tbuckley/cabot-search huggingface dataset:
Framework and Strategies to Eliminate Disparities in Colorectal Cancer Screening Outcomes
Authors: Chyke A. Doubeni, Kevin Selby, Samir Gupta
Journal: Annual Review of Medicine (2020)

Preventable differences in colorectal cancer (CRC) mortality across racial/ethnic, economic, geographic, and other groups can be eliminated by assuring equitable access and quality across the care continuum, but few interventions have been demonstrated to do so. Multicomponent strategies designed with a health equity framework may be effective. A health equity framework takes into account social determinants of health, multilevel influences (policy, community, delivery, and individual levels), screening processes, and community engagement. Effective strategies for increasing screening uptake include patient navigation and other interventions for structural barriers, reminders and clinical decision support, and data to continuously track metrics and guide targets for improvement. Community resource gaps should be addressed to assure high-quality services irrespective of racial/ethnic and socioeconomic status. One model combinespopulation-based proactive outreach screening with screening delivery at in-person or virtual points of contact, as well as community engagement. Patient- and provider-based behavioral interventions may be considered for increasing screening demand and delivery. Providing a choice of screening tests is recommended for CRC screening, and access to colonoscopy is required for completion of the CRC screening process.
Abstract 16255: Acute Pericarditis Related Hospitalization and Readmission in the United States
Authors: Prakash Acharya, Farhad Sami, Omar Al-Taweel, Sagar Ranka, Brianna Stack, Prince Sethi, Siva S Taduru, Zubair Shah, Kamal gupta
Journal: Circulation (2020)

Introduction: Acute pericarditis accounts for one in every twenty emergency department visits for chest pain and a majority of these patients get admitted to a hospital. However, apart from small studies, there is a lack of data regarding the incidence and predictors of readmissions in these patients. Methodology: A secondary analysis of the Nationwide Readmission Database for years 2016-2017 was performed. Patients who were admitted with a primary diagnosis of acute pericarditis in the first six months of each year were identified based on International Classification of Diseases (ICD-10), Clinical Modification codes, and were followed for 180 days. A multivariate cox-regression model was utilized to delineate the predictors of pericarditis related readmissions. Results: A total of 21,115 patients were admitted with a primary diagnosis of acute pericarditis. The mean age was 53.3+19 years and 60.83% were males. About 23% of patients had pericardial effusion or tamponade and 19.4% of patients presenting with pericarditis required pericardiocentesis. The mortality rate during index admission was 3.21% and the mean length of stay was 6.4+9 days. The rate of all-cause readmission was 30.8% within 180 days, of which 23.8% were pericarditis related. The mean time to readmission for pericarditis was 37.7+41 days. Females were at higher risk of readmission for pericarditis [OR 1.66, CI (1.38-1.99), p&lt;0.001] after adjustment for multiple variables (including connective tissue disease, congestive heart failure and malignancy). Presence of comorbidities like diabetes mellitus [HR 1.21, CI(1.01-1.45), p=0.04], obesity [HR 1.27, CI(1.05-1.54), p=0.01], and chronic lung disease [HR 1.32, CI(1.12-1.57), p=0.001] also increased risk of pericarditis related readmissions. Moreover, the length of index hospitalization was significantly higher in patients with pericarditis related readmissions [5.4+6 vs1.6+5 days, p&lt;0.001]. Conclusion: Even though the mortality during index admission in patients admitted with pericarditis is low, about 1 in every 3 patients will be readmitted within 180 days. While females account for a minority of initial admissions for pericarditis, their risk of readmission is significantly higher.
Younger Adults Caught in COVID-19 Crosshairs as Demographics Shift
Authors: Jennifer Abbasi
Journal: JAMA (2020)

Caspar I. van der Made, MD; Annet Simons, PhD; Janneke Schuurs-Hoeijmakers, MD, PhD; Guus van den Heuvel, MD; Tuomo Mantere, PhD; Simone Kersten, MSc; Rosanne C. van Deuren, MSc; Marloes Steehouwer, BSc; Simon V. van Reijmersdal, BSc; Martin Jaeger, PhD; Tom Hofste, BSc; Galuh Astuti, PhD; Jordi Corominas Galbany, PhD; Vyne van der Schoot, MD, PhD; Hans van der Hoeven, MD, PhD; Wanda Hagmolen of ten Have, MD, PhD; Eva Klijn, MD, PhD; Catrien van den Meer, MD; Jeroen Fiddelaers, MD; Quirijn de Mast, MD, PhD; Chantal P. Bleeker-Rovers, MD, PhD; Leo A. B. Joosten, PhD; Helger G. Yntema, PhD; Christian Gilissen, PhD; Marcel Nelen, PhD; Jos W. M. van der Meer, MD, PhD; Han G. Brunner, MD, PhD; Mihai G. Netea, MD, PhD; Frank L. van de Veerdonk, MD, PhD; Alexander Hoischen, PhD
Financial Toxicity From Generic Specialty Drug Use
Authors: Katrina A. Fischer, Robert E. Miller, John A. Glaspy
Journal: JAMA Oncology (2020)

Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA Oncology HomeNew OnlineCurrent IssueFor Authors Podcast Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA Oncology journal
Abstract 13102: Prediction of Incident AF With Deep Learning Can Identify Patients at High Risk for AF-related Stroke
Authors: John Pfeifer, Sushravya M Raghunath, Alvaro Ulloa, Arun Nemani, Tanner Carbonati, Linyuan Jing, David vanMaanen, Dustin Hartzel, Jeffrey Ruhl, Nathan J Stoudt, Kipp W Johnson, Noah Zimmerman, Joseph Leader, H Lester Kirchner, Christoph Griessenauer, Ashraf Hafez, Christopher Good, Brandon Fornwalt, Christopher M Haggerty
Journal: Circulation (2020)

Background: Atrial fibrillation (AF) is associated with stroke, especially when AF goes undetected. Deep neural networks (DNN) can predict incident AF from a 12-lead resting ECG. We hypothesize that use of a DNN to predict new onset AF from an ECG may identify patients at risk of sustaining a potentially preventable AF-related stroke. Methods: We trained a DNN model to predict new-onset AF using 382,604 ECGs prior to 2010. We then evaluated the model performance on a test set of ECGs from 2010 through 2014 linked to patients in an institutional stroke registry. There were 181,969 patients in the test set with at least one ECG and no prior history of AF. Of those patients 3,497 (1.9%) had a stroke following an ECG that did not show AF. Within the set of patients with stroke, 375 had the stroke within 3 years of the ECG and were diagnosed with new AF between -3 and 365 days of the stroke. We considered these potentially preventable AF-related strokes. We report the sensitivity and positive predictive value (PPV) of the model for appropriately risk stratifying these 375 patients who sustained a potentially preventable AF-related stroke. Results: We used F β scores to identify different risk prediction thresholds (operating points) for the model. Operating points chosen by F 0.5 , F 1 , and F 2 scores identified 4, 12, and 21% of the population as high risk for the development of AF within 1 year (Figure 1). Screening 1, 4, 12, and 21% of the overall population resulted in PPV of 28, 21, 15, and 12%, respectively, for identification of new onset AF in one year. Using those same thresholds yielded sensitivities of 4, 17, 45, and 62% for identifying potentially preventable AF-related strokes. The different risk prediction thresholds resulted in a low (120-162) number needed to screen to detect one potentially preventable AF-related stroke at 3 years. Conclusions: Use of a deep learning model to predict new onset AF may identify patients at high risk of sustaining a potentially preventable AF-related stroke.
Abstract 12899: Early Intervention in Transient ST-Elevation Myocardial Infarction Decreases Mortality: A Meta-Analysis
Authors: Sunil Upadhaya, Seetharamprasad Madala, Kanchan Tiwari
Journal: Circulation (2020)

Introduction: About one-fourth of patient with acute coronary syndrome present with transient ST-elevation myocardial infarction (STEMI). No specific recommendations exist in current guidelines regarding the timing of intervention for such patients due to lack of high-quality randomized trials. Methods: The Cochrane library and PubMed databases were searched for relevant studies. Two authors independently screened and included studies that were randomized controlled trials or observational studies comparing early with delayed invasive strategies in transient STEMI. Efficacy outcomes included target vessel revascularization, reinfarction and recurrent ischemia rates. Primary safety outcome was major bleeding. Random-effects model was used for pooled calculation of odds ratio (OR). Results: Out of all studies found, only 4 studies were included in our analysis (295 patients in early intervention group and 307 patients in delayed intervention group). Delayed intervention was associated with significant increase in all-cause mortality (OR: 2.81 [1.39-5.68], I 2 = 0%, p value = 0.004) (Figure 1). We did not find any significant difference in reinfarction rate (OR: 0.75 [0.12-4.66], I 2 = 0%, p value = 0.75), target vessel revascularization rate (OR: 0.66 [0.11-4.14] I 2 = 0%, p value = 0.66) and recurrent ischemia rate (OR 1.52[0.40-5.84], I 2 = 18 %, p value = 0.54). In addition, major bleeding rate was also similar in both groups (OR 0.68 [0.25-2.25], I 2 = 12%, p value = 0.60). Conclusions: This low to moderate-quality evidence suggests that early invasive strategy might reduce the mortality rate in transient STEMI. There is need of well-designed large randomized studies to gather further evidence regarding the best management of transient STEMI.
Abstract 14289: The Effect of Vitamin D Supplementation on Cardiovascular Risk in Patients With Prediabetes in the D2d Study
Authors: Cyrus V Desouza, Ranee Chatterjee, Karen Johnson, sangeeta R kashyap, Michael Lewis, Karen L Margolis, Richard Pratley, Neda Rasouli, Patricia R Sheehan, Anastassios Pittas
Journal: Circulation (2020)

Introduction: Low blood 25(OH)D levels are associated with increased cardiovascular (CVD) risk; however; it is unknown whether vitamin D supplementation reduces CVD risk or CVD events. In a secondary analysis from the D2d study, a large diabetes prevention trial, we investigated effects of vitamin D on CVD outcomes. Methods: Persons with prediabetes (n=2,423) not selected for vitamin D insufficiency were randomized to 4000 IU/day of vitamin D 3 or placebo and followed for a median duration of 2.5 years. The primary outcome for this analysis was first occurrence during the study of a composite 4-point Major Adverse Cardiovascular Events (MACE). Secondary aims evaluated effects on expanded MACE (MACE + revascularization) and on CVD risk variables (BP, lipids, CRP and Atherosclerotic Cardiovascular Disease score). All CVD events were independently adjudicated. In ITT analyses, Cox proportional models compared hazard rates between the two groups on 4-point and expanded MACE. Results: Baseline characteristics included 49% women, mean age was 60 years old, and 13% had established CVD by history. There were no significant differences in key baseline characteristics between the two groups. By month 24, the mean serum 25(OHD) D level in the vitamin D group was 54.3 ng per milliliter (from 27.7 ng per milliliter at baseline), as compared with 28.8 ng per milliliter in the placebo group (from 28.2 ng per milliliter at baseline). A primary MACE event occurred in 21 versus 12 subjects in the vitamin D versus placebo group (Hazard ratio 1.81, 95%CI 0.89-3.69). The number of expanded MACE events were the same between the two groups (n=27 in each group, hazard ratio 1.02, 95%CI, 0.59-1.76). CVD risk variables did not change significantly with vitamin D versus placebo. Conclusion: In a pre-diabetes population not selected for vitamin D insufficiency, vitamin D supplementation did not lower CVD risk.
Abstract 16378: Increased Extracellular Sodium and Calcium Modify the Extracellular Potassium and Cardiac Conduction Velocity Relationship in a Langendorff-perfused Guinea Pig Heart
Authors: David Ryan King, Michael ENTZ, Grace Blair, Ian Crandell, Alexandra Hanlon, Joyce Lin, Gregory HOEKER, Steven Poelzing
Journal: Circulation (2020)

Background: Previous studies have demonstrated a biphasic relationship between extracellular potassium (K o ) and cardiac conduction velocity (CV). With moderate hyperkalemia, CV increases in what is referred to as supernormal conduction, but further increases in K o lead to severe conduction slowing and asystole. We recently demonstrated that altering extracellular sodium (Na o ) and extracellular calcium (Ca o ) modulates CV dependence on gap junctions (GJs). We have also shown that increasing Na o and Ca o can attenuate conduction loss caused by global ischemia ischemia. The purpose of this study was to determine if increasing Na o and Ca o would alter the K o -CV relationship and preserve CV at high K o . Hypothesis: Increasing Na o and Ca o will mitigate conduction slowing and the incidence of asystole associated with severe hyperkalemia in conditions of both normal and uncoupled GJs. Methods: Langendorff-perfused guinea pig hearts were optically mapped to measure CV. Na o was set to 145 or155mM and Ca o to 1.25 or 2.0mM. K o was varied from 4.6, 6.4, 8, to 10 mM in each experiment. Perfusion order was blinded and randomized. GJs were inhibited using carbenoxolone. Results: A biphasic K o -CV relationship was observed under all conditions. Maximum CV was achieved at either 6.4 or 8.0mM K o followed by a decrease in CV with increased K o . Importantly, the degree of CV slowing in the presence of 10mM K o was significantly reduced with the 155mM Na o / 2.0mM Ca o perfusate compared to all other Na o /Ca o combinations. Carbenoxolone reduced CV across all K o , but did not alter the K o -CV relationship. With 145mM Na o / 1.25mM Ca o , all hearts became asystolic at K o =10.0mM. Increasing Na o and Ca o significantly reduced the incidence of asystole at K o =10.0mM. Conclusions: Elevating Na o and Ca o preserves CV during severe hyperkalemia with or without strong GJ coupling. Increasing Na o and Ca o significantly reduces the incidence of asystole during severe hyperkalemia. These data suggest that non-linear and combinatorial effects of sodium, calcium, and GJ uncoupling can differentially modulate cardiac conduction during hyperkalemic perfusion. These results have important implications for cardioplegic arrest and ischemic heart disease when potassium and calcium homeostasis are disrupted.
Abstract 110: Introduction of a Mechanical Chest Compression Device for In-hospital Cardiac Arrest During the Covid-19 Pandemic
Authors: Anish Bhatnagar, Jennifer Lee, Haitham Khraishah, Douglas Hsu, Margaret Hayes, Ari Moskowitz
Journal: Circulation (2020)

Introduction: Cardiopulmonary resuscitation (CPR) for hospitalized patients during the COVID-19 pandemic presents unique challenges to resuscitation teams, including a potentially increased risk from virus aerosolization. As such, the American Heart Association has published guidance, which includes a suggested use of mechanical chest compression devices if available. We herein describe the experience at a tertiary care hospital with a high COVID-19 case load, where mechanical compression devices were rapidly deployed early in the pandemic. Methods: In April 2020, two LUCAS® chest compression systems were deployed and staff trained in their use. In June 2020, an electronic survey was developed that explored experiences of resuscitation providers who responded to in-hospital cardiac arrests (IHCA) during the pandemic. The survey was sent to the physician code leaders, anesthesiologists, and intensive care nurses who had responded to IHCAs. Results: Forty-four (58%) of 76 surveys were returned. There were 21 IHCAs during the study period. Of the respondents, 15 (34%) were nurses and 14 (31.8%) were medical trainees. Thirty-two (73%) respondents had been involved in an IHCA where the LUCAS® was deployed. Ten (31.3%) respondents agreed/strongly agreed that transferring to the LUCAS® backboard was difficult, and that it was difficult to latch the LUCAS® to the backboard. Twelve (37.5%) respondents believed that the LUCAS resulted in delays in care. Twenty-two (68.8%) respondents thought that LUCAS® resulted in a more controlled resuscitation experience, 20 (62.5%) felt the LUCAS® improved the quality of chest compressions, and 23 (71.9%) reported that the LUCAS® allowed for fewer people in the room. Those who responded to arrests where the LUCAS® was not deployed, reported patient size and difficulty attaching the device as common obstacles. Conclusions: Rapid deployment of mechanical chest compression devices during the COVID-19 pandemic is feasible. Although there are substantial technical challenges, most report a more controlled resuscitation experience, better compression quality, and fewer individuals in the room. Additional staff training may be necessary to achieve optimal results.
Abstract 15380: Association of Change in Body Mass Index With Premature Atrial Contractions Frequency and Atrial Fibrillation in Older Age: The Atherosclerosis Risk in Communities (ARIC) Study
Authors: Joseph Decker, Wendy Wang, Faye L Norby, Romil Parikh, Jorge L Reyes, Alvaro Alonso, Pamela L Lutsey, Elsayed Z Soliman, Chiadi E Ndumele, Lin Y Chen
Journal: Circulation (2020)

Introduction: The proportions of obese and aging adults are rapidly growing. While obesity and advancing age are associated with atrial fibrillation (AF), data are limited on weight change in the elderly as a risk factor for premature atrial contractions (PACs)—which are known to precede AF—or AF. Hypothesis: Compared to a stable body mass index (BMI) over time, increasing BMI will be associated with a higher PAC frequency and AF in elderly participants in ARIC. Methods: We included N=2,070 ARIC participants [age mean ± SD 79 ± 4.5 years, 59% female] without known AF who attended visit 6 and wore an ambulatory ECG-monitoring device (Zio XT® Patch, iRhythm Technologies Inc.) for ≥48 hours. BMI change was defined as change between V5 (2011-13) and V6 (2016-17) and was categorized into 4 groups: &gt;10% decrease, 2 to 10% decrease, -2 to 2% change (stable BMI) and &gt; 2% increase. PAC frequency was defined as percent of beats that are PACs. Linear regression was used to evaluate the association between BMI change and % PAC. Incident AF was ascertained after V6 through 2018 from hospital discharge codes and death certificates. Logistic regression was used to evaluate the association between BMI change and incident AF. Results: Median PACs per hour were 8.84. Participants with &gt;2% BMI increase had 0.35% (95% CI: 0.06%-0.64%) higher frequency of PACs compared to those with stable BMI after multivariable adjustment (Table). After a mean (SD) follow-up of 19 (7) months, there were 82 incident AF cases. Compared to stable BMI, both &gt;2% BMI increase and 2 to 10% decrease were nonsignificantly associated with higher odds of AF compared with stable BMI after multivariable adjustment (Table). Conclusion: Increasing BMI in the elderly is associated with higher PAC frequency and is nonsignificantly associated with higher odds of AF compared to stable BMI. This finding suggests that weight management, which is currently emphasized in middle age, may also apply in late-life to prevent atrial arrhythmias.
Abstract 16730: Computerized Prediction of Avoidable Serum Potassium Testing in Critically Ill Cardiac Patients
Authors: Francesca Sperotto, Bhaven B Patel, Mathieu Molina, Satoshi Kimura, Marlon Delgado, Mauricio Santillana, John Kheir
Journal: Circulation (2020)

Introduction: Electrolytes are frequently monitored among critically ill patients, especially among cardiac patients due to higher risk of arrhythmias. However, a percentage of these blood draws may potentially be saved. To date, no studies have investigated strategies to safely reduce the density of electrolyte monitoring in critically ill patients. Hypothesis: We hypothesized that machine learning models can identify potentially avoidable blood draws for serum potassium (K) among pediatric patients following cardiac surgery. Methods: We retrospectively reviewed data of all patients admitted to the CICU at Boston Children’s Hospital during 2010-2018, having a length of stay ≥4 days and ≥2 recorded serum K measurements. We collected variables related to K homeostasis, including serum chemistry, hourly K intake, diuretics, and urine output. Using established machine learning techniques (Random Forest classifiers and hyperparameters) we created models predicting whether a patient’s K would be normal or abnormal based on the most recent K level, medications administered, urine output, and markers of renal function. We developed multiple models based on different age categories and temporal proximity of the most recent K measurement. We assessed the predictive performance of the models using an independent test set. Results: Of the 7,269 admissions (6,196 patients) included, 95,674 serum K was measured on average of 1 (IQR 0-1) time per day. 96% of patients received at least one dose of IV diuretic and 83% received a form of K supplementation. Our models predicted a normal K value with a median positive predictive value of 0.90. A median percentage of 2.1% measurements (mean 2.5%, IQR 1.3%-3.7%) were incorrectly predicted as normal when they were abnormal. A median percentage of 0.0% (IQR 0.0%-0.4%) were incorrectly predicted as normal while being critically low or high. A median of 27.2% (IQR 7.8%-32.4%) of samples were correctly predicted to be normal and could have been potentially avoided. Conclusions: Machine-learning methods can be used to accurately predict avoidable blood tests for serum K in critically ill pediatric patients. A median of 27.2% of samples could have been saved, with decreased costs and risk of infection or anemia.
Abstract 13363: Intensification of the Inflammasome Formation in the Pericardium of Patients With Chronic Severe Pericarditis
Authors: Aldo Bonaventura, Antonio Cannata, Eleonora Mezzaroma, Gianfranco Sinagra, Rossana Bussani, Stefano Toldo, Rohan Gandhi, Myoungjoo Kim, John Paolini, Fabrizio Montecucco, Antonio Abbate, Adolfo Gabriele Mauro
Journal: Circulation (2019)

Introduction: Pericarditis is a clinical syndrome characterized by an inflammation of the pericardium initiated by an ‘irritant’ triggering the response of the innate immune system. Interleukin-1 (...