariatric surgery group. During follow-up, 96 patients in the bariatric surgery group and 780 patients in the nonsurgical control group had an incident obesity-associated cancer (incidence rate of 3.0 events vs 4.6 events, respectively, per 1000 person-years). The cumulative incidence of the primary end point at 10 years was 2.9% (95% CI, 2.2%-3.6%) in the bariatric surgery group and 4.9% (95% CI, 4.5%-5.3%) in the nonsurgical control group (absolute risk difference, 2.0% [95% CI, 1.2%-2.7%]; adjusted hazard ratio, 0.68 [95% CI, 0.53-0.87], P = .002). Cancer-related mortality occurred in 21 patients in the bariatric surgery group and 205 patients in the nonsurgical control group (incidence rate of 0.6 events vs 1.2 events, respectively, per 1000 person-years). The cumulative incidence of cancer-related mortality at 10 years was 0.8% (95% CI, 0.4%-1.2%) in the bariatric surgery group and 1.4% (95% CI, 1.1%-1.6%) in the nonsurgical control group (absolute risk difference, 0.6% [95% CI, 0.1%-1.0%]; adjusted hazard ratio, 0.52 [95% CI, 0.31-0.88], P = .01). Conclusions and Relevance: Among adults with obesity, bariatric surgery compared with no surgery was associated with a significantly lower incidence of obesity-associated cancer and cancer-related mortality.

Computable Phenotype of a Crohn's Disease Natural History Model.

BACKGROUND: Analytic tools to study important clinical issues in complex, chronic diseases such as Crohn's disease (CD) include randomized trials, claims database studies, or small longitudinal epidemiologic cohorts. Using natural language processing (NLP), we sought to define the computable phenotype health state of pediatric and adult CD and develop patient-level longitudinal histories for health outcomes. METHODS: We defined 6 health states for CD using a subjective symptom-based assessment (symptomatic/asymptomatic) and an objective disease state assessment (active/inactive/no testing). Gold standard for the 6 health states was derived using an iterative process during review by our CD experts. We calculated the transition probabilities to estimate the time to transitions between the various health states using nonparametric Kaplan-Meier estimation and a Markov model. Finally, we determined a standard utility measure from clinical patients assigned to different health states. RESULTS: The NLP computable phenotype health state model correctly ascertained the objective test results and symptoms 96% and 85% of the time, respectively, based on a blinded chart evaluation. In our model, >25% of patients who begin as asymptomatic/active transition to symptomatic/active over the following year. For both adult and pediatric CD health states, the utility assessments of a symptomatic/inactive health state closely resembled a symptomatic/active health state. CONCLUSIONS: Our methodology for a computable phenotype health state demonstrates the application of real-world data to define progression and optimal management of a chronic disease such as CD. The application of the model has the potential to lead to a better understanding of the true impact of a therapeutic intervention and can provide long-term cost-effectiveness analyses for a new therapy. HIGHLIGHTS: Using natural language processing, we defined the computable phenotype health state of Crohn's disease and developed patient-level longitudinal histories for health outcomes.Our methodology demonstrates the application of real-world data to define the progression of a chronic disease.The application of the model has the potential to provide better understanding of the true impact of a new therapy.

Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study.

BACKGROUND: Driven by quality outcomes and economic incentives, predicting 30-day hospital readmissions remains important for healthcare systems. The Cleveland Clinic Health System (CCHS) implemented an internally validated readmission risk score in the electronic medical record (EMR). OBJECTIVE: We evaluated the predictive accuracy of the readmission risk score across CCHS hospitals, across primary discharge diagnosis categories, between surgical/medical specialties, and by race and ethnicity. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult patients discharged from a CCHS hospital April 2017-September 2020. MAIN MEASURES: Data was obtained from the CCHS EMR and billing databases. All patients discharged from a CCHS hospital were included except those from Oncology and Labor/Delivery, patients with hospice orders, or patients who died during admission. Discharges were categorized as surgical if from a surgical department or surgery was performed. Primary discharge diagnoses were classified per Agency for Healthcare Research and Quality Clinical Classifications Software Level 1 categories. Discrimination performance predicting 30-day readmission is reported using the c-statistic. RESULTS: The final cohort included 600,872 discharges from 11 Northeast Ohio and Florida CCHS hospitals. The readmission risk score for the cohort had a c-statistic of 0.6875 with consistent yearly performance. The c-statistic for hospital sites ranged from 0.6762, CI [0.6634, 0.6876], to 0.7023, CI [0.6903, 0.7132]. Medical and surgical discharges showed consistent performance with c-statistics of 0.6923, CI [0.6807, 0.7045], and 0.6802, CI [0.6681, 0.6925], respectively. Primary discharge diagnosis showed variation, with lower performance for congenital anomalies and neoplasms. COVID-19 had a c-statistic of 0.6387. Subgroup analyses showed c-statistics of > 0.65 across race and ethnicity categories. CONCLUSIONS: The CCHS readmission risk score showed good performance across diverse hospitals, across diagnosis categories, between surgical/medical specialties, and by patient race and ethnicity categories for 3 years after implementation, including during COVID-19. Evaluating clinical decision-making tools post-implementation is crucial to determine their continued relevance, identify opportunities to improve performance, and guide their appropriate use.