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Background To recognize fully the benefit of lung cancer screening (LCS), annual adherence must approach the high levels seen in the National Lung Screening Trial. Emerging data suggest that annual adherence is poor and that a centralized approach to screening improves adherence. Research Questions Do differences in adherence exist between a centralized and decentralized approach to LCS within a hybrid program and what are predictors of adherence? Study Design A retrospective evaluation of a single-center hybrid LCS program was conducted to compare outcomes including patient eligibility and adherence between the centralized and decentralized approaches. Methods Patient demographics and outcomes were compared between those screened with a centralized and decentralized approach and between adherent and nonadherent patients using two-sample t tests, χ 2 tests, or analyses of variance, as appropriate. Annual adherence analysis was conducted using data from patients who remained eligible for screening with a baseline Lung CT Screening Reporting and Data System (Lung-RADS) score of 1 or 2. Logistic regression was used to estimate the association between adherence and the primary exposure, adjusting for potential confounders. Results A cohort of 1,117 patients underwent baseline low-dose CT imaging. Two hundred eleven patients (19%) were ineligible by United States Preventative Services Task Force criteria and most (90%) were screened with the decentralized approach. After exclusions, 765 patients with Lung-RADS score of 1 or 2 remained eligible for annual screening. Overall adherence was 56%; however, adherence in the centralized program was 70%, compared with 41% with the decentralized approach (P Interpretation Those screened using a centralized approach were more likely to meet eligibility criteria for LCS and more likely to return for annual screening than those screened using a decentralized approach.

Veterans suffer disproportionate health impacts from the opioid epidemic, including overdose, suicide, and death. Prediction models based on electronic medical record data can be powerful tools for identifying patients at greatest risk of such outcomes. The Veterans Health Administration implemented the Stratification Tool for Opioid Risk Mitigation (STORM) in 2018. In this study we propose changes to the original STORM model and propose alternative models that improve risk prediction performance. The best of these proposed models uses a multivariate generalized linear mixed modeling (mGLMM) approach to produce separate predictions for overdose and suicide-related events (SRE) rather than a single prediction for combined outcomes. Further improvements include incorporation of additional data sources and new predictor variables in a longitudinal setting. Compared to a modified version of the STORM model with the same outcome, predictor and interaction terms, our proposed model has a significantly better prediction performance in terms of AUC (84% vs. 77%) and sensitivity (71% vs. 66%). The mGLMM performed particularly well in identifying patients at risk for SREs, where 72% of actual events were accurately predicted among patients with the 100,000 highest risk scores compared with 49.7% for the modified STORM model. The mGLMM’s strong performance in identifying true cases (sensitivity) among this highest risk group was the most important improvement given the model’s primary purpose for accurately identifying patients at most risk for adverse outcomes such that they are prioritized to receive risk mitigation interventions. Some predictors in the proposed model have markedly different associations with overdose and suicide risks, which will allow clinicians to better target interventions to the most relevant risks. Supplementary Information The online version contains supplementary material available at 10.1007/s10742-021-00263-7.

To conduct a quality improvement evaluation of the Empower Veterans Program (EVP), an interdisciplinary pain rehabilitation/functional restoration program option for functional restoration for high-impact chronic pain, offered in a large metro-area Veterans Health Administration (VHA) system.VHA Corporate Data Warehouse electronic medical record data for patients treated by EVP between 2015 and 2019.This retrospective design first compared EVP patients considered engaged or not engaged in completing treatment in terms of demographic characteristics and post-treatment changes in clinical measures related to opioid use and mental health. We then compared mortality risk between matched groups of treated and untreated patients with chronic pain and concurrent opioid prescriptions using propensity score matching and Cox proportional hazards methods. "Treated" in the matched groups was defined as any level of EVP participation (i.e., both engaged and not engaged).We first identified 1053 EVP patients with 1 year of pre-and post-treatment follow-time and determined their engagement level. From those with chronic pain and prescription opioids, we matched 237 EVP patients to 375 untreated patients.Engaged patients (57.4% of treated patients), were somewhat older than the non-engaged (mean age 57.1 vs. 53.7, Cohen's D = 0.30), and achieved lower mean PHQ9 depression scores in the post-treatment year (9.2 vs. 10.6, Cohen's D = 0.20). Participation in EVP was associated with a 65% lower mortality risk among Veterans with chronic pain and opioid use when compared to the untreated patients: (HR: 0.35, 95% CI: 0.17, 0.75).EVP was associated with a large reduction in mortality risk for Veterans with both chronic pain and opioid use. This result could inform the decision process in a VA station or region when considering providing or expanding access to an interdisciplinary rehabilitation/functional restoration program for chronic pain.

The widely studied triple transgenic (3xTg-AD) mouse provides a robust model of Alzheimer's disease (AD) with region dependent patterns of progressive amyloid-β (Aß) and tau pathology. Using diffusion MRI (dMRI), we investigated the sensitivity of dMRI measures in capturing AD pathology associated microstructure alterations in older 3xTg-AD mice, and the degree to which dMRI changes correlate with measurements of Aβ and tau pathology. 3xTg-AD and normal control (NC) mice, 15 to 21 months of age, were used in this study. In vivo dMRI data were acquired for the generation of diffusion tensor (DT) and diffusional kurtosis (DK) measures within the hippocampus and fimbria (Fi). For these same brain regions, Aβ and tau pathology were quantified by morphological analysis of Aß1-42 and AT8 immunoreactivity. Two-tailed, two-sample t-tests were performed to assess group differences in each brain region of interest (ROI), with the Benjamini-Hochberg false discovery rate (FDR) method being applied to adjust for multiple comparisons. Spearman correlation coefficients were calculated to investigate associations between diffusion and morphological measures. Our results revealed, depending on the brain region, DT and DK measures were able to detect group differences. In the dorsal hippocampus (HD), fractional anisotropy (FA) was significantly higher in the 3xTg-AD mice compared with NC mice. In the subiculum (SUB), FA, axial diffusivity (D

Retrospective administrative database review.Analyze patterns of opioid use in patients undergoing lumbar surgery and determine associated risk factors in a Medicaid population.Opioid use in patients undergoing surgery for degenerative lumbar spine conditions is prevalent and impacts outcomes. There is limited information defining the scope of this problem in Medicaid patients.Longitudinal cohort study of adult South Carolina (SC) Medicaid patients undergoing lumbar surgery from 2014 to 2017. All patients had continuous SC Medicaid coverage for 15 consecutive months, including six months before and nine months following surgery. The primary outcome was a longitudinal assessment of postoperative opioid use to determine trajectories and group-based membership using latent modeling. Univariate and multivariable modeling was conducted to assess risk factors for group-based trajectory modeling and chronic opioid use (COU).A total of 1455 surgeries met inclusion criteria. Group-based trajectory model demonstrated patients fit into five groups; very low use (23.4%), rapid wean following surgery (18.8%), increasing use following surgery (12.9%), slow wean following surgery (12.6%) and sustained high use (32.2%). Variables predicting membership in high opioid use included preoperative opioid use, younger age, longer length of stay, concomitant medications, and readmissions. More than three quarter of patients were deemed COUs (76.4%). On bivariate analysis, patients with degenerative disk disease were more likely to be COUs (24.8% vs. 18.6%; P =0.0168), more likely to take opioids before surgery (88.5% vs. 61.9%; P0.001) and received higher amounts of opioids during the 30 days following surgery (mean morphine milligram equivalents 59.6 vs. 25.1; P0.001).Most SC Medicaid patients undergoing lumbar elective lumbar spine surgery were using opioids preoperatively and continued long-term use postoperatively at a higher rate than previously reported databases. Preoperative and perioperative intake, degenerative disk disease, multiple prescribers, depression, and concomitant medications were significant risk factors.

BACKGROUND: Over decades, there have been several alterations to cigarettes, including the addition of filters and flavoring. However, lung cancer remains the leading cause of cancer-related death in the United States. RESEARCH QUESTION: The aim of this study was to examine the association of type of cigarette on nicotine dependence in the setting of lung cancer screening. STUDY DESIGN AND METHODS: This study is a secondary analysis of the American College of Radiology Imaging Network arm of the National Lung Screening Trial. Tobacco dependence was evaluated by using the Fagerstrӧm Test for Nicotine Dependence, the Heaviness of Smoking Index, and time to first cigarette. Clinical outcomes, including nicotine dependence and tobacco abstinence, were assessed with descriptive statistics and χ(2) tests, stratified according to cigarette tar level, flavor, and filter. Logistic regression was used to study the influence of variables on smoking abstinence. RESULTS: More than one-third of individuals presenting for lung cancer screening are highly addicted to nicotine and smoke within 5 min of waking up. Smokers of unfiltered cigarettes were more nicotine dependent compared with filtered cigarette smokers (OR, 1.32; P < .01). Although smokers of light/ultralight cigarettes had lower dependence (OR, 0.76, P < .0001), there was no difference in smoking abstinence compared with regular cigarette smokers. There was no difference in outcomes when comparing smokers of menthol vs unflavored cigarettes. INTERPRETATION: In a screening population, the type of cigarette smoked is associated with different levels of dependence. Eliciting type of cigarette and time to first cigarette has the potential to allow for tailored tobacco treatment interventions within this context.

Opioid Overdose Network is an effort to generalize and adapt an existing research data network, the Accrual to Clinical Trials (ACT) Network, to support design of trials for survivors of opioid overdoses presenting to emergency departments (ED). Four institutions (Medical University of South Carolina [MUSC], Dartmouth Medical School [DMS], University of Kentucky [UK], and University of California San Diego [UCSD]) worked to adapt the ACT network. The approach that was taken to enhance the ACT network focused on 4 activities: cloning and extending the ACT infrastructure, developing an e-phenotype and corresponding registry, developing portable natural language processing tools to enhance data capture, and developing automated documentation templates to enhance extended data capture. Overall, initial results suggest that tailoring of existing multipurpose federated research networks to specific tasks is feasible; however, substantial efforts are required for coordination of the subnetwork and development of new tools for extension of available data. The initial output of the project was a new approach to decision support for the prescription of naloxone for home use in the ED, which is under further study within the network.

Background Adherence to annual low-dose CT was 95% in the National Lung Screening Trial and must be replicated to achieve mortality benefit from screening. Research Question How do we determine adherence rates within the Veterans Affairs Lung Cancer Screening Demonstration Project and identify factors predictive of adherence? Study Design and Methods A secondary data analysis of the Lung Cancer Screening Demonstration Project that was conducted at eight Veterans Affairs medical centers was performed to determine adherence to follow up imaging and to determine factors predictive of adherence. Results A total of 2,103 patients were screened. The adherence to screening from baseline scan (T0) to first follow-up scan (T1) was 82.2% and 65.2% from T1 to second follow-up scan (T2). Logistic regression modeling showed that presence of a nodule and the site of lung cancer screening were predictive of adherence. After three rounds of screening, 1,343 patients (64%) who underwent baseline screening underwent both subsequent annual low-dose CT scans; 225 patients (11%) had only one subsequent low-dose CT; 0.4% did not have a T1 scan but did have a T2 scan; 70 patients (3%) died, and 36 patients (1.7%) were diagnosed with lung cancer. There was significant variation in screening adherence across the eight sites, which ranged from 63% to 94% at T1 and 52% to 82% at T2 (P Interpretation Despite a centralized program design with dedicated navigator and registry to assist with adherence to annual lung cancer screening, variations between sites suggest that active follow-up strategies are needed to optimize adherence. For the mortality benefit from lung cancer screening to be recognized, adherence to annual screening must achieve higher rates.

Lung cancer remains the leading cause of cancer-related mortality in the United States. The National Lung Screening Trial (NLST) demonstrated a 20% reduction in lung cancer mortality resulting from lung cancer screening (LCS) with an additive reduction from smoking abstinence. However, successful smoking cessation within LCS is variable.What patient and treatment factors are associated with attempts to quit smoking among those screened for lung cancer?In a secondary analysis of the American College of Radiology Imaging Network arm of the NLST, patient demographics, patient smoking behaviors, and tobacco treatment variables were stratified by patient smoking status. The Cox proportional hazards ratio was used to evaluate each variable's effect on attempting to quit smoking.Seven thousand three hundred sixty-nine patients were smoking actively at enrollment in the NLST. Of the patients who reported they were smoking, 73.4% did not receive any pharmacologic tobacco treatment. More patients who attempted to quit received pharmacologic tobacco treatment than those who continued to smoke: (nicotine replacement therapy [NRT], 18.0% vs 12.4% [P .01]; bupropion, 7.9% vs 6.9% [P = .02]; both NRT and bupropion, 5.6% vs 3.9% [P .01]). Stable users were more likely to be women (47.8% vs 43.8%; P .01), to be African American (8.2% vs 6.3%; P = .007), to be unmarried (43.2% vs 36.9% [P .01]), and to have less than a college education (47.7% vs 42.3%; P .01). Patients with high dependence who received dual therapy with bupropion and NRT showed the highest likelihood of quit attempt (hazard ratio, 2.07; 95% CI, 1.75-2.44).In this analysis, only one-quarter of patients who underwent LCS and who smoked were treated with pharmacologic therapy, which is associated with increased likelihood of attempting to quit. Certain characteristics are associated with difficulty with attempting to quit smoking. Those with high nicotine dependence benefitted most from dual pharmacologic therapy.

Objective Veterans suffer disproportionately from the combined adverse health impacts of chronic pain and hazardous opioid use. This evaluation involved a substance use treatment program that included medication for opioid use disorder (SATP-MOUD) in a large metro-area Veterans Health Administration (VHA). This form of treatment has become increasingly important during the opioid crisis and is among several important Department of Veteran's Affairs (VA) initiatives to improve treatment for opioid use disorder (OUD), for which chronic pain is often a comorbid condition. Methods We compared clinical measures related to substance use and mental health between groups who were considered either engaged or not engaged in completing treatment. The study used propensity score matching methods and Cox proportional hazards models to compare the mortality risk for treated and untreated veterans who had chronic pain with concurrent opioid use. Results We identified 1559 SATP-MOUD patients with 1 year of pre- and post-treatment follow-time. From those with chronic pain and concurrent opioid use, we matched 478 SATP-MOUD patients to 647 untreated patients. Engaged patients (at least 4 visits in the first 8 weeks of treatment) had significant improvements in Brief Addiction Monitor (BAM) scores and in PHQ-9 depression screening scores compared to those who started treatment but did not meet the engagement threshold. In Cox proportional hazards analysis, participation in SATP-MOUD was associated with a 38% lower mortality risk among veterans with chronic pain and opioid use when compared to the untreated group: (HR: 0.62, 95% CI: 0.47, 0.82). Conclusions SATP-MOUD, as delivered in actual practice, was associated with significant improvements in depression and addiction severity scores, and was associated with reduced mortality risk for veterans with chronic pain and OUD.

This study uses data from the National Lung Screening Trial to investigate the association of cigarette tar level, flavor, and filter status with lung cancer diagnosis, mortality, and all-cause mortality.

Mega-events and their legacies have become increasingly attractive to cities as an urban development tool, and the competition to host mega-events continues to widen and deepen. Mega-events are seen as a unique mechanism to improve a city’s image and to trigger physical transformation which together can enhance their international competitiveness, and promote growth and regenerationIn parallel, ‘sustainability’ has become established as a necessary component of urban development strategies. Sustainability has thus become an essential part of the language of mega-event planning and delivery, and of mega-event legacy, particularly at the local level and especially following the International Olympic Committee’s (IOC) adoption of the theme. This dates from the Centennial Olympic Congress in 1994, where concern for the environment was reflected in the creation of the IOC’s Sport and Environment Commission whose work ensured the incorporation of the twin themes of environment and sustainability in the Olympic Charter in 1996, as the third Pillar of Olympism. The IOC defined its role in the Olympic Charter as ‘to encourage and support a responsible concern for environmental issues, to promote sustainable development in sport and to require that the Olympic Games are held accordingly’ (IOC, 1996:11). It also states that it is an IOC responsibility ‘to promote a positive legacy from the Olympic Games to the host cities and host countries’ (IOC, ibid.).

These diaries by Ralph Ward (fl.1754–6) and Arthur Jessop (1682–1751) were first published in 1952 and paint a valuable portrait of the trials, tribulations and pleasures of everyday life for the middle classes in rural Yorkshire in the mid-eighteenth century. A transcription of Jessop's diary from 1861 was first discovered in a Huddersfield bookshop in 1927. A local apothecary and pious community man, Jessop depicts the cycles of life in West Yorkshire, displaying a very British preoccupation with the weather. His diary, which covers the period 1730–46, notably discusses the impact of the Jacobite uprising of 1745. Ralph Ward was a fairly wealthy cattle trader, farmer and businessman in North Yorkshire. He was involved in local government, which he describes factually and clearly. His diary, covering the period 1754–6, also discusses business transactions, farming methods and, of course, the weather.

The objective of the present work was to develop calibration equations for the prediction of chemical composition and forage digestibility from different populations of alfalfa hay harvested in Parmigiano- Reggiano cheese production area of Northern Italy. Due to annual climatic variations that affect soil and growing conditions and consequently cause high variability in chemical and physical composition, 319 hay samples from four years were used to build robust calibration. NIRS calibration equations were developed for the prediction of in vitro NDF digestibility (IVNDFd) and 20 chemical parameters (dry matter, starch, fat, sugar, fiber fractions, crude protein, nitrogen fractions and some minerals) of Italian hay. The results obtained show that NIRS equations greatly explain the variation in the composition existing in alfalfa hays grown in Northern Italy, except for a few parameters characterized by low variability range value. The equations obtained for the prediction of biological and chemical parameters explain the major part of the variation existing in the reference data, which open great prospects for the use of NIRS in planning feeding strategies of livestock, based on alfalfa forage.