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The neuroinflammatory response to surgery can be characterized by peripheral acute plasma protein changes in blood, but corresponding, persisting alterations in cerebrospinal fluid (CSF) proteins remain mostly unknown. Using the SOMAscan assay, we define acute and longer-term proteome changes associated with surgery in plasma and CSF. We hypothesized that biological pathways identified by these proteins would be in the categories of neuroinflammation and neuronal function and define neuroinflammatory proteome changes associated with surgery in older patients.SOMAscan analyzed 1305 proteins in blood plasma (n = 14) and CSF (n = 15) samples from older patients enrolled in the Role of Inflammation after Surgery for Elders (RISE) study undergoing elective hip and knee replacement surgery with spinal anesthesia. Systems biology analysis identified biological pathways enriched among the surgery-associated differentially expressed proteins in plasma and CSF.Comparison of postoperative day 1 (POD1) to preoperative (PREOP) plasma protein levels identified 343 proteins with postsurgical changes (P.05; absolute value of the fold change [|FC|]1.2). Comparing postoperative 1-month (PO1MO) plasma and CSF with PREOP identified 67 proteins in plasma and 79 proteins in CSF with altered levels (P.05; |FC|1.2). In plasma, 21 proteins, primarily linked to immune response and inflammation, were similarly changed at POD1 and PO1MO. Comparison of plasma to CSF at PO1MO identified 8 shared proteins. Comparison of plasma at POD1 to CSF at PO1MO identified a larger number, 15 proteins in common, most of which are regulated by interleukin-6 (IL-6) or transforming growth factor beta-1 (TGFB1) and linked to the inflammatory response. Of the 79 CSF PO1MO-specific proteins, many are involved in neuronal function and neuroinflammation.SOMAscan can characterize both short- and long-term surgery-induced protein alterations in plasma and CSF. Acute plasma protein changes at POD1 parallel changes in PO1MO CSF and suggest 15 potential biomarkers for longer-term neuroinflammation that warrant further investigation.

Myocardial feature tracking (FT) provides a comprehensive analysis of myocardial deformation from cine balanced steady-state free-precession images (bSSFP). However, FT remains time-consuming, precluding its clinical adoption.To compare left-ventricular global radial strain (GRS) and global circumferential strain (GCS) values measured using automated DeepStrain analysis of short-axis cine images to those calculated using manual commercially available FT analysis.Retrospective, single-center.A total of 30 healthy subjects and 120 patients with cardiac disease for DeepStrain development. For evaluation, 47 healthy subjects (36 male, 53 ± 5 years) and 533 patients who had undergone a clinical cardiac MRI (373 male, 59 ± 14 years). FIELD STRENGTH/SEQUENCE: bSSFP sequence at 1.5 T (Phillips) and 3 T (Siemens).Automated DeepStrain measurements of GRS and GCS were compared to commercially available FT (Circle, cvi42) measures obtained by readers with 1 year and 3 years of experience. Comparisons were performed overall and stratified by scanner manufacturer.Paired t-test, linear regression slope, Pearson correlation coefficient (r).Overall, FT and DeepStrain measurements of GCS were not significantly different (P = 0.207), but measures of GRS were significantly different. Measurements of GRS from Philips (slope = 1.06 [1.03 1.08], r = 0.85) and Siemens (slope = 1.04 [0.99 1.09], r = 0.83) data showed a very strong correlation and agreement between techniques. Measurements of GCS from Philips (slope = 0.98 [0.98 1.01], r = 0.91) and Siemens (slope = 1.0 [0.96 1.03], r = 0.88) data similarly showed a very strong correlation. The average analysis time per subject was 4.1 ± 1.2 minutes for FT and 34.7 ± 3.3 seconds for DeepStrain, representing a 7-fold reduction in analysis time.This study demonstrated high correlation of myocardial GCS and GRS measurements between freely available fully automated DeepStrain and commercially available manual FT software, with substantial time-saving in the analysis.3 TECHNICAL EFFICACY: Stage 3.

This study aimed at assessing the long-term effects of intranasal insulin (INI) on cognition and gait in older people with and without type 2 diabetes mellitus (T2DM).Phase 2 randomized, double-blinded trial consisted of 24 week treatment with 40 IU of INI (NovolinDM-INI had faster NW (~ 7 cm/s; p = 0.025) and DTW on-treatment (p = 0.007; p = 0.812 adjusted for baseline difference) than DM-Placebo. Control-INI had better executive functioning on-treatment (p = 0.008) and post-treatment (p = 0.007) and verbal memory post-treatment (p = 0.004) than Control-Placebo. DM-INI increased cerebral blood flow in medio-prefrontal cortex (p 0.001) on MRI. Better vasoreactivity was associated with faster DTW (p 0.008). In DM-INI, plasma insulin (p = 0.006) and HOMA-IR (p 0.013) decreased post-treatment. Overall INI effect demonstrated faster walking (p = 0.002) and better executive function (p = 0.002) and verbal memory (p = 0.02) (combined DM-INI and Control-INI cohort, hemoglobin A1c-adjusted). INI was not associated with serious adverse events, hypoglycemic episodes, or weight gain.There is evidence for positive INI effects on cognition and gait. INI-treated T2DM participants walked faster, showed increased cerebral blood flow and decreased plasma insulin, while controls improved executive functioning and verbal memory. The MemAID trial provides proof-of-concept for preliminary safety and efficacy and supports future evaluation of INI role to treat T2DM and age-related functional decline.

Background Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with Methods Using competing risk regression and data from 83,330 women > 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.

Effective recruitment and retention strategies are essential in clinical trials.The MemAID trial consisted of 12 visits during 24 weeks of intranasal insulin or placebo treatment and 24 weeks of post-treatment follow-up in older people with and without diabetes. Enhanced retention strategies were implemented mid study to address high drop-out rate. Baseline variables used in Cox regression models to identify dropout risk factors were: demographics and social characteristics, functional measures, metabolic and cardiovascular parameters, and medications.244 participants were randomized; 13 (5.3%) were discontinued due to adverse events. From the remaining 231 randomized participants, 65 (28.1%) dropped out, and 166 (71.9%) did not. The Non-retention group included 95 participants not exposed to retention strategies, of which 43 (45.2%) dropped out. The Retention group included 136 participants exposed to enhanced retention strategies, of which 22 (16.2%) dropped out. Dropout risk factors included being unmarried, a longer diabetes duration, using oral antidiabetics as compared to not using, worse executive function and chronic pain. After adjusting for exposure to retention strategies, worse baseline executive function composite score (p = 0.001) and chronic pain diagnosis (p = 0.032) were independently associated with a greater risk of dropping out. The probability of dropping out decreased with longer exposure to retention strategies and the dropout rate per month decreased from 4.1% to 1.8% (p = 0.04) on retention strategies.Baseline characteristics allow prediction of dropping out from a clinical trial in older participants. Retention strategies has been effective at minimizing the impact of dropout-related risk factors.Clinical trials.gov NCT2415556 3/23/2015 (www.gov).

Background: Clinical management of orthostatic hypotension (OH) prioritizes the prevention of standing hypotension (HYP), sometimes at the expense of supine hypertension (HTN). It is unclear whether supine HTN is associated with adverse outcomes relative to standing HYP. Objectives: To compare supine HTN and standing HYP among middle-aged adults with and without OH. Methods: The Atherosclerosis Risk in Communities Study measured supine and standing blood pressure (BP) in adults aged 45-64 between 1987-1989. We defined OH as a positional drop in systolic BP ≥20 mmHg or diastolic BP ≥10 mmHg, supine HTN as a BP≥140/≥90 mmHg, and standing HYP as a BP≤105/≤65 mmHg. ARIC participants were followed >30 years. Coronary heart disease (CHD) and mortality were adjudicated; falls and syncope were based on hospital claims. We used adjusted Cox models that included both supine HTN and standing HYP. Results: Of 12,580 participants (55% female, 26% Black, mean age 54±6) 5% had OH. Among those without OH (N=11936), 19% had supine HTN and 21% had standing HYP, while among those with OH (N=644), 11% had supine HTN and 34% had standing HYP. Supine HTN was associated with CHD (HR 1.49; 1.36, 1.63), syncope (HR 1.26; 1.15, 1.39), and all-cause mortality (HR 1.47; 1.38, 1.57), while standing HYP was only associated with all-cause mortality (HR 1.08; 1.00, 1.16) and to a lesser extent than supine HTN (P comparing coefficients 0.25). Conclusion: Supine HTN was associated with more adverse events than standing HYP, regardless of OH status, questioning conventional practices of prioritizing standing HYP among adults with OH.

ImportanceThe study results suggest that delirium is the most common postoperative complication in older adults and is associated with poor outcomes, including long-term cognitive decline and incident dementia.ObjectiveTo examine the patterns and pace of cognitive decline up to 72 months (6 years) in a cohort of older adults following delirium.Design, Setting, and ParticipantsThis was a prospective, observational cohort study with long-term follow-up including 560 community-dwelling older adults (older than 70 years) in the ongoing Successful Aging after Elective Surgery study that began in 2010. The data were analyzed from 2021 to 2022.ExposureDevelopment of incident delirium following major elective surgery.Main Outcomes and MeasuresDelirium was assessed daily during hospitalization using the Confusion Assessment Method, which was supplemented with medical record review. Cognitive performance using a comprehensive battery of neuropsychological tests was assessed preoperatively and across multiple points postoperatively to 72 months of follow-up. We evaluated longitudinal cognitive change using a composite measure of neuropsychological performance called the general cognitive performance (GCP), which is scaled so that 10 points on the GCP is equivalent to 1 population SD. Retest effects were adjusted using cognitive test results in a nonsurgical comparison group.ResultsThe 560 participants (326 women [58%]; mean [SD] age, 76.7 [5.2] years) provided a total of 2637 person-years of follow-up. One hundred thirty-four participants (24%) developed postoperative delirium. Cognitive change following surgery was complex: we found evidence for differences in acute, post–short-term, intermediate, and longer-term change from the time of surgery that were associated with the development of postoperative delirium. Long-term cognitive change, which was adjusted for practice and recovery effects, occurred at a pace of about −1.0 GCP units (95% CI, −1.1 to −0.9) per year (about 0.10 population SD units per year). Participants with delirium showed significantly faster long-term cognitive change with an additional −0.4 GCP units (95% CI, −0.1 to −0.7) or −1.4 units per year (about 0.14 population SD units per year).Conclusions and RelevanceThis cohort study found that delirium was associated with a 40% acceleration in the slope of cognitive decline out to 72 months following elective surgery. Because this is an observational study, we cannot be sure whether delirium directly causes subsequent cognitive decline, or whether patients with preclinical brain disease are more likely to develop delirium. Future research is needed to understand the causal pathway between delirium and cognitive decline.

Policy Points Patients and families can identify clinically relevant errors, including "blindspots"-safety hazards that are difficult for clinicians or organizations to see. Health information transparency, including patient access to electronic visit notes, now federally mandated in the US and the subject of policy debate worldwide, creates a new opportunity to engage patients in diagnostic safety. However, not all patients access notes. Patient identification of blindspots in their notes underscores the need to systematically and equitably engage willing patients in safety, promote patient "good catches," and establish routine systems for patient feedback to help avoid preventable diagnostic errors and delays.Policy shifts toward health information transparency provide a new opportunity for patients to contribute to diagnostic safety. We investigated whether sharing clinical notes with patients can support identification of "diagnostic safety blindspots"-potentially consequential breakdowns in the diagnostic process that may be difficult for clinical staff to observe.We used mixed methods to analyze patient-reported ambulatory documentation errors among 22,889 patients at three US health care centers who read ≥ 1 visit note(s). We identified blindspots by tailoring a previously established taxonomy. We used multiple regression analysis to identify factors associated with blindspot identification.774 patients reported a total of 962 blindspots in 4 categories: (1) diagnostic misalignments (n = 421, 43.8%), including inaccurate symptoms or histories and failures or delay in diagnosis; (2) errors of omission (38.1%) including missed main concerns or next steps, and failure to listen to patients; (3) problems occurring outside visits (14.3%) such as tests, referrals, or appointment access; and (4) multiple low-level problems (3.7%) cascading into diagnostic breakdowns. Many patients acted on the blindspots they identified, resulting in "good catches" that may prevent potential negative consequences. Older, female, sicker, unemployed or disabled patients, or those who work in health care were more likely to identify a blindspot. Individuals reporting less formal education; those self-identifying as Black, Asian, other, or multiple races; and participants who deferred decision-making to providers were less likely to report a blindspot.Patients who read notes have unique insight about potential errors in their medical records that could impact diagnostic reasoning but may not be known to clinicians-underscoring a critical role for patients in diagnostic safety and organizational learning. From a policy standpoint, organizations should encourage patient review of visit notes, build systems to track patient-reported blindspots, and promote equity in note access and blindspot reporting.

Objective: To model the probability of improvement on gait and cognition among patients who received intranasal insulin (INI) Methods: 223 patients (1diabetes, 117 controls) randomized into 4 arms: 55 diabetes placebo, 51 diabetes INI, 59 control placebo, 58 control INI, 1women, 66±9 years of age. INI treatment lasted 24 weeks with 40 IU of INI (Novolin® R, off-label use) or placebo (sterile saline) . normal walk speed (NW) , dual task walk speed (DT) , executive function (EF) , verbal memory (VB) . Improvement due was defined to be better performance at end of treatment compared to baseline. Eleven of 20 baseline predictors were selected in a multivariable generalized linear model with logit link and binomial error to predict the probability of improvement among the 1patients who received INI. Results: 58% of the INI patients improved on NW, 62% improved on DT, 69% EF, and 47% VB. The predictors for the final model included 6 baseline demographic variables (age, number of years of diabetes, number of years in school, Wechsler Adult Reading test, global depression score, and waist circumference; and 5 metabolism-related variables of hemoglobinA1c, fasting plasma glucose, total cholesterol, microalbumin in urine, and microalbumin to creatinine ratio. Conclusion: Modeling technique also allows us to compute the estimated probability of improvement for any individual patients, thus, enabling us to understand better the particular demographic and metabolic profiles that best predict who among those receiving INI could benefit the most from the treatment. Funded by NIH-NIDDK (1R01DK103902) , FDA (IND#107690) , Novo Nordisk, Inc. (ISS-001063) , Medtronic Inc. (NERP15-0310) and registered on www.clinicaltrials.gov (NCT02415556.) Disclosure L.H.Ngo: None. V.Novak: None. P.Novak: Stock/Shareholder; Moderna, Inc., Novavax, Pfizer Inc., Prothena. C.Mantzoros: Advisory Panel; Novo Nordisk. W.Dai: None. V.Lioutas: None. Funding Funded by NIH-NIDDK (1R01DK103902) , FDA (IND#107690) , Novo Nordisk, Inc. (ISS-001063) , Medtronic Inc. (NERP15-0310)

Systematic screening can improve delirium identification among hospitalized older adults. Prior studies have shown clinicians and health system leaders may believe they do not have the time and resources for assessment. We conducted a comparative salary-related cost analysis of an adaptive delirium identification protocol directed by an iPad app.We recruited 527 older adult medicine patients from an urban academic medical center (n = 269) and a rural community hospital (n = 258). Physicians and nurses completed the two-step Ultra-brief Confusion Assessment Method (UB-CAM) protocol (with or without a skip pattern), while certified nursing assistants completed only the UB-2 ultra-brief screen. The sample included 527 patients (average age 80, 57% women, 35% with dementia). Time required to administer the protocol was collected automatically by the iPad app. Salary-related costs of screening were determined by multiplying the time required by the hourly wage for the three disciplines, as obtained from national and regional published healthcare salary cost data. Cost estimates for entire hospital implementation were also calculated.Participants were screened on 924 hospital days by 399 clinicians (53 physicians, 236 nurses, 110 CNAs). For the UB-2, CNAs cost per screen was lower than the other clinician types ($0.37 per screen vs. $0.73 for nurses and $2.39 for hospitalists). For the UB-CAM with skip (UB-CAM), costs per protocol were $1.10 for nurses vs. $3.61 for physicians. The annual salary-related costs of hospital-wide implementation of a nurse-based UB-CAM protocol in a medium-sized (300-bed) hospital was $63,015 plus $4356 for initial and annual training.CNAs and nurses had the lowest salary-associated costs for app-directed CAM-based delirium screening and identification, respectively. Salary-related annual hospital costs for the most efficient protocols in a medium-sized hospital were less than the annual cost of hiring 1 FTE of the discipline performing the protocols.

Background: Previous estimates of CVT incidence vary widely (3-20 per million per year), with more recent studies reporting a higher incidence. Here we present CVT incidence obtained from a large inclusive cohort from the province of British Columbia (BC), Canada (population 5 million) identified through linkage of provincial administrative data. Methods: A retrospective population-based cohort of CVT patients was constructed using ICD 9/10 codes to capture CVT hospitalizations from 2001-2017 in the BC subset of the Canadian Institute for Health Information’s Discharge Abstract Database. The first instance of CVT was extracted and a one-year look-back period was used to exclude prevalent cases. Linkages were made to outpatient prescription data, cancer and prenatal registries to determine patient risk factors. Results: Five hundred and fifty-four unique CVT cases were identified (mean age 50.9, SD 19.4; 55.4% female) (Table 1). Males were more likely to have cases associated with head trauma (12% male vs 7% female, p =0.03) and head and neck infections (13% vs 6%, p =0.009). Cases were diagnosed in the peripartum setting (within 3 months of delivery) for 11% of females. Overall annual incidence was 8.7 (95% CI 8.0-9.4) per 1 000 000 inhabitants. Annual CVT incidence increased over the study period for both men and women (Figure 1). Conclusions: Annual incidence of CVT diagnosis increased from 2001-2017 in BC Canada, similar to trends reported within the United States. This may be due in part to improved ascertainment with increased use of routine vascular neuroimaging over time. Nearly half of cases were male but were more likely to have CVT in the context of trauma or infection.

To be filled; La classification d'images est une discipline majeure en traitement d’images et en intelligence artificielle. La classification est d'une importance fondamentale pour qu'un système intelligent puisse exploiter et gérer efficacement l'information visuelle. L'objectif est de développer des algorithmes qui trouvent automatiquement la catégorie à laquelle appartient un échantillon d'image, à partir d'échantillons d'entraînement. Dans nos études, nous nous concentrons sur l'étude et le développement des algorithmes basés sur la représentation parcimonieuse pour la classification d'images, y compris, mais sans s'y limiter, les visages, les objets et les lésions cutanées. Cette étude met l'accent sur le développement des problèmes de classification basés sur la représentation parcimonieuse dans les domaines spécifiques tels que le domaine des ondelettes ou le domaine des ondelettes quaternioniques dans le but d'améliorer les performances de séparation des classes. En outre, notre objectif est de mettre en œuvre une nouvelle méthode pour le diagnostic du mélanome assisté par ordinateur, réalisé à partir d'images dermoscopiques. Le mélanome est le type de cancer de la peau le plus mortel. Heureusement, les lésions cutanées sont curables si elles sont diagnostiquées et traitées suffisamment tôt. Pour cette raison, le diagnostic automatique du mélanome assisté par ordinateur suscite aujourd'hui un grand intérêt de la part des chercheurs. Dans la première partie de cette étude, nous proposons une nouvelle méthode basée sur la représentation parcimonieuse, à savoir la classification basée sur la représentation parcimonieuse dans le domaine des ondelettes (SRWC), qui résout le problème du codage parcimonieux dans le domaine des ondelettes. Le cadre de la SRWC montre que les caractéristiques obtenues à partir de la transformation en ondelettes peuvent contribuer au processus de classification. En particulier, nous fusionnons les caractéristiques de l'image décrites par les informations complémentaires des coefficients d'ondelettes à basse fréquence et la représentation parcimonieuse pour améliorer les performances de classification et en comparant avec des méthodes conventionnelles de classification par représentation parcimonieuse. Comme les ondelettes favorisent la parcimonie et fournissent des informations structurelles sur l'image, la méthode proposée augmente la précision de la classification. En outre, notre méthode peut naturellement gérer l'occlusion et la corruption des images. Dans la deuxième partie de cette étude, nous étendons la méthode SRWC à l'espace 4D des quaternions pour développer une nouvelle méthode de classification basée sur la représentation parcimonieuse dans le domaine des ondelttes quaternioniques, appelé SRCQW (Sparse Representation based Classification in the Quaternion Wavelet domain). En particulier, cette méthode exploite la transformée en ondelettes quaternioniques, qui utilise les filtres et la transformée de Hilbert, pour générer les coefficients d'ondelettes quaternioniques. Comme pour la méthode précédente, nous n'utilisons que les caractéristiques quaternioniques décrites par les coefficients des sous-bandes de basse fréquence pour mapper le dictionnaire parcimonieux et le problème de classification dans l'espace quaternionique 4D. Pour calculer le vecteur quaternionique parcimonieux, nous formulons le modèle QWLasso (quaternion wavelet least absolute shrinkage and selection operator) en utilisant la minimisation du $l_1$ quaternionique. Pour résoudre le problème QWLasso, nous développons le nouvel algorithme QFISTA (quaternion fast iterative shrinkage-thresholding algorithm). La combinaison des ondelettes quaternionques, qui favorisent la parcimonie, et du modèle de représentation parcimonieuse garantit la convergence de la méthode proposée vers une grande précision de la classification.Dans la troisième partie de l'étude, nous combinons le SRWC et le réseau de neurones (NN) pour pallier aux inconvénients des deux approches. Plus précisément, il s'agit d'une méthode de classification par apprentissage qui se base sur un modèle d’autoencodage convolutif (CAE), et sur une représentation parcimonieuse dans le domaine des ondelettes afin de classer les images étiquetées. Pour cela, nous appelons cette méthode CAE-SRWC. Ce travail est réalisé dans le cadre d'une collaboration avec un étudiant de Master. Dans l'approche proposée, la CAE apprend, avec une couche latente parcimonieuse, les codes parcimonieux des caractéristiques des ondelettes. Ensuite, un critère probabiliste basé sur les résidus est utilisé pour attribuer des étiquettes aux échantillons de test en fonction des codes parcimonieux estimés. En outre, la méthode proposée montre explicitement une réduction substantielle du nombre de paramètres du réseau par rapport aux méthodes récentes de réseaux de neurones.L'efficacité des avancées théoriques et des méthodes proposées est validée expérimentalement en les appliquant à des bases de données couramment utilisées, telles que celles de visages et des objets, et en comparant leurs résultats avec celles des méthodes de pointe dans le domaine, y compris les méthodes de réseaux de neurones. Dans la dernière partie du travail, nous démontrons les capacités des algorithmes proposés, notamment SRWC, SRCQW et CAE-SRWC, pour le traitement des images biomédicales en les appliquant à la classification des images de lésions cutanées. Les résultats obtenus montrent le potentiel des méthodes nouvellement développées, pour classer les images de lésions cutanées dermoscopiques. De plus, les trois approches proposées montrent leur supériorité pour la reconnaissance des images de mélanome avec de bons résultats de sensibilité.

Type 2 diabetes mellitus (T2DM) increases the risk of dementia. Intranasal insulin (INI) has emerged as treatment for T2DM-related cognitive impairment. This randomized, doubled blind trial consisted of 24-week treatment with 40 IU of intranasal insulin (Novolin® R) or placebo (sterile saline) once daily and 24-week follow-up period. T2DM and control participants > 50 years old and able to walk for 6 minutes, were enrolled. The primary outcomes were INI effect on cognition and normal and dual task walking. A total of 244 participants (122 women; 65.8 ± 9.1 years old) were randomized in the four groups (57 DM-INI, 58 DM-Placebo, 65 Control-INI, 64 Control-Placebo). Of 223 at baseline, 174 completed treatment (84 DM [70% of planned enrollment] and 90 controls [100%]), and 156 (69 DM) completed the follow-up. In T2DM, INI did not improve cognitive outcomes or depression as compared to placebo. In controls, INI improved verbal learning during on-treatment (p=0.03) and post-treatment (p=0.03) periods (Mixed Models). DM-INI group had faster normal walking at baseline and on-treatment (p Disclosure V. Novak: Advisory Panel; Spouse/Partner; Endonovo Therapeutics, Inc., Consultant; Spouse/Partner; Dysimmune Foundtation, Other Relationship; Spouse/Partner; Oxford University Press. L. Aponte becerra: None. L. H. Ngo: Consultant; Self; Five Islands Consulting, Other Relationship; Self; Radiological Society of America. C. Mantzoros: Advisory Panel; Self; Amgen Inc., GENFIT, Intercept Pharmaceuticals, Inc., Novo Nordisk, Regeneron Pharmaceuticals Inc. P. Novak: Other Relationship; Self; Dysimmune Foundation, Endonovo Therapeutics, Oxford Press. R. Mcglinchey: None. W. Dai: None. V. Lioutas: Consultant; Self; QMetis. S. Buss: Consultant; Self; Kinto Care. C. B. Fortier: None. F. Khan: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK103902); U.S. Food and Drug Administration (IND107690); Novo Nordisk (ISS-001063), Medtronic (NERP15-0310); World Health Organization (UTN-U111-1175-1588)

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). 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 correlation between biofluids. For the plasma-CSF biofluids with significant correlations, we determined whether the markers were associated by using linear regression models. Results Mean Qalb did not change between baseline and PO1MO. Plasma and CSF levels of IL-6, CRP, and YKL-40 were higher on PO1MO relative to baseline, with a disproportionally higher increase in CSF levels relative to plasma levels (IL-6 doubled and CRP tripled in CSF). Significant plasma-CSF correlations for CRP (baseline r = 0.70 and PO1MO r = 0.89, p

In this paper, we propose an effective Convolutional Autoencoder (AE) model for Sparse Representation (SR) in the Wavelet Domain for Classification (SRWC). The proposed approach involves an autoencoder with a sparse latent layer for learning sparse codes of wavelet features. The estimated sparse codes are used for assigning classes to test samples using a residual-based probabilistic criterion. Intensive experiments carried out on various datasets revealed that the proposed method yields better classification accuracy while exhibiting a significant reduction in the number of network parameters, compared to several recent deep learning-based methods.

This study sought to determine whether myocardial tissue heterogeneity scanned by native TThe benefit of insertable cardiac-defibrillator (ICD) as primary prevention ICD in patients with NICM remains to be fully clarified.A total of 115 NICM candidates for primary prevention and 55 healthy controls with similar distributions of age and sex were prospectively enrolled. Imaging was performed at 1.5-T using a protocol that included cine magnetic resonance for left ventricular function, late gadolinium enhancement (LGE) for focal scarring, and 5-slice native TDuring a median follow-up of 24 months, 13 patients (11%) experienced the primary endpoint. Dichotomized Mad-SD0.24 provided a comparable outcome to the presence of LGE for the primary endpoint (annual event rate: 9.8% vs. 10.9%). The integration of Mad-SD to global native TCombined myocardium tissue heterogeneity and interstitial fibrosis assessment by native T

"Cardiovascular disease (CVD) affects daily living functionality, cognitive ability, and mood. We evaluated the effects of a CVD risk score on disability and assessed the characteristics that may modify this relationship in 192 older adults (mean age: 65.6 years, 96 women). WHODAS 2.0 was used to measure global disability and mobility difficulty. Framingham Risk Score (FRS) was used to predict 10-year cardiovascular mortality risk. Sociodemographic characteristics, mental status, overall mood, and gait speed were evaluated for their potential modification of the effect of FRS on WHODAS. We used general linear models to estimate the main effect and interaction effects for the modifiers. A higher effect of FRS was significantly associated with worse WHODAS total score and mobility subscore. We found female gender, younger age, higher IQ, more years of education, higher MMSE, faster gait speed, and higher GDS to be potential effect modifiers."

This paper improves the conventional sparse representation based classification (SRC) method, through incorporating wavelet coefficients. For this reason, the proposed method is called Sparse Representation Wavelet based Classification (SRWC). In the present study, we fuse the image features described by the complementary information from the low sub-band of the wavelet coefficients and sparse representation to outperform the conventional SRC according to accuracy. This holds because the wavelets promote sparsity and provide structural information about the image, which increases the accuracy of classification. To validate the capabilities and underline the advantages of the novel SRWC, we conducted an extensive number of experiments using publicly available datasets and compared our results with contemporary methods.

This study assessed changes in myocardial native TWith emerging data on the long-term retention of gadolinium in the body and brain, there is a need for an alternative noncontrast cardiovascular magnetic resonance (CMR)-based myocardial ischemia assessment.Twenty-eight healthy adult subjects and 14 patients with coronary artery disease (CAD) referred for exercise stress and/or rest single-photon emission computed tomography/myocardial perfusion imaging (SPECT/MPI) for evaluation of chest pain were prospectively enrolled. Free-breathing myocardial native TThe mean exercise intensity was 104 W, with exercise duration of 6 to 12 min. After exercise, native TFree-breathing stress/rest native T

To analyze the pattern and longitudinal evolution of honorary authorship in major radiology journals.In this Institutional Review Board-approved study, an electronic survey was sent to first authors of original research articles published in the American Journal of Roentgenology, European Radiology, the Journal of Magnetic Resonance Imaging, and Radiology during 2 years (July 2014 through June 2016). Questions addressed the perception of honorary authorship and contributing factors, as well as demographic information. Univariate analysis was performed by using χ2 tests. Multivariable logistic regression models were used to assess independent factors associated with the perception of honorary authorship.Of 1839 first authors, 315 (17.3%) responded. Of these, 31.4% (97/309) perceived that at least one coauthor did not make sufficient contributions to merit authorship and 54.3% (159/293) stated that one or more coauthors performed only "nonauthor" tasks according to International Committee of Medical Journal Editors criteria. Of eight factors significantly associated with the perception of honorary authorship on univariate analysis, two were retained by the stepwise multivariate model: having someone suggest adding an author and a coauthor performing only a nonauthorship task.There has been little variation in the perception of honorary authorship among first authors of original research articles in radiology. The suggestion of adding an author and having coauthors performing only nonauthorship tasks are the two most important risk factors for honorary authorship. Our findings indicate that a prolonged course of transformation of current cultural norms is required to decrease honorary authorship.

To assess measurement reproducibility and image quality of myocardial TEleven healthy subjects (33 ± 16 years; 6 males) underwent a slice-interleaved TIn the healthy cohort, the slice-interleaved TSlice-interleaved T

Although postoperative atrial fibrillation (AF) is prevalent after cardiac surgery, the corresponding medication burden associated with this postoperative arrhythmia is unknown.We conducted a prospective study of 204 patients aged 60 or older (median age 73) undergoing cardiac surgery at two academic medical centers. We defined "AF at discharge" as AF that developed after surgery and was present on the day of discharge. We evaluated the prevalence of anticoagulant and antiarrhythmic use at discharge, and out to 1 year post-discharge. We investigated the association between age and prescription of both classes of medications at discharge.Ninety-one (45%) patients developed new postoperative AF, which persisted at discharge in 28 (14%) patients. Thirty-four percent of patients with postoperative AF were discharged on warfarin, 62% were discharged on antiarrhythmic medication, and 25% were discharged on both. Eighty-two percent of those discharged on both were older than 72 years of age. Patients with AF present at discharge were more likely to be discharged on anticoagulant agents than patients whose AF resolved prior to discharge (54% versus 26%, p=0.01), and more likely to be discharged on antiarrhythmic agents than patients whose AF resolved prior to discharge, though not significantly so (73% versus 57%, p=0.2). At 12 months, the proportion of patients on antiarrhythmic and anticoagulant medications had still not returned to preoperative rates.AF persists at hospital discharge in nearly one-third of affected patients. Cardiac surgery results in the initiation of anticoagulant and antiarrhythmic medications in many older patients annually, often concurrently. Our findings underscore the need for additional studies on the natural history of this arrhythmia and clinical trials investigating different management strategies after discharge. Such research will help to inform development of guidelines addressing duration of use for these medications, to aid physicians in these complicated post-discharge management decisions.

Recent studies in the outpatient setting have demonstrated high rates of opioid prescribing and overdose-related deaths. Prescribing practices in hospitalized patients are unexamined.To investigate patterns and predictors of opioid utilization in nonsurgical admissions to US hospitals, variation in use, and the association between hospital-level use and rates of severe opioid-related adverse events.Adult nonsurgical admissions to 286 US hospitals.Opioid exposure and severe opioid-related adverse events during hospitalization, defined using hospital charges and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes.Of 1.14 million admissions, opioids were used in 51%. The mean ± standard deviation daily dose received in oral morphine equivalents was 68 ± 185 mg; 23% of exposed received a total daily dose of ≥100 mg oral morphine equivalents. Opioid-prescribing rates ranged from 5% in the lowest-prescribing hospital to 72% in the highest-prescribing hospital (mean, 51% ± 10%). After adjusting for patient characteristics, the adjusted opioid-prescribing rates ranged from 33% to 64% (mean, 50% ± standard deviation 4%). Among exposed, 0.60% experienced severe opioid-related adverse events. Hospitals with higher opioid-prescribing rates had higher adjusted relative risk of a severe opioid-related adverse event per patient exposed (relative risk: 1.23 [1.14-1.33] for highest-prescribing compared with lowest-prescribing quartile).The majority of hospitalized nonsurgical patients were exposed to opioids, often at high doses. Hospitals that used opioids most frequently had increased adjusted risk of a severe opioid-related adverse event per patient exposed. Interventions to standardize and enhance the safety of opioid prescribing in hospitalized patients should be investigated.