Citations

In prediabetes, anthropometric characteristics as well as insulin action do not alter the hepatic response to glucagon. The postprandial suppression or lack of suppression of glucagon secretion is an important factor governing postprandial glucose tolerance independent of insulin secretion.

Background: Patient-reported outcomes (PROs) measure progression and quality of care. While legacy PROs such as the International Knee Documentation Committee (IKDC) survey are well-validated, a lengthy PRO creates a time burden on patients, decreasing adherence. In recent years, PROs such as the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function and Pain Interference surveys were developed as computer adaptive tests, reducing time to completion. Previous studies have examined correlation between legacy PROs and PROMIS; however, no studies have developed effective prediction models utilizing PROMIS to create an IKDC index. While the IKDC is the standard knee PRO, computer adaptive PROs offer numerous practical advantages. Purpose: To develop a nonlinear predictive model utilizing PROMIS Physical Function and Pain Interference to estimate IKDC survey scores and examine algorithm sensitivity and validity. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: The MOTION (Military Orthopaedics Tracking Injuries and Outcomes Network) database is a prospectively collected repository of PROs and intraoperative variables. Patients undergoing knee surgery completed the IKDC and PROMIS surveys at varying time points. Nonlinear multivariable predictive models using Gaussian and beta distributions were created to establish an IKDC index score, which was then validated using leave-one-out techniques and minimal clinically important difference analysis. Results: A total of 1011 patients completed the IKDC and PROMIS Physical Function and Pain Interference, providing 1618 complete observations. The algorithms for the Gaussian and beta distribution were validated to predict the IKDC (Pearson = 0.84-0.86; R 2 = 0.71-0.74; root mean square error = 9.3-10.0). Conclusion: The publicly available predictive models can approximate the IKDC score. The results can be used to compare PROMIS Physical Function and Pain Interference against historical IKDC scores by creating an IKDC index score. Serial use of the IKDC index allows for a lower minimal clinically important difference than the conventional IKDC. PROMIS can be substituted to reduce patient burden, increase completion rates, and produce orthopaedic-specific survey analogs.

Abstract Background The objective of this paper was to examine temporal changes of infective endocarditis (IE) incidence and epidemiology in North America. Methods A systematic review was conducted at Mayo Clinic, Rochester. Ovid EBM Reviews, Ovid Embase, Ovid Medline, Scopus, and Web of Science were searched for studies published between January 1, 2000, and May 31, 2020. Four referees independently reviewed all studies, and those that reported a population-based incidence of IE in patients aged 18 years and older in North America were included. Results Of 8588 articles screened, 14 were included. Overall, IE incidence remained largely unchanged throughout the study period, except for 2 studies that demonstrated a rise in incidence after 2014. Five studies reported temporal trends of injection drug use (IDU) prevalence among IE patients with a notable increase in prevalence observed. Staphylococcus aureus was the most common pathogen in 7 of 9 studies that included microbiologic findings. In-patient mortality ranged from 3.7% to 14.4%, while the percentage of patients who underwent surgery ranged from 6.4% to 16.0%. Conclusions The overall incidence of IE has remained stable among the 14 population-based investigations in North America identified in our systematic review. Standardization of study design for future population-based investigations has been highlighted for use in subsequent systematic reviews of IE.

Abstract Aims To determine if there is an association between better County Health Rankings and the increased odds of a hospital gaining Magnet designation in subsequent years (2014–2019) compared with counties with lower rankings. Background The Magnet hospital model is recognized to have a great effect on nurses, patients and organizational outcomes. Although Magnet hospital designation is a well‐established structural marker for nursing excellence, the effect of County Health Rankings and subsequent hospital achievement of Magnet status is unknown. Design A descriptive, cross‐sectional quantitative approach was adopted for this study. Methods Data were derived from 2010 to 2019 U.S. County Health Rankings, American Hospital Association, and American Nursing Credentialing Center databases. Logistic regression models were utilized to determine associations between county rankings for health behaviours, clinical care, social and economic factors, physical environment and counties with a new Magnet hospital after 2014. Results Counties with the worst rankings for clinical care and socio‐economic status had reduced odds of obtaining a Magnet hospital designation compared with best‐ranking counties. While middle‐ranking counties for the physical environment ranking had increased odds of having Magnet designation compared with best‐ranking counties. Additionally, having an increased percent of government non‐federal hospital or a higher percentage of critical access hospitals in the county reduced the odds of having a Magnet‐designated facility after 2014. Conclusion The findings underscore the important associations between Magnet‐designated facilities’ location and the health of its surrounding counties. This study is the first to examine the relationship between County Health Rankings and a hospital's likelihood of obtaining Magnet status and points to the need for future research to explore outcomes of care previously identified as improved in Magnet‐designated hospitals. Implications Recognizing the benefits of Magnet facilities, it is important for health care leaders and policy makers to seek opportunities to promote centres of excellence in higher need communities through policy and financial intervention.

INTRODUCTION: We examined national Google Trends and local healthcare utilization after 3 high-impact gastroenterology publications. METHODS: Changes in US Google Trends and Olmsted County health utilization were studied. RESULTS: Publication views within 30 days were 51,458 ( Imperiale ), 49,759 ( Pimentel ), and 18,750 ( Gomm ). Colonoscopy searches ( P = 0.04) and Cologuard tests performed ( P < 0.01) increased while colonoscopies decreased ( P < 0.01). Searches for rifaximin ( P = 0.05), irritable bowel syndrome ( P < 0.01), diarrhea ( P < 0.01), and rifaximin prescriptions ( P = 0.02) increased. Increase in hydrogen-2 blocker searches ( P = 0.02) and prescriptions ( P < 0.01) and gastroesophageal reflux disease ( P < 0.01) and dementia office visits ( P < 0.01) occurred. DISCUSSION: High-impact gastroenterology publications influence Google searches and local population-based healthcare utilization.

ABSTRACT/SUMMARY Purpose Common LOXL1 protein-altering variants are significant genetic risk factors for exfoliation syndrome (XFS) and the related secondary glaucoma (XFG). A rare LOXL1 missense allele was associated with protective effects in a Japanese cohort, suggesting that other rare alleles may also exhibit protective effects. The goal of this study is to assess the contributions of rare LOXL1 variants to XFS/XFG risk in cases and controls from the United States (US). Methods LOXL1 rare variants (minor allele frequency (MAF) < 1%) were identified from Human exome BeadArray (Illumina) data for 1118 XFS/XFG cases and 3661 controls (Mass Eye and Ear (MEE) cohort) and from exome sequence data for 284 cases and 37,499 controls in All of Us (AoU) The distribution of rare variants, haplotypes, and diplotypes was examined using Fisher exact test. Results Four rare LOXL1 missense alleles, more common in controls, were identified in MEE, P= 7.6E-4), and 456 variants identified in AoU were found only in controls (P=0.045). The rare protective alleles were preferentially located (P= 5.8E-45) in a LOXL1 intrinsic disordered region (IDR) potentially involved in LOXL1 aggregation. Haplotypes that included the rare or minor variants were more common in controls compared to cases in both MEE (Odds Ratio (OR)= 0.21 (95% Confidence interval (CI): 0.19-0.24), P=1.7E-173) and AoU (OR=0.28 (95% CI: 0.23-0.34), P=4.4E-41), and heterozygous diplotypes were also significantly associated with reduced risk overall in both MEE (OR= 0.45 (95% CI: 0.52-0.39), P= 1.7E-89) and AoU (OR=0.26 (95% CI: 0.18-0.33, P=7.6E-28). Diplotypes comprised of only homozygous genotypes were associated with increased disease risk in both MEE and AoU (OR= 4.16 (95% CI: 3.60-4.76), P= 4.2E-89 and 5.26 (95% CI: 4.12-6.73), P=1.87E-42, respectively) and excess homozygosity and decreased heterozygosity was correlated with disease risk for common LOXL1 variants across multi-ethnic populations (P=1.0E-6). Conclusions Using exome array and exome sequence data from XFS/XFG cases and controls from the United States, we identified rare protective LOXL1 missense variants and show that the distribution of the corresponding haplotypes and diplotypes was associated with lower risk of XFS/XFG. Diplotype results also demonstrated that LOXL1 allelic heterozygosity was inversely associated, while homozygosity was associated with increased disease risk. These results suggest that LOXL1 MAF variation among populations, with corresponding variation in genotype heterozygosity and homozygosity, determines the XFS/XFG association.

Abstract Background : Non‐motor symptoms are well established phenotypic components of adult‐onset idiopathic, isolated, focal cervical dystonia (AOIFCD). However, improved understanding of their clinical heterogeneity is needed to better target therapeutic intervention. Here, we examine non‐motor phenotypic features to identify possible AOIFCD subgroups. Methods : Participants diagnosed with AOIFCD were recruited via specialist neurology clinics (dystonia wales: n = 114, dystonia coalition: n = 183). Non‐motor assessment included psychiatric symptoms, pain, sleep disturbance, and quality of life, assessed using self‐completed questionnaires or face‐to‐face assessment. Both cohorts were analyzed independently using Cluster, and Bayesian multiple mixed model phenotype analyses to investigate the relationship between non‐motor symptoms and determine evidence of phenotypic subgroups. Results : Independent cluster analysis of the two cohorts suggests two predominant phenotypic subgroups, one consisting of approximately a third of participants in both cohorts, experiencing increased levels of depression, anxiety, sleep impairment, and pain catastrophizing, as well as, decreased quality of life. The Bayesian approach reinforced this with the primary axis, which explained the majority of the variance, in each cohort being associated with psychiatric symptomology, and also sleep impairment and pain catastrophizing in the Dystonia Wales cohort. Conclusions : Non‐motor symptoms accompanying AOIFCD parse into two predominant phenotypic sub‐groups, with differences in psychiatric symptoms, pain catastrophizing, sleep quality, and quality of life. Improved understanding of these symptom groups will enable better targeted pathophysiological investigation and future therapeutic intervention.

Abstract There is growing evidence showing that sex disparity in lung cancer risk cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotype from a lung cancer cohort including ~ 47,000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 (OR=0.71, p=4.29x10-8); rs79942605 (OR=2.17, p=2.81x10-8); and rs208908 (OR=0.70, p=4.54x10-8), were identified with different risk effect of lung cancer between men and women. Further eQTL and functional annotation analysis suggested rs208908 affect lung cancer risk through differential regulation of CXADR (Coxsackie Virus And Adenovirus Receptor) gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Introduction: Therapy with warfarin has been shown to decrease the risk of stroke associated with atrial fibrillation and flutter. Current guidelines recommend warfarin therapy for patients with atrial fibrillation who are at intermediate to high risk of thromboembolism. Multiple studies have shown that increasing age and female gender have been associated with underutilization of warfarin. We evaluated women in the Kentucky Women's Health Registry (KWHR) with self-reported atrial fibrillation to determine the rates of warfarin utilization in this population. Methods: Between November 2009 and June 2010, we administered electronic or mailed surveys to KWHR participants who reported an arrhythmia on the Registry questionnaire. Survey questions targeted arrhythmia identification and treatment, medical and social history, pregnancy history and demographics. Herein we analyze the data to determine baseline characteristics of the atrial fibrillation (and flutter) group, including CHADS 2 score and use of anticoagulation. Results: Of the 572 women initially surveyed, 365 responded to the questionnaire, yielding 107 cases of atrial fibrillation and flutter. Baseline characteristics of this group were notable for high education levels and greater than average annual income (see table). Of this population, 36 of 106, (34%) had a CHADS 2 score of >1. Of the women with CHADS 2 scores of >1 who reported their warfarin use, only 10 of 33 [30% (95% confidence intervals, 17-47%)] were receiving warfarin. As expected, the warfarin treated group tended to be older with mean age 73.4 years vs 61.8 years (p<0.001) with a higher CHADS 2 score (p<0.003). Conclusion: Warfarin anticoagulation is underutilized in this group of Kentucky women. This is not attributable to disparities in socioeconomic status given the relatively affluent, highly educated status of the survey respondents. Baseline Characterisitics of Paticipants with Atrial Fibrillation and Flutter Variable Proportion of responders n 95% Confidence Intervals Age (mean years) 63.2 102 61.1-65.3 Hypertension 65% (68) 104 0.56 -0.74 Diabetes 13% (13) 102 0.08-0.21 Congestive heart failure 11% (11) 104 0.06-0 .18 Stroke/TIA 8% (8) 102 0.04-0.15 BMI in kg/m 2 (mean) 28.8 104 27.5-30.1 Aspirin use 49% (51) 104 0.40-0.59 Clopidogrel use 5 % (5) 104 0.02 -0.11 Warfarin use 15% (16) 104 0.10-0.24 CHADS 2 score >1 34% (36) 106 0.25-0 .43 White Race 93% (98) 105 0.87-0 .97 Level of education: Some college or higher 85% (89) 105 0.77-0.90 Median annual household income (Dollars) 60-79,999 101 Inter-quartile range: 40-89,999 (Kentucky median 41,489)

The importance of coronary artery disease (CAD) surveillance, as recently underscored by the American Heart Association, is heightened by the obesity/diabetes epidemics. The need for surveillance is especially great for subclinical CAD, as the greatest increases in obesity/diabetes are occurring among younger age groups, where clinically-recognized CAD is infrequent. Yet few methods for such population-based surveillance exist. Using one such method, unbiased heart autopsy data, we previously showed that declines in grade of CAD observed since 1981 ended in the mid-1990s and may have reversed. In order to assess and interpret the factors underlying these observations, it is necessary to first examine trends in CAD risk factors among heart autopsied decedents and investigate the extent to which they mirror trends in the general population. Rochester Epidemiology Project (REP) medical records linkage resources were used to identify 1) all Olmsted County residents age 16-64 years who died from non-natural causes and went to autopsy 1981-2009 (96% autopsy rate) and 2) all Olmsted County residents age 16-64 years 1981-2009. We randomly selected two population subjects per decedent, stratified by calendar year. All REP inpatient/ ambulatory records were reviewed for CAD risk factors. Compared to population subjects, decedents were older and more likely to be male, smokers, alcohol abusers, and treated for hypertension; however, risk factor trends for both groups were generally of similar magnitude and direction, i.e., smoking, alcohol use, and blood pressure declined and anti-hypertensive medication use, diagnosed hyperlipidemia, and body mass index increased ( Table ). These population-based longitudinal data indicate that temporal trends in risk factors among autopsied decedents parallel those for the general population, supporting the concept that data on autopsied decedents can provide insight into trends in CAD risk and the changing burden of atherosclerosis within the source population. Characteristics of all 1) non-elderly adult Olmsted County residents who died non-natural deaths and were autopsied and 2) non-elderly adult Olmsted County residents with respect to CAD risk factors and calendar year trends CAD Risk Factor Autopsied Decedents (N=315) Population Subjects (N=672) P Value Autopsied Decedents, Temporal Trend Population Subjects, Temporal Trend N Calendar Year Estimate P value N Calendar Year Estimate P Value Age at Index, Mean (SD) 37.5 (14.0) 34.1 (13.6) <0.01 1 315 0.172 0.06 1 672 −0.059 0.33 1 Sex, % Male 236 (75%) 339 (50%) <0.01 2 315 0.008 0.60 2 672 −0.008 0.39 2 Race, % Non-White 29 (9%) 85 (13%) 0.14 3 305 0.054 0.04 3 589 0.023 0.12 3 Of Ever Smokers, Current = Yes 128/184 (70%) 118/210 (56%) 0.01 3 184 −0.040 0.048 3 210 −0.052 <0.01 3 Of Ever Alcohol Use, Current = Yes 175/238 (74%) 284/364 (78%) 0.08 3 238 −0.065 <0.01 3 364 −0.027 0.09 3 Mention of Alcoholism, Yes 80 (25%) 41 (6%) <0.01 3 315 0.014 0.35 3 672 0.042 0.04 3 Closest Systolic BP, Mean (SD) 124.1 (16.6) 120.3 (15.7) 0.34 3 285 −0.179 0.09 3 600 −0.156 0.02 3 Closest Diastolic BP, Mean (SD) 76.2 (11.6) 74.0 (10.5) 0.53 3 285 −0.194 0.01 3 600 −0.112 0.02 3 Closest BP on Medication, Yes 44 (14%) 36 (5%) <0.01 3 283 0.046 0.03 3 599 0.063 <0.01 3 Hyperlipidemia Diagnosis, Yes 32 (10%) 65 (10%) 0.32 3 315 0.114 <0.01 3 672 0.078 <0.01 3 Closest Fasting Glucose, Mean (SD) 95.8 (26.0) 95.0 (27.6) 0.63 3 177 0.270 0.23 3 335 0.505 <0.01 3 Closest BMI, Mean (SD) 26.1 (5.8) 25.9 (5.4) 0.52 3 280 0.080 0.04 3 593 0.091 <0.01 3 1 Unadjusted, Chi-square; 2 Unadjusted, Wilcoxon rank sum test; 3 Adjusted for age and sex, linear or logistic regression; BP = Blood Pressure; BMI = Body Mass Index