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BackgroundGuidelines recommend shared decision making when choosing treatment for severe aortic stenosis but implementation has lagged. We assessed the feasibility and impact of a novel decision aid for severe aortic stenosis at point-of-care.MethodsThis prospective multi-site pilot cohort study included adults with severe aortic stenosis and their clinicians. Patients were referred by their heart team when scheduled to discuss treatment options. Outcomes included shared decision-making processes, communication quality, decision-making confidence, decisional conflict, knowledge, stage of decision making, decision quality, and perceptions of the tool. Patients were assessed at baseline (T0), after using the intervention (T1), and after the clinical encounter (T2); clinicians were assessed at T2. Before the encounter, patients reviewed the intervention, Aortic Valve Improved Treatment Approaches (AVITA), an interactive, online decision aid. AVITA presents options, frames decisions, clarifies patient goals and values, and generates a summary to use with clinicians during the encounter.Results30 patients (9 women [30.0%]; mean [SD] age 70.4 years [11.0]) and 14 clinicians (4 women [28.6%], 7 cardiothoracic surgeons [50%]) comprised 28 clinical encounters Most patients [85.7%] and clinicians [84.6%] endorsed AVITA. Patients reported AVITA easy to use [89.3%] and helped them choose treatment [95.5%]. Clinicians reported the AVITA summary helped them understand their patients' values [80.8%] and make values-aligned recommendations [61.5%]. Patient knowledge significantly improved at T1 and T2 (p = 0.004). Decisional conflict, decision-making stage, and decision quality improved at T2 (p = 0.0001, 0.0005, and 0.083, respectively). Most patients [60%] changed treatment preference between T0 and T2. Initial treatment preferences were associated with low knowledge, high decisional conflict, and poor decision quality; final preferences were associated with high knowledge, low conflict, and high quality.ConclusionsAVITA was endorsed by patients and clinicians, easy to use, improved shared decision-making quality and helped patients and clinicians arrive at a treatment that reflected patients' values.Trial registrationTrial ID: NCT04755426, Clinicaltrials.gov/ct2/show/NCT04755426.

BackgroundMaintaining independence in older age is an important aspect of quality of life. We investigated depressive symptoms as an important modifiable risk factor that may mediate the effects of physical and cognitive decline on disability.MethodsWe prospectively analyzed data from 223 adults (age 50-85; 117 controls and 106 with type-2 diabetes) over 48 weeks who were participating in a clinical trial "Memory Advancement by Intranasal Insulin in Type 2 Diabetes." Data from self-reported disability (World Health Organization Disability Assessment Schedule) and depressive symptoms (Geriatric Depression Scale) were obtained from baseline, week 25, and week 48 visits. Cognition (Mini-mental status examination) and medical comorbidities (Charlson Comorbidity Index) were assessed at baseline. Longitudinal analysis assessed the extent to which change in depressive symptoms predicted worsening disability. Mediation analyses were performed to determine the extent to which depressive symptoms accounted for disability associated with worse cognition, walking speed, and comorbidities.ResultsAt baseline, depressive symptoms, cognition, and walking speed were within normal limits, but participants had a high 10-year risk of cardiovascular mortality. Depressive symptoms were related to disability at baseline (pConclusionsDepressive symptoms substantially exacerbated the effects of worsening cognition, gait speed, and comorbidities on disability. In our sample, most individuals scored within the "normal" range of the Geriatric Depression Scale, suggesting that even subclinical symptoms can lead to disability. Treating subclinical depression, which may be under-recognized in older adults, should be a public health priority to help preserve independence with aging.

BackgroundPatients with opioid use disorder (OUD) who are hospitalized for serious infections requiring prolonged intravenous antibiotics may face barriers to discharge, which could prolong hospital length of stay (LOS) and increase financial burden. We investigated differences in LOS, discharge disposition, and charges between hospitalizations for serious infections in patients with and without OUD.Methods and findingsWe utilized the 2016 National Inpatient Sample-a nationally representative database of all discharges from US acute care hospitals. The population of interest was all hospitalizations for infective endocarditis, epidural abscess, septic arthritis, or osteomyelitis. The exposure was OUD, and the primary outcome was LOS until discharge, assessed by using a competing risks analysis to estimate adjusted hazard ratios (aHRs). Adjusted odds ratio (aOR) of discharge disposition and adjusted differences in hospital charges were also reported. Of 95,470 estimated hospitalizations for serious infections (infective endocarditis, epidural abscess, septic arthritis, and osteomyelitis), the mean age was 49 years and 35% were female. 46% had Medicare (government-based insurance coverage for people age 65+ years), and 70% were non-Hispanic white. After adjustment for potential confounders, OUD was associated with a lower probability of discharge at any given LOS (aHR 0.61; 95% CI 0.59-0.63; p < 0.001). OUD was also associated with lower odds of discharge to home (aOR 0.38; 95% CI 0.33-0.43; p < 0.001) and higher odds of discharge to a post-acute care facility (aOR 1.85; 95% CI 1.57-2.17; p < 0.001) or patient-directed discharge (also referred to as "discharge against medical advice") (aOR 3.47; 95% CI 2.80-4.29; p < 0.001). There was no significant difference in average total hospital charges, though daily hospital charges were significantly lower for patients with OUD. Limitations include the potential for unmeasured confounders and the use of billing codes to identify cohorts.ConclusionsOur findings suggest that among hospitalizations for some serious infections, those involving patients with OUD were associated with longer LOS, higher odds of discharge to post-acute care facilities or patient-directed discharge, and similar total hospital charges, despite lower daily charges. These findings highlight opportunities to improve care for patients with OUD hospitalized with serious infections, and to reduce the growing associated costs.

BackgroundQuantifying reproducibility of native T1 and T2 mapping over a long period (> 1 year) is necessary to assess whether changes in T1 and T2 over repeated sessions in a longitudinal study are associated with variability due to underlying tissue composition or technical confounders.ObjectivesTo carry out a single-center phantom study to 1) investigate measurement reproducibility of slice-interleaved T1 (STONE) and T2 mapping over 20 months, 2) quantify sources of variability, and 3) compare reproducibility and measurements against reference spin-echo measurements.MethodsMR imaging was performed on a 1.5 Tesla Philips Achieva scanner every 2-3 weeks over 20 months using the T1MES phantom. In each session, slice-interleaved T1 and T2 mapping was repeated 3 times for 5 slices, and maps were reconstructed using both 2-parameter and 3-parameter fit models. Reproducibility between sessions, and repeatability between repetitions and slices were evaluated using coefficients of variation (CV). Different sources of variability were quantified using variance decomposition analysis. The slice-interleaved measurement was compared to the spin-echo reference and MOLLI.ResultsSlice-interleaved T1 had excellent reproducibility and repeatability with a CV < 2%. The main sources of T1 variability were temperature in 2-parameter maps, and slice in 3-parameter maps. Superior between-session reproducibility to the spin-echo T1 was shown in 2-parameter maps, and similar reproducibility in 3-parameter maps. Superior reproducibility to MOLLI T1 was also shown. Similar measurements to the spin-echo T1 were observed with linear regression slopes of 0.94-0.99, but slight underestimation. Slice-interleaved T2 showed good reproducibility and repeatability with a CV < 7%. The main source of T2 variability was slice location/orientation. Between-session reproducibility was lower than the spin-echo T2 reference and showed good measurement agreement with linear regression slopes of 0.78-1.06.ConclusionsSlice-interleaved T1 and T2 mapping sequences yield excellent long-term reproducibility over 20 months.

Background: Delirium is common, leads to other adverse outcomes, and is costly. However, it often remains unrecognized in most clinical settings. The Confusion Assessment Method (CAM) is the most widely used diagnostic algorithm, and operationalizing its features would be a substantial advance for clinical care. Objective: To derive the 3D-CAM, a new 3-minute diagnostic assessment fo CAM-defined delirium, and validate it against a clinical reference standard. Design: Derivation and validation study. Setting; 4 general medicine units in an academic medical center. Participants: 201 inpatients aged 75 years or older. Measurements: 20 items that best operationalized the 4 CAM diagnostic features were identified to create the 3D-CAM. For prospective validation, 3D-CAM assessments were administered by trained research assistants. Clinicians independently did an extensive assessment, including patient and family interviews and medical record reviews. These data were considered by an expert panel to determine the presence or absence of delirium and dementia (reference standard). The 3D-CAM delirium diagnosis was compared with the reference standard in all patients and subgroups with and without dementia. Results: The 201 participants in the prospective validation study had a mean age of 84 years, and 28% had dementia. The expert panel identified 21% with delirium, 88% of whom had hypoactive or normal psychomotor features. Median administration time for the 3D-CAM was 3 minutes (interquartile range, 2 to 5 minutes), sensitivity was 95% (95% Cl, 84% to 99%), and specificity was 94% (Cl, 90% to 97%). The 3D-CAM did well in patients with dementia (sensitivity, 96% [Cl, 82% to 100%]; specificity, 86% [Cl, 67% to 96%]) and without dementia (sensitivity, 93% [Cl, 66% to 100%]; specificity, 96% [Cl, 91% to 99%]). Limitation: Limited to single-center, cross-sectional, and medical patients only. Conclusion: The 3D-CAM operationalizes the CAM algorithm using a 3-minute structured assessment with high sensitivity and specificity relative to a reference standard and could be an important tool for improving recognition of delirium. [ABSTRACT FROM AUTHOR]

The article presents research examining the possible association between acid-suppressive medication and hospital-acquired pneumonia. The design of the cohort study involving patients of at least 18 years of age who were admitted to a large, urban, academic medical center for 3 or more days is described. The outcomes measured include the incidence of hospital-acquired pneumonia in patients exposed and unexposed to acid-suppressive medication. Results indicated that acid-suppressive medication use was associated with a 30% increase in the risk of contracting pneumonia in a hospital setting. However, statistically significant risk was only demonstrated for proton-pump inhibitor use.

ABSTRACT: Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging enables imaging of scar/fibrosis and is a cornerstone of most CMR imaging protocols. CMR imaging can benefit from image acceleration; however, image acceleration in LGE remains challenging due to its limited signal-to-noise ratio. In this study, we sought to evaluate a rapid two-dimensional (2D) LGE imaging protocol using a generative artificial intelligence (AI) algorithm with inline reconstruction. Methods: A generative AI-based image enhancement was used to improve the sharpness of 2D LGE images acquired with low spatial resolution in the phase-encode direction. The generative AI model is an image enhancement technique built on the enhanced super-resolution generative adversarial network. The model was trained using balanced steady-state free-precession cine images, readily used for LGE without additional training. The model was implemented inline, allowing the reconstruction of images on the scanner console. We prospectively enrolled 100 patients (55 ± 14 years, 72 males) referred for clinical CMR at 3T. We collected three sets of LGE images in each subject, with in-plane spatial resolutions of 1.5 × 1.5-3-6 mm2. The generative AI model enhanced in-plane resolution to 1.5 × 1.5 mm2 from the low-resolution counterparts. Images were compared using a blur metric, quantifying the perceived image sharpness (0 = sharpest, 1 = blurriest). LGE image sharpness (using a 5-point scale) was assessed by three independent readers. Results: The scan times for the three imaging sets were 15 ± 3, 9 ± 2, and 6 ± 1 s, with inline generative AI-based images reconstructed time of ∼37 ms. The generative AI-based model improved visual image sharpness, resulting in lower blur metric compared to low-resolution counterparts (AI-enhanced from 1.5 × 3 mm2 resolution: 0.3 ± 0.03 vs 0.35 ± 0.03, P

Preoperative risk biomarkers for delirium may aid in identifying high-risk patients and developing intervention therapies, which would minimize the health and economic burden of postoperative delirium. Previous studies have typically used single omics approaches to identify such biomarkers. Preoperative cerebrospinal fluid (CSF) from the Healthier Postoperative Recovery study of adults ≥ 63 years old undergoing elective major orthopedic surgery was used in a matched pair delirium case–no delirium control design. We performed metabolomics and lipidomics, which were combined with our previously reported proteomics results on the same samples. Differential expression, clustering, classification, and systems biology analyses were applied to individual and combined omics datasets. Probabilistic graph models were used to identify an integrated multi-omics interaction network, which included clusters of heterogeneous omics interactions among lipids, metabolites, and proteins. The combined multi-omics signature of 25 molecules attained an AUC of 0.96 [95% CI: 0.85–1.00], showing improvement over individual omics-based classification. We conclude that multi-omics integration of preoperative CSF identifies potential risk markers for delirium and generates new insights into the complex pathways associated with delirium. With future validation, this hypotheses-generating study may serve to build robust biomarkers for delirium and improve our understanding of its pathophysiology.

ABSTRACT: Background: The extent of late gadolinium enhancement (LGE) on cardiovascular magnetic resonance (CMR) in patients with hypertrophic cardiomyopathy (HCM) is associated with an increased risk of sudden cardiac death events. However, the clinical significance of age-specific longitudinal changes in LGE is not well characterized in HCM. We sought to assess whether the risk of LGE progression diverges between young to middle-aged (ages 20-59 years) and older (≥ 60) adults with HCM. Methods: A total of 102 HCM patients (age 6 SD above the nulled remote myocardium and manually adjusting a grayscale threshold. Results: LGE was identified at baseline in 61 of the 102 HCM patients (60%), occupying 4.8 ± 3.9% of the left ventricular (LV) mass. At the end of the follow-up period, 53 of the 61 patients (87%) demonstrated an increase in the extent of LGE to 7.7 ± 5.4%, and 8 patients had no change. In 5 patients (5%), LGE increased to extensive with >15% of the LV mass. The rate of LGE progression was 0.7 ± 1.0%/year, including 21 patients (21%) with particularly accelerated progression of ≥1%/year. The risk of LGE progression ≥1%/year was significantly higher in patients

Abstract Background Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with 55 years who completed the 2004 Nurses’ Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women’s Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk. Results Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784–0.796) in NHS and 0.768 (0.757–0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538–0.641) in NHS and 0.573 (0.536–0.611) in BWHS. Conclusions We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening.

In this study, we propose a novel sparse representation learning method in the Quaternion Wavelet (QW) domain for multi-class image classification. The proposed method takes advantages from: i) the QW decomposition, which promotes sparsity and provides structural information about the image data while allowing approximate shift-invariance, to extract meaningful features from low-frequency QW sub-bands, ii) the dimensionality reduction method using Principal Component Analysis (PCA) for reducing the complexity of the problem, and iii) the sparse representation of the generated QW features to efficiently learn and capture the meaningful and compact information of this data. After the QW decomposition, the features extracted from low-frequency image sub-bands information are projected, by the PCA, into a new feature space with lower dimensionality. The features extracted from the training samples are used to construct a dictionary, while the features of the test samples are sparsely coded for the classification step. The sparse coding problem is formulated in a QW Least Absolute Shrinkage and Selection Operator (QWLasso) model applying quaternion $l_{1}$ minimization. A novel Quaternion Fast Iterative Shrinkage-Thresholding Algorithm (QFISTA) is developed to solve the QWLasso model. The experiments conducted on various public image datasets validated that the proposed method possesses higher accuracy, sparsity, and robustness in comparison with several contemporary methods in the field including Neural Networks.

Abstract Background Our understanding of the relationship between plasma and cerebrospinal fluid (CSF) remains limited, which poses an obstacle to the identification of blood-based markers of neuroinflammatory disorders. To better understand the relationship between peripheral and central nervous system (CNS) markers of inflammation before and after surgery, we aimed to examine whether surgery compromises the blood-brain barrier (BBB), evaluate postoperative changes in inflammatory markers, and assess the correlations between plasma and CSF levels of inflammation. Methods We examined the Role of Inflammation after Surgery for Elders (RISE) study of adults aged ≥ 65 who underwent elective hip or knee surgery under spinal anesthesia who had plasma and CSF samples collected at baseline and postoperative 1 month (PO1MO) (n = 29). Plasma and CSF levels of three inflammatory markers previously identified as increasing after surgery were measured using enzyme-linked immunosorbent assay: interleukin-6 (IL-6), C-reactive protein (CRP), and chitinase 3-like protein (also known as YKL-40). The integrity of the BBB was computed as the ratio of CSF/plasma albumin levels (Qalb). Mean Qalb and levels of inflammation were compared between baseline and PO1MO. Spearman correlation coefficients were used to determine the correlation between biofluids. Results Mean Qalb did not change between baseline and PO1MO. Mean plasma and CSF levels of CRP and plasma levels of YKL-40 and IL-6 were higher on PO1MO relative to baseline, with a disproportionally higher increase in CRP CSF levels relative to plasma levels (CRP tripled in CSF vs. increased 10% in plasma). Significant plasma-CSF correlations for CRP (baseline r = 0.70 and PO1MO r = 0.89, p < .01 for both) and IL-6 (PO1MO r = 0.48, p < .01) were observed, with higher correlations on PO1MO compared with baseline. Conclusions In this elective surgical sample of older adults, BBB integrity was similar between baseline and PO1MO, plasma-CSF correlations were observed for CRP and IL-6, plasma levels of all three markers (CRP, IL-6, and YKL-40) increased from PREOP to PO1MO, and CSF levels of only CRP increased between the two time points. Our identification of potential promising plasma markers of inflammation in the CNS may facilitate the early identification of patients at greatest risk for neuroinflammation and its associated adverse cognitive outcomes.

Abstract Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered “valine, leucine, and isoleucine biosynthesis” at PREOP and “citrate cycle” at POD2 as the most significantly enriched pathways (false discovery rate

Abstract Blood protein concentrations are clinically useful, predictive biomarkers of cardiovascular disease (CVD). Despite a higher burden of CVD among U.S. South Asians, no CVD-related proteomics study has been conducted in this sub-population. The aim of this study is to investigate the associations between plasma protein levels and CVD incidence, and to assess the potential influence of religiosity/spirituality (R/S) on significant protein-CVD associations, in South Asians from the MASALA Study. We used a nested case–control design of 50 participants with incident CVD and 50 sex- and age-matched controls. Plasma samples were analyzed by SOMAscan for expression of 1305 proteins. Multivariable logistic regression models and model selection using Akaike Information Criteria were performed on the proteins and clinical covariates, with further effect modification analyses conducted to assess the influence of R/S measures on significant associations between proteins and incident CVD events. We identified 36 proteins that were significantly expressed differentially among CVD cases compared to matched controls. These proteins are involved in immune cell recruitment, atherosclerosis, endothelial cell differentiation, and vascularization. A final multivariable model found three proteins (Contactin-5 [CNTN5], Low affinity immunoglobulin gamma Fc region receptor II-a [FCGR2A], and Complement factor B [CFB]) associated with incident CVD after adjustment for diabetes (AUC = 0.82). Religious struggles that exacerbate the adverse impact of stressful life events, significantly modified the effect of Contactin-5 and Complement factor B on risk of CVD. Our research is this first assessment of the relationship between protein concentrations and risk of CVD in a South Asian sample. Further research is needed to understand patterns of proteomic profiles across diverse ethnic communities, and the influence of resources for resiliency on proteomic signatures and ultimately, risk of CVD.

Propose: The purpose of this study was to compare the performance of deep learning networks trained with complex-valued and magnitude images in suppressing the aliasing artifact for highly accelerated real-time cine MRI.Methods: Two 3D U-net models (Complex-Valued-Net and Magnitude-Net) were implemented to suppress aliasing artifacts in real-time cine images. ECG-segmented cine images (n = 503) generated from both complex k-space data and magnitude-only DICOM were used to synthetize radial real-time cine MRI. Complex-Valued-Net and Magnitude-Net were trained with fully sampled and synthetized radial real-time cine pairs generated from highly undersampled (12-fold) complex k-space and DICOM images, respectively. Real-time cine was prospectively acquired in 29 patients with 12-fold accelerated free-breathing tiny golden-angle radial sequence and reconstructed with both Complex-Valued-Net and Magnitude-Net. Cardiac function, left-ventricular (LV) structure, and subjective image quality [1(non-diagnostic)-5(excellent)] were calculated from Complex-Valued-Net– and Magnitude-Net–reconstructed real-time cine datasets and compared to those of ECG-segmented cine (reference).Results: Free-breathing real-time cine reconstructed by both networks had high correlation (all R2 > 0.7) and good agreement (all p > 0.05) with standard clinical ECG-segmented cine with respect to LV function and structural parameters. Real-time cine reconstructed by Complex-Valued-Net had superior image quality compared to images from Magnitude-Net in terms of myocardial edge sharpness (Complex-Valued-Net = 3.5 ± 0.5; Magnitude-Net = 2.6 ± 0.5), temporal fidelity (Complex-Valued-Net = 3.1 ± 0.4; Magnitude-Net = 2.1 ± 0.4), and artifact suppression (Complex-Valued-Net = 3.1 ± 0.5; Magnitude-Net = 2.0 ± 0.0), which were all inferior to those of ECG-segmented cine (4.1 ± 1.4, 3.9 ± 1.0, and 4.0 ± 1.1).Conclusion: Compared to Magnitude-Net, Complex-Valued-Net produced improved subjective image quality for reconstructed real-time cine images and did not show any difference in quantitative measures of LV function and structure.

Abstract. Introduction:. Chronic back pain is the leading cause of disability in the United States. Based on the hypothesis that nonspecific back pain may be rooted in a psychophysiologic etiology, we propose a new approach to chronic back pain. Objectives:. A pilot study was conducted to assess whether psychophysiologic symptom relief therapy (PSRT) can reduce disability and back pain bothersomeness for patients with chronic back pain. Methods:. This was a three-armed, randomized trial for adults with nonspecific chronic back pain that compared PSRT with usual care and an active comparator (mindfulness-based stress reduction [MBSR]). Psychophysiologic symptom relief therapy–randomized participants received a 12-week (36 hours) course based on the psychophysiological model of pain. All groups were administered validated questionnaires at baseline and at 4, 8, 13, and 26 weeks. The primary outcome was the reduction in pain disability measured by the Roland–Morris Disability Questionnaire. Results:. The mean Roland–Morris Disability Questionnaire score for the PSRT group (n = 11) decreased from 9.5 (±4.3 SDs) to 3.3 (±5.1) after 26 weeks which was statistically significant compared with both MBSR (n = 12) (P = 0.04) and usual care (n = 12) (P = 0.03). Pain bothersomeness scores and pain-related anxiety decreased significantly over 26 weeks in PSRT compared with MBSR and usual care (data in manuscript). At 26 weeks, 63.6% of the PSRT arm reported being pain free (0/10 pain) compared with 25.0% and 16.7% in MBSR and usual care arms, respectively. Psychophysiologic symptom relief therapy attendance was 76%, and there was 100% follow-up of all groups. Conclusion:. Psychophysiologic symptom relief therapy is a feasible and potentially highly beneficial treatment for patients with nonspecific back pain.

Background Vietnam’s network of commune health centers (CHCs) have historically managed acute infectious diseases and implemented national disease-specific vertical programs. Vietnam has undergone an epidemiological transition towards non-communicable diseases (NCDs). Limited data exist on Vietnamese CHC capacity to prevent, diagnose, and treat NCDs. In this paper, we assess NCD service readiness, availability, and utilization at rural CHCs in 3 provinces in northern Vietnam. Methods Between January 2014 and April 2014, we conducted a cross-sectional survey of a representative sample of 89 rural CHCs from 3 provinces. Our study outcomes included service readiness, availability of equipment and medications, and utilization for five NCD conditions: hypertension, diabetes, chronic pulmonary diseases, cancer, and mental illnesses. Results NCD service availability was limited, except for mental health. Only 25% of CHCs indicated that they conducted activities focused on NCD prevention. Patient utilization of CHCs was approximately 223 visits per month or 8 visits per day. We found a statistically significant difference (P < .05) for NCD service availability, medication availability and CHC utilization among the 3 provinces studied. Conclusion This is the first multi-site study on NCD service availability in Vietnam and the first study in a mountainous region consisting predominately of ethnic minorities. Despite strong government support for NCD prevention and control, Vietnam’s current network of CHCs has limited NCD service capacity.

Background The ISAT (International Subarachnoid Aneurysm Trial) has generated a paradigm shift towards endovascular treatment for intracranial aneurysms but remains unclear if this has led to a true reduction in the risk for aneurysmal subarachnoid hemorrhage (aSAH). We sought to study the association between the treatment burden of unruptured and ruptured aneurysms in the post‐ISAT era. Methods and Results Admissions data from the National Inpatient Sample (2004–2014) were extracted, including patients with a primary diagnosis of aSAH or unruptured intracranial aneurysms treated by clipping or coiling. Within each year, this combined group was randomly matched to non‐aneurysmal control group, based on age, sex, and Elixhauser comorbidity index. Multinomial regression was performed to calculate the relative risk ratio of undergoing treatment for either ruptured or unruptured aneurysms in comparison with the reference control group, adjusted for time. After adjusting for National Inpatient Sample sampling effects, 243 754 patients with aneurysm were identified, 174 580 (71.6%) were women; mean age, 55.4±13.2 years. A total of 121 882 (50.01%) patients were treated for unruptured aneurysms, 79 627 (65.3%) endovascularly and 42 256 (34.7%) surgically. A total of 121 872 (49.99%) patients underwent procedures for aSAH, 68 921 (56.6%) endovascular, and 52 951 (43.5%) surgically. Multinomial regression revealed a significant year‐to‐year decrease in aSAH procedures compared with the control group of non‐aneurysmal hospitalizations (relative risk ratio, 0.963 per year; P

Abstract Background Most patients with implantable cardioverter-defibrillator (ICD) implantation fail to utilize the device resulting in increasing societal costs and patient exposure to device morbidity. We sought to determine whether volumetric cardiovascular magnetic resonance (CMR) left ventricular (LV) spherical remodeling predicts future ventricular arrhythmias in primary ICD patients with reduced LV ejection fraction (EF). Methods Sixty-eight consecutive patients with transthoracic echocardiographic LVEF

Abstract Background The nested case-control study (NCC) design within a prospective cohort study is used when outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects. A NCC analysis with good matching procedures yields estimates that are as efficient and unbiased as estimates from the full cohort study. We present methodological considerations in a matched NCC design and analysis, which include the choice of match algorithms, analysis methods to evaluate the association of exposures of interest with outcomes, and consideration of overmatching. Methods Matched, NCC design within a longitudinal observational prospective cohort study in the setting of two academic hospitals. Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery. The primary outcome was postoperative delirium from in-hospital interviews and medical record review. The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred. We used nonparametric signed ranked test to test for the median of the paired differences. We used conditional logistic regression to model the risk of IL-6 on delirium incidence. Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression. Partial R-square was used to assess the level of overmatching. Results We found that the optimal match algorithm yielded more matched pairs than the greedy algorithm. The choice of analytic strategy—whether to consider measured cytokine levels as the predictor or outcome-- yielded inferences that have different clinical interpretations but similar levels of statistical significance. Estimation results from NCC design using conditional logistic regression, and from simulated cohort design using unconditional logistic regression, were similar. We found minimal evidence for overmatching. Conclusions Using a matched NCC approach introduces methodological challenges into the study design and data analysis. Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.

Background Left atrial (LA) enlargement is a marker for increased risk of atrial fibrillation (AF). However, LA remodeling is a complex process that is poorly understood, and LA geometric remodeling may also be associated with the development of AF. We sought to determine whether LA spherical remodeling or its temporal change predict late AF recurrence after pulmonary vein isolation (PVI). Methods and Results Two hundred twenty‐seven consecutive patients scheduled for their first PVI for paroxysmal or persistent AF who underwent cardiovascular magnetic resonance before and within 6 months after PVI were retrospectively identified. The LA sphericity index was computed as the ratio of the measured LA maximum volume to the volume of a sphere with maximum LA length diameter. During mean follow‐up of 25 months, 88 patients (39%) experienced late recurrence of AF. Multivariable Cox regression analyses identified an increased pre‐PVI LA sphericity index as an independent predictor of late AF recurrence (hazard ratio, 1.32; 95% confidence interval, 1.07–1.62, P=0.009). Patients in the highest LA sphericity index tertile were at highest risk of late recurrence (highest versus lowest: 59% versus 28%; P

BackgroundRecent studies demonstrated a strong association between atrial fibrillation (AF) and epicardial fat around the left atrium (LA). We sought to assess whether epicardial fat volume around the LA is associated with AF, and to determine the additive value of LA‐epicardial fat measurements to LA structural remodeling for identifying patients with AF using 3‐dimensional multi‐echo Dixon fat–water separated cardiovascular magnetic resonance. Methods and ResultsA total of 105 subjects were studied: 53 patients with a history of AF and 52 age‐matched patients with other cardiovascular diseases but no history of AF. The 3‐dimensional multi‐echo Dixon fat‐water separated sequence was performed for LA‐epicardial fat measurements. AF patients had significantly greater LA‐epicardial fat (28.9±12.3 and 14.2±7.3 mL for AF and non‐AF, respectively; P